"Business, Sauder School of"@en . "Operations and Logistics (OPLOG), Division of"@en . "DSpace"@en . "UBCV"@en . "Loke, Wai Leng"@en . "2008-10-09T18:09:30Z"@en . "2008"@en . "Master of Science in Business - MScB"@en . "University of British Columbia"@en . "Since the events of 9/11, there has been tremendous amount of renewed interests in the study of trade security. There has been an influx of security regulations and the private sector has been trying to keep pace in complying with them. However, due to the public externalities of security improvements and the lack of quantified and proven benefits, the private sector is struggling to establish business cases for their security initiatives.\nThere is very little quantitative research in this area. Using exploratory factor analysis (EFA) and structural equation modeling (SEM), this study serves to fill this gap by introducing a statistical way of analysing and understanding the complex relationships amongst security effort, its motivators and performance and traditional supply chain performance (SCP). This study also proposes an evaluation framework for security efforts.\nEFA results show that security is a dimension of SCP. This means that organizations have all along been measuring an aspect of their operations that relates to security. As such, organizations should not perceive the current heightened interests in security as throwing them off-balance. In evaluating security efforts, organizations should select key performance indicators (KPIs) that represent each of the four areas of information, cargo, people and cost.\nSEM results show that organizations undertake security efforts as a result of both perceived security benefits and perceived collateral benefits, with perceived security benefits carrying a greater weight in the decision-making process. Results also show that organizations are implementing security initiatives out-of-compliance i.e. implementing initiatives that they perceive as not having significant impacts on security and SCP.\nIn view of the positive relationships among perceived security impact, security effort and security performance, there is further imperative for an objective method for evaluating security efforts to prevent effort justification behaviour in determining the effectiveness of the same. Results also show that organizations perceive an improved performance in security leads to an overall improvement in SCP. However, as with other supply chain strategies, there are tradeoffs and not all aspects of SCP are impacted in the same way. Time, responsiveness and efficiency for instance are negatively impacted while reliability is positively impacted."@en . "https://circle.library.ubc.ca/rest/handle/2429/2519?expand=metadata"@en . "16300272 bytes"@en . "application/pdf"@en . "AN EVALUATION OF THE VALUE OF SECURITY IN THE INTERNATIONAL MARINE SUPPLY CHAIN by Wai Leng Loke B.BA, The National University of Singapore (2001) A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in BUSINESS ADMINISTRATION in THE FACULTY OF GRADUATE STUDIES (Transportation and Logistics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2008 \u00C2\u00A9 Wai Leng Loke, 2008 ABSTRACT Since the events of 9/11, there has been tremendous amount of renewed interests in the study of trade security. There has been an influx of security regulations and the private sector has been trying to keep pace in complying with them. However, due to the public externalities of security improvements and the lack of quantified and proven benefits, the private sector is struggling to establish business cases for their security initiatives. There is very little quantitative research in this area. Using exploratory factor analysis (EFA) and structural equation modeling (SEM), this study serves to fill this gap by introducing a statistical way of analysing and understanding the complex relationships amongst security effort, its motivators and performance and traditional supply chain performance (SCP). This study also proposes an evaluation framework for security efforts. EFA results show that security is a dimension of SCP. This means that organizations have all along been measuring an aspect of their operations that relates to security. As such, organizations should not perceive the current heightened interests in security as throwing them off-balance. In evaluating security efforts, organizations should select key performance indicators (KPIs) that represent each of the four areas of information, cargo, people and cost. SEM results show that organizations undertake security efforts as a result of both perceived security benefits and perceived collateral benefits, with perceived security benefits carrying a greater weight in the decision-making process. Results also show that organizations are implementing security initiatives out-of-compliance i.e. implementing initiatives that they perceive as not having significant impacts on security and SCP. In view of the positive relationships among perceived security impact, security effort and security performance, there is further imperative for an objective method for evaluating security efforts to prevent effort justification behaviour in determining the effectiveness of the same. Results also show that organizations perceive an improved performance in security leads to an overall improvement in SCP. However, as with other supply chain strategies, there are tradeoffs and not all aspects of SCP are impacted in the same way. Time, responsiveness and efficiency for instance are negatively impacted while reliability is positively impacted. ii TABLE OF CONTENTS Abstract^ ii List of Tables vi List of Figures ix List of Abbreviations^ xi Acknowledgements xiv Dedication^ xv CHAPTER 1 INTRODUCTION^ 1 1.1^Outline of Thesis 2 CHAPTER 2 LITERATURE REVIEW^ 5 2.1^Supply Chain Risks^ 5 2.1.1 What Events Represent Supply Chain Risks?^ 8 2.1.2 Managing Supply Chain Risks^ 10 2.2^Supply Chain Security Risks 14 2.2.1 What are Supply Chain Security Risks?^ 15 2.2.2 Classification of Supply Chain Security Risks 16 2.2.3 The Public Sector's Take on Supply Chain Security^ 17 2.2.4 The Private Sector's Take on Supply Chain Security 20 2.3^Managing Supply Chain Security Risks^ 22 2.3.1^Mitigating Supply Chain Security Risks 23 2.4^Security Risks in an International Maritime Supply Chain ^ 31 2.4.1^Relative Importance of Maritime Transportation 32 2.4.2 Potential Security Breach Points^ 33 2.5^Supply Chain Security Performance 34 2.6^Summary and Research Gap^ 38 CHAPTER 3 METHODOLOGY 45 3.1^Key Phases in this Study^ 46 3.2^Research Conceptual Framework^ 46 3.3^Fieldwork/Interviews^ 48 3.3.1 The Use of Fieldwork in Logistics Research^ 49 3.3.2^Field Interviews in This Study^ 50 3.4^Web/Email Survey^ 52 3.4.1^Survey Characteristics 54 3.4.1.1^Scale Design 54 3.4.2 Self Performance Appraisal^ 57 iii 3.4.3^Organization Profiling^ 59 3.4.4 Key Performance Indicators (KPIs)^ 61 3.4.5^Supply Chain Security Initiatives 62 3.4.6 Respondents' Information^ 64 3.5^Factor Analysis^ 66 3.5.1^What is Factor Analysis? ^ 67 3.5.2 Use of Factor Analysis in This Study^ 67 3.5.3 Advantages and Challenges of Factor Analysis^ 68 3.6^Structural Equation Modeling (SEM)^ 68 3.6.1 What is SEM?^ 69 3.6.2 Use of SEM in This Study^ 69 3.6.3 Advantages and Challenges of Using SEM^ 70 CHAPTER 4 DATA^ 71 4.1^Profile of Field Interview Respondents^ 71 4.2^Profile of Web/Email Survey Respondents 73 4.3^Types of Variables^ 81 CHAPTER 5 ANALYSIS 83 5.1^General Attitude Towards Supply Chain Security^ 83 5.2^Factors that Affect Attitude Towards Security 88 5.2.1 Organization Size (Annual Revenue)^ 89 5.2.2 Extent of Overseas Sourcing^ 93 5.2.3 Cargo Nature^ 93 5.2.4 Size of Shipment 95 5.2.5 Scope of Supply Chain Control/Influence^ 98 5.2.6 Summary of Attitude Analyses^ 102 5.3^Supply Chain Security a Holistic Effort 103 5.4^KPIs for Supply Chain Performance and Security Performance^ 104 5.4.1^Determining the Appropriate KPIs for Factor Analysis^ 105 5.4.2 Factor Analysis for SCP KPIs^ 106 5.4.3 Factor Analysis for SP KPIs 115 5.5^Security Initiatives, SCP and Security Performance^ 119 5.5.1^Perceptions of Security Initiatives and their Popularity 119 5.6^Structural Equation Modeling (SEM) Analysis^ 122 5.6.1^Data Considerations^ 123 5.6.2 Model Specification 123 5.6.3 Model Estimation 124 5.6.4 Model Evaluation^ 126 5.6.4.1^Measurement Model Evaluation^ 127 iv 5.6.4.2^Structural Model Evaluation ^ 135 5.6.5 Interpreting Parameters^ 140 5.6.6 Analysis of Structural Model 143 CHAPTER 6 CONCLUSION^ 156 ^ 6.1^Undertaking Security Effort 156 6.2^Evaluating the Effectiveness of Security Effort^ 160 6.3^Managerial Implications of Results ^ 161 6.4^Limitations of Study^ 166 6.5^Future Research 168 REFERENCES^ 169 APPENDIX A 178 APPENDIX B^ 193 APPENDIX C 248 APPENDIX D^ 250 APPENDIX E 255 APPENDIX F^ 259 APPENDIX G 268 APPENDIX H^ 281 v LIST OF TABLES Table 2.1^Common supply chain strategies 6 Table 2.2^Classifying security risks. ^ 16 Table 2.3^Examples of freight security technologies ^ 27 Table 2.4^TQM features. ^ 31 Table 3.1^Use of different methods in logistics research^ 49 Table 3.2^Reliability of rating scales.^ 56 Table 3.3^Popularity of Likert scales used in logistics research.^ 57 Table 3.4^Comparison of SCP dimensions.^ 58 Table 3.5^Security initiatives^ 63 Table 3.6^Societal cluster classification.^ 66 Table 4.1^General profile of organizations interviewed.^ 71 Table 4.2^Shipper vs. service providers^ 74 Table 4.3^Shipper profile.^ 74 Table 4.4^Service provider profile.^ 74 Table 4.5^Respondents' supply chain types.^ 75 Table 4.6^Cargo nature handled by respondents' organizations.^ 76 Table 4.7^Shipment size nature of respondents. ^ 77 Table 4.8^Respondents' trade route profile 77 Table 4.9^Respondents' 2006 annual revenues profile.^ 78 Table 4.10 Respondents' scope of influence over their supply chain^ 79 Table 4.11 Physical locations of respondents^ 80 Table 4.12 Respondents' dominant culture in business management.^ 81 Table 4.13 Types of variables. ^ 82 Table 5.1^Respondents' view of security as a supply chain driver. ^ 85 Table 5.2^Results for statistical tests for significance in differences in ranking of drivers. ^87 Table 5.3^Ranking of security driver by organizations of different sizes^ 90 Table 5.4^Mean ranking of security driver for different revenue groups. 90 Table 5.5^Results for statistical tests for significance in differences in security driver ranking. ^ 91 v i Table 5.6^Cross-tabulation results (respondent type).^ 92 Table 5.7^x2 test for cross-tabulation results with respondent type as control variable^92 Table 5.8^Ranking of security driver (between hazardous and non-hazardous cargo carrying organizations).^94 Table 5.9^Mean ranking of security driver (between hazardous and non-hazardous cargo carrying organizations).^94 Table 5.10 Results for statistical tests for significance in differences in security driver ranking.^ 95 Table 5.11 Ranking of security driver (FCL and no-FCL cargo carrying organizations). ^96 Table 5.12 Mean ranking of security driver (between organizations who ship FCL and those who do not).^97 Table 5.13 Results of statistical tests for significance in differences in security driver ranking.^ 97 Table 5.14 List of supply chain activities. ^ 99 Table 5.15 Definitions of span-of-control. 100 Table 5.16 Ranking of security driver among organizations with different span of control....101 Table 5.17 Mean ranking of security driver among organizations with different control span. ^ 101 Table 5.18 Results for statistical tests for significance in differences in security driver ranking. ^ 102 Table 5.19 Ordinal regression results \u00E2\u0080\u0094 model-fitting information. ^ 103 Table 5.20 KPIs and their appropriateness frequencies. ^ 105 Table 5.21 KMO-MSA index and Bartlett's test results. 107 Table 5.22 Comparison of rotation methods^ 109 Table 5.23 Pattern matrix (Principal component with promax rotation \u00E2\u0080\u0094 6 factors). ^ 110 Table 5.24 Pattern matrix (Principal component with promax rotation \u00E2\u0080\u0094 29 variables). ^ 112 Table 5.25 KMO-MSA index and Bartlett's test results. ^ 112 Table 5.26 Cronbach's alpha values for generated factors 113 Table 5.27 KPIs deemed appropriate for security performance.^ 115 Table 5.28 KMO-MSA index and Bartlett's test results.^ 117 Table 5.29 Pattern matrix for SP factors (Principal component with promax rotation)^ 118 Table 5.30 Cronbach's alpha values for SP factors.^ 118 Table 5.31 Comparison of ML and GLS estimation techniques.^ 125 Table 5.32 Comparison of model having path H5a and model not having H5a^ 126 Vii Table 5.33 Cronbach's alpha values for each measurement model. ^ 129 Table 5.34 SEM construct reliability measures for each measurement model.^ 130 Table 5.35 Observed variables item-to-item correlation matrix.^ 131 Table 5.36 Variables (Items) to latent constructs correlation matrix 132 Table 5.37 Correlations between measurement models^ 132 Table 5.38 Supply Chain Security measurement models fit evaluation^ 133 Table 5.39 Standardized residuals matrix for Supply Chain Security model.^ 137 Table 5.40 Modification indices for Supply Chain Security model^ 137 Table 5.41 Supply Chain Security model fit evaluation^ 139 Table 5.42 Minimum sample size required to achieve specified power (test of close fit)^ 140 Table 5.43 Parameter estimates for Supply Chain Security model.^ 141 Table 5.44 Goodness-of-fit indices for X2 difference tests.^ 142 Table 5.45 Cross-tabulation results for security initiatives and security performance. ^ 146 Table 5.46 Cross-tabulation results for security initiatives and traditional SCP.^ 149 Table 6.1^Ranking security initiatives by implementation popularity with no. of SCP aspects that are statistically significant^ 159 Table 6.2^Ranking security initiatives. ^ 162 viii LIST OF FIGURES Figure 2.1^Risk classification framework^ 9 Figure 2.2^A framework for assessing and positioning supply chain risk issues^ 11 Figure 2.3^Supply chain risk management framework.^ 12 Figure 2.4^Positioning security risks. ^ 16 Figure 2.5^Structural model for research questions and hypotheses^ 44 Figure 3.1^Key phases in study. ^ 46 Figure 3.2^Research framework. 47 Figure 3.3^Conducting factor analysis^ 67 Figure 3.4^Steps in SEM modeling process. 69 Figure 4.1^Respondent profile in terms of type and representation.^ 73 Figure 4.2^Industry profile of shippers^ 74 Figure 4.3^Industry profile of service providers. ^ 74 Figure 4.4^Illustration of respondents' supply chain type proportions^ 76 Figure 4.5^Variation in cargo nature handled by respondents' organizations. ^ 76 Figure 4.6^Variation in shipment size nature of respondents. ^ 77 Figure 4.7^Variation in respondents' trade route profile 78 Figure 4.8^Respondents' 2006 annual revenues profile^ 79 Figure 4.9^Respondents' scope of influence over their supply chain^ 79 Figure 4.10 Variation in physical locations of respondents. ^ 80 Figure 4.11 Variation in respondents' dominant culture in business management^ 81 Figure 5.1^Respondents' view of security as a supply chain driver. ^ 85 Figure 5.2^Shipper respondents' view of security as a supply chain driver. ^ 86 Figure 5.3^Service providers' view of security as a supply chain driver. 86 Figure 5.4^Ranking of security driver by organizations of different sizes.^ 90 Figure 5.5^Ranking of security driver (between hazardous and non-hazardous cargo carrying organizations). ^ 94 Figure 5.6^Ranking of security driver (between FCL and no-FCL cargo carrying organizations).^ 96 Figure 5.7^Ranking of security driver among organizations with different span of control.. 101 ix Figure 5.8^Scree plot for initial solution.^ 109 Figure 5.9^Scree plot for SP factor analysis (eigenvalues > 1)^ 117 Figure 5.10 Respondents' perceived impact of security initiatives on SCP.^ 120 Figure 5.11 \"Popularity\" of security initiatives. ^ 121 Figure 5.12 Structural model for Supply Chain Security^ 124 Figure 5.13 Perceived Collateral Benefits measurement model^ 127 Figure 5.14 SCP measurement model^ 128 Figure 5.15 Security Effort measurement model^ 128 Figure 5.16 Supply Chain Security SEM model. 136 Figure 5.17 The motivators of security efforts^ 145 Figure 6.1^The route to improving supply chain security.^ 163 Figure 6.2^Security efforts evaluation framework. 164 LIST OF ABBREVIATIONS 3PL^-rd Party Logistics Service Provider 9/11 September 11, 2001 ACE^Automated Commercial Environment ACI Advanced Commercial Information ADF^Asymptotically Distribution Free AMOS Analysis of Moment Structures AMR^Advanced Manifest Rule ASN Advanced Shipment Notice Bil^Billion BITSAFS^Bureau of Intelligent Transportation System and Freight Security CBP Customs and Border Protection CBSA^Canadian Customs Border Service Agency CCTV Close-Circuit Television CEO^Chief Executive Officer CFI Comparative Fit Index CN^Hoelter's Critical N CSCMP^Council of Supply Chain Management Professionals CSDs Container Security Devices CSI^Container Security Initiative C-T PAT Customs -Trade Partnership Against Terrorism DC^Distribution Center DSC Digital Signal Controller DSRC^Dedicated Short-Range Communication ECMT European Conference of Ministers of Transport EDI^Electronic Data Interchange FAA Federal Aviation Administration FAST^Free and Secure Trade FBI Federal Bureau of Investigation FCL^Full Container Loads FDA Food and Drug Administration FMCG^Fast Moving Consumer Goods GAO General Accounting Office xi GFI^Goodness-of-Fit Index GLS Generalized Least Squares GPS^Global Positioning System GSM Global System for Mobile communications IFI^Incremental Fit Index IMO International Maritime Organization Incoterms^International Commercial Terms ISPS International Ship and Port Facility Security ITS^Intelligent Transportation Systems JBL Journal of Business Logistics JoC^Journal of Commerce KPI Key Performance Indicator LCD^Liquid Crystal Display LCL Less-than-Container Loads Mil^Million Mgt Management ML^Maximum Likelihood NBC Nuclear, Biological, or Chemical weapons NDA^Non-Disclosure Agreement NFI Normed Fit Index OSC^Operations Safe Commerce PIP Partners in Protection PIR^Passive Infrared RFID Radio-Frequency Identification RMSEA^Root Mean Squared Approximation of Error ROI Return on Investment Sarbox^Sarbanes-Oxley Act SBU Strategic Business Unit SCA^Security Consent Agreement SCOR Supply-Chain Operations Reference SCL^Supply Chain Logistics Council SCP Supply Chain Performance SEM^Structural Equation Modeling SMS Short Message Service xii SOX^Sarbanes-Oxley Act SST Safe and Secure Trade Lane TEU^Twenty-Foot Equivalent Units TLI / NNFI^Tucker-Lewis Index or Non-Normed Fit Index TQM Total Quality Management U.K.^The United Kingdom U.S. United States of America ULD^Unit Load Device VDC Voltage Direct Current VMI^Vendor Managed Inventory WCO World Customs Organization WLS^Weighted Least Squares x2 Statistic^Chi-Square Statistic ACKNOWLEDGMENTS I would like to offer my enduring gratitude to Dr. Garland Chow, whose penetrating questions have taught me to question more deeply. Without his patient guidance and advice, his relentless support in the empirical work required for this study, this thesis would not have been successful. I am also grateful to Professor Trevor D. Heaver and Dr. Chunyan Yu for the care with which they reviewed the original manuscript, the conversations and the challenging questions that have all served to enlarge and clarify my thinking on my work in the field of transportation and logistics. I am equally indebted to Dr. Chris Dubelaar and Dr. Ronald T. Cenfetelli for their patient guidance on the statistical aspects of this thesis, especially with the use of the Structural Equation Modeling statistical technique. I would also like to offer my heartfelt thanks to the following groups of people. Without their valuable insights, suggestions and help, this study would not have been possible. \u00E2\u0080\u00A2 Danny, Rena and Edmund who has contributed their valuable time in helping to make the online survey a reality and a success \u00E2\u0080\u00A2 those who have been instrumental in making the field interviews a reality with special mention to Mr. Paul Tay in Shanghai \u00E2\u0080\u00A2 all participants in the field interviews from Singapore, Shanghai and Vancouver \u00E2\u0080\u00A2 all who have responded to this study's online survey I would also like to express my thanks to the faculty, staff and my fellow students at the University of British Columbia (UBC), who have in one way or another, inspired me to continue my work in this field. I also owe special thanks and deepest gratitude to my amazing parents and three wonderful sisters, who have given me their unconditional support and encouragement at critical and opportune times and basically in whatever I do. Special mention also goes to my twin sister Ashley for her great help on the Chinese translations and Sarah for proof reading and editing my final thesis. xiv to: my amazing parents and three wonderful sisters CHAPTER 1 INTRODUCTION Since the terrorist attacks on the U.S. soil on the 11 th of September 2001 (also commonly known as \"9/11\"), there has been tremendous amount of renewed interests in the study of risk management in supply chain management especially in the areas of trade security and safety. Since the tragic events of 9/11, there has been an influx of security regulations and mandates that include the Customs-Trade Partnership Against Terrorism (C-TPAT), the Container Security Initiative (CSI), the Advanced Manifest Rule (AMR) and the Free and Secure Trade initiative (FAST) from the public sector' and private organisations have been trying to keep pace in complying with these mandates. Public Effects of Security Investments The nature of the costs and benefits from security investments are such that they suggest public effects which are largely externalities to the private sector. Much of the expected benefits from improving security come from reduced danger and risks to human life and public properties. As such the public sector has been taking most of the initiatives in addressing trade security since the tragic events of 9/11. However, the responsibilities of ensuring secure trade movement are beginning to shift from the public to the private sector. Organisations are now tasked to make appropriate supply chain security investments to protect their assets and improve the security of their supply chain. However, the very existence of public externalities has raised much discussion within the private sector as to who should assume the cost of security investments. Organisations are finding it challenging to evaluate the many security initiatives and/or technologies and build business cases for them. This is because the nature of security investments is such that they do not directly increase revenues and they defy many traditional methods of calculating Return on Investments (ROI) if firms only consider cost avoidance. Moreover, the fact that certain investments in traditional supply chain operations such as visibility tools, can easily overspill to affect the security of a supply chain, makes it even harder for private organisations to isolate the benefits of security investments. 1 A study done by the Bureau of Intelligent Transportation Systems and Freight Security (BITSAFS) indicates that there are about 60 or more existing security related regulations in the United States and Canada. 1 Therefore, there needs to be a way to help organisations measure security performance so that they can use it to evaluate various security options and strategies and justify their investments accordingly. Performance Measurement for Security Investments Supply chain security performance as defined in this study is the overall confidence that the supply chain system will not be compromised, either as a target for terrorism and other criminal activities or as a vehicle to facilitate terrorist and other criminal activities. The purpose of this study is to identify a key set of performance measurements that most appropriately reflects the security performance of the operations of an international maritime supply chain. Having a \"common\" set of performance measures for security performance will enable managers and policy makers to compare and contrast security initiatives, programs and technologies and thereby help them to make better investment and policy decisions. Specifically, the study addresses the questions: \u00E2\u0080\u00A2 What are the key performance measurements for security performance of an international maritime supply chain, from the industry practitioners' point of view? \u00E2\u0080\u00A2 What is the relationship between security performance measurements and traditional 2 supply chain performance measurements? \u00E2\u0080\u00A2 What is the relationship between security initiatives and supply chain security performance? \u00E2\u0080\u00A2 What is the relationship between security initiatives and traditional supply chain performance? 1.1 Outline of Thesis Chapter 2 reviews the literature of risk management in supply chain management, particularly focusing on the security aspects of supply chain risks. This chapter includes a history of supply chain risk management and introduces some recent frameworks for thinking about and managing supply chain risks. This chapter then moves on to introduce a specific aspect of 2 Traditional supply chain performance measurements refer to those measurements that organizations commonly use to monitor their supply chain operations e.g. on-time deliveries, number of back orders per time period, information accuracy rates etc. 2 supply chain risk - security risks, and some of the ways that organisations both public and private, are currently employing to manage supply chain security risks. Chapter 3 briefly reviews the methodologies employed in this study, namely, (1) Field Interviews, (2) Internet and mail survey, (3) Factor Analysis and (4) Structural Equation Modelling (SEM). This chapter discusses the rationale behind the use of each of these methodologies in their respective stages of this research study, their advantages, disadvantages and limitations. Chapter 4 describes the data that is being used to investigate the primary questions of interests. The chapter describes the survey instrument used in the primary data collection, the respondent sample and provides some descriptive statistical analyses of the data collected. Chapter 5 presents the results from the factor and SEM analysis of the survey data and discusses the steps taken. The results are used to discuss the primary research questions of interests and hypotheses. Research Questions of Interest \u00E2\u0080\u00A2 What are the key performance measurements for security performance of an international maritime supply chain, from the industry practitioners' point of view? \u00E2\u0080\u00A2 What is the relationship between supply chain security performance measurements and traditional SCP measurements? \u00E2\u0080\u00A2 What is the relationship between security initiatives and supply chain security performance? \u00E2\u0080\u00A2 What is the relationship between security initiatives and traditional SCP? Hypotheses \u00E2\u0080\u00A2 The amount of an organization's security efforts is affected positively by how much impact on security performance the organization perceives the effort(s) will have. \u00E2\u0080\u00A2 The amount of an organization's security efforts is affected positively by how much collateral benefits the organization perceives the effort(s) will bring. \u00E2\u0080\u00A2 An organization's security efforts will positively affect their supply chain performance in terms of security. 3 \u00E2\u0080\u00A2 An organization's positive perception of the security impact of their security efforts will positively affect their self-perceived performance in the security of their supply chain operations. \u00E2\u0080\u00A2 An improvement in the security performance of an organization's supply chain operations will have a positive impact on traditional SCP. Chapter 6 concludes the study and addresses the contributions and limitations of the study, final thoughts and potential future research directions. 4 CHAPTER 2 LITERATURE REVIEW 2.1 Supply Chain Risks Risk pervades every aspect of our lives. Risk, in itself a timeless element, is defined in 1921 by Knight and in 1992 by Warren, as the complete knowledge of the potential outcomes of a given situation, the objective probability of the occurrence of each and their consequences. Deloach (2000) defines business risk as the level of exposure to uncertainties that the enterprise must understand and effectively manage as it executes its strategies to achieve its business objectives and create value (Norrman and Lindroth, 2004). The term \"supply chain\" describes an overall process that results in good being transported from the point of origin to their final destination and includes the movement of goods, the shipping data and the associated processes as well as a series of dynamic relationships (Peleg-Gillai et al., 2003). Supply chains exhibit risks in a variety of dimensions (Ritchie and Brindley, 2004). Within a supply chain network, there exist numerous participating stakeholders and hand-offs. The disparate nature of these stakeholders, their activities and interests, give rise to the many areas of vulnerability that are susceptible to negative impacts of events that might happen with or without certainty. A number of trends during the last decade have affected the supply chain risk situation. One is that the supply chain should be lean (Christopher and Towill, 2000; Towill and Christopher, 2003; Li et al.,2005; Cubalchini-Travis, 2006; Goldsby et al., 2006). Another is that it should be agile (Christopher, 2000; Christopher and Towill, 2000; Mason-Jones et al., 2000; Goldsby et al., 2006). A third trend is the evolution of sourcing strategies. Outsourcing resulted in more links in the chain. Single sourcing has increased an organization's supply dependence. Global sourcing takes advantage of lower product costs but has increased an organization's susceptibility to greater business uncertainty such as exchange rate fluctuations and longer lead times. All these trends are making supply chains more vulnerable to disruptions than they used to be. The essence of supply chain risk is the risk of malfunctioning. A supply chain network can malfunction as a result of events as mild as a one hour delay in supply of raw materials that are running out of stock or a recall of a particular model of cars because of a faulty speedometer to 5 as serious as a complete shut down or destruction of a transportation service due to a terrorist attack. Risk management in the realm of supply chain management is not new. However, several key developments have advocated the case for increased attention to the management of risk in supply chains (Ritchie and Bindley, 2004): i. Strategies and structure relating to supply chains are evolving more rapidly in the search for competitive advantage. Table 2.1 lists some of the common supply chain strategies that organizations are adopting today to build competitiveness into their customer fulfilment process. Table 2.1: Common supply chain strategies. Design Purchasing Manufacturing Inventory Mgt Distribution Facility Push/Pull Collaborate Lean VMI Inter-modal Lease vsOwn Outsource Consolidate Off-Shore Risk Pooling Cross-Dock NetworkDesign Multi Source Just-In-Time Decentralise Hub and Spoke Warehousevs DC Single Source Postponement VirtualInventories Deconsolidate Global Sourcing Mass Customise Reverse Auction Depending on the strategy(s) that an organization adopts, the organization exposes itself to various types of supply chain risks. For example, an organization facing competitive pressures to lower manufacturing costs may be prompted to outsource their manufacturing activities offshore. As a result, the organization's customer order fulfilment lead time is lengthened and they will have to assume greater capital risks due to the need to hold additional safety stock. The organization also runs the risk of non-supply should their supplier run into production problems and greater order fulfillment cycle time uncertainty due to a more extended supply chain. 6 ii. With the rapid advancement in telecommunications, Internet and its applications, technological changes provide opportunities to alter the shape and the relationships within supply chain networks. Technological advancements provide enormous opportunities for companies to revolutionalize their supply chain networks through enriching their supply chain operations with information and integrating stakeholders along the same supply chain. For example, the project to convert NMS Communications to an electronically integrated, demand-driven (build-to-order (BTO)) supply chain was made possible through an extensive integration of trading partners' information systems. The increased real-time visibility allows stakeholders in the supply chain to synchronize their activities, reduce cycle time, and eliminate large buffers of inventory.' For instance, the extensive information system integration allows suppliers to see the demand in real time and begin mustering the raw materials needed to respond quickly. iii. Increased exposure to global competitive pressures means that most organizations are exposed to new and additional risks that may impact more rapidly and with more severe consequences than previously. With the increase liberalisation in international trade and investments, organizations are experiencing mounting global competitive pressures. A tougher global playing field exposes organizations to disruptions not only on their home country but also those in other parts of the world. For example, the bird flu epidemic in China about four years ago brought chicken exports from China to the rest of the world to a sudden halt. Organizations around the world had to take immediate steps to either assure their customers of the supply source of their chicken meat or find alternative sources of chicken meat (if they had relied on chicken exports from China). Nonetheless, companies such as Kentucky Fried Chicken, who uses a large proportion of chicken meat on their menu, still experienced severe reductions in sales as a result of the bird flu epidemic in China regardless of whether they had relied on chicken exports from China or not. 3 Supply Chain Management Review, January/February (2002). 7 2.1.1 What Events Represent Supply Chain Risks? Supply chain risk is in essence the probability of a supply chain malfunctioning. Therefore any event or activity or action that can lead to the malfunctioning (be it permanently or temporarily) of an otherwise \"healthy\" supply chain, is one that introduces uncertainty and variability into the supply chain and they represent risks in supply chain management. There are many ways to perceive and classify risks. Since management attention is a scarce resource, an appropriate and simple approach to classifying risks is based on how manageable they are. Doherty (2000) defines risk quantitatively as both the range of possible outcomes and the distribution of respective probabilities for each of the outcomes. This is commonly referred to as the \"Expected Value\". Deloach (2000) classifies risks based on their sources into three categories \u00E2\u0080\u0094 (1) Externally-driven or environmental risk, (2) Internally-driven or process risk and (3) Decision-driven or information risk. Deloach (2000) also advocates that risk is dynamic and that risk categories are interrelated, meaning that some risk events could be sources or drivers of other risk events. JUttner et al. (2002) moved on to suggest that risk sources relevant for supply chains should be categorised into three categories \u00E2\u0080\u0094 (1) External to the supply chain, (2) Internal to the supply chain and (3) Network related. Although these classification methods highlights to management, the source or driver of a risk, it does not indicate how preventable (i.e. manageable) a risk is. Hiles and Barnes (2001) categorises risks into five core groups \u00E2\u0080\u0094 (1) Strategic, (2) Financial, (3) Operational, (4) Commercial and (5) Technical. Hiles and Barnes also indicate that these risk groups are not mutually exclusive. This classification method is based on where a risk has an impact. Although comprehensive in identifying the major areas of impact in a typical organization, this classification method does not guide management to the required or appropriate actions or efforts. Although dealing with geographical and social risks, Wolpert's 1980 work on risk management lends some insightful ideas to classifying supply chain risks. Wolpert (1980) analysed, by means of case studies, the risk management and prevention of catastrophe caused by institutional and technological hazards. He introduced the concepts of competency and dangerousness into the 8 discussion of risk management and talked about the effects of the degree of competency or knowlegeability on one's ability to mitigate the potential impacts of risks and disruptions. The ideas and academic contribution of these earlier works to classifying risks lead the author of this thesis to develop a framework that guides manager's supply chain risk management efforts according to how manageable (i.e. predictable and preventable) they are (see Figure 2.1). Figure 2.1: Risk classification framework. LowA Volcano Hurricanes^Earthquakes eruptions Market forces Terrorist activities P 2z c w> o.)a. High Plane crashs Forecastable variability in demand ^\u00E2\u0096\u00A0 High^ Predictability ^Low This classification framework consists of two dimensions. Both dimensions seek to determine how manageable a particular risk event is or will be. The first dimension (horizontal axis) is predictability of a particular risk. Wolpert, in his 1980 work on institutional and technological hazards and the mechanisms for risk management and prevention of catastrophe, advocated the importance of the means of predicting, controlling and managing such risks so that their impacts can be curtailed or reduced (Wolpert, 1980). Predictability therefore refers to, how reasonably a particular risk can be anticipated and whether there are reliable tools or processes in place to monitor and anticipate it, such as market research for new market penetration risks, monitoring rain and water levels for flood potentials? This is the ability of the company and/or manager to anticipate or determine the probability of a risk event occurring. As illustrated in Figure 2.1, events that are less predictable if not unpredictable, fall towards the right end of the x-axis and are events that are external to the organization. They are relatively if not impossible to predict. Rare events such as natural 9 disasters (e.g. earthquakes 4) and terrorist activities fall into this category. These events are usually catastrophic in magnitude and has either never occurred historically or occurs with such low probability that its next occurrence cannot be predicted (Wolpert, 1980). They therefore disturb our sense of competency and sense of security, stability and permanence and, thereby, threaten a very basic and elemental need and source of satisfaction (Wolpert, 1980). The other dimension (vertical axis) indicates how preventable a risk event is. This is similar to what Wolpert refers to as competency or knowledgeability. It therefore refers to one's ability to reasonably prevent or minimise the probability of a risk event occurring or the negative consequences of that risk event. Such competency or knowledgeability may be impacted by the existence or lack thereof of risk assessment capabilities. Therefore most of the risks that lie towards the bottom of the framework are either risks that are internal to organization (e.g. operational process risks) or risks that organizations can do something about to mitigate their negative impacts. These risks are usually man-made hazards (e.g. terrorist activities). As opposed to natural disasters, man-made disruptions can be typically subjected to the development of a logic structure which can be used to analyse the preventability of the rare event (Wolpert, 1980). 2.1.2 Managing Supply Chain Risks Different types of risks require different levels of management attention and management strategies. Although the study of risk management is not new, there are not many explicit definitions of supply chain risk management. Norrman and Lindroth (2002) defines supply chain risk management as the effort to collaboratively work with partners in a supply chain to apply risk management process tools to deal with risks and uncertainties caused by, or impacting on, logistics related activities or resources. Subsequently in their 2004 work on supply chain risk and risk management, Norrman and Lindroth proposed a conceptual framework that seeks to categorise supply chain risk management issues (both research and managerial) along three dimensions (see Figure 2.2). 4 \"Although there are successful theory such as plate tectonics to explain why earthquakes happen, scientists still can't say when an earthquake will happen.\" \u00E2\u0080\u0094 The National Geographic, April 2006, p. 126. 10 Type of Risk and Uncertainty Risk Management * Sharing * Transferring * Reducing * Avoiding Risk Assessment Figure 2.2: A framework for assessing and positioning supply chain risk issues. Business Continuity Management Risk and Business Continuity Management Process Risk Identification/ Analysis C. Single Logistics Activities Company Logistics Dyadic Relations Supply Chain Supply Network Strategic Uncertainties Operational Catastrophes Operational Accidents Unit of Analysis The first dimension is the logistics unit of analysis which seeks to define how complex the risk at hand is. The unit of analysis can range from a single logistics activity to the entire supply chain network, thereby taking into consideration the rippling effects for organizations in the same supply chain. The second dimension is the type of risk which seeks to define the nature of the risk in terms of whether it is an operational accident (e.g. collapse of a stack of block-stowed cartons and hurting a warehouseman), catastrophe (e.g. warehouse flooding, fires) or a strategic uncertainty (e.g. mergers and acquisitions, new market penetration). The third dimension is the stage of the risk management process, from risk identification and analysis to business continuity management. Source: Norrman and Lindroth (2004). The purpose of this framework is to help position different managerial actions or research contributions in supply chain risk management. However, it does not guide managerial decision making in terms of what efforts or strategies or type of actions to take in response to a particular type of or particular risk. Based on the proposed classification of the various types of risks in Figure 2.1, a more appropriate management decision guiding tool for supply chain risk management is shown in 1 1 Figure 2.3. The supply chain risk management framework in Figure 2.3 allows the management user to determine what type of managerial attention or strategies they should take in response to different types of risks. Figure 2.3: Supply chain risk management framework. \u00E2\u0080\u00A2 Unpreventable Preventable Measures to^Measures for avoid or mitigate^business continuity Measures to Measures to^prevent or for prevent quick response / reaction Predictable Unpredictable In response to a risk / disruptive event, an organization may adopt one or more strategies or actions. These strategies or action plans can be classified into four major categories, namely, (1) Prevent, (2) Quick response / reaction, (3) Avoid or mitigate and (4) Business continuity. These are explained and elaborated in greater details below. Linking the ideas illustrated in Figures 2.2 and 2.3, risks that are preventable and predictable include operational accidents such as the collapsing of a stack of block-stowed cargo, cargo pilferage, incorrect order picking etc. These are risks that one can be sure will occur if due diligence is not done to prevent them. The appropriate approach to managing such risks is to adopt or put in place preventive measures such as process monitoring and control mechanisms. For example, to prevent the negative impacts of receiving the wrong products, there should be tally checks during the inbound receiving process at the warehouse. Ti-Hi guidelines (that is, how many cartons per layer and how many layers to stack on a pallet) can be instituted to mandate how cargo should be safely block-stowed and close-circuit cameras (CCTVs) can be installed in a warehouse to deter pilferages. 12 Moving horizontally on the x-axis towards the other end of the continuum, risk events get more unpredictable and can include operational accidents such as an employee getting electrocuted due to carelessness, floods or catastrophes such as port closures due to terrorist activities or labour union strikes. Training and rigorous handling procedures may prevent carelessness but not eliminate or make accidents more predictable. Many of the process and infrastructural changes made by organizations seeking C-TPAT certification or shipping lines meeting the security requirements of the World Maritime Organization (WMO) seek to reduce the probability of successful terrorist incidents. For risks that are can be reasonably predicted although not with perfect certainty, one can undertake reasonable measures to prevent or respond quickly to their negative impacts. For instance, if a particular river is expected to flood every year during the monsoon season, an organization can either relocate its warehouse (that is, prevent) or set up barriers around the warehouse during the high-risk season to prevent flooding. For risks that are practically unpredictable or cannot be reasonably predicted but preventable such as terrorist events, organizations should have in place quick response plans such as evacuation for catastrophic disasters and exception management capabilities such as having alternative shipping routes or carriers in the event of port closures. They should also have in place robust risk assessment tools to competently reduce the dangerousness of such rare events. Moving diagonally across the grid, we have risks that are unpreventable but predictable and these risks usually refers to natural disasters such as volcano eruptions and hurricanes. They can also include strategic uncertainties such as interest rates changes by the Federal Reserve or a relatively obvious impending increase in the price of oil. These are events that can be reasonably predicted but one cannot prevent them from happening. As such, in response to such risks, organizations should undertake measures to either avoid (e.g. refrain from locating your facility near volcanic mountains or flood-prone rivers) or mitigate (e.g. undertake sound hedging options) their negative impacts. The top right hand corner of the framework illustrates risks that are both unpredictable and unpreventable such as earthquakes. Earthquakes are still one of the most catastrophic natural disasters that scientists are still unable to predict and such can be considered strategic uncertainties as well. For example, the Kobe earthquake on January 17, 1995, indirectly 5 brought about the collapse of United Kingdom's oldest investment bank - Barings Bank. The 5 Coupled with the unsupervised speculative trading of Nicolas Leeson, Baring's appointed manager of a new operation in futures markets on the Singapore international Monetary Exchange (SIMEX). 13 collapse of the World Trade Center on September 11, 2001 destroyed the extensive computer networks and databases of many international investment companies whose operations depends largely if not solely on these information systems. It also led to the immediate closures of all major ports and airports in the U.S., halting many international movements of cargo. For disruptive events such as these, organizations should have in place measures for quick operations recovery and business continuity such as backup for its organization-wide information technology systems. In summary, one can see that operational accidents, operational catastrophes and strategic uncertainties can fall anywhere on the predictability and preventability continuums. However, the more unpredictable a risk, the more catastrophic it's impact. Therefore, there is an essential need for organizations to be cognizant of the types of risks that their business operations are exposed to and take appropriate measures to manage them. 2.2 Supply Chain Security Risks Since the terrorist attacks on the U.S. soil on the 11 th of September 2001, there has been a tremendous amount of renewed interests in the study of risk management in supply chain management especially in the areas of trade security and safety. The U.S. is the largest trading nation in the world for both imports and exports. Accounting for nearly 20% of world trade in goods, the combined value of US imports and exports of goods in 2004 was approximately US$2.23 trillion s. It is therefore small wonder why the terrorist attacks in New York and Washington in 2001, have created an unprecedented sense of urgency for all governments of countries worldwide which are engaged in international trade to look into improving international trade security, especially in terms of the physical movement of cargo. Coupled with recent series of security breaches and disruptions that threaten the national security of many countries, such as the Madrid bombing in 2004, the Asia tsunami in December 2004 and the London attempted bomb attempt in 2005, business managers throughout the world have recently become more sensitised to the vulnerability of their supply chains. As 6 Statistics from the World Shipping Council at http://www.worldshipping.orci . 14 described by former U.S. Customs and Border Protection (CBP) Commissioner' Robert Bonner, \"A terrorist attack using a container to conceal a so-called dirty bomb...could probably stop global trade in its tracks unless we have a maritime security system that can detect and deter such an attack.\" (Langhoff et al., 2005). 2.2.1 What are Supply Chain Security Risks? Security as the word is defined means: \u00E2\u0080\u00A2 freedom from risks or danger (i.e. safe), \u00E2\u0080\u00A2 freedom from doubt, anxiety or fear (i.e. reliable) \u00E2\u0080\u00A2 or measures that give or assure safety and prevent sabotage or attacks or other forms of criminal activities. Security risks or security breaches are a subset of supply chain risks and are those events that threaten the safety, reliability and flexibility of the supply chain or its constituent parts. It includes mainly but not limited to, events such as contraband smuggling, theft of goods and vehicles, fraud, illegal immigration, drug smuggling, potential targeting of dangerous goods shipments and the targeting of transport vehicles and infrastructure by terrorists and last but not least, the use of one's supply chain as a delivery vehicle for chemical, biological, radiological or nuclear (CBRN) weapons. Using the risk classification framework in Figure 2.1, security risks are classified as unpredictable but preventable (see circle in Figure 2.4). As noted by Wolpert (1980), one of the major distinctions between man-made rare events which can lead to catastrophe and the natural hazards is the notion that the event is possibly preventable. This is because as mentioned earlier, man-made or institutional hazards are typically subjected to the development of a logic structure which can be used to analyse the preventability of the rare event. Risk assessment methods such as fault-tree analysis, can be and have been used to establish a classification of some potential accident sequence and permit identification of procedures for estimating risks associated with these sequences (Wolpert, 1980). Also, depending on the effectiveness of the security measures and/or technologies adopted, these risks can reasonably be expected to be preventable. 7 On 6 June 2006, W. Ralph Basham has sworn in as the new CBP Commissioner. 15 Figure 2.4: Positioning security risks. \u00E2\u0080\u00A2 Unpreventable Security Risks : Terrorist and other criminal activities Preventable Predictable Unpredictable These illegal activities pose serious daily problems for authorities and can have important impacts on a supply chain's ability to fulfill the 7R's 8 (Right product, Right place, Right time, Right quantity, Right condition, Right cost, Right customer) of supply chain operations. 2.2.2 Classification of Supply Chain Security Risks Combining and summarising the classification ideas and perspectives mentioned earlier, there are several ways of classifying supply chain security risks (see Table 2.2). Table 2.2: Classifying security risks. Classification Description By nature of the security risks \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 Controllable / uncontrollable Internal / external Human Inflicted / Natural Disasters \u00E2\u0080\u00A2 \u00E2\u0080\u00A2 Demand security (unexpected surge in demand due to a security threat) Supply security (unexpected cut in supply due to a security threat) \u00E2\u0080\u00A2 Conveyance security (unexpected denial of conveyance due to a security By the supply threat) chain \u00E2\u0080\u00A2 Information security (loss of access or theft of important information due to a management area security threat) that the risk is \u00E2\u0080\u00A2 Financial security / cash flow security (loss of access to funds due to a impacting security threat) \u00E2\u0080\u00A2 Operations security (loss of ability to operate or continue business due to a security threat) \u00E2\u0080\u00A2 Human resources security (loss of or loss of access to manpower due to a security threat) 8 Page 6-7, Coyle et al. (1992). 16 Table 2.2 (continued): Classifying security risks. Classification Description \u00E2\u0080\u00A2 Destroy (unrecoverable) By type of impact \u00E2\u0080\u00A2\u00E2\u0080\u00A2 Disrupt (short term recoverable) Paralyses (long term recoverable) \u00E2\u0080\u00A2 Slight tremors (immediate term recoverable / unaffected) \u00E2\u0080\u00A2 Prevent By types of \u00E2\u0080\u00A2 Quick response / React reaction necessary \u00E2\u0080\u00A2 Avoid \u00E2\u0080\u00A2 Mitigate 2.2.3 The Public Sector's Take on Supply Chain Security \"For the first time in our nation's history, one agency has the lone responsibility for protecting our borders. As the single, unified border agency, CBP's mission is vitally important to the protection of America and the American people. CBP's priority mission is preventing terrorists and terrorist weapons from entering the United States, while also facilitating the flow of legitimate trade and travel.\" - Robert C. Bonner Commissioner of U.S. Customs and Border Protection (CBP) Sheffi (2001) noted that much of the disruptions to the private sector after the 9/11 attack were not caused by the attack itself, but rather by the government's response to the attack \u00E2\u0080\u0094 closing borders, shutting down air traffic, and evacuating buildings throughout the country. Therefore since 9/11, the public sector, especially in the U.S., has taken unto itself a lot of initial responsibilities for instituting measures to improve national security 9. With the responsibility to protect the public and their interests, the U.S. Federal government has taken steps to improve national security in the following ways'''. \u00E2\u0080\u00A2 Improved their radiation detection capabilities by deploying 10,400 Personal Radiation Detectors to their officers and agents, more than 274 Radiation Portal Monitors to ports of entry, and in excess of 60 Radiation Isotope Identification Detection System to Border Patrol field locations. 9 http://www.cbp.gov. 10 \u00C2\u00ABExecutive Summary CBP Actions Taken Since 9/11\u00C2\u00BB, word document posted on September 17, 2004 at http://www.cbp.gov/xp/cgov/toolbox/about/accomplish/. 17 \u00E2\u0080\u00A2 Improved inspection capabilities by deploying 87 additional non-intrusive inspection systems to detect terrorist weapons in vehicles and cargo. \u00E2\u0080\u00A2 Improved remote monitoring, detection and illegal crossing response capabilities by increasing the use of remotely monitored cameras and sensing systems, aircraft, helicopters and unmanned aerial vehicles. \u00E2\u0080\u00A2 Improved selectivity, screening and targeting by establishing the National Targeting Center as the centralized coordination point for all CBP's anti-terrorism efforts and implementing the 24-Hour Rule in December 2002 to obtain advance information to screen and assess all cargo, passengers and high risk imported food shipments before arrival into the United States. The government also made efforts to work with the private sector and governments of other countries by establishing the C-TPAT program to emphasize a seamless security conscious environment throughout the supply chain and the CSI program to target and screen containers prior to them being loaded onto vessels destined for the U.S. New security measures following the 9/11 events, are estimated to cost the U.S. economy alone over US$150 billion, of which US$65 billion is for changes in supply chains (Bernasek, 2000; Damas, 2001). Internally, the government also made efforts to restructure themselves in order to better respond to any form of security breaches especially terrorist attacks. Since 11 September 2001, the U.S. government has successfully integrated four different organizations from three different departments into CBP. They have subsequently converted more than 18,000 Customs, Immigration and Agriculture Inspectors to two new positions \u00E2\u0080\u0094 Customs and Border Protection Officer and Agriculture Inspector, thereby fully integrating the inspectional functions of CBP's legacy inspectors. However, despite all these efforts, to date, the public sector still views supply chain security as pretty much the responsibility of the private sector. Governments have in essence 'contracted' out some responsibility in managing supply chain security to the private sector, in hope that the private sector can come up with innovative solutions (Chow et al., 2006). This can be seen from a couple of the key security regulations that they have since developed to counter terrorism and other acts of security breaches. 18 First, it's asking the private sector to assume legal responsibility for their supply chain security. Legally (and pre-9/11), an organization is responsible for a container only when it formally purchases it, which; precisely for that reason; usually doesn't occur until it reaches the destination port, either in the U.S. or abroad (Worthen, 2006). However, since the September 11 attacks, the government has instituted the C-TPAT program, which mandates importers to take responsibility for everything that occurs prior to purchase, even if the container is in the custody of a trucker in China or a longshoreman in Panama. The program is still very much voluntary and gives certain benefits, such as reduced inspections, to organizations that are able to show that they meet a minimum level of supply chain security. C-TPAT seeks to certify known shippers through self-appraisals of security procedures coupled with Customs audits and verifications (Closs and McGarrell, 2004). There are currently three tiers of C-TPAT compliance, and containers belonging to members in the top tier sail through Customs virtually un-inspected. The first level simply requires an attestation that the company has performed a risk analysis of your supply chain and has taken steps to mitigate any vulnerabilities. By far, 5,757 of these attestations have been accepted by the U.S. Customs (Worthen, 2006). The second level requires that members have this attestation validated by Customs officials and so far, 1,511 organizations have achieved tier-two. Tier-three members are organizations that the U.S. Customs has determined to follow supply chain security best practices (although the U.S. Customs has not yet defined any) and these organizations are eligible for the Green Lane (Worthen, 2006). As of March 2006, only 126 organizations have qualified for this level, including Boeing, General Motors and Target. Second, the public sector requires organizations to put in place reasonable safeguards against events that could materially affect the organization's value. The principle vehicle for this is the Sarbanes-Oxley Act (commonly known as SOX or Sarbox). Third, the introduction of the Advanced Manifest Rule (AMR) and the more recent Advanced Commercial Information (ACI) requires shippers to submit detailed cargo data before the cargo is brought into U.S. and Canada respectively, by ocean, air, rail or truck. Since information needs to transfer from the private organization to government authorities in a timely manner, compatibility in technological standards is very important. 19 Despite all these compliance requirements, to date, the public sector has yet to make any clear indications in terms of the future standards of security technology and practices. 2.2.4 The Private Sector's Take on Supply Chain Security The influx of compliance requirements may have pushed many organizations to step up on their supply chain security efforts but the compliance theory does not serve to fully account for the private sector's hesitation in investing in supply chain security for their self-interests. Rice and Spayd (2005) and Langhoff et al. (2005) has indicated that although there is a clear need for increased security in global supply chains and organizations are tasked to make appropriate supply chain security investments\" to protect their assets and operations for their own private interests, there has been much hesitation among industry players. And there are several key reasons for this phenomenon. Firstly, the nature of the costs and benefits from security investments are such that they suggest largely public effects which are externalities to private interests. Security improvements or lack thereof, come at a cost. A private-sector analysis conducted by the International Monetary Fund (IMF) estimates the increase to business costs due to higher security costs at $1.6 billion per year, the extra financing burden of carrying 10% higher inventories at $7.5 billion per year. 12 Another study estimates an increase in commercial insurance premiums of 20% at about $30 billion a year (Pelg-Gillai et al, 2003). 13 The results and conclusions from these studies also suggest that the private sector seems to consider holding additional safety stock and increasing insurance coverage as measures to improving security in their supply chain. If this is so, it is then small wonder that the private sector sees little \"natural\" business incentives to undertake more direct and sophisticated security improvements such as container tracking technology and electronic seals and undertake them out of self-interests. 11 Supply chain security investments range from capital equipment, human resources, process changes and/or improvements and operating expenses for a range of activities including physical security improvements, monitoring and incident investigation. 12 IMF Website, \"World Economic Outlook: The Global Economy After September 11.\" December 2001. http://www. imforg/external/pubs/ft/weo/2001/03. 13 UBS Warburg, 2001. 20 The lack of public sector's directions for standards amidst of the influx of technologies only serves to make matters worse. The general lack of standards (especially for technology) and international jurisdiction is validated by the 2005 study done by Langhoff et al., which conducted multiple workshops with key industry stakeholders. The study found that although key industry stakeholders such as customs brokers, logistics service providers and shippers, feel that the International Ship and Port Facility Security (ISPS) code, World Customs Organization (WCO) framework, and the U.S. CBP's security pillars (i.e. CSI, C-TPAT and Advanced Trade Data) provide the right foundation to build a secure system of trade, improved execution needs to follow. And the public sector must lead and articulate a clear vision or the private sector will continue to delay investments in security. Another reason for the private sector's hesitation is their difficulty in calculating the Return on Investment (ROI) for security investments (Closs and McGarrell, 2003; Rice and Spayd, 2005; Peleg-Gillai et al., 2006). Traditional ROls of business investments focus on cost savings or avoidance but this is certainly not the case for security investments. This is because security improvements cannot be assessed for their effectiveness until something bad happens while the very purpose of investing in security initiatives is to prevent something bad from happening. And in most cases, other than theft reduction where there is tangible evidence of improvements when loss levels are reduced, it is difficult to measure the cost of a security breach or disruption that did not occur (Rice and Spayd, 2005). Besides there is also currently no established or recognized way of measuring supply chain security performance. Without the ability to measure what one is trying to improve, organizations are finding it hard to build a business case for supply chain security investments. Although some focus was given to the importance of customs cycle time in the latest version of the Supply-Chain Operations Reference (SCOR version 8.0) model, the security dimension has not been incorporated into its performance metrics and best practices. And since SCOR is developed by a large team of private sector personnel and executives, this could suggest that security is still not considered as an important element in supply chain management benchmarking and best practices. In addition, the fact that certain investments in traditional supply chain operations such as visibility tools, can easily spill over to affect the security of a supply chain, makes it even harder for private organizations to isolate the benefits of security investments. The ROI for one 21 organisation's security investments is a function of the spill-over effects from the security investments from the other players operating in the same supply chain. As Closs and McGarrell (2004) puts it \"Not only must firms be concerned about security procedures within their own processes and those of first-tier suppliers, but also they are dependent on the security procedures throughout the entire supply chain\". This also creates \"free-rider\" problems wherein those who do not invest can still benefit (Willis and Ortiz, 2004). Therefore, one can see that despite having a common goal to conduct trade and business securely, there are considerable discrepancies between how the public sector and private sector views supply chain security investments and initiatives. For the profit-driven private sector, although they face the challenges of preparing for another attack, managing supply chains under increased uncertainty and increased complexity in their relationships with the government in this new era, the self-interest theory still has it that there clearly needs to be stronger incentives (be it monetary or non-monetary) for security investments. And the public sector as the authority with the ultimate jurisdiction should work jointly with the private sector, to look into how best these incentives can be provided or created. 2.3 Managing Supply Chain Security Risks To manage supply chain risks is to become informed about security hazards, to know and be able to make good decisions and/or take appropriate actions to avoid, prevent and/or mitigate them. Supply chain managers therefore need to adopt a range of strategies from preventive to reactive / repair measures (refer to Figure 2.3). An effective response to security threats and breaches thus involves a number of steps. First, taking preventive measures such as: (1) predicting actions through intelligence such as an appropriate adoption of intelligent freight information technologies that will allow the organization to track and be alerted in advance of any forms of intended foul play, (2) preventing actions by containment through the institution of necessary monitoring and control mechanisms and ensuring compliance with various security regulations, (3) protecting targets by enhanced physical measures and (4) interdicting attacks as they occur. Next, taking reactive / repair measures such as: (1) responding post-attack to minimize damage and disruption through having business continuity action plans and (2) identifying the perpetrators of attacks to support targeted retaliation. 22 2.3.1 Mitigating Supply Chain Security Risks Langhoff et al. (2005) also found the following from their analysis of container movements and workshops with key industry stakeholders: \u00E2\u0080\u00A2 Leave the container alone. Most technologies are not commercially viable and Container Security Devices (CSDs) 14 are the only viable container technology in the near-term \u00E2\u0080\u00A2 Stakeholders agree that improved information sharing and profiling are the most important security controls \u00E2\u0080\u00A2 Overseas commercial intelligence must be integrated and shared across the private and public sectors... There is no easy solution, silver bullet technology, single policy or regulation that can comprehensively address this challenge. Supply chain security can only be achieved through practical solutions and effective collaboration between public and private sector stakeholders (Langhoff et al., 2005). Gloss and McGarrell (2004) advocates that government agencies responsible for the movement of goods and people across borders must continuously review and update security procedures with the goal of enhancing both security and efficiency. This includes balancing the essential governmental obligation to protect citizens with the critical role of promoting economic viability through trade. Private sector's security improvements must also go beyond the organization itself and extend throughout the supply chain (Closs and McGarrell, 2004). The improvement focus should also be global, with the goal of expanding the number of trusted partners to enhance global trade. Complying with Security Regulations An organization's first step to improving supply chain security is to ensure compliance with any mandatory security regulations. Ensuring compliance and requiring compliance from other partners in the supply chain also helps build the necessary trusted partner network for an organization's supply chain. This is a new business reality and stakeholders in the supply chain and transportation sector cannot afford to take a lax approach towards compliance. 14 CDSs reside on the inside of the container and detect unauthorized breaches or openings of container door. They communicate via hand-held or fixed readers over a given wireless range (Langhoff et al., 2005). 23 The events of 11 September 2001 in New York and Washington has served as a catalyst for a new wave of heightened security measures at international, national and local levels (ECMT, 2005). These new measures have been designed to take stock of the security weaknesses revealed in the 2001 attacks; specifically, they aim to minimize terrorist threats, share good practices and assess necessary technical, legal and legislative adjustments to ensure maximum protection from terrorist activity in transport (ECMT, 2005). The public sector's efforts in countering security breaches in the transportation sector primarily aim to reduce the \"haystack\" (i.e. the number of suspicious containers that they will need to inspect). The importance of security in the current regulatory environment cannot be overstated (Chow et al., 2006). There are many new security regulations today and some overlap. Some pre- September 11 programs have also either been fully decommissioned or have been integrated into new programs. Of the current 38 new security regulations related to international trade movement (Chow et al., 2006), 17 of them were initiated by the U.S. CBP, two initiated jointly by the U.S. CBP and the Canadian Customs Border Service Agency (CBSA) and Immigration Canada, four initiated by the CBSA, three initiated by the International Maritime Organization (IMO), four initiated by the U.S. department of homeland security and eight by other stakeholders in the community such as port terminals and other federal departments in the U.S. government' s. Many of these regulations and initiatives seek to increase data collection and availability and security monitoring. Chow et al. (2006) contains details of these regulations and their implications on supply chain management. Ensuring corporate-wide compliance with these measures has now become an imperative for organizations engaged in international trade (in one way or another) especially with North America and taking this first step will, at the very least, ensure that an organization's supply chain flow will not be unduly delayed. Even so, there are advocacies against compliance with these mushrooming new regulations. Instead of helping organizations move towards more secure networks, Piazza (2006) advocates that complying with these regulations may be having the opposite effect. This is similar to the concept of risk tradeoffs analysis commonly known in the healthcare industry where regulations undertaken to minimize or eliminate certain health risks often have the perverse effect of 15 Other organizations include the Food and Drug Administration (FDA), the Department of Defense, the Transportation Security Administration within the Department of Homeland Security, Federal Aviation Administration (FAA) and the Federal Bureau of Investigation (FBI). 24 promoting other risks (Rascoff and Revesz, 2002). Viscusi and Gayer (2002) writes about how health and safety regulations have often fallen short of any reasonable standard of performance and how economic findings with respect to risk-risk tradeoffs highlight the fallacies inherent in a zero-risk mentality. Rather than focusing regulations on instances of market failure, the emphasis is- on reductions of risks irrespective of cost (Viscusi and Gayer, 2002). Health and safety regulations that have the current inordinate imbalance between costs incurred and risk reductions achieved divert society's resources from a mix of expenditures that would be more health enhancing. Similarly in supply chain security regulations, certainly more time is being spent on compliance than ever before. In terms of physical security, several publications have mentioned that despite the efforts spent on security thus far in terms of compliance are not making their supply chains any more secure than before. In her letter to The Council of Ministers at the Council Working Group September 4-5, Tina Sommer, President of the European Small Business Alliance said \"We are concerned that the struggle to defeat terrorism, which we all of course support, is being misused to create a heavy-handed and bureaucratic system that will put many people out of work without actually increasing security.\" Tom Gould, a C-TPAT consultant with the Zisser Group in Los Angeles also said \"I'm talking to people all the time who make comments like \"We're no more secure than we were before 9/11.\" (Edmonson, 2006). Another cargo industry executive was quoted saying \"Shutting down our commercial supply chains is one of the goals of terrorists. Wouldn't some of these legislative proposals do exactly that?\" (Page, 2006). In an e-mail poll done by Journal of Commerce (JoC) to subscribers, when asked to rate the probability of such an attack on a scale of 1 to 10 16 , 30% rated the probability at 5 and above. Only 3% rated it 1 (Edmonson, 2006). In terms of information security, a survey done by Forsythe Solutions Group on 100 senior IT and data security professionals at Fortune 1000 companies across the U.S. found that 43% of respondents cited legislation-induced triumvirate of policy, process and procedures as their top priority. And majority of the respondents cited that they have or are in the process of planning for encryption, enhanced security awareness programs, and updating incident response plans and authentication processes. However, 28% of the respondents cited that they have little or no confidence that they had detected all significant security breaches in the past year and rated their current IT environment as more vulnerable than a year before. This, according to John 16 Where \"1\" corresponds to 0% probability and \"10\" correspond to 100% probability. 25 Kiser, CEO of Gray Hat Research Corporation, may be a sign that time or money spent on ensuring compliance to top management are resources taken away from other crucial security tasks. But it is also important to note that the current governmental regulation evaluation tools, known as \"regulatory scorecards\" may be fundamentally flawed in themselves. Parker (2003) demonstrated how three regulatory scorecard studies 17 are fundamentally flawed in terms of their use of undisclosed data and non-replicable calculations, biased regulatory samples, misrepresentation of ex ante guesses about costs and benefits as actual measurements and grossly underestimation of benefits, exclusion of all unquantified costs and benefits and disregards for all questions about the fairness of the distribution of cost and risk. Due to their fundamental flaws, Parker (2003) advocates that these studies prove nothing about the rationality of regulations. Employing Intelligent Technology According to Caton (2004), government agencies acting under the premise that they are protecting the U.S. from terrorism, are developing requirements that do little for security but will have a serious impact on foreign trade. Each agency has a specific responsibility, yet many of the regulatory issues overlap. The result is confusion that will do more harm than good for the US economy. Paper security (that is, by simply providing more information about the shipment) is relatively insignificant and can be easily circumvented. Therefore, any plan that does not include more physical inspections, along with the use of more sophisticated detection devices, is only as good as the paper it generates. The only real protection against terrorism is using advanced, strategically re-engineered technology to detect potential harm and to provide alerts. Along with the heightened emphasis on secure trade movement is an influx of intelligent transportation systems, which seeks to enhance the secured movement of freight while improving freight movement efficiency. These technologies can be generally classified into five major categories based on their primary purpose/function \u00E2\u0080\u0094 (1) Detection, (2) Sensoring / Identification and Monitoring, (3) Locking and Securing, (4) Access Control and Personnel 17 Parker (2003) cites: A study by John Morrall, an OMB economist, claims that government regulations cost up to $72 billion per life saved. Another study, co-authored by Bush's regulatory \"czar,\" John Graham, claims that over 60,000 people lose their lives each year due to irrational government regulation. A third study by Robert Hahn of the AEI-Brookings Joint Center for Regulatory Studies claims that over half of all major regulations issued since 1981 fail cost-benefit tests. 26 Security and (5) Backup and Protection. Most if not all of these intelligent transportation systems claim to enhance the security of an international supply chain while improving its efficiency. Table 2.3 provides some examples consolidated from volume 50, issues 4 to 6 of the Security Management magazine. Table 2.3: Examples of freight security technologies. Category Name Description of Capabilities Application Detection Mobile NBC Reconnaissance Robot - highly perceptive sensors - determine type and concentration of gases while simultaneously transmit video images from location to a control center Container inspection at port or other container rest points. MVXR5000 Multi-View X- Ray (for Explosives Detection) - provides enhanced image and dual energy x-ray images enabling automated detection of explosives materials - process up to 1,800 bags per hour In line hold baggage system OmniView Gantry Inspection System - scanning platform operates by moving on rails past stationary vehicles and cargo - compact footprint accommodates limited space in congested areas and minimise radiation zones - bi-directional, multiple views. provides high energy penetration of densely loaded cargo Detecting security threats and contraband in cargo and vehicles Sensoring and Identification / Monitoring Exit Sensor - combines radar motion sensing and lens passive infrared (PIR) technologies - uses physical motion and heat to trigger device, thus resisting common attempts to defeat sensors using only PIR. - limits duration door can be opened Facilities containing highly sensitive information, cargo or materials. IP Video \u00E2\u0080\u0094 Omnicast 4.0 - enables citywide video surveillance by managing multiple independent systems from numerous organizations as a single, unified security system, real time LifeTrak Real- Time GPS Tracking System - reports time, location, speeding violations and ignition on/off for vehicles in real time for effective management of cars and trucks - GPS, 24/7 control center monitoring, notifications to cell phones or email of unauthorised usage and optional real time messaging between dispatchers Fleet management and theft prevention and facilitates recovery of stolen vehicles 27 Table 2.3 (continued): Examples of freight security technologies. Category Name Description of Capabilities Application Sensoring and Identification / Monitoring secureCam (housing for CCTV) - made of heavy gauge stainless steel - protects preset bearing with tamper resistant bracket mount. withstands hurricane-force winds, torrential rain and corrosive environments Protect cameras at terrorist targets and high-crime locations Sensoring and Identification / Monitoring RoomGuard - installed in a room and constantly monitors for illicit listening devices by detecting unusual radio frequency activity - can work online/offline. Using distributed intelligence, monitor several rooms simultaneously over a network or remotely Facilities that are potential terrorist targets or in high- crime locations ASI 2000 Security Integrator Version 3.11 - includes new audit capabilities for improved user accountability, database partitioning options for restricted viewing of cardholder records, a new hot key for instant access to frequently used transaction activity screens and a real- time master report Combi-Booster LEGiL (auto long-range vehicle identification) - in-vehicle mounted device based on RFID smart card technology - using directional beam, can identify vehicles up to 10m away at high speeds and solve multilane, entry and exit reader challenges encountered in parking lots and secured areas Control vehicle access to facilities/gated areas such as air and sea port. Use for automated parking payments, fleet management, and toll collections Lock / Secure Electric Lockset (for doors) - offers a choice of failsafe or failsecure mode. clutch for vandal resistance and dual 12 and 24 Voltage Direct Current (VDC) power input - assess control or key entry Securing container at origin or sensitive handoffs. NO-REZ Security Seals - printable and adaptable to die-cutting adhesive seals that detect tampering without leaving residue on the container - when seal is tampered with, it displays the message \"VOID OPEN VOID\", informing inspectors that a break-in has occurred - can be used with most conventional label dispensing devices and in conjunction with other sealing products Single-use decals, such as parking validations, and seals for data ports, envelopes, and documents 28 Table 2.3 (continued): Examples of freight security technologies. Category Name Description of Capabilities Application Personnel Security / Access Control Visitor Signature Tablet - preconfigured for use with visitor management solutions - interactive LCD to capture signatures - programmed to automatically display NDAs la , SCAs 19 and other notices Facilities containing highly sensitive information, cargo or materials MAPSANDS - modular perimeter security and non- lethal defense system - includes software, wireless communications, remote power systems, detection and tracking sensors, directed energy acoustics and a suite of non- lethal munitions - relies on advanced radars to detect and track intruders and aim acoustic devices that deliver clear verbal warnings and aversive warning tones Secure perimeters that range from < 1 mile in length to several hundred continuous miles e.g. sovereign borders, power plants, pipelines, seaports and other high value facilities Iris on the Move (biometric identification) - powerful, accurate and reliable capture of subject's iris image while in motion - allows up to 20 subjects per min Facilities with highly restricted access Backup / Protection DSC GSM universal wireless alarm communicator - connects alarm control panel to the GSM network. When alarm is triggered, the communicator assesses its connections to the phone line. If line is disrupted, it connects to GSM network to send an alarm signal to central monitoring station - operate as an SMS dialer to automatically dial up to 8 phone numbers to deliver alarm message - can control externally connected devices such as lights and powered gates via SMS messaging though cellular phones Backup to traditional phone lines against accidental line cuts caused by storms, construction, or tampering Mobile Guard Shelter - bullet-resistant booth mounted on a double-axle, heavy-duty trailer. - equipped with a rooftop air conditioning unit and a platform-mounted generator to create an immediate security checkpoint. For trailers on long hauls deliveries A report \u00E2\u0080\u0094 Review of ITS Technologies with Application to the Security and Efficiency of Cross- Border Freight Movement, by Chow et al. (2006) contains a comprehensive review of available intelligent transportation systems for secure freight movement. Specifically, the study reviewed 18 Non-disclosure Agreements. 19 Security Consent Agreements. 29 custom trade compliance systems, pre-screening and pre-processing systems, in-bond cargo systems, and supply chain cargo tracking systems. It also examined the technologies that are used to support these systems, namely, electronic data interchange (EDI), web-based interfaces, radio-frequency identification (RFID), dedicated short-range communication (DSRC), transponders, e-seals, global system for mobile communications (GSM), global positioning system (GPS) and risk assessment systems. Instituting Secured Processes (TQM Concepts) Regardless of the type of freight security technology used, the security efforts in a supply chain can only be as effective as the process of freight movement itself. Some of the principles of total quality management (TQM) can and should therefore be applied to guide an organization's efforts towards creating a secured supply chain (Lee and Wolfe, 2003). Table 2.4 lists the features of TQM. Most if not all of the TQM principles listed in Table 2.4, should be applied to an organization's efforts for continued improvement in freight movement security. First and foremost, the goals and values for a secured supply chain should be provided and championed by top management, who must recognise that security is a long term strategy and any analysis and decisions should be at the group / organization level. The employees within the company should then be provided with the necessary skills and tools, guidelines and empowerment to innovate and implement security best practices. Measurement, monitoring and benchmarking should also be in place to ensure operational effectiveness of any security efforts. Last but not least, efforts should also be invested to archive the security knowledge and best practices to facilitate transfer of knowledge and continuous learning. In summary, global logistics security systems can learn form the quality movement by focusing on \"prevention\" and adopting the \"total supply chain\" approach (Sheu et al., 2006). 30 Table 2.4: TQM features. Sub Systems Basic Variables TQM Features Governance Time perspective Medium / long term Level of analysis Group and organization Empowerment Oriented to improvement of customer service Decision-making focus Tending towards perfect rationality Innovation Continuous and incremental changes Objectives Priority given to efficiency Orientation of the culture People / employees as a resource Content of the culture Professional development Goals and Values Origin of the shared vision Provided by the leader Content of the shared vision Specific and oriented towards quality in a general sense (multiple dimensions of quality) Achievement of excellence Styles of learning Implicit and adaptive (single loop learning) Transfer of knowledge Exploitation of professional knowledge Psychosocial Processes associated with learning Intuition (expert) Interpretation (specialist) Integration (formal) Institutionalisation Consideration of mental models Implicit Type of structure Organic Linking mechanisms Expert coordination Structural Team working Improvement teams and quality circles Cause-effect analysis Static and more effective at the operational level Focus of anticipation of customer needs Explicit Operational Critical techniques Quantitative, analytical, positive Analysis and diagnosis Emphasis on retrospective approach (measurement, self monitoring, benchmarking) Source: Ferguson et al. (2005). 2.4 Security Risks in an International Maritime Supply Chain It is estimated that as many as 25 different parties are involved in the global movement of a container (buyers, sellers, inland transportation service providers, ocean carriers, middlemen such as customs brokers and banks, government) (Russell and Saldanha, 2003; Sheu et al., 2006). As products and information travel through those parties, the potential increases for loss of information, damage to products and delay. Companies operating within this complex network also experience more complex barriers including documentation requirements, transportation modes, information processing and varying regulations (Sheu et al., 2006). For instance Cassidy (2003) cited that a typical cross-border transaction might involve filing 35 31 documents, communicating with 25 parties and complying with more than 600 laws and 500 trade agreements. The ocean transportation supply chain, with its many stakeholders and handoffs, therefore exhibits many of the security risk issues and characteristics mentioned above. 2.4.1 Relative Importance of Maritime Transportation There are more than 2,000 ports in the world, from single berth locations handling a few hundreds tons a year to multipurpose facilities handling up to 300 million tons a year. More than 80% of international trade with origins or destinations in developing countries, in tonnage, is enabled by ocean conveyance 20 . The U.S. alone operates about 15% of all the ports in the world. Of the combined value of U.S. imports and exports of goods in 2004, approximately US$948.7 billion was international trade moved via ocean conveyance arriving at or departing from U.S. ports. And US$521.4 billion, or 55% of that, was containerized cargo carried on liner vessels. This averages out to about US$1.43 billion worth of containerized goods moving through U.S. ports each day. Additional waterborne U.S. imports and exports worth roughly US$30 billion were transshipped via Canadian and Mexican ports. As at the beginning of 2005, the worldwide fleet of ocean containers in circulation is estimated to be about 13 million, with overall capacity of approximately 20 million Twenty Foot Equivalent Units (TEUs). 21 It is estimated that there are more than 4 million containers in use at any given time in the U.S. trades. 22 In 2004, more than 23.5 million TEUs of containerized cargo were imported or exported from the U.S. on roughly 1,050 different individual containerships making more than 18,000 total port calls. 23 20 Statistics from http://www.ibm.com 21 Statistics from http://www.ibm.com . 22 Statistics from http://www.ibm.com . 23 Statistics from http://www.ibm.com . 32 Growth in global container trade was 12.6% in 2004, while shipping capacity rose by around 8%. With the addition of global shipping capacity, as a result of the launch of more than 100 vessels in the coming two to three years and also the introduction of larger vessels with capacity of 8,000 TEUs or more, we can expect to see continued growth in global container trade as shipping rates adjust themselves according to the laws of demand and supply. It is no doubt that ocean shipping is a key lubricant of international trade and the attributes of the transportation system are precisely what make it attractive as a terrorist target. It is open and accessible, by design. Ocean shipping is global in its reach but institutionally diverse with many providers and operators. And it can be brutally efficient, whether moving sneakers or weapons of mass destruction. The sheer scale of ocean conveyance operations thus presents numerous opportunities for foul play and enhancing the security (and safety as a spill over effect) of container trade movement is therefore an emerging imperative for organizations. 2.4.2 Potential Security Breach Points Anonymity of contents, opaque ownership arrangements for vessels, and corruption in foreign ports have facilitated the efforts of those who are inclined to use container shipping for illegal purposes (Willis and Ortiz, 2004). And given that millions of containers enter the U.S. very year through its seaports and only very few of these containers are physically inspected, the containerized shipping system seems to present itself as an attractive target (GAO, 2003). Therefore security experts believe it is only a matter of time before the U.S. or one of it allies is the victim of a terrorist attack using a shipping container, resulting in significant loss of life and in widespread and global economic damage (Willis and Ortiz, 2004). According to Worthen (2006), between 2002 and 2005, the Department of Homeland Security spent US$75 million to track several companies' cargo containers into the U.S. via seaports in Seattle/Tacoma, Los Angeles/Long Beach and New York/New Jersey. Called Operation Safe Commerce (OSC), this project aims to identify weak links in the global supply chain, by using GPS technology and radio frequency identification (RFID) to monitor cargo from a handful of major importers (including Sara Lee and Motorola) as it made its way from overseas factories to its final destination in the U.S. (Worthen, 2006). Although one of the startling realizations of the OSC is that organizations actually know very little about what goes on in their supply chains, some common unsafe practices were managed to be identified by the project participants. 33 These include truckers dropping off containers without ever encountering terminal security, containers left in unsecured areas and containers bypassing a port that is considered (even if scheduled to pass through that port) and travelling instead through a country that poses a greater threat, without either the organization or the U.S. CBP being informed (Worthen, 2006). Langhoff et al.'s 2005 industry study reveals the following thoughts about security from key industry stakeholders: \u00E2\u0080\u00A2 Illegitimate entities or demand are a real and probable vulnerability \u00E2\u0080\u00A2 Buying terms (i.e. lncoterms) have implications on ownership, liability and security \u00E2\u0080\u00A2 Stuffing integrity at the overseas source is a necessity \u00E2\u0080\u00A2 Overseas inland drayage is the most vulnerable link in the supply chain and there are no direct controls that currently mitigates these risks In line with the concept of \"garbage-in, garbage-out\", one of the most vulnerable loop holes for security breaches are at source of the supply chain i.e. the upstream origin of the goods. Also, considering the various major handoffs along an ocean shipping supply chain', the probability of something bad happening is higher when the container is not in motion. 2.5 Supply Chain Security Performance What Constitutes a Secured Supply Chain? Specifically, in the realm of supply chain management, a secured supply chain would refer to a supply chain that is safe from predictable destructive dangers (such as forecasted natural disasters), resilient against relatively unpredictable destructive dangers (such as unpredicted natural disasters, union strikes and terrorist attacks etc.) and have measures in place that can protect the supply chain against such predictable or unpredictable acts of destruction or disruption. 24 Major handoffs include: (1) factory-truck, (2) truck-origin port container yard, (3) origin port container yard-vessel, (4) vessel-destination port container yard, (5) destination port container yard-truck, (6) truck-distribution center, (7) distribution center-retail store/final customer. 34 Measuring Supply Chain Performance (SCP) SCP, can be viewed as consisting of five key dimensions. These dimensions were determined after a rigorous review of past scholarly research on SCP as well as recent security-related studies on SCP. Keller et al. (2002) conducted an extensive study on items and constructs used in logistics performance research for the past 40 years. Their study covered a wide range of latent performance concepts in logistics and supply chain management, from customer satisfaction and organizational leadership to operating performance and employee satisfaction. The Supply-Chain Operations Reference-Model (SCOR) version 8.0, a process reference model that has been developed and endorsed by the Supply-Chain Council (SCC) as the cross- industry de facto standard diagnostic tool for supply chain management, is another extensive piece of research that contains 307 key indicators that measure the performance of supply chain operations. These key performance indicators (KPIs) are derived from the experience and contribution of the Council members. A rigorous review of 20 of the 116 relevant research studies summarized in Keller et al. (2002) and SCOR version 8.0 revealed the following five key dimensions for SCP: \u00E2\u0080\u00A2 Efficiency refers to the accomplishment of or ability to accomplish a job with a minimum expenditure of time and effort. Example: asset turnover, total logistics costs, productivity, asset utilization. \u00E2\u0080\u00A2 Timeliness refers to the time performance aspect of supply chain operations including duration and speed. Example: delivery lead time, on-time delivery, truck turnaround time, order cycle time. \u00E2\u0080\u00A2 Reliability refers to the dependability and accuracy of supply chain operations. Examples: amount of customer complaints, claims, information transmission accuracy. 35 \u00E2\u0080\u00A2 Availability refers to the ability to ensure undisrupted supply of products and/or services and/or information. This could be achieved through the provision of shipment information, ensuring supply of special equipment or products, ensuring that sales force is readily available to respond to customers' inquiries and needs. Examples: Order fill rate, supply rate, amount of backorders, provision of shipment transit information. \u00E2\u0080\u00A2 Responsiveness refers to the accomplishment of or ability to react to demand or supply side changes and/or requests. This capability includes flexibility and agility and could be enhanced by the use of information technology in terms of greater visibility and/or configuration of business operations to allow operations scaling flexibility and agility. Example: customer satisfaction survey results, problem respond lead time. Key scholarly studies that advocated the use of these dimensions for SCP include Raghunathan et al. (1988), Fawcett et al. (1997), and Sharma and Lambert (1990). Other studies that have proven these as important dimensions include Gassenheimer et al. (1989), Novack et al. (1994), Daugherty et al. (1998), Mentzer et al. (1999), Maloni and Benton (2000) and Stank et al. (2001). Measuring Supply Chain Security Performance Because organizations have multiple and frequently changing and conflicting goals, measuring performance of any kind, has always been a challenge for researchers (Hall 1991). One of the challenges that come along with securing the supply chain is measuring the success of your security efforts. In other words, how do you know you have prevented something that has not happened? (Rice and Spayd, 2005 and Worthen, 2006). In an effort to measure how secured a supply chain is, one encounters the same complexity as measuring supply chain performance (SCP), from defining the performance to be measured to selecting the right measure(s) to use so that the performance is most appropriately, objectively and adequately measured. Helferich and Cook (2003), a recent study on supply chain security, identified five \"V\" elements for SCP - Value, Velocity, Variability, Visibility and Vulnerability. An analysis of these five \"Vs\" reveals that each of the \"Vs\" are end results in itself except for Visibility, which is more a means to achieving outstanding SCP rather than an end result. 36 Willis and Ortiz (2004) also listed the capabilities of the global container supply chain using similar categories: \u00E2\u0080\u00A2 Efficiency deliver goods more quickly and more cheaply than other modes of transport, when volume and mass are taken into consideration. \u00E2\u0080\u00A2 Shipment Reliability behaving as expected, retrieving and delivering goods as directed, with a minimum amount of loss due to theft and accident. \u00E2\u0080\u00A2 Resilience ability to return to normal operating conditions quickly after the failure of one or more components and make it's services available. \u00E2\u0080\u00A2 Fault Tolerance ability to respond to disruptions and failures of isolated components without bringing the entire system to a grinding halt. \u00E2\u0080\u00A2 Shipment Transparency the goods that flow through a supply chain must be legitimately represented to authorities and must be legal to transport. Each of these categories are also all end results in itself except for shipment transparency, which is more a means to achieving outstanding SCP rather than an end result. Other scholarly works that have been done on supply chain security dealt with the topic of the value of security efforts (Lee, 2004, Rice and Spayd, 2005 and Worthen, 2006) where the ROI for security investments was of interest. The ROI as an important motivator and incentive for the private sector in making security investments is also an important driver for successful security policy implementation since the private sector has been \"given\" the responsibilities to ensure that their supply chains are secure. 37 Security is an abstract aspect of SCP. Moreover, different supply chains have different operating environments, constraints and objectives. As such, in order to provide or create the necessary incentives for security investments, there needs to be means to evaluate performance so as to evaluate the incentives. 2.6 Summary and Research Gap As mentioned, risk management is not new and there are many studies and works on risk assessment, risk classification and management. Risk management in supply chain is certainly not new to supply chain professionals either, in the academia and industry alike. Heightened Interests in Supply Chain Security Risk Management However, the recent surge in terrorist activities worldwide has brought unprecedented interest and attention on a particular subset of supply chain risk management \u00E2\u0080\u0094 security risk. The review of existing literature has shown that since the 9/11 attacks in New York and Washington, the U.S. government has undertaken several initiatives at the public level to improve national security. From reorganising the country's border and customs related agencies, setting up national security councils and special agencies to working with foreign governments to heighten trade security and intelligence. Some of these initiatives have impacts on the private sector and they come mainly in the form of regulations such the CSI and the C- TPAT. Although most of these regulations are not currently mandatory, one key trend that can be observed is the shifting of supply chain security responsibilities from the public to the private sector. Private Sector's Hesitation in Making Supply Chain Security Investments The private sector however, has been quite hesitant about investing in security initiatives. Most of the security initiatives undertaken in the private sector currently are driven by compliance. Supply chain security initiatives in the private sector, motivated by self-interests are still considered rather limited. And several studies have indicated the following reasons for this lack of enthusiasm: 38 \u00E2\u0080\u00A2 private sector's difficulty in calculating ROI for security investments due to the very nature of \"security improvements\" \u00E2\u0080\u00A2 lack of proven collateral benefits from security investments \u00E2\u0080\u00A2 lack of clear direction from the public sector in terms of security standards \u00E2\u0080\u00A2 the influx of intelligent technologies for security but no clear directions of technology standards from the public sector These reasons together with the existence of public externalities in the costs and benefit nature of security investments are making it difficult for private organizations to justify investments in security. It is therefore hypothesized that companies will look at improvements to both security performance and traditional aspects of supply chain management performance (i.e. collateral benefits), when making decisions about their security efforts. Hypothesis 1: The amount of an organization's security efforts is affected positively by how much impact on security performance the organization perceives the effort(s) will have. Hypothesis 2: The amount of an organization's security efforts is affected positively by how much collateral benefits the organization perceives the effort(s) will bring. Need for the Ability to Evaluate Supply Chain Security Performance And it certainly doesn't help that there is currently no supply chain security performance measurement metric available to help management measure what they are trying to improve. And as the saying goes, you cannot improve what you cannot measure. \"For the government official, the desired outcome is to be able to say, \"We have increased security to maximize the protection of our citizens while facilitating the efficient movement of goods across borders.\" For the CEO, the desired goal is to be able to say, \"We are better off competitively because of our investments in supply chain security.\" - Closs and McGarrell (2004) 39 The quotation above illustrates the imperative to develop a way to help organizations measure and evaluate the security performance of the supply chains that they participate in. This will enable private organizations to appraise various security options and strategies and justify their investments accordingly and public organizations in developing and implementing public policies. One of the key purposes of this study is therefore to identify a key set of performance measurements/indicators for the security performance of the operations of an international maritime supply chain. In doing so, this study will also shed light on the relationships between security performance and traditional SCP and their measurements respectively. Research question of interest 1: What are the key performance measurements for security performance of an international maritime supply chain, from the industry practitioners' point of view? Research question of interest 2: What is the relationship between supply chain security performance measurements and traditional SCP measurements? Need for Better Understanding of the Relationship Between Various Supply Chain Security Initiatives and Supply Chain Security Performance As mentioned in Section 2.3.1 previously, there are ways in which organizations can mitigate the security risks in their supply chain, from compliance with regulatory requirements to employing intelligent transportation systems to TQM principles in everyday operations. Examples of key security initiatives implemented by the government of the United States since 9/11 include the following: \u00E2\u0080\u00A2 Container Security Initiative (CSI) This program aims to identify high-risk containers before they arrive in the U.S. by placing U.S. Customs inspector at foreign ports where they screen U.S.-bound containers. 40 \u00E2\u0080\u00A2 Customs-Trade Partnership Against Terrorism (C-TPAT) This program is a joint government-business initiative to build cooperative relationships that strengthen overall supply chain and border security. \u00E2\u0080\u00A2 Advanced Manifest Rule (AMR) for ocean carriers This rule allows Customs to evaluate containerized shipments for potential terrorist threats before they are loaded onto ships. Ocean carriers must submit a complete manifest for all shipments with Customs at least 24 hours before they are due for departure from a foreign port bounding for the U.S. \u00E2\u0080\u00A2 Free and Secure Trade (FAST) program for truckers Using dedicated lanes, this program allows expedited processing of trucks that have been identified prior to arrival at the border as carrying low risk shipments. \u00E2\u0080\u00A2 Safe and Secure Tradelane (SST) program This program focuses on deploying security of goods from the point of origin to the point of delivery across multiple global trade countries. \u00E2\u0080\u00A2 Operations Safe Commerce (OSC) program for ocean containerized cargo movement. This program is a collaborative effort between the federal government, business interested and the maritime industry to develop and share best practices for the safe and expeditious movement of containerized cargo. \u00E2\u0080\u00A2 Partners-in-Protection (PIP) The government of Canada has also responded to the need for better security in trade movement by implementing the Partners-in-Protection (PIP) program, an equivalent of C-TPAT. For more security options and best practices, please refer to the following studies: (1) Closs and McGarrell (2004), (2) Rice and Spayd (2005), (3) U.S. CBP (2006) and (4) Peleg-Gillai et al. (2006). With the wide array of security solutions available, there needs to be a better understanding of the relationship between supply chain security options and practices and their respective 41 impacts on supply chain security performance so that organizations can prioritize and make more informed decisions with regards to their security investments. There have been several studies done on the impact of security initiatives on overall business cost and performance (Helferich and Cook, 2003; Closs and McGarrell, 2004; Koch, 2004; Banomyong, 2005; Langhoff et al., 2005; Rice and Spayd, 2005; Peleg-Gillai et al., 2006). But none has yet to statistically identify the actual impact of security initiatives on security performance itself. This study takes current research further by attempting to statistically analyze the relationship between security initiatives and perceived supply chain security performance. Research question of interest 3: What is the relationship between security initiatives and supply chain security performance? It is therefore hypothesized that any security efforts will positively impact the security performance of an organization's supply chain operations. Hypothesis 3: An organization's security efforts will positively affect their supply chain performance in terms of security. Because of the existing general trend of sentiments that any effort to improve security will yield positive improvement in security performance, it is therefore hypothesized that in the absence of any objective KPIs, an organization's positive perception of the security impact of their security efforts will positively affect their self-perceived performance in the security of their supply chain operations. Hypothesis 4: An organization's positive perception of the security impact of their security efforts will positively affect their self-perceived performance in the security of their supply chain operations. 42 Need for Better Understanding of the Relationship Between Various Supply Chain Security Initiatives and Traditional SCP A few studies have been done on this aspect of supply chain security research such as Helferich and Cook (2003), Rice and Spayd (2005) and Peleg-Gillai et al. (2006). Helferich and Cook (2003) advocated that the supply chain security challenge is to effectively manage the \"Five V's\" \u00E2\u0080\u0094 Value, Velocity, Variability, Visibility and Vulnerability. Value refers to the value that the customer gets in return for their money on a certain good or service. Velocity refers to order fulfillment cycle time. Variability refers to the consistency of an organization's order fulfilment performance. Visibility refers to an organization's ability in responding to customers' requirements and problem resolutions through leveraging on greater visibility of its supply chain. Vulnerability refers to a supply chain's susceptibility to disruptions. Effective and efficient supply chains require the balancing of the five \"V\" elements to provide customer value while minimising the cost and threat vulnerability. Rice and Spayd (2005) raised a similar need for organizations to consider the collateral benefits (that is, benefits to other traditional aspects of SCP) of security investments but they also highlighted the fact that at this time, the collateral benefits approach remains difficult to quantify and there is little if any analysis of hard data documenting the actual collateral ROI in security, as very few firms have taken a systematic and disciplined approach to understand and create collateral benefits. Peleg-Gillai et al. (2006) took this a step further and investigated via an industry survey to identity the collateral or indirect benefits that organizations can receive from security investments. The study's conclusions were based on a sample of eleven manufacturers and three logistics service providers and respondents were asked to do a self-assessment of the benefits that they have experienced as a result of their investments in security. Besides a limited sample, this study also does not take into account the potential differences in the extent of collateral benefits as a result of varying degrees of implementation of a security initiative. This study therefore takes this approach further by using a larger sample of organizations so as to statistically determine the relationship between security initiatives and traditional SCP. Research question of interest 4: What is the relationship between security initiatives and traditional SCP? 43 It is therefore hypothesized that an improvement in security performance will have a positive impact on other aspects of traditional SCP. Hypothesis 5: An improvement in the security performance of an organization's supply chain operations will have a positive impact on traditional SCP. This impact could be a direct result of security effort (H5a) or it could be an indirect result from an improvement in security (H5b). These research questions and hypotheses can be illustrated in Figure 2.5. Figure 2.5: Structural model for research questions and hypotheses. Perceived Collateral Benefits Security Effort H 5a ^SCP Perceived Security Impact H4 Security Performance 44 CHAPTER 3 METHODOLOGY The early development of modern logistics performance measurements has focused largely on the \"hard\" or more \"objective\" dimensions (e.g. cost tradeoffs and efficiency and fulfillment lead times.) of logistics and supply chain management. Researchers and practitioners applied econometrics, simulation modeling, and management science analytical techniques to evaluate cost tradeoffs between manufacturing, storing, and transporting raw materials, component parts, and finished goods (Keller et al., 2002). Examples of scholarly studies include Blanchard (1992), Dunn et al. (1994), Mossman et al. (1977). More recently, the logistics discipline has evolved in directions that reflect greater influences from marketing, organizational behaviour, and strategic management research and practice These disciplines have helped logisticians better understand and manage the behavioural dimensions (that is, the \"soft\" or the more \"subjective\" dimensions) of logistics and supply chain management including customer satisfaction, integration, collaboration, partnerships and the development of logistics personnel (Keller et al., 2002). Research focusing on attitudinal and behavioural concepts differs notably from traditional approaches applied to studying say inventory levels or facility locations in that they are not directly measurable, that is, these concepts are \"latent\". And researchers in the field of logistics and supply chain management have since begun to use tools and techniques developed in the social sciences to examine these \"latent\" concepts. Keller et al. (2002) advocates that the evolution of more established business fields suggests that logistics researchers should continuously work to develop, test, and strengthen a complete set of measures for latent logistics concepts. This research study, in its endeavour to shed light on the relationships between security performance and traditional SCP and their measurements respectively, is also dealing with a latent logistics concept. Therefore, this study uses tools and techniques developed and commonly used in social sciences research. 45 3.1 Key Phases in this Study There are several key phases in this study (see Figure 3.1). An extensive review of existing literature was first done on the areas of supply chain risk management and supply chain security (see Chapter 2) and four research questions of interests were raised to be answered and five hypotheses were identified to be tested using the factor analysis and structural equation modeling (SEM) techniques. Figure 3.1: Key phases in study. Literature Review Field Interviews V^ V Survey Questionnaire V Factor Analysis V Structural Equation Modeling V Results and Conclusions The set of preliminary hypotheses or issues were initially tested and subsequently refined by a series of comprehensive field interviews conducted with various stakeholders in the international maritime supply chain. This series of field interviews collected inputs which led to the development of a web/e-mail survey questionnaire. The survey questionnaire used in this study was developed and finalised after extensive reviews with field practitioners and academicians. The data collected were then analysed using factor analysis and SEM. This chapter discusses the methodologies employed in this study including the rationale behind their use in various stages of the study, their advantages, disadvantages and limitations and also their application in this study. 3.2 Research Conceptual Framework The research framework in Figure 3.2 guides the collection and analysis of the data in this study. 46 (1) Supply Chain Performance KPIs .4^ \u00E2\u0080\u00A2 Personnel Security * Certification* rr Conveyance Security *(3) Figure 3.2: Research framework. inspection cost * c-tpat certification inventory levels * customs * lead time Identify supply chain security initiatives background checks visibility * asset utilisation Identify KPIs tool Literature Review Field Interviews Email/Web Survey (2) (2)Integrate & generalise KPIs Factor Analysis - based on survey data Timeliness * Performance Efficiency * Performance liability * rmance Re Pert Availability * Performance \u00E2\u0080\u00A2 Responsive Performance SEM - based on survey data ( 3 ) (3 ) 7? (3) ?? ???? 4( ) Security Performance ) Performance (4) Security Performance KPIs Incident * counts Integrate & generalise Initiatives questions to be asked in survey Establish relationships : between supply chain performance KPIs and security performance KPIs 2 amongst security performance KPIs 3 between security initiatives and supply chain performance 4 between security initiatives and security performance 47 The literature review provided an initial set of hypotheses for testing during the field interviews. Specifically, an initial list of KPIs and security initiatives was drawn up to guide interviewees who face difficulties in articulating their responses. The list of KPIs for SCP included indicators such as asset turnover, inventory holding cost, delivery lead times, customer response time, inventory accuracy and shipment information transmission accuracy and were grouped based on the five key dimensions identified in Chapter 2. The list of KPIs for security included indicators commonly mentioned in existing security related literature, such as amount of pilferage, customs clearance lead time, inspection cost and inventory discrepancies. They are not pre-grouped because this is an exploratory study on security KPIs. A list of ten groups of security initiatives was also drawn up based on the classification of security initiatives in the Supply Chain Security Best Practices Catalogue (U.S. CBP, January 2006). A close-ended survey questionnaire is then developed to collect more structured opinions on the appropriateness of each listed KPIs as an indicator for SCP and security performance. This will then allow the employment of factor analysis to reduce the list of KPIs into groups that reflect meaningful aspects of SCP and security performance that organizations should be monitoring and measuring. This is indicated as relationships (1) and (2) in Figure 3.2. In order to understand the inter-related relationships between security initiatives, SCP and security performance, the more complex multivariate statistical technique - Structural Equation Modeling (SEM) is used so that multiple regression equations can be performed simultaneously while taking into account the reliability of observed variables and allowing the representation of latent concepts such as security efforts and SCP. This is indicated as relationships (3) and (4) in Figure 3.2. 3.3 Fieldwork/Interviews Field work involves either the researcher or trained field workers making contact with respondents, collecting and recording primary data and information necessary for the purpose of the research study. 48 3.3.1 The Use of Fieldwork in Logistics Research The use of field interviews in logistics and supply chain management research has been pretty extensive. Mentzer and Kahn (1995) reviewed all the articles published in the Journal of Business Logistics (JBL) from 1978 to 1993 and Table 3.1 below shows their results. Table 3.1: Use of different methods in logistics research Category % of Articles Published in JBL Survey 54.3 Simulation 14.9 Interviews 13.8 Archival Studies 9.6 Math Modelling 4.3 Case Studies 3.2 Source: Mentzer and Kahn (1995). A similar investigation performed by Dunn et al. (1993) which looked at methods used in the research presented in four logistics journals between 1998 and 1992, also indicated the extensive use of surveys/structures interviewing at 36%. Although popularity does not conclusively indicate the effectiveness of a method, it does reflect the practical applicability of the technique in the relevant field of research. Field interview is an appropriate approach for this study because it this study is exploratory in nature with no primary data available about industry's opinions on appropriate security KPIs and the impact of specific security initiatives on SCP. Field interviews therefore help gather enough information to initiate a preliminary structure for subsequent close-ended data collection for statistical analyses. Advantages of Field Interviews and Surveys Field interviews are exploratory in nature. Unstructured or semi-structured interviews are usually used by researchers endeavouring to understand peoples' perspectives on a scene, to retrieve their experiences from the past, to gain expert insight or information. This is especially useful when the problem or question on hand is new and complex. 49 Although relatively less exploratory in nature, the structured survey is an excellent way to help researchers obtain primary data that are not available from public sources, private data companies or previous research studies at the time of their research. The data obtained are also reliable because responses are limited to the alternatives stated. This use of fixed- response questions reduces the variability in the results that may be caused by differences in interviewers. Most importantly, the data collected can be coded, analysed and interpreted using appropriate statistical analytical techniques. Challenges and Limitations of Field Interviews and Surveys As with all tools and techniques, there are challenges and limitations associated with the use of field interviews and surveys. For one, respondents may be unable or unwilling to provide the information due to sensitivity or inability to understand what is being asked for. As such, conducting the series of field interviews prior to the web survey have also helped to identify potentially sensitive questions for omission. In addition, when using field interviews and surveys to gather data and information, the researcher or the field worker has to be very cognizant of the wording of each question, the sequence in which the questions are being asked and even the manner in which each question is asked. This is because even a slight change in the wording, sequence or manner in which a question is asked can distort its meaning and bias the response. Rationale for Using Field Interviews in This Study As can be seen from the review of existing literature, research in the area of supply chain security is still in its infancy. As such, the questions of interest of this study are best dealt using field interviews and surveys. This will allow the researcher to investigate the complex nature of the issue and obtain the necessary data non-existent at the time of this investigation. Moreover, since the questions of interest in this study are of intimate concern to the industry, it is important that their viewpoints and expertise be taken into consideration in the analysis. 3.3.2 Field Interviews in This Study A total of 21 field interviews were conducted in Vancouver, Canada; Shanghai, China and Singapore from 14 January 2007 to 16 March 2007. The interviews were conducted over a six- week period with two weeks in each location. All interviews were conducted in-person except for 50 three which were done over-the-phone due to unavailability of one interviewee and impractical travelling distance required for the other two interviewees. Each interview lasted between one and two hours. All interviews were conducted using the English language except for those conducted in Shanghai, China, which were conducted in Mandarin. A series of questions were asked to gather the following information about the respondent's organization: \u00E2\u0080\u00A2 performance measurements used in evaluating supply chain performance such as efficiency, timeliness, responsiveness, availability and reliability and the organization's perceived performance in these measures relative to their competition. \u00E2\u0080\u00A2 performance measurements used in evaluating supply chain security performance and the organization's perceived performance in these measures relative to their competition. \u00E2\u0080\u00A2 security initiatives adopted or to be adopted \u00E2\u0080\u00A2 opinions about the relative importance and contributions of supply chain security to supply chain performance. \u00E2\u0080\u00A2 basic demographical information about the organization size in terms of annual revenue and number of employees, key trade routes, logistics set up and supply chain strategy. A pre-prepared interview questionnaire was used to structure the interview session. The questionnaire was prepared in both English and Chinese and consists of four sections A to D. Section A asks general information about the respondent's organization such as annual revenues, major trade routes, number of employees, scope of supply chain control and the extent to which supply chain management is a business driver. Sections B and C ask respondents to identify the KPIs that they are using to measure their supply chain and security performance respectively. They are also asked to self-rate their performance on these KPIs as best as possible on a 5-point Likert scale. Section D is the last section of the questionnaire and asks the respondent to identify the security initiatives that their organization has undertaken both before and after the 9/11 incident. On a 5-point Likert scale, respondents are also asked to express their opinions about the impacts of these initiatives on their supply chain and security performance as best as possible. Appendix A contains copies of the interview questionnaire in both the English and Mandarin. The interviewees were selected to adequately represent the different stakeholders (i.e. shippers, ocean carrier, customs authority, port, terminals etc.) in the international marine supply chain as much as possible. 51 Prior to each interview, the interview questionnaire was shared with the interviewees for the purpose of their preparing and gathering necessary information. The interviewees were also informed of the purpose of the study. Each interview was recorded both on paper and on a voice recorder whenever possible. Any discrepancies in the information collected during the interviews were dealt with by follow-up emails with the respective interviewee(s). Details of the profile of the stakeholders interviewed and the findings from the field interviews can be found in Chapter 4. 3.4 Web/Email Survey Information gathered from the field interviews were combined with knowledge from earlier scholarly works on SCP and supply chain security to develop the questions on the close-ended web/email survey tool used in this study. The findings from the field interviews suggest additional hypotheses below and the appropriate questions were included in the survey to collect the necessary data for subsequent statistical analyses. Hypothesis 6: Organization size affects attitude towards security. Hypothesis 7: The nature of cargo handled (hazardous or lack thereof) affects attitude towards security. Hypothesis 8: Typical shipment size (FCL or LCL) affects attitude towards security. Hypothesis 9: Scope of supply chain decision control/influence affects attitude towards security. The stakeholders in the international maritime supply chain community were grouped into two major groups. The first group consists of those stakeholders who initiate trade and includes buyers (importers) and sellers (exporters). The second group consists of the rest of the stakeholders who facilitates the realization of trade movement and includes the logistics service providers, the ports and terminals and customs authorities. This is an appropriate way of grouping because cargo final ownership and general nature of business operations, can speak a lot about the reasonable and expected amount of security due diligence an organization 52 should or would assume or have already assumed. A similar study done by The Manufacturing Institute (Peleg-Gillai et al., 2006) also divided their sample into manufacturers and logistics service providers. One survey questionnaire was developed for each of the two major groups, a Shipper Survey and a Service Provider Survey. Both surveys were prepared in English and Mandarin (see Appendix B). The English version of the surveys is administered to samples residing in primarily English-speaking countries like U.S., Canada and Singapore. The Chinese version of the surveys is administered to the sample in primarily Chinese-speaking China. The Chinese sample has the option to respond to the English version as well. The Shipper survey and the Service Provider surveys are different only in the guiding examples for some of the KPIs due to the inherent differences between the business nature of a shipper and that of a service provider. Both surveys were administered to a much larger sample of organizations in the international maritime supply chain community. The mailing lists used to create the sample size for this study included entries from Council of Supply Chain Management Professionals (CSCMP) membership in Canada, China, Hong Kong, Singapore and U.S., persons receiving the Canadian Transportation & Logistics weekly e-newsletter and members of Supply Chain Logistics Council (SCL) Canada. Each potential respondent received an email informing them of the study, its purpose and the value of the findings and results and are invited to participate in the online web survey. All potential respondents received the same information regarding the study and survey. Emails to the CSCMP mailing lists were sent out using a mailbox created and dedicated to this research project. It is not personal and respondents were only able to identify the sender of the email (without opening the mail) as \"Freight Security Study\". Emails to the Canadian Transportation & Logistics mailing list were sent together with the magazine's weekly e-newsletter. Emails to the SCL Canada mailing list were sent directly from the association's mailbox together with an endorsement letter from them. The first emails to potential respondents residing in North America under the CSCMP mailing list were sent out on 1 5t June 2007 (Friday) 08:00 hours Pacific Time. Those under the 53 Canadian Transportation & Logistics mailing list received their first notification on 7 th June 2007 (Thursday) 08:00 Pacific Time. The first emails to respondents residing in Asia under the CSCMP mailing list were sent out on 3 rd June 2007 (Sunday) 20:00 hours Pacific Time and this is done to avoid the weekend time difference between North America and Asia. All respondents were given a dateline of 30 th June 2007 to respond to the survey. A second email was sent to all respondents on 11 th June 2007 (Monday) 08:00 hours Pacific Time. Finally, a reminder email was sent to all potential respondents on 18 th June 2007 (Monday) 08:00 hours Pacific Time. 3.4.1 Survey Characteristics The sections that follow describe in greater details the different sections in the web survey. There are five sections in the web survey (Sections A to E) and Sections A to D utilize Likert scales extensively to capture the required data. Therefore, first and foremost, an introduction to the fundamental principles of the design of the Likert scales used in the survey is discussed. These scale design principles are employed in the designing the scales used in sections A to D of the web survey. 3.4.1.1 Scale Design An effective construct is a function of the number of items in the construct and the number of response categories (i.e. intervals) in the measuring scale (Roznowski, 1989). A construct is a concept that is made up of one or more objective and measurable indicators. Number of Items in a Construct Constructs with too many items can create problems with respondent fatigue or response bias (Anastasi, 1976). Although, keeping the number of items in a construct few may be an effective means of minimizing response bias (Schmitt and Stults, 1985; Schriesheim and Eisenbach, 1990), constructs with too few items may lack content and construct validity, internal consistency and test-retest reliability (Kenny, 1979; Nunally, 1976), with single-item construct particularly prone to these problems (Hinkin and Schriesheim, 1989). However, additional items also means more time in both the development and administration of a construct (Carmines and Zeller, 1979). Cook et al. (1981) advocated that as few as three items can provide adequate 54 internal consistency reliabilities. Carmines and Zeller (1979) went further to suggest that adding items indefinitely makes progressively less impact on construct reliability. Keller et al. (2002) indicated a trend of using about four to five items per construct in logistics researches that uses multi-item constructs in the last 20 years. In this study, each potential construct in SCP (i.e. efficiency, time, reliability, availability and responsiveness) and including security, has at least five KPI items, yielding a list of at least 30 KPIs in the final survey questionnaire. The KPIs representing each construct are determined after a rigorous review of the Keller et al. (2002) study and SCOR version 8.0 (see Appendix C for the complete list of KPIs included in the survey questionnaire). Number of Response Categories on the Measuring Scale Determining the optimal number of response categories is especially important in constructing the ubiquitous Likert-type scale, which is often used in collecting attitudinal and image data in marketing and public opinion research (Jacoby and Matell, 1971). Jacoby and Matell (1971) advocate that too few response categories may result in too coarse a scale and loss of much of the raters' discriminative powers while too fine a scale may go beyond the raters' limited powers of discrimination. Likert scales are used in this study to capture respondents' self ratings on SCP, their opinions on KPIs for SCP and security performance and their opinions on the impact of security initiatives on their SCP. Each of these purposes will require Likert scales of different lengths depending on how discriminatory the data has to be in order to fulfill each research purpose. A literature review was done on the impact of different number of response categories on reliability of results. This was followed by a review of the scales used in past logistics research was done, using the comprehensive study on multi-item scales used in logistics research by Keller et al. (2002). This information were then combined with the data requirements of each of the above mentioned research purposes to determine the optimal number of response categories for their respective scales. Hinkin (1995) advocates that it is important that the measuring scale used, generate sufficient variance among respondents for subsequent statistical analysis. But how many is sufficient? Symonds (1924) was the first to suggest that reliability (in this case inter-rater reliability) of 55 scores is optimized by the use of seven response categories. Subsequent studies have shown that the coefficient alpha reliability with Likert-type scales increase more significantly up to seven response categories and levels off (Lissitz and Green, 1975; Cox, 1980; Preston and Colman, 1999) (see Table 3.2 below). Table 3.2: Reliability of rating scales. Test-retest Response Categories2 3 4 5 6 7 8 9 10 11 101 Reliability 0.88 0.86 0.89 0.91 0.92 0.93 0.94 0.94 0.93 0.92 0.90 Cronbach's a 0.81 0.79 0.82 0.82 0.83 0.85 0.85 0.85 0.85 0.86 0.85 Source: Preston and Colman (1999). Preston and Colman's study reported statistical significance at p < 0.05 for the differences between: \u00E2\u0080\u00A2 the 2-point scale and the scales with 6, 7, 8, 9 and 10 response categories \u00E2\u0080\u00A2 the 3-point scale and the scales with 6, 7, 8, 9, 10 and 11 response categories \u00E2\u0080\u00A2 the 4-point scale and the scales with 8 and 9 response categories All other differences between the Test-retest reliability coefficients were statistically non- significant in Preston and Colman's study. Since the differences in reliability are non-significant among scales with between five to nine response categories, we look to their respective Cronbach's a value to determine the appropriate length for the scale. Scales with between seven to nine response categories have slightly higher Cronbach's a value at 0.85. Miller (1956) suggested in an influential article that the human mind has a span of apprehension capable of distinguishing about seven different items (plus or minus two). This implies a limit of about seven on the number of response categories that people are able to use in making judgements about the magnitudes of unidimensional stimuli and suggests that little if any additional information can be obtained by increasing the number of response categories beyond about seven. Thus, balancing the human apprehension capability with the goal of obtaining adequate response variance, a 7-point scale is deemed appropriate. 56 The practicality and popular adoption of 7-point scales (both Likert-type scales and other attitude and opinion measures) are noted by Bearden et al. (1993), Peter (1979) and Shaw and Wright (1967). In the area of supply chain management and logistics, the extensive use of 7- point Likert scales is supported by Keller et al.'s study 25 (see Table 3.3). Table 3.3: Popularity of Likert scales used in logistics research. Scale Type Used in Number of Studies % Used / Popularity < 3 points 119 17.25% 3 points 8 1.16% 4 points 21 3.04% 5 points 256 37.10% 6 points 18 2.61% 7 points 250 36.23% 8 points 9 1.30% 9 points 5 0.72% 10 points 2 0.29% > 10 points 2 0.29% Total 690 100% For the purpose of this study, a 7-point Likert scale is therefore used where respondents are asked to self-rate their performance because a good amount of discrimination is desired for performance data. A 3-point Likert scale is used instead where respondents are asked to indicate whether a particular KPI is an appropriate indicator for SCP and/or supply chain security performance. A 3-point scale is deemed suitable for this purpose because it is not necessary to discriminate among degrees of appropriateness or inappropriateness in this study. 3.4.2 Self Performance Appraisal Section A is a self-appraisal of the responding person's organization's supply chain performance and security performance. This section is made up of questions A1, A2 and A3 on the questionnaire. The first question sets the context within which the respondent is answering the survey questions. It asks if the respondent is responding on behalf of the entire firm or just the specific strategic business unit (SBU) that he/she is responsible for. The other two questions 25 Keller et al.'s study focuses on all survey research studies employing multi-item measures published in the International Journal of Logistics Management, International Journal of Physical Distribution and Logistics Management, Journal of Business Logistics, and Transportation Journal from 1961 to 2000. A total of 116 studies, done over a span of 40 years, employing a total sample of 690 multi-item scales, all of which have been subjected to at least minimal development procedures to assess the reliability and validity of the measures as part of the research process. 57 allow the respondent to appraise his/her organization's overall supply chain operations performance and security performance respectively, using a 7-point Likert scale (1=Not Acceptable, 2=Very Poor, 3=Poor, 4=Fair, 5=Good, 6=Very Good, 7=Excellent). Security is defined to be how probable the respondent thinks his/her organization's supply chain(s) can be or will be compromised in terms of pilferages, thefts, damages, terrorism and other crimes such as smuggling, contraband etc. SCP, on the other hand consists of the five dimensions that were determined after a rigorous review of past scholarly research on SCP including SCOR and other recent security-related studies on SCP. The Cronbach's Alpha of the individual items within each of these dimensions were greater than 0.70 (the recommended level by most studies using multi-item scales). Table 3.4 is a quick recap of these dimensions and they are compared to those advocated by Helferich and Cook (2003) and Willis and Ortiz (2004). Table 3.4: Comparison of SCP dimensions. SCP Aspect Corresponding Other Relevant Studies5 V's Helferich and Cook (2003) Categories Willis and Ortiz (2004) Efficiency Value Efficiency McGinnis et al. (1981), Mentzer and Konrad (1991), Stank and Lackey (1997), Koch (2004), Lee (2004). Timeliness Velocity - Sterling and Lambert (1987), McGinnis (1990), Matear and Gray (1993), Novack et al. (1994), Emerson and Grimm (1996), Stank and Lackey (1997), Crosby and Lemay (1998), Menon et al. (1998), Stank et al. (2001), Koch (2004), Price (2004), Banomyong (2005). Reliability Variability Shipmentreliability McGinnis et al. (1981), Sterling and Lambert (1987), McGinnis (1990), Mentzer and Konrad (1991), Matear and Gray (1993), Emerson and Grimm (1996), Menon et al. (1998), Pearson and Semeijn (1999), Koch (2004). Availability / Resilience Vulnerability Resilience & Fault tolerance Emerson and Grimm (1996). Responsiveness Visibility Shipmenttransparency Sterling and Lambert (1987), Matear and Gray (1993), Novack et al. (1994), Emerson and Grimm (1996). 58 As can be seen from Table 3.4, the five dimensions synthesized from an extensive review of current literature on SCP are aligned with those proposed by Helferich and Cook (2003) and Willis and Ortiz (2004). These five dimensions are therefore deemed comprehensive enough for the purpose of this research study. 3.4.3 Organization Profiling This is Section B on the questionnaire and collects data about the responding person's organization's nature of business and operating environment. There are eight questions in this section and is included because results from the field interviews revealed that certain key variables in an organization's operating environment seem to affect their attitude and performance in terms of security. Industrial Sector The type of business determines the primary nature of an organization's supply chain operations. In turn, the nature of an organization's supply chain operations has an impact on the types of activities that are managed and the kinds of vulnerabilities experienced. Example: importer, exporter, logistics service provider, port, terminal, ocean carrier and customs broker. Type of Supply Chain and Hazardous Cargo Content The type and nature of the commodities carried determines the vulnerability of the supply chain or lack thereof. With regards to types of supply chains, supply chains handling cargo of higher value may be seen as more vulnerable to pilferages. However, their shipment size may be typically small (i.e. less-than-container-loads) and thus a less attractive target for terrorist acts such as planting a bomb compared to cargo typically shipped in full-container-loads. The question designed to collect the type of supply chain information is close-ended and includes the following answer choices: fast moving consumer goods, electronics, perishables/food products, automotive, pharmaceuticals, chemicals, heavy machinery and aerospace. 59 The hazardous nature of the products also impacts the extent to which an organization might be concerned about security and they may have different security initiatives. A separate question is asked to collect information about the percentage of hazardous cargo handled. Average Shipment Size Does the responding organization ship a greater proportion in full-container-loads (FCL) or less- than-container-loads (LCL)? The average shipment size determines how a typical shipment is handled (e.g. the number of handoffs in the process) and affects the kinds of vulnerabilities that a shipment is exposed to. Key Trade Routes An organization's major trade routes determine the kind of operating environments and logistics challenges that it is most often exposed to. It also identifies the types and degree of mandatory security regulations that they are subjected to. It can be reasonably expected that these operating factors affect an organization's stance and efforts toward security. This observation is supported by preliminary results from the field interviews. The question designed to collect this information is close-ended and includes both the east- bound and west-bound routes between any two of the five major continents. Organization Size Based on Annual Revenues Annual revenue is a common measure for organization size in scholarly studies. In this study, the annual revenues of an organization can indicate the extent of what can be at stake if the organization's ability to satisfy their customers is disrupted. This can affect the organization's attitude towards crisis and risk management. The financial capability of an organization may also affect the type of security investments that they can undertake. Responses from organizations during the field interviews indicate this to be highly sensitive and confidential information. As such, close-ended ranges instead of open-ended estimates are used. The annual revenue ranges used in this study is adopted from a recent supply chain security study done by Closs et al. (2006). Scope of Decision Making For the purpose of this study, it is more important to gather information about the scope of decision making authority the organization as a whole has over their supply chain as opposed to 60 the individual respondent. This is because the scope of supply chain control has direct implications on which business entity in a particular supply chain relationship has the responsibility to do the due diligence in ensuring security. Based on the author's professional experience and interviews with industry practitioners in international freight movement, 15 and 16 key logistics activities involved in international freight were identified for the Service Provider and Shipper surveys respectively. The activity of selecting suppliers/manufacturers is not relevant for service providers. Respondents are asked to indicate whether or not each of these activities is applicable to their organization's operations and if they are, if their organization makes the final decision regarding that activity. Supply Chain Management Strategy Drivers For the purpose of this study, we need to know what drives an organization's excellence in supply chain operations because that had direct implications on how their supply chain is organized, and how related efforts and investments are prioritised. For instance, an organization that places greater emphasis on cost and efficiency may be more hesitant in adopting security initiatives especially those that are perceived to be unable to bring positive impact to the organization's bottom line. On the contrary, an organization that places greater emphasis on timeliness performance in their customer fulfilment may be more ready to adopt security initiatives that will help improve customs clearance lead times. The supply chain drivers used are the key supply chain performance dimensions identified for measuring SCP in Section A. 3.4.4 Key Performance Indicators (KPIs) This is Section C of the questionnaire and contains two questions which collect information about the respondent's opinions on what the appropriate KPIs for SCP and security performance should be. The first question initiates the respondent's thinking in this aspect by asking them if it is at all necessary to have KPIs for supply chain security performance. This is followed by the second question which contains a list of 32 different KPIs. This list of KPIs is the result of past literature review and responses gathered during field interviews. For each KPI, respondents are asked to 61 use 3-point Likert scales (1=Not Appropriate, 2=Indifferent, 3=Appropriate), to indicate whether or not they think that a particular KPI is an appropriate indicator for SCP and security performance respectively. The same list of KPIs is used for both SCP and security performance so that a subsequent comparison can be made to determine if security performance indicators are a subset of current common SCP indicators. 3.4.5 Supply Chain Security Initiatives This is Section D of the questionnaire and asks the respondent to indicate their opinions on whether various groups of security initiatives have been implemented. And if a particular group of initiatives has been implemented, what has been the impact on their SCP, if any. These security initiatives are classified into 10 key groups based on the classification of security initiatives in the Supply Chain Security Best Practices Catalogue (U.S. CBP, January 2006) (see Table 3.5). The best practices included in this catalogue were identified through more than 1,400 validations and site visits conducted by C-TPAT Supply Chain Security Specialists. The examples of security practices in this catalogue include not only advanced security technologies but also lower cost security practices. They are grouped according to the primary purpose of each practice such as to secure conveyance, to secure containers or ensure security of personnel safety. For example, concerning \"conveyance security\", the intended purpose of accurately tracking conveyance movements and detect deviations can be achieved through the use of GPS tracking systems, or through a lower cost security practice of requiring drivers to follow designated routes with predetermined average travel times, along with periodic communication between the truck driver and company officials (U.S. CBP, 2006). 62 Table 3.5: Security initiatives. Group Security Initiative Examples (for details, refer to Supply Chain Security Best Practices Catalogue (U.S. CBP, Jan 2006)) 1 Operations/Security Related Certifications \u00E2\u0080\u00A2 Customs-Trade Partnership Against Terrorism (C-TPAT) (U.S.). \u00E2\u0080\u00A2 Partners-In-Protection (PIP) (Canada). \u00E2\u0080\u00A2 Free and Secure Trade (FAST) (U.S. and Canada). 2 Advanced Data \u00E2\u0080\u00A2 24-hours Advance Manifest Rule & Automated Commercial Environment (ACE) (U.S.). \u00E2\u0080\u00A2 Advanced Commercial Information (ACI) (Canada). \u00E2\u0080\u00A2 Advanced shipping notices (ASNs). 3 Business Partners Requirements \u00E2\u0080\u00A2 Contractual obligations and supplier code of conduct. \u00E2\u0080\u00A2 Verify business references, credit checks. \u00E2\u0080\u00A2 Establish routine pickup/drop-off points. 4 Security Training & Outreach Programs \u00E2\u0080\u00A2 Communicate terrorism information to employees and provide incentives for incident reporting. \u00E2\u0080\u00A2 Periodic training, specialized training in handling breaches, conducting investigations, inspections etc. \u00E2\u0080\u00A2 Collaborate with local law enforcement. 5 Procedural Security \u00E2\u0080\u00A2 Establish internal security personnel network. \u00E2\u0080\u00A2 Establish incident database and procedures to handle suspicious activities, reporting and response. \u00E2\u0080\u00A2 Barcode/RFID scanning to detect discrepancies and ensure only manifested cargo is loaded. 6 Physical Security & Access Control \u00E2\u0080\u00A2 24-hours security guard and/or police patrol, fence/gate with magnetic sensors, alarm systems. \u00E2\u0080\u00A2 Biometric technology, color-coding uniforms, photo ID cards and password controlled locks. \u00E2\u0080\u00A2 Screen/random inspect incoming packages/vehicles. 7 Tracking & Monitoring (Conveyance Security) \u00E2\u0080\u00A2 Monitor \"unusual\" requests and time lags for container turnaround time on premises. \u00E2\u0080\u00A2 Global Positioning System (GPS), truck transponders, online shipment visibility tool, CCTVs. \u00E2\u0080\u00A2 Examine fuel consumption to detect route deviations, satellite monitoring and detect stowaways 8 Personnel Security \u00E2\u0080\u00A2 Pre-employment background checks. \u00E2\u0080\u00A2 Termination procedures. \u00E2\u0080\u00A2 Employee handbook for internal code of conduct and security awareness training. 9 Container/Trailer/Unit Load Device (ULD) Security. \u00E2\u0080\u00A2 Exterior inspection, container and seal condition, and seal no. verification and seal issuance controls. \u00E2\u0080\u00A2 E-seals, other advanced container locking technology. \u00E2\u0080\u00A2 \"Smart Box\" \u00E2\u0080\u0094 container with heavy-duty seal and electronic security device that communicates evidence of tampering, register every legitimate and unauthorized opening of container. 10 Management Support & Sponsorship \u00E2\u0080\u00A2 Establish security committee and conduct periodic briefings \u00E2\u0080\u00A2 Incorporate security into \"Continuous Improvement\" philosophy and mission statement \u00E2\u0080\u00A2 Top management maintains high level of familiarity with overseas business partners, their practices and affiliations and ensures all subsidiaries develop and implement a sound security plan 63 For each group of security initiatives, respondents are asked whether it is being implemented in their organization. Respondents are presented with three options: (1) Implemented, (2) Planning to Implement or (3) Not Implementing. With each group of initiatives that the respondent's organization has implemented or is planning to implement, the respondent will be directed to an additional question related to that group of initiatives. This additional question requires the respondent to indicate their opinions about the impacts (if any) a particular initiative has or will have on their SCP based on the six dimensions of efficiency, timeliness, reliability, availability, responsiveness and security. The respondents voice their opinions using a 7-point scale where 1=Extremely Negative, 2=Very Negative, 3=Moderately Negative, 4=Unsure/Neutral, 5=Moderately Positive, 6=Very Positive and 7=Extremely Positive. The purpose of this question is to gather data to understand the existence or lack thereof of the collateral benefits of security initiatives. For instance, if a responding organization has implemented security/operations related certifications and indicates a significantly positive impact on efficiency, this expression of opinion reflects the existence of the collateral benefit of efficiency of having a security certification even though this benefit is not quantified. The quantification of collateral benefits is not a purpose of this study. 3.4.6 Respondents' Information This is Section E of the questionnaire and there are six questions to collect demographical information about the respondent. These demographical information will serve the purpose of understanding the impact of demographics on the results. The first question asks the respondent how he/she learned about the existence of this research study and survey exercise. The channel through which a person was informed about the study may influence their readiness to respond. For example, it is expected that a personal contact of the author would be more ready to respond to the survey compared to someone who got the email through a mass mailing list. The second question asks the respondent to indicate the physical location which they are residing in. Preliminary information gathered from suggested that one's physical location can have significant impact on one's viewpoints and perspectives on the criticality and urgency of 64 supply chain security issues. For instance, the results from the field interviews with Chinese companies suggest to a large extent that Chinese companies currently do not see security issues as imminent problems compared to their counterparts in North America. Thus this question was included. The third question asks the respondent for his/her position within their organization. The purpose of this question is the collect information to understand how much decision making authority the respondent has in his/her organization and how much of a bird's eye view 26 the respondent has about his/her organization's business directions. This information will affect how substantial some of the information provided in the survey is. For instance, someone at the strategic planning level can be expected to have a better grasp of the impact of a security initiative on the organization's supply chain's reliability compared to someone at the ground operation level. The fourth question is an optional question and asks for the respondent's organization's name. Research of the past two decades has shown that cultures exert considerable influence over emotion (Matsumoto, 1993). And strategic behaviors differ across nations (Hofstede, 1980; Kagono et al., 1985; Kelley et al., 1987; Sallivan and Nonaka, 1988; Schneider and Meyer, 1991). Schneider and Meyer's study in 1991 on the effect of perceptions of environmental uncertainty and organizational control on strategic behaviors also found that national cultures influence the interpretation and response to strategic issues. Specifically, the results of the study showed that national cultures have significant influences over whether an issue is seen as a crisis, as a stimulant or as a threat. It also affects the interpretations of the issue's difficulty, urgency, certainty and future outlook. Because the sample for this study includes respondents from more than one country, it is more important to capture the cultural similarities and differences between countries rather than within countries. Moreover, preliminary results from the field interviews are suggesting more significant differences in attitudes between countries than within countries. A fifth question is thus included to ask the respondent which national culture influences his/her business perspectives and attitude the most. The countries are then grouped based on the clustering synthesis by Gupta et al. (2002) (see Table 3.6). The variables used to cluster these 61 countries are performance 26 An English idiom that refers to a view from high above i.e. gaining the ability to see the big picture. 65 orientation, uncertainty avoidance, future orientation, humane orientation, institutional collectivism, in-group collectivism, gender egalitarianism, assertiveness and power distance. Table 3.6: Societal cluster classification. Cluster Name Countries Anglo Cultures Australia, Canada, England, Ireland, New Zealand, South Africa (White Sample), USA Arab Cultures Egypt, Kuwait, Morocco, Qatar, Turkey Confucian Asia China, Hong Kong, Japan, Singapore, South Korea, Taiwan Eastern Europe Albania, Georgia, Greece, Hungary, Kazakhstan, Poland, Russia Germanic Europe Austria, Germany, Switzerland, The Netherlands Latin America Argentina, Bolivia, Brazil, Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Mexico, Venezuela Latin Europe France, Israel, Italy, Portugal, Spain, Switzerland (French Speaking) Nordic Europe Denmark, Finland, Sweden Southern Asia India, Indonesia, Iran, Malaysia, Philippines, Thailand Sub-Sahara Africa Namibia, Nigeria, South Africa (Black Sample), Zambia, Zimbabwe 3.5 Factor Analysis Factor analysis is used in this study to reduce the KPI data to a smaller set of key dimensions in two areas. Firstly, the SCP KPIs are factor analyzed in order to reveal if there is a dimension within SCP that measures security. Secondly, factor analysis is also employed on security KPIs to uncover the key dimensions for performance measurements within the area of security. There are other grouping techniques such as cluster analysis and multidimensional scaling. Cluster analysis is not appropriate for the purpose of data reduction because the technique seeks to group objects (i.e. respondents) based on certain characteristics that they possess, as opposed to grouping characteristics. Multidimensional scaling seeks to determine the perceived relative image of a set of objects (such as products or ideas). This technique is based on the comparison of objects and therefore not appropriate for the purpose of this study, which does not assume KPIs to be interdependent on one another. 66 Formulate Problem \u00E2\u0080\u00A2 Determine Extraction Method \u00E2\u0080\u00A2 Determine Rotation Method \u00E2\u0080\u00A2 Determine No.of Factors Rotate Factors Interpret Factors 3.5.1 What is Factor Analysis? Factor analysis is concerned with the resolution of a set of variables into a smaller number of meaningful categories or \"factors\". Factor analysis is commonly used in psychology and other areas of social sciences where exploratory studies are common. Exploratory studies typically use a large initial set of variables because no prior factor items are available. Exploratory studies are also very common in logistics research 27 and examples of such studies include Gassenheimer et al. (1989), Novack et al. (1994), Daugherty et al. (1998), Mentzer et al. (1999), Maloni and Benton (2000), Stank et al. (2001) and many more can be found in Keller et al. (2002). Factor analysis is therefore appropriate for this exploratory study because it serves to organize and reduce the KPI data collected via the online survey into fewer more meaningful and manageable groups, thereby achieving scientific parsimony. 3.5.2 Use of Factor Analysis in This Study There are six key steps involved in the factor analysis in this study (see Figure 3.3). The variables that will be factor analyzed in this study are the KPIs for SCP and security performance. Discussion of the steps taken can be found together with the results in Chapter 5. Figure 3.3: Conducting factor analysis. 27 According to Mentzer and Kahn (1995), exploratory studies published in the Journal of Business Logistics are the second most popular type of research performed with an overall percentage of 36.2%. 67 3.5.3 Advantages and Challenges of Factor Analysis Although factor analysis has the advantage of expediting the computation of multiple regression statistics (see Craeger, 1958 and Dwyer, 1940) and allows data reduction (i.e. parsimony in scientific explanation), Fabrigar et al. (1999) contented that perhaps more than any other commonly used statistical method, factor analysis requires a researcher to make a number of important decisions with respect to how the analysis is performed. They suggest that there are at least five major methodological issues that should be considered: i. The variables that should be included in the study and the size and nature of the sample on which the study is based. ii. Appropriateness of factor analysis given the goals of the research. iii. Selecting the right procedure to fit the model to the data. iv. Determining the number of factors that should be included in the model. ^ v.^Selecting a method for rotating the initial factor analytic solution to a final solution that can be more readily interpreted. Several other studies (Armstrong and Soelberg, 1968; Catell, 1978; Comrey, 1978; Ford et al., 1986; MacCallum, 1983; MacCallum, Widaman, Zhang and Hong, 1999; Velicer and Fava, 1998; Weiss, 1976) have also suggested that each of the above decisions can have important consequences for the results obtained. Therefore, the challenge for the researcher is to ensure that the above methodological decisions are sound and rational. 3.6 Structural Equation Modeling (SEM) SEM is used in this study to analyze the complex relationships between security effort, security performance, perceived collateral benefits and SCP. SEM is chosen as the technique of choice as opposed to multiple or logistic regressions because it allows the simultaneous analysis of more than one regression equation i.e. a complex network of relationships where are there more than one dependent variable and more than one independent variable. 68 3.6.1 What is SEM? SEM is a statistical methodology that tests a hypothesized model statistically to determine the extent the proposed model is consistent with the sample data (Wisner, 2003). It has been long known in marketing to be especially appropriate for theory testing (Savalei and Bentler, 2006). 3.6.2 Use of SEM in This Study SEM is used in this study to test the a priori hypotheses of the relationships between security initiatives, security performance and traditional SCP. There are four key steps in the SEM modeling process: specification, estimation, evaluation and modification (see Figure 3.4). Figure 3.4: Steps in SEM modeling process. Model Specification Model Estimation Model Fit Evaluation Model Modification In the specification step, the model to be tested is developed and converted into a format that the SEM computer program \u00E2\u0080\u0094 Analysis of Moment Structures (AMOS 7.0) can understand. In the estimation step, a fitting function is chosen and parameter estimates for the model are obtained. In the evaluation step, the test of model fit and other indices of fit are interpreted. In the modification step, the original model is modified in accordance with the information obtained in the previous step as well as theory. Steps 3 and 4 are usually conducted simultaneously. Discussion of the steps taken can be found together with the results in Chapter 5. 69 3.6.3 Advantages and Challenges of Using SEM Several aspects of SEM set it apart from the older generation of multivariate procedures. First, traditional multivariate procedures are incapable of assessing or correcting for measurement error, SEM provides explicit estimates of these error variance parameters. Second, whereas data analyses using the former methods are based on observed measurements only, those using SEM procedures can incorporate both unobserved (that is, latent) and observed variables (Savalei and Bentler, 2006). Finally, there are no widely and easily applied alternative methods for modelling multivariate relations or for estimating point and/or interval indirect effects. However, when employing SEM, it is important that the researcher keep in mind the following potential pitfalls (Savalei and Bentler, 2006): \u00E2\u0080\u00A2 Ignoring the test of model fit especially when your sample size is smaller than a few hundreds. \u00E2\u0080\u00A2 Basing model acceptance or rejection on just one or two fit indices. \u00E2\u0080\u00A2 Going wild with model modification and not ensuring that the modified model is consistent with some theory. \u00E2\u0080\u00A2 Inferring causation and global truth. It is important not to simply draw causal conclusions from correlational data simply because SEM is used. \u00E2\u0080\u00A2 Equating R2 and a well-fitting model. It is important not to assume that the constructs are strongly related simply when the model fits well. 70 CHAPTER 4 DATA 4.1 Profile of Field Interview Respondents A total of 21 field interviews were conducted in Vancouver, Canada; Shanghai, China and Singapore from 14 January 2007 to 16 March 2007. Five, nine and eight companies were interviewed in Vancouver, Canada, Shanghai, China, and Singapore respectively. Table 4.1 displays the general profile of the organizations interviewed. Table 4.1: General profile of organizations interviewed. Stakeholder Type Proportion of Total Shipper (Importer + Exporter) Logistics Service Provider Ports + Terminals + Customs 47.62% (10) 28.57% (6) 23.81% (5) Revenues (US$)* Large (>1 bil) 50.00% (5) 66.67% (4) 40.00% (2) Medium (100 mil - 1 bil) 40.00% (4) 33.33% (2) - Small (< 100 mil) 10.00% (1) 20.00% (1) Employee Count Large (> 5,000) 40.00% (4) 33.33% (2) 40.00% (2) Medium (500 - 5,000) 40.00% (4) 50.00% (3) 20.00% (1) Small (< 500) 20.00% (2) 16.67% (1) 40.00% (2) Commodity Type FMCG 60.00% (6) N.A. N.A. Automotive 10.00% (1) N.A. N.A. Pharmaceuticals 10.00% (1) N.A. N.A. Heavy Machinery 10.00% (1) N.A. N.A. Others 10.00% (1) N.A. N.A. Major Trade Routes A Infra Asia 40.00% (4) 66.67% (4) 80.00% (4) Infra Americas 20.00% (2) - - Asia E-4 N. America 80.00% (8) 83.33% (5) 80.00% (4) Asia E-4 Europe 40.00% (4) 83.33% (5) 20.00% (1) Europe E--* N. America 10.00% (1) Interviewee's Position Within Organization President/CEO 20.00% (2) - 20.00\u00C2\u00B0/0_(1) 20.00% (1)Supply Chain Director 10.00% (1) 16.67% (1) Supply Chain Manager 50.00% (5) 50.00% (3) - Security Manager 10.00% (1) 33.33% (2) 60.00% (3) Logistics Analyst 10.00% (1) - Notes to Table 4.1: The number in brackets refers to the number of organizations that fall into that particular category. * Two organizations interviewed under the category of Ports + Terminals + Customs were unable to disclose their annual revenues for 2005. A Interviewees are allowed to mention more than one major trade routes. 71 The different key stakeholders in the international maritime supply chain include shippers, and buyers (48%), customs brokers, freight forwarders and consolidators, third party logistics providers, trucking and inter-modal transportation companies (28%), ocean carriers, ports and terminals and customs authorities (24%). The majority of the interviewees represent large organizations with annual revenues of more than US$1 billion (-52%). About 29% represent medium-sized organizations with annual revenues between US$100 million and US$1 billion. Another 10% represent smaller organizations with annual revenues of US$100 million or less. Two organizations (i.e. 9%) interviewed were unable to disclose their annual revenues for 2005. Interviewees were asked to indicate their major trade routes and they are allowed to mention more than one. A significant majority of the organizations interviewed (-80%) have trade movements or handle trade movements between Asia and North America. The next most popular trade route is within Asia (-60% of respondents) followed by Asia-Europe (-48%). The majority of the shipper organizations interviewed belong to the fast moving consumer goods (FMCG) industry (60%) with the rest from a varied mix of industries such as pharmaceuticals (10%), automotive (10%), and heavy machinery (10%). The rest of the 10% are classified as other industries such as forestry and chemicals. The majority of the interviewees from these organizations are either managers or directors of their organization's supply chain operations. This was particularly true for shippers (80%) and logistics service providers (67%) than for the representatives from port and terminals and customs (40%). A good number of them are also managers for their company's supply chain security matters. A summary of the responses gathered from these interviews can be found in Appendix E 28 . Since only one government organization was interviewed, it is deemed that its responses cannot be reliably generalized. As such, the field interview response from the government organization was not taken into consideration in the analyses discussed in Chapter 5. 28 The names of the organizations and personnel interviewed are kept confidential as agreed with all field interview participants. A summary of their profile by industry type can be found in Table 4.2. 72 4.2 Profile of Web/Email Survey Respondents A total of 163 organizations from Asia and North America responded to the web/email survey. Of these 113 responded to the survey in entirety while 12 of the rest of the 50 omitted a few questions for the last section \u00E2\u0080\u0094 Section D (Security Initiatives) and omitted Section E (Respondents' Information). The rest of the 38 only completed half of the survey, that is, only Section A (Self-Performance Appraisal) and Section B (Organization Profiling). 29 The omitted sections include Section C (KPIs), Section D (Security Initiatives) and Section E (Respondents' Information). On the web survey, respondents are only allowed to proceed upon completion of a question. The profile of the web/email survey respondents is similar to that of the field interview interviewees. They represent a good mix of various stakeholders in the international marine supply chain. The paragraphs below discuss the profile of the web/email survey respondents. Shipper vs. Service Provider Figure 4.1 illustrate the proportion of service providers and shippers who responded to the survey and whether they represented only a single Strategic Business Unit (SBU) or the entire firm. Table 4.2 provides the detailed numbers. As can be seen, there is enough variation in respondent type to determine if being a shipper versus a service provider affects the pattern of responses. There is also enough variation in respondents' scope of responsibility to determine if scope of responsibility affects the pattern of responses. Figure 4.1: Respondent profile in terms of type and representation. Shipper vs Service Provider ^ Firm vs SBU Service Provider- 31% Shipper 69% 29 Possible reasons for a partially completed survey could be due to the sensitivity of the issues asked (i.e. security) and potential technical difficulties with some private organizations' firewall protection. 73 Table 4.3: Shipper profile. Shipper Count Percentage Buyer (Importer) 81 50.63 Seller (Exporter) 74 46.25 Others 5 3.13 Buyer (Importer) Seller (Exporter) Others 0^20^40^60 ^ 80 ^ 100 Frequency (Count) 3rd Party Logistics ^ Trucker^ 0 Customs Broker Freight Consolidator Freight Forw arder Others AM Ocean Carrier HI Port 111 ^0 ^5^10^15^20 Frequency (Count) 25 ^ 30 74 Table 4.2: Shipper vs. service providers. Firm SBU Total Shipper 58 55 113 Service Provider 30 20 50 Total 88 75 163 Industry Sector In terms of industry profile, shippers are classified as either importers (buyers) or exporters (sellers) or both (e.g. a trading company) (see Table 4.3 and Figure 4.2) and service providers are further classified into sub groups based on the logistics services they provide. The groupings used for service providers are 3rd party logistics service provider (3PL), trucking companies, customs brokerage firms, freight consolidators, freight forwarders, terminal operators, ocean carriers and port (see Table 4.4 and Figure 4.3). Table 4.4: Service provider profile. Service Provider Count 3rd Party Logistics 30 Trucker 17 Customs Broker 10 Freight Consolidator 10 Freight Forwarder 10 Terminal 5 Others 4 Ocean Carrier 2 Port 1 Note: Count totals in Table 4.4 and 4.5 do not add up to 113 or 50 for shippers and service providers respectively because respondents are allowed to select more than one industry type. Figure 4.2: Industry profile of shippers.^Figure 4.3: Industry profile of service providers. Although it is regretful that no customs authorities responded to the web survey, the field interviews with a customs authority in Asia revealed that the key role of customs authority is in setting and implementing regulations. They have little impact or opinions in terms of determining or influencing the type of security initiatives adopted and also the kind of performance measurements used for security and supply chain management. Supply Chain Types Figure 4.4 and Table 4.5 shows that majority of the respondents come from the FMCG/Retail sector which can include respondents from both the FMCG/Retail and Electronics group. This makeup is ideal for our analysis because these supply chains more often than not dealing with container freight. The bulk and break bulk freight-dominant supply chains such as the agriculture, oil and gas and forestry make up the minority of the sample population. Table 4.5: Respondents' supply chain types. Shipper Service Provider Total FMCG / Retail 35 27 62 Electronics / Hi-Tech / Semi-Conductors 18 22 40 Chemicals / Petro-Chemicals 21 12 33 Perishables / Food 15 16 31 Automotive 5 19 24 Pharmaceuticals 9 13 22 Heavy Machinery / Fittings 6 10 16 Others 6 4 10 Aerospace 4 5 9 Furniture / Consumer Durables 4 0 4 Mining & Metals 4 0 4 Forestry 3 1 4 Agriculture 3 0 3 Oil & Gas 0 1 1 75 0 10 20 30 40 50 60 70 FMCG / Retail Electronics / I-i-Tech / Seni-Conductors Chenicals / Petro-Chenicals Perishables / Food Automotive Pharmaceuticals riONS,M;X.VA, Heavy Machinery / Fittings Others Aerospace Furniture / Consumer Durables AM Kitting & Metals^--I Forestry Agriculture OR Oil & Gas No Hazardous 55% Figure 4.4: Illustration of respondents' supply chain type proportions. Frequency (Count) Hazardous Cargo Composition Figure 4.5 and Table 4.6 show a balanced variation in the proportion of respondents carrying hazardous versus non-hazardous cargo is balanced. Table 4.6: Cargo nature handled by respondents' organizations. Shipper Service Provider Total Hazardous 45 28 73 No Hazardous 68 22 90 Figure 4.5: Variation in cargo nature handled by respondents' organizations. FCL Cargo Composition Figure 4.6 and Table 4.7 show that a significant majority of respondents carry primarily FCL cargo. This is perfect for our study because the assumption is that if the entire container 76 belongs to an organization, the organization will have greater incentives to ensure that the integrity of its international movement is not compromised. Therefore, the responses given by these companies can be seen as more credible in terms of perceptions and intentions. Table 4.7: Shipment size nature of respondents. Shipper Service Provider Total FCL 95 37 132 Not FCL 18 13 31 Figure 4.6: Variation in shipment size nature of respondents. Not FCL 19% Trade Route Profile Respondents are asked to indicate their three most frequently used trade routes. Figure 4.7 and Table 4.8 show that a significant majority of the respondents are moving cargo within North America and between North America and Asia. Table 4.8: Respondents' trade route profile. Trade Route Shipper Service Provider Total Infra Americas 67 22 89 Asia >> N.America 52 26 78 N.America >> Asia 28 8 36 Infra Asia 21 11 32 N.America >> Europe 23 7 30 Europe >> N.America 27 3 30 Asia >> Europe 8 9 17 Infra Europe 14 2 16 Europe \u00C2\u00BB Asia 6 2 8 Others 1 6 7 N.America >> Middle East 5 1 6 S.America \u00C2\u00BB Europe 3 2 5 Asia >> Middle East 2 2 4 Middle East \u00C2\u00BB N.America 3 0 3 Asia >> S.America 2 0 2 S.America >> Asia 0 1 1 Europe >> S.America 1 0 1 Europe >> Middle East 1 0 1 S.America >> Middle East 0 0 0 Middle East \u00C2\u00BB Asia 0 0 0 Middle East \u00C2\u00BB S.America 0 0 0 Middle East >> Europe 0 0 0 77 Intra Americas Asia \u00C2\u00BB N.Amenca N.America >> Asia Infra Asia NAmerica \u00C2\u00BB Europe Europe >> N.America Asia \u00C2\u00BB Europe Infra Europe Europe \u00C2\u00BB Asia Others it.iffin N.America \u00C2\u00BB kiddie East\" S.America \u00C2\u00BB Europe ; \u00E2\u0080\u0094771 Asia >> kiddie East IRO kiddie East \u00C2\u00BB N.America Asia \u00C2\u00BB S.A merica S.America >> Asia Europe >> S.America Europe \u00C2\u00BB Riddle East J 0 ^ 10^20^30^40^50^60^70 ^ 80^90 Figure 4.7: Variation in respondents' trade route profile. Frequency (Count) Organization Size Respondents' organization size is reflected by their 2006 annual revenues in U.S. dollars. Figure 4.8 and Table 4.9 show that majority of the respondents belong to large organizations with annual revenues exceeding US$1 billion. More than two-thirds belong to organizations with annual revenues exceeding US$100 million. It is however interesting to note that most of the large organizations belong to the Shipper category. The organization size of surveyed service providers are more evenly distributed with most of them being relatively smaller organizations with annual revenues between US$20 million and US$500 million. Table 4.9: Respondents' 2006 annual revenues profile. Range Shipper Service Provider Total < 20 mil 5 13 18 20 mil - 100 mil 11 14 25 100 mil - 500 mil 21 10 31 500 mil - 1 bil 11 2 13 > 1 bil 65 11 76 78 Overall Firm Size (Annual Revenues US$) 11% 47% 8% Shipper Firm Size (Annual Revenues US$) <20 nil 20 nil - 100 nil 100 nil - 500 nil 500 nil - 1 bil > 1 bil Service Provider Firm Size (Annual Revenues US$) F-4% 22\u00C2\u00B04 26% < 20 nil tg 20 nil - 100 nil 100 nil- 500 nil 500 nil- 1 bil > 1 bil Narrow 14% Wide^ Average 62\u00C2\u00B0A 24% Figure 4.8: Respondents' 2006 annual revenues profile. < 20 nil 20 nil- 100 nil 100 nil- 500 mil 500 nil - 1 bil > 1 bil Decision Making Scope/Scope of Supply Chain Influence Figure 4.9 and Table 4.10 show that majority of the respondents hold considerable influence and/or decision making authority over the operations of their supply chain. This profile demonstrates the credibility of the opinions gathered in the survey and is especially encouraging for the analysis and results of this study. Please refer to section 5.2.5 for a detailed discussion and definition of the various scopes of control. Table 4.10: Respondents' scope of influence over their supply chain. Decision Making Scope Shipper Service Provider Narrow 16 7 Average 27 12 Wide 70 31 Figure 4.9: Respondents' scope of influence over their supply chain. Decision Making Scope - Shipper Decision Making Scope - Service Provider Narrow 147, 79 Physical Locations of Respondents Others 1% China a Hong Kong Singapore Canada USA \u00E2\u0096\u00A0 OthersUSA 44% China 35% Respondents' Physical Locations Figure 4.10 and Table 4.11 below show a balanced variation in the proportion of respondents from North America and Asia. Table 4.11: Physical locations of respondents. Location Shipper Service Provider Total China 28 16 44 Hong Kong 3 2 5 Singapore 6 4 10 Canada 3 7 10 USA 39 16 55 Others 1 0 1 Figure 4.10: Variation in physical locations of respondents. Hong Kong Singapore^4% 8%Canada 8% Note: The country included in the \"Others\" category is United Kingdom. Respondents' Dominate Culture in Business Management With globalization, we can reasonably expect respondents to be physically located in a country but be influenced by another country's culture in managing their business. The survey asked each respondent to indicate the culture that dominates their behaviour and attitude in the day to day management of their business. Figure 4.11 and Table 4.12 show that even though respondents are evenly located in North America and Asia, majority of them are influenced by the Anglo culture, which includes countries such as England, Australia, South Africa (White), Canada, New Zealand, Ireland and the U.S.. 3\u00C2\u00B0 China, Singapore and Hong Kong all belong to the Confucian Asia cluster. 3\u00C2\u00B0 The cultural clusters used in Figure 4.11 and Table 4.13 are from Gupta et al. (2002). Using data collected on cultural values and beliefs from 61 nations, Gupta et al. (2002) used discriminant analysis, split half sample and cross-validation to provide strong support to the existence of 10 cultural clusters: South Asia, Anglo, Arab, Germanic Europe, Latin Europe, Eastern Europe, Confucian Asia, Latin America, Sub Sahara Africa and Nordic Europe. 80 Germanic South Asian^1% 2% Anglo Confucian Asia South Asian Germanic Latin Europe Na Latin America Respondents' Dominant Culture Latin Europe 5%^Latin America 3% Table 4.12: Respondents' dominant culture in business management. Cluster Group Shipper Service Provider , Total Anglo 62 30 92 Confucian Asia 14 13 27 South Asian 2 0 2 Germanic 0 1 1 Latin Europe 4 2 6 Latin America 3 1 4 Arab 0 0 0 Eastern Europe 0 0 0 Nordic Europe 0 0 0 Sub-Sahara Africa 0 0 0 Figure 4.11: Variation in respondents' dominant culture in business management. Confucian Asia \u00E2\u0080\u0094 20% 4.3 Types of Variables The survey responses can be represented by two main types of variables \u00E2\u0080\u0094 observed and latent. Observed variables are those variables that can be observed and directly measured. Latent variables, on the other hand are those variables that are not or cannot be directly observed but are rather inferred from observed variables. Based on the research conceptual framework presented in Chapter 3, the types of variables required to answer the research questions of interests were identified and are listed in Table 4.13. How each variable is operationalized in the web/e-mail survey instrument is shown in the right hand column. 81 Table 4.13: Types of variables. Variable Observed/Latent How Operationalized A. Organization size Observed \u00E2\u0080\u00A2 Annual sales revenue (2005) B. Supply chain characteristics Observed \u00E2\u0080\u00A2 Industrial sector \u00E2\u0080\u00A2 Commodity carried \u00E2\u0080\u00A2 Hazardous / Non-hazardous \u00E2\u0080\u00A2 Average shipment size \u00E2\u0080\u00A2 Major trade routes C. Supply chain control Latent \u00E2\u0080\u00A2 # of aspects of supply chain operations that are performed in-house and outsourced versus not controlled D. Supply chain drivers Observed \u00E2\u0080\u00A2 Self rate importance of five supply chain drivers* and security E. Supply chain performance Observed \u00E2\u0080\u00A2 Self rate performance on five key aspects of supply chain performance* on 7-point Likert scale F. Security performance Observed \u00E2\u0080\u00A2 Self rate performance on 7-point Likert scale G. Supply chain KPIs Observed \u00E2\u0080\u00A2 Rate appropriateness on 32 KPIs H. Supply chain security KPIs Observed \u00E2\u0080\u00A2 Respondent opinion on necessity for security KPIs \u00E2\u0080\u00A2 Rate appropriateness on 32 KPIs^ Notes to Table 4.1: * the selection of the drivers and key performance indicators is based on the comprehensive review of 20 of the 116 studies in Keller et al. (2002), SCOR version 8.0 and several other recent studies on supply chain performance and results from the field interviews. Citations of these studies can be found in Appendix D. A the selection of the security KPIs is based on the results from the field interviews and recent literature on supply chain security. Other observed variables in this study includes various supply chain characteristics/facts such as industrial sector, commodity and their hazardous nature, the average shipment sizes and key trade routes and the performance on various supply chain performance KPIs. It also includes organization size in terms of annual revenues and importance of various supply chain drivers. There is only one latent variable \u00E2\u0080\u0094 span of supply chain control/influence. The span of supply chain control variable is considered a latent variable because respondents are asked to indicate if they have decision influence over a set of 12 activities and the span of control variable is inferred by arbitrarily grouping respondents into three categories. Respondents in the first group have eight or more of the 12 activities managed in-house and therefore are considered to have a wide span of control. Respondents in the second group have four to seven activities managed in-house and are considered as having an average span of control. Lastly, the respondents in the third group have less than 4 activities managed in-house and are therefore considered as having a narrow span of control. 82 CHAPTER 5 ANALYSIS This Chapter discusses the analyses performed on the data collected in this study. 5.1 General Attitude Towards Supply Chain Security The opinions gathered from the field interviews revealed that many of the shipper and service provider organizations interviewed do not see advancement in security as a competitive advantage at this point in time. They see security threats as mainly thefts, pilferages and cargo damage. This opinion does not vary significantly among respondents from Asia and North America. The majority of the organizations interviewed during the field interviews also pointed out that what are considered reasonable requirements for some businesses might not necessarily be reasonable for others. For instance, an organization trading low value items such as plastic household products for hyper-marts will definitely find GPS-equipped trucks a less reasonable security requirement as compared to an organization handling non-weaponry supply business for the U.S. army in Iraq. The majority of the organizations interviewed also have their principal physical operating activities in China and South East Asia and most do not perceive these geographic locations as imminent targets or breeding grounds for terrorism as compared to some other countries such as U.S. and U.K. The U.S. Customs and Border Protection (2006) publication has also explicitly mentioned that the adoption of certain best practices depends on the risks assessments on the operating environment. It writes that while the adoption of certain best practices in a low risk environment might be sufficient to mitigate the risks present and enable the importer to qualify for Tier Three standing under the C-TPAT program, the adoption of the same practices may be viewed as a necessary, minimum security measure in a high risk environment and therefore not elevate the overall security environment to the point at which the importer would be considered for Tier Three. The majority of the service provider organizations interviewed also cite the fact that their customers are not currently demanding security requirements beyond what they are already receiving, as a key reason behind the lack of enthusiasm. 83 Supply chain security is more than just mitigating the risks of terrorism. However, many of the organizations interviewed, especially those in Shanghai, China, perceive incidents such as human smuggling, which they have experienced, as harmless incidents that do not cause devastating damages to human lives and public infrastructures. Hence they do not consider them as security threats. Moreover, they feel that the same means used for preventing such crimes can also be used against terrorism. This opinion is echoed by the participants in Wills and Ortiz's 2004 study which noted that terrorism can be prevented using many of the same means used for preventing theft and smuggling because each objective requires the system to be able to control the cargos enter and leave the system. Many of the organizations interviewed also do not see an impending need to invest heavily in security improvement initiatives unless required by legislation in order to continue operations legally. These sentiments are shared by the respondents in Peleg-Gillai et al.'s 2006 study where many found it difficult to provide a business case to justify security investments and are therefore reluctant to invest in security beyond the minimum necessary. However, the organizations interviewed in this study are cognizant that depending on how the market dynamics and public sector's legislations and regulations around security develop, their organizations need to be ready and willing to comply within their best ability. For example, a few of the larger companies are already investing in relatively more high-tech security solutions such as GPS and Biometrics. Most of these solutions were undertaken as a result of the need to comply with regulations or requirements from their business customers. These security requirements can range from basic items such as installing a minimum number of CCTVs within a warehouse to sophisticated ones such as being C-TPAT certified and/or having all trucks GPS-equipped. These same sentiments can be seen in the results from the web survey. Respondents to the web survey were asked to evaluate and rank the importance of security as a supply chain driver relative to five other traditional supply chain drivers \u00E2\u0080\u0094 efficiency, reliability, responsiveness, availability and timeliness. 84 Efficiency ^ Timeliness ^ Reliability ^ Availablity ^ Responsiveness ^ Security Figure 5.1 and Table 5.1 show that the security driver is ranked very differently (lower) 31 from the other traditional supply chain drivers. Within the \"Extremely Important\" ranking, a significant smaller proportion of respondents ranked security as such (26% for security vs an average of 37% for the rest of the drivers). Combining \"Extremely Important\" and \"Very Important\" categories, still a significantly smaller of proportion of respondents rank security as such (59% for security vs. an average of 77% for the rest of the drivers. A further cumulative combination of \"Extremely Important\", \"Very Important\" and \"Important\" categories, still a significantly smaller proportion of respondents rank security as such (85% for security vs. an average of 92.4% for the rest of the drivers). Table 5.1: Respondents' view of security as a supply chain driver. Importance Efficiency Timeliness Reliability Availability Responsiveness Security Extremely Important 29% 38% 38% 36% 44% 26% Very Important 46% 44% 45% 31% 34% 33% Important 15% 13% 11% 22% 16% 26% Moderately Important 9% 5% 6% 8% 6% 10% Somewhat Important 0% 1% 0% 2% 0% 2% Slightly Important 1% 0% 0% 0% 0% 1% Not Important 0% 0% 0% 1% 0% 2% Total_^163 163 163 163 163 163 Average Rank 5.94 6.13 6.15 5.90 6.15 5.60 50th Percentile 6.00 6.00 6.00 6.00 6.00 6.00 90th Percentile 7.00 7.00 7.00 7.00 7.00 7.00 Figure 5.1: Respondents' view of security as a supply chain driver. El Not at all Important LI Slightly Important LI Somewhat Important 0 Moderately Important ^ Important LI Very Important Extremely Important 31 Recall from Chapter 4 that only one out of the 163 web survey respondents come from a port authority. As such, the result in Figure 5.1 reflects only the sentiments from the shippers and service provider organizations. 85 t O \u00E2\u0080\u00A2 60% 0. 0 it 40% 100% 80% 20% Efficiency Timeliness Reliability Availability Responsiveness^Security 0 Not at all Important Ei Slightly Important ; ^ Somewhat Important El Moderately Important Important 2 Very Important Extremely Important The sample is also split into shippers and service providers to see if there are any attitude differences between the two groups. An initial visual analysis of the same charts for shippers and service providers (Figures 5.2 and 5.3 respectively) show that there are no apparent differences in attitudes towards security as a supply chain driver. Within the shipper and service provider groups separately, respondents rank security lower as a supply chain driver compared to the other five traditional aspects of SCP. Figure 5.2: Shipper respondents' view of security as a supply chain driver. Efficiency^Timeliness^Re iabity^Availability^Responsiveness^Security E Not at all Important 7 Slightly Important Somewhat Important -; Moderately Imported ^ Important Very Important :\u00E2\u0080\u00A21 Extremely Important Figure 5.3: Service providers' view of security as a supply chain driver. Since there are no apparent differences between shipper and service provider groups, the following statistical tests were carried out using a combined sample. These tests are performed to determine if the difference in ranking between security and other aspects of SCP are 86 statistically significant. The average ranking for security as a driver is 5.60 (Table 5.1), which is 0.55 points lower than the highest ranked drivers - Reliability and Responsiveness. Two-tailed 32 paired t-tests 33 were performed to determine if these differences are statistically significant (see Table 5.2). Table 5.2 shows that the differences between all drivers paired with security driver are statistically significant (i.e. pairs 5, 9, 12, 14 and 15), where the Sig. (2-tailed) values are smaller than 0.025. These pairs are marked with an \"*\". The differences in mean for these pairs are positive, indicating that the security driver (being the latter variable in each pair), is ranked significantly lower than the former variable in the pair. Table 5.2: Results for statistical tests for significance in differences in ranking of drivers. Paired Differences t df Sig. (2-tailed) Mean Std. Deviation Std. Error Mean Mean Std. Deviation Std. Error Mean Pair 1\" Efficiency - Time -0.1902 0.8281 0.0649 -2.9320 162 0.0039 Pair 2* Efficiency - Reliability -0.2025 0.7467 0.0585 -3.4617 162 0.0007 Pair 3 Efficiency - Availability 0.0491 1.0049 0.0787 0.6235 162 0.5338 Pair 4* Efficiency - Responsiveness -0.2086 0.8989 0.0704 -2.9625 162 0.0035 Pair 5* Efficiency - Security 0.3436 1.0851 0.0850 4.0421 162 0.0001 Pair 6 Time - Reliability -0.0123 0.6666 0.0522 -0.2350 162 0.8145 Pair 7* Time - Availability 0.2393 0.9676 0.0758 3.1570 162 0.0019 Pair 8 Time - Responsiveness -0.0184 0.6981 0.0547 -0.3366 162 0.7368 Pair 9* Time - Security 0.5337 1.1401 0.0893 5.9771 162 0.0000 Pair 10* Reliability - Availability 0.2515 0.9645 0.0755 3.3297 162 0.0011 Pair 11 Reliability - Responsiveness -0.0061 0.7973 0.0625 -0.0982 162 0.9219 Pair 12* Reliability - Security 0.5460 1.0316 0.0808 6.7574 162 0.0000 Pair 13* Availability - Responsiveness -0.2577 1.0691 0.0837 -3.0769 162 0.0025 Pair 14* Availability - Security 0.2945 1.2469 0.0977 3.0152 162 0.0030 Pair 15* Responsiveness - Security 0.5521 1.2676 0.0993 5.5611 162 0.0000 This result is consistent with the findings from the field interviews where the majority of the respondents from the shipper and service provider groups expressed that they do not see security as an apparent competitive advantage that is distinct from the other traditional drivers of supply chain. This result is also consistent with current literature that talks about the fact that 32 Since there are no a priori theories supporting a higher ranking of one driver versus another driver, the null hypotheses being tested here are whether the difference between the mean rankings of two drivers are significantly different from 0. Therefore, two-tailed tests are used. 33 Paired t-tests are used instead of Analysis of Variance (ANOVA). This is because the paired t-test procedure compares the means of two variables for a single group with no assumption made about the causal relationship between the two variables. ANOVA on the other hand, seeks to explain the variation in a variable (dependent variable) as a result of the treatment to another variable (independent variable). In this case, since a causal relationship is not logically expected among the ranking of the supply chain drivers, the paired t-test procedure is used. 87 most private organizations are reluctant to invest in security beyond the minimum necessary for compliance and reducing cargo theft and pilferages (Willis and Ortiz, 2004; Peleg-Gillai et al., 2006). Although so, it is also important to share that some of the interviewees from the field interviews cited that regardless of what their specific business value propositions are, they either see or are beginning to see security as a potential disruptor to their ability to deliver their value proposition all the time. One of the main reasons cited by respondents is that their general consumer base in North America are very concerned about security and they do not want any breaches to impact their reputation as a preferred supplier. Some of them have also assisted their customers' in their C-TPAT applications. For those organizations that also consider supply chain management as a competitive advantage and key driver to the fulfilment of their customer service value proposition, notwithstanding what the underlying supply chain driver(s) (e.g. efficiency, timeliness, responsiveness and agility, availability and reliability) are, they do see the potential of supply chain security as becoming an ultimate driver to supply chain excellence, although not immediately. This is because security breaches threaten the fundamental reliability of their operations and value delivery. 5.2 Factors that Affect Attitude Towards Security From the results of the field interviews, several characteristics stood out as factors that affect an organization's attitude and the extensiveness of their efforts towards ensuring security in the supply chain that they are participating in. These factors are what these organizations look at when they evaluate the general level of risk in their trading environment. Several hypotheses were derived based on the review of existing literature and the information gathered from the field interviews. The following analyses uses data collected from the web/email survey to validate these hypotheses. Cross-tabulation 34 analyses are performed where appropriate to validate some of these findings. 34 The cross-tabulation technique is used because the variables used are categorical in nature (Hair et al., 1998). ANOVA is appropriate when variables are scaled. 88 5.2.1 Organization Size (Annual Revenue) At the development stage of the field interview questionnaire, the author hypothesized that the size of an organization can have impacts on its attitude towards security improvements. Organization size is measured by the organization's 2006 annual revenues in US dollars. Results from the field interviews supported this hypothesis. There is a general attitude difference between large and small organizations. Large organizations are characterised by higher annual revenues and/or greater employee count. Large organizations tend to place or have already placed considerably more emphasis on supply chain security. Most, if not all of them expressed that ensuring security in their supply chain is very to extremely important (though not a competitive advantage or supply chain driver). Many of them have also undertaken some form of security initiatives beyond the basic requirements for safe business operations. Eight of the 21 organizations interviewed are C-TPAT certified or in the process of getting their certification and all of them are large organizations with annual revenues greater than US$1 billion. These organizations also tend to be more proactive in employing more sophisticated security enhancement technology. For example, the number of employees within the organization may affect the degree of negative impacts of security breaches. As such, organizations with more employees especially those located in less secure environments, tend to place greater emphasis on personnel security and have more stringent security measures in place such as biometric access controls. With a larger volume of cargo movement and transactions, these larger organizations also have more to lose if a security breach impacts the flow of goods to their markets. Results from the web/email survey are discussed next. Recall that respondents were asked to express their opinions about the importance of security as a supply chain driver using a 7-point Likert scale. These ratings have been consolidated into three categories \u00E2\u0080\u0094 (1) Not important, (2) Moderately important and (3) Very important, for ease of evaluation (see Table 5.3). An initial visual analysis of the data and bar charts comparing the security driver rating among different annual revenue groups (Table 5.3 and Figure 5.4) show that although there is a larger proportion of organizations in the larger revenue group ranking security as very important, there are no significantly large differences in attitudes between large and small organizations. 89 Table 5.3: Ranking of security driver by organizations of different sizes. Security_Driver TotalVery Important Moderately Important Not Important Annual Revenue < 20 mil 78% 17% 6% 100% 20 mil - 100 92% 4% 4% 100% 100 mil - 500 87% 13% 0% 100% 500 mil - 1 bil 85% 8% 8% 100% > 1 bil 84% 13% 3% 100% Total 85% 12% 3% 100% Figure 5.4: Ranking of security driver by organizations of different sizes. Not Important Moderately Important Very Important < 20 nil^20 nil - 100 100 nil - 500 500 mil - 1 bil ^ > 1 bil nil^nil 2006 Annual Revenue (US$) Table 5.4 shows that the difference in mean ranking of security as a supply chain driver between the largest and smallest revenue groups is 0.02. In fact, the results are reversed of our expectations, i.e. respondents in the smallest revenue group have a higher mean ranking compared to respondents in the largest revenue group. Table 5.4: Mean ranking of security driver for different revenue groups. Label Annual_Revenue Mean N Std. Deviation AR1 < 20 mil 5.61 18 1.29 AR2 20 mil - 100 mil 5.36 25 1.11 AR3 100 mil - 500 mil 5.84 31 1.04 AR4 500 mil - 1 bil 5.54 13 1.66 AR5 > 1 bil 5.59 76 1.32 Total 5.60 163 1.26 90 Further statistical tests were performed to determine if these slight differences are statistically significant. Paired sample t-tests were performed and results shown in Table 5.5 are inconclusive. There are only two pairs of revenue groups that have significant differences in their mean ranking of security as a supply chain driver. Pair 2 is between AR1 (< 20 mil) and AR3 (100 mil - 500 mil). Pair 5 is between AR2 (20 mil and 100 mil) and AR3 (100 mil - 500 mil). There are however no consistent patterns between these pairs for any meaningful conclusions to be drawn. Table 5.5: Results for statistical tests for significance in differences in security driver ranking. Paired Differences t df Sig. (2- tailed)Mean Std. Deviation Std. Error Mean 95% Confidence Upper Lower Pair 1 AR1 - AR2 0.1111 1.3672 0.3223 -0.5688 0.7910 0.3448 17 0.7345 Pair 2* AR1 - AR3 -0.6111 1.7536 0.4133 -1.4832 0.2609 -1.4785 17 0.1576 Pair 3 AR1 - AR4 0.0769 2.5646 0.7113 -1.4728 1.6267 0.1081 12 0.9157 Pair 4 AR1 -AR5 0.3333 2.2229 0.5239 -0.7721 1.4387 0.6362 17 0.5331 Pair 5* AR2 - AR3 -0.6800 1.2490 0.2498 -1.1956 -0.1644 -2.7222 24 0.0119 Pair 6 AR2 - AR4 0.1538 1.7723 0.4915 -0.9171 1.2248 0.3130 12 0.7597 Pair 7 AR2 - AR5 -0.0400 2.0306 0.4061 -0.8782 0.7982 -0.0985 24 0.9224 Pair 8 AR3 - AR4 1.0769 1.7541 0.4865 0.0169 2.1369 2.2136 12 0.0470 Pair 9 AR3 - AR5 0.2581 2.0489 0.3680 -0.4935 1.0096 0.7013 30 0.4885 Pair 10 AR4 - AR5 0.1538 1.9936 0.5529 -1.0509 1.3586 0.2782 12 0.7856 Further cross-tabulation analyses were also conducted with the following control variables: (1) respondent type (i.e. shipper versus service provider), (2) entire firm versus SBU and (3) respondent physical location (i.e. Asia versus North America). Table 5.6 shows one of the cross-tabulation results with respondent type as the control variable. The corresponding chi-square test is shown in Table 5.7 and results indicate no statistically significant differences in the mean ranking of security as a supply chain driver among the groups. None of the other cross-tabulation results for control variables - firm versus SBU and respondent physical location, indicate statistically significant differences in the mean ranking of security as a supply chain driver among the groups. Detailed results for the other cross- tabulation analyses are not provided here because they are all statistically insignificant. They can however be found in Appendix F. 91 Table 5.6: Cross-tabulation results (respondent type). Respondent Type Security Driver Total Not Important Moderately Important Very Important Shipper Annual_ < 20 mil Count 0 1 4 5 Revenue % within Annual_ Revenue .0% 20.0% 80.0% 100.0% 20 mil - 100 mil Count 1 1 9 11 % within Annual_ Revenue 9.1% 9.1% 81.8% 100.0% 100 mil - 500 mil Count 0 4 17 21 % within Annual_ Revenue .0% 19.0% 81.0% 100.0% 500 mil - 1 bil Count 1 1 9 11 % within Annual_ Revenue 9.1% 9.1% 81.8% 100.0% > 1 bil Count 1 9 55 65 % within Annual_ Revenue 1.5% 13.8% 84.6% 100.0% Total Count 3 16 94 113 % within Annual_ Revenue 2.7% 14.2% 83.2% 100.0% Service Annual_ < 20 mil Count 1 2 10 13 Provider Revenue % within Annual_ Revenue 7.7% 15.4% 76.9% 100.0% 20 mil - 100 mil Count 0 0 14 14 % within Annual_ Revenue .0% .0% 100.0% 100.0% 100 mil - 500 mil Count 0 0 10 10 % within Annual_ Revenue .0% .0% 100.0% 100.0% 500 mil - 1 bil Count 0 0 2 2 % within Annual_ Revenue .0% .0% 100.0% 100.0% > 1 bil Count 1 1 9 11 % within Annual_ Revenue 9.1% 9.1% 81.8% 100.0% Total Count 2 3 45 50 % within Annual_ Revenue 4.0% 6.0% 90.0% 100.0% Table 5.7: x 2 test for cross-tabulation results with respondent type as control variable. Respondent_Type Value df Asymp. Sig. (2-sided) Shipper^Pearson Chi-Square 5.346a 8 .720 Likelihood Ratio 4.760 8 .783 Linear-by-Linear Association .306 1 .580 N of Valid Cases 113 Service Provider^Pearson Chi-Square 6.457b 8 .596 Likelihood Ratio 8.170 8 .417 Linear-by-Linear Association .003 1 .959 N of Valid Cases 50 92 Therefore, we conclude that the survey data does not seem to support the hypothesis that larger organizations tend to place more importance on security improvements. This could be a reflection of a \"need\" to be \"politically correct\" when it comes to security issues. 5.2.2 Extent of Overseas Sourcing An organization's key sourcing countries also affect the degree of their security efforts. Of the sample of organizations interviewed in Vancouver, Canada, organizations that do a lot of overseas sourcing especially from Asia and/or the Middle East, tend to place more efforts and emphasis on security issues and related legislative developments. Organizations that source the majority of their products from within Canada or just across the border from U.S. are less concerned about security breaches such as terrorism. This could be due to the confidence they have in the integrity of both the Canadian national transportation network and the U.S. customs authorities at the border-crossings between the two countries. Similarly for exporters in Asia, organizations that use a relatively larger percentage of raw material imports in their production of final products tend to see security as a more immediate operations element compared to organizations that source most of their raw materials locally. Information regarding the respondent's organization's degree of overseas sourcing is not collected in the survey instrument. 5.2.3 Cargo Nature Based on the findings from field interviews, it was hypothesized that the nature of an organization's products may also affect the extent and type of security measures an organization adopts. Organizations that carry hazardous materials may be more willing to invest in security improvements compared to organizations that do not. Again, similar analyses are performed to determine if the data from the survey supported this hypothesis. 93 An initial visual analysis of the data and bar charts (Table 5.8 and Figure 5.5) shows that there are no significant differences in the ranking of security as a supply chain driver between organizations who carry hazardous cargo and those who do not. Table 5.8: Ranking of security driver. (Between hazardous and non-hazardous cargo carrying organizations) Security_Driver TotalVery Important Moderately Important Not Important Hazardous No 84.44% 11.11% 4.44% 100% Yes 86.30% 12.33% 1.37% 100% Total 85.28% 11.66% 3.07% 100% Figure 5.5: Ranking of security driver. (Between hazardous and non-hazardous cargo carrying organizations) Not Important Moderately Important Very Important No ^Yes Hazardous? Table 5.9 shows that the difference in mean ranking of security as a supply chain driver between the two groups is 0.27. Further statistical tests were performed to determine if the difference in mean rankings between the two groups of respondents is statistically significant. Results of the paired sample t-tests show that this slight difference of 0.27 is statistically not significant (Table 5.10). Table 5.9: Mean ranking of security driver. (Between hazardous and non-hazardous cargo carrying organizations) Hazardous Mean N Std. Deviation No 5.48 90 1.33 Yes 5.75 73 1.16 Total 5.60 163 1.26 94 Table 5.10: Results for statistical tests for significance in differences in security driver ranking. Paired Differences t df Sig. (2- tailed)Mean Std. Deviation Std. Error Mean 95% Confidence Interval Upper Lower Pair 1^IN0 - Yes -0.3151 1.9499 0.2282 -0.7700 0.1399 -1.3806 72 0.1717 Further cross-tabulation analyses were conducted with the following control variables: (1) respondent type (i.e. shipper versus service provider), (2) entire firm versus SBU and (3) respondent physical location (i.e. Asia versus North America). None of the cross-tabulation results indicate statistically significant differences in the mean ranking of security as a supply chain driver between the two groups. Detailed results of these cross-tabulations are not provided here because they are statistically insignificant but they can be found in Appendix F. We therefore conclude that the results from the survey do not support the hypothesis that organizations carrying hazardous cargo have a greater tendency to view security as a supply chain driver compared to organizations that do not. This observation could be due to the fact that the movement of hazardous cargo has had a long history of being under the governance of The Responsible Care \u00C2\u00AE ethic. 35 As such, for organizations that move hazardous materials, they do not see themselves as doing anything very differently. They have also always viewed safety and security of cargo movement as an important element in their customer fulfilment process. Organizations that do not move hazardous cargo, on the other hand, will now view security as more important than in the past because of the influx of international cargo movement security regulations and requirements. 5.2.4 Size of Shipment The typical size of an organization's shipments also speaks of the amount of risk and potential losses an organization will suffer in the event of a security breach. All else being equal, organizations with typically smaller shipments are exposed to considerably lesser potential losses from security breaches, although they experience a greater number of hand-offs in their cargo movement process. 35 The Responsible Care \u00C2\u00AE ethic is the chemical industry's global voluntary initiative under which companies, through their national associations, work together to continuously improve their health, safety and environmental performance, and to communicate with stakeholders about their products and processes. http://www.responsiblecare.orq 95 Organizations interviewed that tend to have relatively smaller shipments (that is, less-than- container loads), are less worried about security breaches compared to those who typically ship full container loads and in large quantities. For example, one of the organizations interviewed uses mainly air freight because of the very small size of their shipments and relatively high retail value of their products. The supply chain manager interviewed cited his confidence in airfreight movement as one of the reasons why his organization has yet to invest heavily in security initiatives. Again, data collected from the web survey is analysed to determine if this hypothesis is valid. An initial visual analysis of the data and bar charts (Table 5.11 and Figure 5.6) show that there are no significant differences in the ranking of security as a driver between the two groups. Table 5.11: Ranking of security driver between FCL and no-FCL cargo carrying organizations. Security_Driver TotalVery Important Moderately Important Not Important FCL No 90.32% 6.45% 3.23% 100% Yes 84.09% 12.88% 3.03% 100% Total 85.28% 11.66% 3.07% 100% Figure 5.6: Ranking of security driver. (Between FCL and No-FCL cargo carrying organizations) Not Important Moderately Important Very Important No^Yes FCL? Table 5.12 shows that the difference in mean ranking of security as a supply chain driver between the two groups is 0.13. In fact, these mean values are reversed of our expectations. Respondents in the No-FCL group have a greater mean ranking than respondents in the Yes- FCL group. Reasons for this observation include: 96 \u00E2\u0080\u00A2 Respondents in the no-FCL group may perceive non-FCL shipments as more vulnerable compared to FCL shipments as a result of more number of hand-offs and re-handling of cargo. \u00E2\u0080\u00A2 A closer look at the supply chain types of the respondents in the non-FCL group and FCL group reveals a wider mix of respondents in the FCL group. Respondents in the non-FCL group consist of organizations handling FMCG, food and pharmaceuticals and electronics. The FCL group on the other hand consist of organizations handling anything from FMCG to heavy machinery, chemicals, forestry and aerospace. This wide mix may have even-out any strong opinions some respondents might have regarding the importance of security as a business driver. Further statistical tests were however performed to determine if the difference in mean rankings between the two groups of respondents is statistically significant. Results of the paired sample t- tests show that this slight difference of 0.13 is statistically not significant (Table 5.13). Table 5.12: Mean ranking of security driver. (Between organizations who ship FCL and those who do not) FCL Mean N Std. Deviation No 5.71 31 1.13 Yes 5.58 132 1.29 Total 5.60 163 1.26 Table 5.13: Results of statistical tests for significance in differences in security driver ranking. Paired Differences t df Sig. (2- tailed) 0.5035 Mean Std. Deviation Std. Error Mean 95% Confidence Interval Upper Lower Pair 1^!No - Yes 0.2258 1.8567 0.3335 -0.4552 0.9068 0.6771 30 Further cross-tabulation analyses were conducted with same control variables: (1) respondent type (i.e. shipper versus service provider), (2) entire firm versus SBU and (3) respondent physical location (i.e. Asia versus North America). None of the cross-tabulation results indicate statistically significant differences in the mean ranking of security as a supply chain driver between the two groups. Detailed results for these cross-tabulation analyses are not provided because they are all statistically insignificant but can be found in Appendix F. 97 We therefore conclude that the results from the survey do not support the hypothesis that organizations carrying FCL cargo have a greater tendency to view security as a supply chain driver compared to organizations that do not. Again this could be due to the \"need\" to be \"politically correct\" on a sensitive issue such as security. 5.2.5 Scope of Supply Chain Control/Influence In the field interviews, interviewees were also asked to give an assessment of the span of control and influence their organization has over the supply chain that they are participating in. Although most of the organizations interviewed consider supply chain security to be very to extremely important and recognize the importance of the role of market dynamics in their onward efforts in supply chain security, organizations with different scope of control over their supply chain can take quite a different stance as to of who should lead the security initiatives in the supply chain. Organizations with a narrower span of control/influence (such as terminals and suppliers selling mainly Ex-works) tend to feel that the ultimate customer (i.e. the buyer) should take the lead in initiating supply chain wide security improvements and also assume the costs of such initiatives. Organizations that has a wider span of control or influence over their supply chain, on the other hand, tends to view supply chain management as one of their organization's competitive advantage. These organizations tend to be shippers (either exporters or importers) but can also be large service providers. These organizations tend to take a more proactive approach towards ensuring security in the supply chain that they are participating in. Organizations in this group also can afford more high-tech security solutions such as biometrics access controls but most of the initiatives taken by this group of organizations are more internal in nature and seeks to protect the safety and interests of their company's personnel only. Based on a list of 16 supply chain activities (Table 5.14), interviewees and survey respondents were asked to indicate whether an activity is controlled in-house, outsourced and managed through contractual obligations and performance measurements or not controlled at all. 98 Table 5.14: List of supply chain activities. Activity Aspects of Supply Chain A Choice of suppliers (e.g. manufacturers) B Trucking or other inter-modal transportation from factory to origin port C Warehousing at origin D Freight consolidation at origin E Customs clearance at origin F Cross-border trucking to origin port or final destination (if required) G Choice of port of loading H Choice of terminal at origin I Choice of carriers (i.e. freight contracts) J Choice of port of destination K Choice of terminal at destination L Customs clearance at destination M Cross-border trucking from destination port to final destination (if required) N Warehousing at destination 0 Freight deconsolidation / break bulk at destination P Trucking or other inter-modal transportation to final location at destination For shippers, these activities are grouped into two clusters based on where these activities take place (i.e. where the control is exerted). This is because the origin operations and destination operations are usually handled or overseen by different business entities (i.e. sellers for origin and buyers for destination). The origin cluster for shippers includes seven activities B to H. The destination cluster for shippers includes nine activities A, I to P. Activity A is included in the destination cluster because the decision as to which suppliers to use is made by the buyer at destination. Activity I \u00E2\u0080\u0094 choice of carriers is included in the destination cluster because sellers/suppliers usually sell free-on-board (FOB) and buyers are more often than not the ones who determine which carrier to use based on either pre-negotiated contracts (for volume discount) or sailing schedules that meet their cargo required date. Even when buyers themselves do not command the volumes for full-container-load shipping, they are usually the ones who engage freight forwarders. For service providers, there are also two clusters \u00E2\u0080\u0094 one for origin and one for destination. These clusters are appropriate because service providers always have a physical presence in the geographical locations that they serve and operations decisions are always made locally. However, activity A is not applicable. Therefore, the eight activities in the origin cluster include activities B to I and destination cluster includes seven activities J to P. In the case of service providers, Activity 7 \u00E2\u0080\u0094 choice of carriers, is included in the origin cluster because in the rare event that the service provider gets to decide which carrier to use, it is the office at the origin location that makes that decision and triggers the booking with the ocean carrier. 99 An organization's span of control is represented as wide, average or narrow (see Table 5.15). For shippers, wide span of control refer to sellers with at least some destination control or buyers with at least some origin control. Average span of control refer to sellers with only destination control or buyers with only origin control. Narrow span of control refers to sellers with less than total origin control and buyers with less than total destination control. For service providers, those with wide control include (1) primarily origin service providers 36 (such as origin port, terminals, customs broker, 3PL, trucker, freight forwarder and consolidator) with at least some destination control, (2) primarily destination service providers (such as destination port, terminal, customs broker, 3PL, trucker, freight forwarder and consolidator) with at least some origin control and (3) global service providers with control over at least 70% of the activities. Those with average control include (1) primarily origin service providers with only origin control, (2) primarily destination service providers with only destination control and (3) global service providers with control of 40% to 70% of the activities. Those with narrow control include (1) primarily origin service providers with control over less than 100% of origin activities, (2) primarily destination service providers with control over less than 100% of destination activities and (3) global service providers with control over less than 30% of the activities. Table 5.15: Definitions of span-of-control. Span-of-Control Definition Wide Sellers with at least some destination control. Buyers with at least some origin control. Primarily origin service providers with at least some destination control. Primarily destination service providers with at least some origin control. Global service providers with control over > 70% of activities. Average Sellers with only destination control. Buyers with only origin control. Primarily origin service providers with only origin control. Primarily destination service providers with only destination control. Global service providers with control over 40% to 70% of activities. Narrow Sellers with less than total origin control. Buyers with less than total destination control. Primarily origin service providers with less than total origin control. Primarily destination service providers with less than total destination control. Global service providers with control over <30% of activities. 36 Determined based on a combination of characteristics: (1) the physical location of the respondent, (2) the industry type and (3) the major trade routes or simply the name of the organization. Origins are in Asia and destinations are in North America. 100 So does an organization's span of control over their supply chain affect the amount of importance they place on security as a supply chain driver? The data and bar charts in Table 5.16 and Figure 5.7 show that there are no significant differences among organizations with different span of supply chain control. Table 5.16: Ranking of security driver among organizations with different span of control. Security_Driver TotalVery Important Moderately Important Not Important Control Span Wide 86.25% 12.50% 1.25% 100% Average 80.00% 15.00% 5.00% 100% Narrow 88.37% 6.98% 4.65% 100% Total 85.28% 11.66% 3.07% 100% Figure 5.7: Ranking of security driver among organizations with different span of control. Not Important Moderately Important Very Important Wide^Average^Narrow Span of Supply Chain Control Table 5.17 shows that the difference in the mean ranking between the wide and the narrow group is 0.01 and that between the wide group and the average group is 0.1. In order to determine if these very slight differences are significant, paired sample t-tests are performed. Table 5.17: Mean ranking of security driver among organizations with different control span. Control Span Mean N Std. Deviation Wide 2.85 80 0.39 Average 2.75 40 0.54 Narrow 2.84 43 0.48 Total 2.82 163 0.46 101 Table 5.18 shows that none of the differences between any two groups are statistically significant. Therefore, the data does not support the hypothesis that an organization's span of supply chain control affects the amount of importance they place on security. The reason why this was otherwise in the field interviews could be due to the \"need\" for the interviewee to say the \"right thing\" in the presence of an interviewer (i.e. lack of anonymity). Table 5.18: Results for statistical tests for significance in differences in security driver ranking. Paired Differences t df Sig. (2- tailed)Mean Std. Deviation Std. Error Mean 95% Confidence Interval Upper Lower Pair 1 Wide - Average 0.3250 2.1648 0.3423 -0.3673 1.0173 0.9495 39 0.3482 Pair 2 Wide - Narrow 0.3953 1.8276 0.2787 -0.1671 0.9578 1.4185 42 0.1634 Pair 3 Average - Narrow 0.0750 1.8171 0.2873 -0.5061 0.6561 0.2610 39 0.7954 5.2.6 Summary of Attitude Analyses In summary, hypotheses 6 to 9 below are not supported when the web/email survey data are analysed in isolation. Even when control variables such as respondent type, physical location and firm/SBU responsibility scope are introduced separately, the results are not statistically significant. Hypothesis 6: Organization size affects attitude towards security. Hypothesis 7: The nature of cargo handled (hazardous or lack thereof) affects attitude towards security. Hypothesis 8: Typical shipment size (FCL or LCL) affects attitude towards security. Hypothesis 9: Scope of supply chain decision control/influence affects attitude towards security. This may mean that an organization's attitude towards security is impacted by a simultaneous existence of one or more of the above variables \u00E2\u0080\u0094 organization size, nature of cargo, shipment size and scope of supply chain control. It is possible in principle to cross-tabulate many variables with the possibility of obtaining further insights into lower order associations. However, the need to maintain an adequate cell size for all categories presents a practical limitation. 102 Ordinal regression is used to validate this conjecture 37 because the dependent and independent variables in this case are non-metric. For details of this technique, please refer to McCullagh (1980). Results of the ordinal regression 38 are shown in Table 5.19. Table 5.19: Ordinal regression results \u00E2\u0080\u0094 model-fitting information. Model Fitting Information Model -2 Log Likelihood Chi-Square df Sig. Intercept Only Final 283.587 276.149 7.438 8 .490 The significance level for the chi-square statistic as shown in Table 5.19 is greater than 0.05, indicating that the model is only as good as simple guessing. This statistically insignificant result shows a divergence in the security attitudes found in the field interviews and web/email survey. This could be a reflection of the need for respondents to give \"politically correct\" answers during an interview. But when given the opportunity to remain anonymous on a web/email survey, respondents can be more candid about their opinions. For instance, larger organizations especially those with global operations, may be more concern about their corporate image compared to smaller local organizations. As such during a face-to-face interview, they can be more likely to give \"politically correct\" responses. Organizations who carry hazardous cargo certainly do not want to be perceived as not placing enough importance on security and thus during a face-to-face interview may \"overstate\" their efforts and positive attitudes towards security. Organizations who has a greater span of control certainly also do not want to be perceived as not doing much when especially when they have the ability to do so and thus may also \"overstate\" their enthusiasm towards security. 5.3 Supply Chain Security a Holistic Effort Although the majority of the organizations interviewed during the field interviews have not assumed a lead role in driving security initiatives within the supply chain that they are 37 Multiple regression and multiple discriminant analyses are not appropriate techniques because they require the independent variables to be metric. Multiple-way ANOVA is also not appropriate because the dependent variables are required to be metric. 38 The complementary log-log function is chosen as the link function because the bulk of the responses for security driver is found in the higher categories. 103 participating in, they recognize that security within a supply chain can only be achieved through a holistic effort from all stakeholders. This is consistent with the findings from Langhoff et al. (2005) where it is noted that although a wide variety of organizations have put forth proposals and solutions for increasing security, each has fallen short of addressing the needs of the integrated supply chain. Supply chain participants are also found to protect their financial interests without regard to other parties in the integrated chain. Responses from the organizations interviewed during the field interviews suggest that there are generally two ways in which organizations can influence their supply chain partners' efforts in security \u00E2\u0080\u0094 the hard approach and the soft approach. The hard approach includes measures such as instituting the desired security requirements as pre-requisites to business negotiations or making them legal obligations in business contracts. These measures are more popular with buyer organizations than with service provider organizations. However, there is one buyer organization that commented that unless it can be proven that security initiatives have tangible benefits to their bottom-line or top-line, it will be tough to convince his organization and probably other companies in his industry to adopt any security efforts out of self-interests, not to even mention about driving their other partners in the same direction. The soft approach includes proactive engagement measures such as communications, education and training to create awareness about security among the other stakeholders in their supply chain. A few of the organizations interviewed have already conducted security training with their suppliers/vendors. These training efforts can come in the form of formalised security manuals, online training modules and/or security seminars. 5.4 KPIs for Supply Chain Performance and Security Performance In this section, we want to find out what KPIs are appropriate for security performance of an international maritime supply chain from industry's practitioners' point of view. From there, we seek to understand how security KPIs are related to traditional supply chain KPIs. 104 5.4.1 Determining the Appropriate KPIs for Factor Analysis First, the frequency statistics for the appropriateness of the KPI variables were computed to identify those KPI variables that are deemed to be inappropriate for measuring Supply Chain Performance (SCP) or Security Performance (SP). KPI variables that are deemed inappropriate will not be included in the initial factor analysis. Table 5.20 shows that for each KPI variable, the percentage (%) of respondents who thinks that it is an appropriate or inappropriate measurement for SCP and SP. The total number of respondents (N) = 125. The total number of KPI variables = 32. A full description of the KPIs can be found in Appendix C. Table 5.20: KPIs and their appropriateness frequencies. SIN KPI SCP Security Appi Indiffi Not app App^Indiffi Not app 1 AssetUtilize 89.6 9.6 0.8 41 31.2 27.2 2 SecurityAudit 68 26.4 5.6 87.2 11.2 1.6 3 OpsEfficiency 90.4 8 1.6 .^: 21 33.6 35.2 4 PolicyViolations 70.4 20.8 8.8 91.2- 7.2 1.6 5 InsurancePremiums 56 34.4 9.6 57.6 34.4 8 6 InventoryLevel 84.8 13.6 1.6 42J. j 34.4 23.2 7 InspectionCost 60 29.6 10.4 67.2 24 8.8 8 LogCostSavings 83.2 12 4.8 - - 24 11^36.8 39.2 9 Shipmentlnfo 88 12 0 54.4 26.4 19.2 10 UnauthorizedEntry 56.8 30.4 12.8 85.6 10.4 4 11 FulfillmentLT 90.4 8 1.6 2f. 2 34.4 38.4 12 OTDelivery 96 4 0 31.2 30.4 13 ExpeditedOrders 93.6 5.6 0.8 ..., 37.6 32.8 14 CustomsLT 75.2 18.4 6.4 54.4 31.2 14.4 15 InfoAccuracy 88.8 11.2 0 63.2 20 16.8 16 ServiceErrors 88.8 10.4 0.8 50.4 28.8 20.8 17 SafetyAudit 68 28 4 69.6 18.4 12 18 InventoryAccuracy 88.8 8.8 2.4 55.2 24.8 20 19 InvoiceAccuracy 85.6 12 2.4 I 31.2 31.2 20 Pilferage 79.2 15.2 5.6 90.4 6.4 3.2 21 FreightClaims 84.8 13.6 1.6 74.4 15.2 10.4 22 SafetyAccidents 78.4 19.2 2.4 53.6 24 22.4 23 OSD 88 8.8 3.2 72.8 14.4 12.8 24 OpsDeviation 81.6 16 2.4 34.4 29.6 25 BackOrders 80.8 14.4 4.8 224 35.2 42.4 26 Cancellations 72 21.6 6.4 i6 a 39.2 40 27 Problem Response 88.8 10.4 0.8 35.2 38.4 28 ProblemResolution 85.6 12.8 1.6 35.2 40 29 FeedbackSurvey 91.2 8 0.8 37.6 29.6 30 FillRate 85.6 13.6 0.8 10.2 36.8 44 31 SpecialRequests 73.6 20.8 5.6 39.2 36.8 32 Complaints 84 13.6 2.4 42.4 28.8 Legend:^App = Appropriate^Indiff = Indifferent^Not app = Inappropriate 105 Table 5.20 shows that all the KPI variables are deemed appropriate for SCP by majority of the respondents (i.e. greater than two-thirds or greater than 66.7%) of the respondents except for: \u00E2\u0080\u00A2 Insurance premiums^56% \u00E2\u0080\u00A2 Inspection costs 60% \u00E2\u0080\u00A2 Unauthorized entry^57% With regards to SP, less than 50% of the respondents deemed 17 of the 32 KPI variables as appropriate measurements for security performance (Table 5.20). These KPI variables are highlighted and boxed in Table 5.20 and will not be included in the SP factor analysis. 5.4.2 Factor Analysis for SCP KPIs Since all the KPI variables are deemed appropriate by more than half the respondents, all were included in the initial factor analysis for SCP. Appropriateness of Factor Analysis The data for SCP KPI appropriateness is considered categorical (ordinal data). To determine whether factor analysis is appropriate, the Bartlett's Test and Measure of Sampling Adequacy were calculated. The Bartlett's Test is a statistical test for the presence of correlations among the variables. If there is insufficient correlation among variables, then factor analysis may not be appropriate. The Bartlett's Test provides the statistical probability that the correlation matrix has significant correlations among at least some of the variables. In this case, when taken overall, the correlations among the KPI variables are significant at 0.000. However, as the sample size increases, the Bartlett's Test becomes more sensitive to detecting correlations among the variables. Moreover, the Bartlett's Test only indicates the presence of non-zero correlations, not the pattern of these correlations. Another measure to quantify the degree of inter-correlations among the variables and the appropriateness of factor analysis is the MSA index, which can range from 0 to 1. Therefore, the larger the MSA index, the more appropriate is factor analysis for the data set. The general 106 guidelines are 0.80 and above, meritorious; 0.70 or above, middling; 0.60 or above, mediocre; 0.50 or above, miserable; and below 0.50, unacceptable. Table 5.21: KMO-MSA index and Bartlett's test results. Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .724 Bartlett's Test of^Approx. Chi-Square 2031.196 Sphericity^df 496 Sig. .000 Both the MSA index and Bartlett's Test indicates the appropriateness and support the use of Factor Analysis for data reduction for SCP KPIs (see Table 5.21). Choice of Extraction Method There are two basic models to obtain factor solutions (Hair et al., 1998) \u00E2\u0080\u0094 Principal Component Analysis and Common Factor Analysis (also known as Principal Factor Analysis or Principal Axis Factoring). The principal component factor model is appropriate when the primary concern is about prediction or the minimum number of factors needed to account for the maximum portion of the variance. Wilkinson, Blank and Gruber, 1996) notes that for most datasets, principal component method and common factor method will lead to similar substantive conclusions, though principal component method is generally preferred for purposes of data reduction (translating variable space into optimal factor space), while common factor method is generally preferred when the research purpose is detecting data structure or causal modeling. Since data reduction is the objective over here, the Principal Component method shall be used. The Principal Axis method and Image Factoring methods are also conducted for comparison purposes and comprehensiveness of the analysis. Image factoring is a factor analysis method based on the correlation matrix of predicted variables rather than actual variables, where each variable is predicted from the others using multiple regression. 107 The factor pattern matrices were compared 39 . Although the factors generated are similar, the total amount of variance explained is larger when the principal component method is used. Choice of Rotation Methods An important tool in interpreting factors is factor rotation. There are two major rotation options \u00E2\u0080\u0094 orthogonal or oblique. Orthogonal rotational approach includes approaches such as Quartimax, Varimax and Equimax. Orthogonal rotational approaches assume independence between factors whereas oblique rotational approaches allow factors to be correlated. Oblique rotational approach includes Direct Oblimin and Promax. The oblique rotational approach should be chosen for this case because a KPI used to measure one aspect of SCP is likely and expected to be correlated with another KPI used to measure another aspect of SCP. This is because the different aspects of SCP are known to be inter- dependent in fulfilling a supply chain objective. A comparison study by Costello and Osborne (2005) also argues and supports the use of a true factor analysis extraction method with oblique rotation for optimal results. Costello and Osborne (2005) adds that while principal components with Varimax rotation and the Kaiser criterion are the norm, they are not optimal particularly when data do not meet assumptions, which are often the case in the social sciences. However, for the purpose of a comprehensive analysis again, three rotation methods, namely, Direct Oblimin, Promax and Varimax were used on all three methods of extraction mentioned above (i.e. Principal Component, Principal Axis and Image Factoring), and the one that generates the most interpretable factors is chosen as the final factor analysis result. Table 5.22 summarizes the comparison of factor analysis results among the different combination of extraction and rotation methods. A \"tick\" indicates that the factor matrix generated by the combination of rotation method and extraction method is the most easily interpretable. Under different scenarios of extraction criteria (i.e. eigenvalues > 1 and number of factors extracted = 6) and variables used (i.e. all variables are used versus three variables removed), the Promax rotation method generates factors that have variables loading more distinctively on 39 Factor pattern matrices generated using the Principal Axia, Image Factoring and Principal Component methods are similar. 108 11111111111111111111111111111111 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 Component Number any one factor, thus making the factor more interpretable. On the other hand, Direct Oblimin and Varimax rotation methods, tend to generate factors that have variables loading significantly on more than one factor. Table 5.22: Comparison of rotation methods. Extraction Methods Rotation Methods Promax Oblimin Varimax Principal Component ^ x x Principal Axis 4c x x Image Factoring x x X Therefore, overall, the Principal Component extraction method with Promax rotation yielded the most interpretable factors with reasonable total variance explained. The following sections will explain the rationale and logic behind the final selection of the factor matrix. Interpreting the Factor Matrix With a total of 32 variables, using the Principal Component extraction method with Promax rotation, the total variance explained by the initial solution of 10 factors (where extraction is based on eigenvalues > 1) is 72%. However, the scree plot suggests the retention of six factors instead (see Figure 5.8 where the \"leveling-off' occurs). Figure 5.8: Scree plot for initial solution. (Principal component with promax rotation \u00E2\u0080\u0094 eigenvalues > 1) 109 Therefore the extraction criteria used is changed from eigenvalues > 1 to six factors to be extracted. With the extraction criteria of six factors, the total variance explained using all 32 variables is 57%. The generated factors are shown in Table 5.23 and they are not straightforwardly interpretable. Table 5.23: Pattern matrix. (Principal component with promax rotation - 6 factors) Component 1 2 3 4 5 6 SCP AssetUtilize .406 -.054 -.076 .238 -.101 E -\":46T SCP_SecurityAudit -.066 .043 r---- .683- .033 -.325 .186- SCP_OpsEfficiency B1 .011 -.076 .165 .061 .113 SCP_PolicyViolations .006 -.053 -.7851 .049 -.063 -.027 SCP_InsurancePremiums .012 .225 .387 .317 .010 -.230,\u00E2\u0080\u009E\u00E2\u0080\u009E\u00E2\u0080\u009E\u00E2\u0080\u009E\u00E2\u0080\u009E.\u00E2\u0080\u009E. SCP_InventoryLevel .214 -.109 -.106 .050 .671 .044 SCP_InspectionCost -.127 .203 .273 .175 :31-0\u00E2\u0080\u0098: -.264 SCP_LogCostSavings -.169 -.210 -.123 _.'5110 .5261 .104 SCP_Shipmentlnfo .225 .073 .081 .227 .074 .266 SCP_UnauthorizedEntry -.004 .284 717 .037 -.148 -.085 SCP_FulfillmentLT -.117 .016 .156 -.009 .103 i SCP_OTDelivery SCP_ExpeditedOrders .004 -.026 .261 .9061 .133 -.102 .164 -.239 -.233 .002 ,611561 SCP_CustomsLT -.366 .390 .247 .022 .308 .290 SCP_InfoAccuracy .061 r--776121:1 .080 .169 -.043 -.083 SCP_ServiceErrors r----.5S1- .149 -.124 -.121 .122 .221 SCP_SafetyAudit .209 -.267 XV - .111 .011 .265 SCP_InventoryAccuracy .569 -.028 .107 .377 .090 -.171 SCP_InvoiceAccuracy .502 .655 1 -.136 -.167 -.095 -.132 SCP_Pilferage -.087 -.147 -.5f i- 1\u00E2\u0080\u009E. -.037 .281 .124 SCP_FreightClaims .167 .661 .085 -.136 .101 .226 SCP_SafetyAccidents L^.670 1 -.158 - .271 .109 -.050 SCP_OSD -.029 1- .6721 -.113 .224 .059 .142 SCP_OpsDeviation -.022 -.044 .015 \"\":8401 -.030 -.027 SCP_BackOrders .122 -.027 -.048 .746 .: -.017 .140 SCP_Cancellations .154 -.043 .105 .651^i .043 .039 SCP_ProblemResponse .129 .117 -.016 -.066 .871 .070 SCP_ProblemResolution .159 .095 -.094 -.051 .8101 -.063 SCP_FeedbackSurvey .200 .036 -.031 -.047 .159 604 SCP_FillRate -.671 i .011 -.061 .462 -.101 .049 SCP_SpecialRequests .248 .308 .067 .052 .367 -.056 SCP_Complaints .589^' .055 -.031 .023 .349 -.097 110 As seen from Table 5.23, based on the significant loading(s) 40 each variable has on a particular factor, the factors generated are not immediately interpretable (see values boxed in Table 5.23) because there are three variables (Logistics Cost Savings, Invoice Accuracy and Safety Accidents) with significant loadings (i.e. greater than or equal to 0.40 or at least 0.30 to be acceptable) on more than one factor and there are three variables (Shipment Information, Customs Lead-time and Special Requests) with no significant loadings on any factor. In order to obtain better loadings, the correlation and communalities tables are reviewed. Variables with small communalities (i.e. < 0.40) and high correlation (i.e. > 0.50) with one or more other variables are deleted. Variable SCP_ShipmentInfo is the only variable with a communality value that is less than 0.40 at 0.333 and is therefore a candidate for removal. There are two variables with very high correlations with more than one other variables - SCP_ProblemResponse and SCP_InventoryAccuracy. SCP_ProblemResponse has a large correlation of 0.821 with SCP_ProblemResolution and 0.527 with SCP_SpecialRequests. It is therefore an ideal candidate for removal to minimize duplication of variable representation. SCP_InventoryAccuracy also has a large correlation of 0.641 with SCP_FillRate, 0.524 with SCP_Complaints and 0.501 with SCP_Cancellations. It is therefore also a good candidate for removal to improve the factor loadings. The factor analysis is re-run with the rest of the 29 variables and the resulting factor matrix is shown in Table 5.24. The factors are interpretable based on each variables highest loading (boxed in Table 5.24) or their alternative significant loadings (circled in Table 5.24). As seen from Table 5.24, based on their other significant loading values, two variables were loaded on an alternative factor that makes the most sense (see values circled). With this new interpretation, the factors can be named in order from 1 to 6 as, (1) Accuracy of Operations, (2) Security, (3) Efficiency, (4) Availability, (5) Responsiveness/Customer Service and (6) Reliability. This factor analysis result explains -58% of total variance. In social sciences or situations where information is less precise, it is not uncommon to consider a solution that accounts for -60% (and in some instances even less) as satisfactory (Hair et al., 1998). 40 Generally accepted guidelines for determining whether a loading is significant or not can be found in Hair et al. (1998). 111 Table 5.24: Pattern matrix. (Principal component with promax rotation - 29 variables) Component Accuracy Security Efficiency Responsiveness Reliability SCP_AssetUtilize -.055 -.034 r 7575 .304 -.168 .328 SCP_SecurityAudit -.016 .676 .027 -.289 .187 SCP_OpsEfficiency .016 -.050 pp^685 j .181 .151 -.014 SCP_PolicyViolations -.042 790 1' -.045 -.083 -.031 SCP_InsurancePremiurm .243 .4201 -.026 .311 -.033 -.242 SCP_InventoryLevel -.043 -.134 .149 .052 .753 .094 SCP_InspectionCost .231 (::::28) -.180 .178 .301 -.224 SCP_LogCostSavings -.149 -.122 L -76577 -.105 .500 .088 SCP_UnauthorizedEntry .287 (^.747 -.021 .043 -.228 -.074 SCP_FulfillmentLT .032 .093 -.069 -.042 .184 i .659j SCP_OTDelivery .264 .108 .111 .143 -.241 1 .929.1 SCP_ExpeditedOrders .8991 -.125 -.040 -.262 .021 \"--.147 SCP_CustomsLT .4501 .215 -.342 .012 .228 .385 SCP_InfoAccuracy 7E21 .086 .026 .132 -.037 -.076 SCP_ServiceErrors 161 -.142 .531 ] -.102 .321 .140 SCPSafetyAudit -.293 .6M .183 -.109 .107 .301 SCP_InvoiceAccuracy .662] -.091 .489 -.157 -.128 -.156 SCP_Pilferage ' :.iiii ^:6241 -.067 .004 .181 .103 SCP_FreightClaims .5501 .052 .151 -.151 .210 .205 SCP_SafetyAccidents -.149 .546 .593 -.251 .182 -.086 SCPOSD .694] -.115 .007 .209 .046 .139 SCP_OpsDeviation ----.148 .036 -.002 .ifil .025 -.032 SCP Backorders -.028 -.013 .223 IIY69 -.001 .040 SCP_Cancellations -.052 .117 .151 .618 .157 .066 SCP_ProblemResolution 226 -.043 215 .053 .il -.115 SCP_FeedbackSurvey .090 -.010 .382 .029 -.003 :514] SCP_FillRate -.013 -.036 .558 C.:0D .042 .027 SCP_SpecialRequests .347 .077 .201 .053 .392 I -.003 SCP_Complaints .055 -.032 .505 .021 I .533 I -.124 The Bartlett's Test and MSA index were re-calculated and both still indicate the appropriateness of the use of factor analysis. In fact the MSA index is now higher than when the two variables were included (see Table 5.25). Table 5.25: KMO-MSA index and Bartlett's test results. Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .715 Bartlett's Test of^Approx. Chi-Square 1619.503 Sphericity^df 406 Sig. .000 As seen from Table 5.26, all the factors (also known as scales) have satisfactory Cronbach's Alpha values. These scales are similar to the key dimensions of SCP discussed in Section 2.5 112 in Chapter 2. These key dimensions were identified from a rigorous review of 20 of the 116 relevant research studies summarized in Keller et al. (2002), SCOR version 8.0, other current literature on supply chain security and information gathered from the field interviews. Table 5.26: Cronbach's alpha values for generated factors. Scale Cronbach's Alpha N of Items Accuracy 0.761 6 Security 0.769 7 Efficiency 0.700 5 Availability 0.748 4 Responsiveness 0.802 4 Reliability 0.792 3 However, instead of having a factor named Timeliness, we have one that's named Accuracy. The time element is instead found in the Reliability and Accuracy factors. For instance, the KPIs for fulfillment lead-time and on-time delivery are found in the Reliability factor and this could be because respondents interpreted the word \"Reliability\" to mean delivery reliability, a commonly held definition of this term in the logistics industry, despite the definition provided in the survey questionnaire. The paragraphs below explain the rationale for each scale's labeling. Factor 1: Accuracy Factor 1 is made up of six variables \u00E2\u0080\u0094 (1) Expedited Orders, (2) Customs Lead-time, (3) Info Accuracy, (4) Invoice Accuracy, (5) Freight Claims and (6) OSD. Info Accuracy and Invoice Accuracy are straightforward indicators of operations accuracy. Freight Claims and OSD are consequences of inaccurate operations such as stuffing and order preparation. Expedited Orders can also be interpreted as a result of errors made in order fulfillment operations because when there are errors in fulfilling the orders, customers usually need to have a re-order expedited in order to meet their business needs. Customs clearance lead-time can be affected if there are inaccuracies between shipment documentation and the physical shipment itself. This is especially relevant in today's global maritime logistics regulatory environment. Factor 2: Security Security refers to an organization's state of being secure. And secure refers to the likelihood of an organization's supply chain being compromised in terms of pilferages, thefts, damages, 113 terrorism and other crimes such as smuggling and contraband etc. The KPI variables in this factor therefore include custom inspection cost, security audit, policy violations, insurance premiums, unauthorized entry, pilferage and safety audit. Factor 3: Efficiency Efficiency refers to an organization's accomplishment of or ability to accomplish a job with a minimum expenditure of time, effort and resources. The KPI variables in this factor therefore include asset utilization, operations efficiency and logistics cost savings. The Service Error and Safety Accident variables are also included because it represents wastes in the system and wastes negatively impact an organization's bottom-line. Factor 4: Availability Availability refers to an organization's ability to ensure undisrupted supply of products and/or services and/or information. This could be achieved through the provision of shipment information, ensuring supply of special equipment or products, ensuring that sales force is readily available to respond to customers' inquiries and needs. As such, the KPI variables in this factor include order fill rate, amount of backorders and order cancellations. Operations Deviation refers to the deviation in production capacity or capacity to service a client. This variable is included here because without the required operations capacity, an organization is unable to make available her products or services to her customers. Factor 4: Responsiveness Responsiveness refers to an organization's accomplishment of or ability to react to changes and/or requests from demand or supply side. This capability includes flexibility and agility and could be enhanced by the use of information technology in terms of greater visibility and/or configuration of business operations to allow operations scaling flexibility and agility. Therefore the KPI variables in this factor include problem resolution lead-time, number of and ability to handle special requests and customer complaints. The KPI variable Inventory Level is included in this factor because without an adequate and appropriate level of inventory, an organization will not be able to respond effectively and reliably to customer demand. Factor 5: Reliability Reliability refers to an organization's dependability of product/service delivery operations. KPI variables in this factor therefore include delivery related measures such as on-time delivery and 114 fulfillment lead-time. The KPI variable Feedback Survey is also included in this factor because the customer feedback survey usually asks about the areas where an organization comes into contact with the customer and a large part of the contact happens downstream during the product/service delivery stage. What is really important here is that it can also be seen from the resulting factors that there is indeed a component for Security. This means that organizations have all along been measuring an aspect of their operations that relates to security. As such, organizations should not perceive the current change in intensity of interests in security as throwing them off-balance. The KPI variables for security are looked at next to identify what the KPIs are for security performance from the industry practitioners' point of view. 5.4.3 Factor Analysis for SP KPIs Recall that less than 50% of the respondents deemed 17 of the 32 KPI variables as appropriate measurements for security performance (see Table 5.20 on page 104). These KPI variables are boxed in Table 5.20 and will not be included in the factor analysis. The remaining 15 KPI variables are ranked below in a descending order (in Table 5.27) based on the appropriate percentage. Table 5.27: KPIs deemed appropriate for security performance. S/N KPI Name % of Respondents Corresponding SCP Factor 1 Policy violations 91.2 Security Factor 2 Pilferage 90.4 Security Factor 3 Security audit 87.2 Security Factor 4 Unauthorized entry 85.6 Security Factor 5 Freight claims 74.4 Accuracy Factor 6 OSD 72.8 Accuracy Factor 7 Safety audit 69.6 Security Factor 8 Inspection cost 67.2 Security Factor 9 Information accuracy 63.2 Accuracy Factor 10 Insurance premiums 57.6 Security Factor 11 Inventory accuracy 55.2 Not included in SCP Analysis 12 On-time shipment information 54.4 Not included in SCP Analysis 13 Customs lead time 54.4 Accuracy Factor 14 Safety accidents 53.6 Efficiency Factor 15 Service errors 50.4 Efficiency Factor 115 As expected, eight of these 15 KPI variables that are deemed appropriate measures of SP by majority of the respondents are also loaded in the Security Factor of SCP. For the other KPI variables in Table 5.27, three coincide with those that load in the Reliability factor of SCP, two in the Timeliness factor, one in the Efficiency factor and one in the Availability factor respectively. This set of results shows that respondents feel that security performance will have an impact on not just one but many aspects of SCP. This is consistent with current literature on the collateral benefits of security efforts and this is logical for the following reasons: \u00E2\u0080\u00A2 security issues create uncertainties in the supply chain and uncertainties affects the reliability of supply chain operations. As noted by Rice and Spayd (2005), some firms have estimated the cost of trade discontinuity to be as high as US$50-100 million/day. \u00E2\u0080\u00A2 unreliable supply chain operations in turn jeopardize the ability of the organization to make available their products and services to their customers. \u00E2\u0080\u00A2 customs regulations such as advanced shipment information has lengthened supply chains in terms of overall time required to move cargo. \u00E2\u0080\u00A2 the overall increase in fulfillment lead time in turn brings about negative impacts to the efficiency of an organization's supply chain operations. \u00E2\u0080\u00A2 the mushrooming of security regulations now present more opportunities for non- compliance (either deliberate or due to ignorance) and therefore presenting more windows for service errors and inefficiencies in the supply chain. Factor Analysis Results Since only these 15 KPI variables are deemed appropriate, the data reduction effort for SP is based only on these 15 variables. 116 1^2^3^4^ 15^6^17^8^9^10^11^12^13^14^15 Component Number The same extraction method and rotation methods are employed \u00E2\u0080\u0094 Principal Components and Promax. The Bartlett's Test and MSA index both indicate the appropriateness of the use of factor analysis (see Table 5.28). The total variance explained is 65% and four factors have been extracted in the initial solution with extraction criteria as eigenvalues > 1. Table 5.28: KMO-MSA index and Bartlett's test results. Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .814 Bartlett's Test of^Approx. Chi-Square 742.130 Sphericity^df 105 Sig. .000 The scree plot in Figure 5.9 also supports the extraction of four factors. The last dip is between four and five factors. Figure 5.9: Scree plot for SP factor analysis (eigenvalues > 1). 117 The resulting factor pattern matrix is shown in Table 5.29. Table 5.29: Pattern matrix for SP factors. (Principal component with promax rotation) Component Information Breaches Cost Safety SP_SecurityAudit -.008 -.083 -.068 SP_PolicyViolations .101 -.232 .039 SP_InsurancePremiums -.111 -.042 .120 SP_InspectionCost .090 .002 -.132 SP_Shipmentlnfo -.115 .015 .158 SP_UnauthorizedEntry -.095 737 .141 .005 SP_CustomsLT j^.\u00E2\u0080\u009E,.. -.071 .081 -.195 SP_InfoAccuracy .012 -.002 -.215 SP_ServiceErrors .639 -.021 -.211 C-.395-: SP_SafetyAudit -.147 .099 .028 - 881 . SPInventoryAccuracy .212 -.004 .122 SP_Pilferage -.068 933 j .282 .024 SP_FreightClaims .303 -.083 .120 SP_SafetyAccidents .022 -.107 .045 SP_OSD 11.4\u00C2\u00A77 .214 .254 .083 All the four factors generated are interpretable. In fact, they are consistent with the concept of supply chain flows - information flow (information), physical flow (breaches), financial flow (cost) and people (safety). The Cronbach's Alphas for each of these factors are also higher than or at least very close to the recommended 0.70, which means that these scales are reliable (see Table 5.30). Table 5.30: Cronbach's alpha values for SP factors. Scale Cronbach's Alpha N of Items Information 0.806 5 Physical Breaches 0.815 4 Cost 0.684 3 Safety 0.747 3 The Insights In conclusion, the above analyses show that the KPIs for security performance (SP) are indeed a subset of traditional SCP from the industry practitioners' point of view. This means that organizations have all along been measuring an aspect of their operations that relates to 118 security. As such, organizations should not perceive the current change in intensity of interests in security as throwing them off-balance. Specifically, security performance measurements can be classified into four key components: \u00E2\u0080\u00A2 those measuring the accuracy and reliability of information \u00E2\u0080\u00A2 those measuring the effectiveness of physical breaches prevention \u00E2\u0080\u00A2 those measuring the cost of security initiatives \u00E2\u0080\u00A2 those measuring the safety of operations and personnel This means that when evaluating security performance, organizations should select key performance indicators (KPIs) that comprehensively represent each of the four areas of information, cargo, people and cost. In addition, the information presented seems to indicate that industry practitioners feel that security performance has implications on not only one but many aspects of traditional SCP, especially in terms of timeliness, reliability, availability and efficiency. To better identify and understand these relationships and those among security initiatives, security performance and traditional SCP, we employ the Structural Equation Modeling (SEM) technique and the analyses are discussed in the sections that follow. 5.5 Security Initiatives, SCP and Security Performance As a first step to understanding the relationships between security initiatives and security performance, we take a look at the descriptive statistics of the data collected. 5.5.1 Perceptions of Security Initiatives and their Popularity Supply chain security has been redefined as preventing terrorists from targeting the maritime supply chain or transporting a weapon in a shipping container. This change in focus raises questions about the effectiveness of proposed security efforts and the consequences they may have for supply chain performance (Willis and Ortiz, 2004). As a first step to understanding the 119 relationships among security initiatives, SCP and security performance, we take a look at the descriptive statistics of the data collected. Perceived Impact of Security Initiatives on SCP Respondents to the web/email survey were asked directly the degree of negative or positive impact they perceived a particular initiative has on various aspects of SCP. Respondents used a 7-point Likert scale where 1=Extremely Negative and 7=Extremely Positive. Figure 5.10 shows the mean value of the perceived impact of a particular initiative on the six different aspects of SCP. The data is sorted in descending magnitude of the mean value. Figure 5.10: Respondents' perceived impact of security initiatives on SCP. 41 Initiatives Efficiency Tracking & Monitoring 5.43 Business Partner Requirements 5,26 Management Support & Sponsorship 5.20 Physical Security & Access Control 5.17 Security Training and Outreach Programs 5.16 Advanced Data 5.05 Container Security 5.02 procedural Se,...:: Overall Average 5.10 Initiatives Availability Tracking & Monitoring 5.18 Physical Security & Access Control 5.10 Management Support & Sponsorship 5.05 Business Partner Requirements 4.99 Personnel Security 4.98 Procedural Security 4.97 Security Training and Outreach Programs 4.96 Container tEaOunty 4.96 d Datd 4,86 4,69 Overall Average 4.97 Initiatives Reliability Tracking & Monitoring 5.48 Security Training and Outreach Programs 5.39 Physical Security & Access Control 5.34 Management Support & Sponsorship 5.34 Personnel Security 5.30 Business Partner Requirements 5.29 Procedural Security 5.24 Co\u00C2\u00B01ta,ner Seou;4 Advanced Data 5,14 Security Certification Overall Average 5.28 Initiatives Time Tracking & Monitoring 5.38 Business Partner Requirements 5.21 Physical Security & Access Control 5.09 Management Support & Sponsorship 5.08 Container Security 5.01 Security Training and Outreach Programs 4.98 Advanced Data 4.94 .L,^.ilae.o.ri y 8?, 4 ;'6 Overall Average 5.00 Initiatives Responsiveness 5.47Tracking & Monitoring Management Support & Sponsorship 5.36 Physical Security & Access Control 5.19 Security Training and Outreach Programs 5.16 Business Partner Requirements 5.11 Procedural Security 5.10 Advanced Data 5.09 Cont.y1:n^, S( (: . or ty ...i^c. itiuo Overall Average 5.12 Initiatives Security Tracking & Monitoring 5.92 Procedural Security 5.91 Management Support & Sponsorship 5.88 Personnel Security 5.79 Physical Security & Access Control 5.78 Security Training and Outreach Programs 5.75 Advanced Data 5.62 ''.:Cr S ,;;:;t: Bur,4te,sto t.irrti ,tr^e^i Overall Average 5.71 Note: The standard deviations of these mean values range from 0.91 to 1.25. 41 Paired t-tests are not performed on these means because the sample size of each selected pair is not consistent. This is because respondents are only required to indicate their perception on impact on supply chain performance if they have implemented that initiative or is planning to implement that initiative. 120 Although the differences in these mean values are not huge, it does reflect a general trend among these respondents that they perceive all of these initiatives as a whole to have a greater positive impact on security performance compared to other aspects of traditional SCP (see Figure 5.10 where the overall mean value for security is 5.71, which is 0.73 points higher than a mean of 4.97 for availability aspect of SCP and 5.00 for time aspect of SCP). As can be seen from Table 5.10, security initiatives under the Tracking and Monitoring group are consistently ranked the best in terms of their perceived impact on traditional aspects of SCP. In addition, management support and sponsorship is ranked in the top three groups of initiatives with the most impact for three out of six aspects of SCP. This indicates that respondents also view security efforts as strategic endeavors where success in their implementation requires management support and sponsorship. Externally oriented initiatives such as instituting business partner requirements are also perceived to have a relatively greater impact on SCP's efficiency and time performance compared to other groups of initiatives. Types of Security Initiatives Implemented Respondents to the web/email survey were also asked to indicate which group of initiatives their organization has implemented or is planning to implement or has no intention to implement in the near future. Figure 5.11 shows the \"popularity\" of the ten groups of security initiatives among the respondents. Popularity of an initiative is determined by the number of respondents' whose organizations have implemented or planning to implement that initiative. Figure 5.11: \"Popularity\" of security initiatives. o Implemented o Planning to Implement o Not Implementing Personnel security r '.. - -\"- i Physical security & access control =T----.7 _...\u00E2\u0080\u009E._ ^ Operations/Security related certifications ^'''mm=wimrl.7.. 1..,..,....,....1 Advanced data compliance \u00E2\u0080\u00941^1---^. ^Business partners requirements^ -T- ralmsztwasu-aulnimr,--seurazdozonsgu.........4^Container /Unit Load Device secutity^,___, n^ra^......=_T _ Procedural security Securitytraining & outreach programs p^, \u00E2\u0080\u0094 Management support & sponsorship l --\"A--- -tT. \u00E2\u0080\u0094 -- - -,^Tracking & monitoring ^, 7\u00E2\u0080\u0094 -7\"--7\u00E2\u0080\u0094 /` 0%^10%^20%^30%^40%^50% ^ 60% ^ 70% ^ 80% ^ 90%^100% VV. 121 As seen from Figure 5.11, the groups of initiatives that most organizations have implemented or are planning to implement include personnel security, physical security and access control and obtaining security related certifications. The groups of initiatives that the least number of organizations have chosen to implement include tracking and monitoring of cargo conveyance and clear management support and sponsorship. The Insights It is especially interesting to note that although Tracking and Monitoring is the least implemented security initiative, it is perceived by respondents to be the one with the greatest positive impact on supply chain performance (see Figure 5.10). 42 Similarly, for some of the more widely implemented security initiatives such as Personnel Security, Security Related Certifications, Container Security and Advanced Data Compliance, respondents are either neutral or unsure of the positive impacts they have on SCP (See Figure 5.10). This initial analysis suggests that the current motivations behind security initiatives implementation in the private sector are very much that of a pressure to comply with public sector regulations and/or simply the ease of implementation. This is consistent with current literature on security such as Willis and Ortiz (2004). Wolfe (2004), Langhoff et al. (2005), Rice and Spayd (2005), Peleg-Gillai et al. (2006). Organizations are not yet motivated by their perceptions to implement initiatives that they think will have positive impacts on traditional SCP. And to the extent that security is a consideration, it is focused on reducing cargo theft and protecting proprietary data from competition (Smart and Secure Tradelanes, 2003). 5.6 Structural Equation Modeling (SEM) Analysis To understand the relationship between security initiatives, security performance and traditional SCP, SEM is employed. SEM provides a test of the overall model as opposed to performing a series of multiple regressions and takes into account the reliability of observed variables by representing each construct as a latent variable (as opposed to simple path analysis) (Savalei and Bentler, 2006). The relationships among these constructs constitute the structural part of the model. The measurement part of the model consists of the relationships between the latent variables and their indicators. 42 4 on the Likert scale = Neutral/Unsure. 5 on the Likert scale = Moderately Positive. 6 on the Likert scale = Very Positive. 122 There are three measurement models and one structural model in the model used for this study. The steps in a SEM modeling process will be described together with the results in the sections that follow. 5.6.1 Data Considerations Sample Size Required Although there are several recommendations for a minimum sample size of at least 200 or 5 or 10 times the number of variables or estimated parameters (Garver and Mentzer, 1999 and Savalei and Bentler, 2006), McQuitty (2004) notes that these recommendations may be outdated. Hair et. al (1998) provides an argument that the absolute minimum sample size must be at least greater than the number of covariances or correlations in the input data matrix. The sample size used in this SEM model is 113 and there are 112 correlations in the input data matrix. Moreover, according to Hair et. al (1998), using the Maximum Likelihood method, the generally accepted minimum sample size can be between 100 to 150. In fact, Hair et. al (1998) wrote that as the sample size becomes large, the Maximum Likelihood method can become \"too sensitive\" and almost any difference is detected, making all goodness-of-fit measures to indicate poor fit. Therefore it is decided that it is appropriate to proceed with the SEM analysis. Departures from Normality The skewness and kurtosis statistics for the variables used in the Supply Chain Security model are evaluated and the variables used are mostly non-normal. It is therefore necessary to employ appropriate model estimation techniques that compensates for the non-normality of the data used. Further discussion can be found in the model estimation section. 5.6.2 Model Specification Figure 5.12 shows the Supply Chain Security model to be tested. Based on the extensive review of existing literature (see Chapter 2) and field interviews conducted (see Chapter 4 and 123 Appendix E), it is hypothesized that the amount of security effort undertaken by an organization is dependent on the amount of collateral benefits perceived from undertaking that security effort (H2) and the resulting impact on security itself (H1). An organization's security effort is expected to have an impact on the security performance of its business operations (H3 and H4). The changes and/or improvements made to an organization's business operations as a result of undertaking such security efforts are expected to have impact on the other traditional aspects of SCP such as efficiency, availability, responsiveness, reliability and timeliness (H5). This impact could be a direct result of security effort (H5a) or it could be an indirect result from an improvement in security (H5b) or it could be both. Figure 5.12: Structural model for Supply Chain Security. Perceived Collateral Benefits 5.6.3 Model Estimation The model estimation process is an iterative process and there are many techniques available depending on the computer program used. Although the Maximum Likelihood (ML) technique is by far the most widely used, this technique is sensitive to non-normal data. There are some estimation procedures specifically designed to deal with non-normal data (Hair et al., 1998). Examples include Weighted Least Squares (WLS), Generalized Least Squares (GLS) and Asymptotically Distribution Free (ADF). The ADF technique has received particular attention due to its insensitivity to non-normality of the data but its primary drawback is the increased samples size required (Hair et al., 1998; Savalei and Bentler, 2003). As the WLS technique is not available in AMOS 7.0, the GLS estimation technique will be used to compensate the non-normality of the data used. 124 However, Savalei and Bentler (2006) conclude that despite the restrictive normality assumption, the ML parameter estimates are actually fairly robust to the violation of this assumption, and ML is the preferred method of estimation even if this assumption is violated. The ML method is therefore also performed on the same model with the same data set. The ML and GLS results are compared on eleven aspects of model explanation and fit (see Table 5.31). Table 5.31: Comparison of ML and GLS estimation techniques. Model Explanation Statistics GLS ML R2 \u00E2\u0080\u0094 SCP 0.557 0.500 Standardized Residuals* 7 0 Modification Indices** 1 2 Insignificant Parameters 16 13 Model Fit Statistics GLS ML Chi-Square (x2) (p-value) 90.920 (0.338) 99.816 (0.146) GFI 0.899 0.909 RMSEA 0.023 0.038 TLI/NNFI 0.943 0.988 CFI 0.959 0.991 IFI 0.968 0.992 number of standardized residuals greater than 2.0 43 . number of modification indices greater than 7.88 44 . Both techniques generated significant x2 values and other model fit statistics. Their explanation powers are also comparable with similar R 2 values for SCP at 0.500 for ML and 0.557 for GLS. Although GLS has a larger R 2 value, it has a significantly larger number of standardized residuals that are considered large; seven compared to none for ML. There are also a greater number of insignificant parameter estimates for GLS than ML. Taking all ten indices together, the ML technique is selected as the model estimation technique used in this study. There are also several estimation processes available, ranging from direct estimation of the model, which is common in most multivariate techniques, to methods that generate thousands of model estimations from which the final model results are obtained such as bootstrapping and jackknife. Detailed discussions of these methods can be found in standard multivariate statistics 43 Garver and Mentzer (1999) recommended that standardized residuals > 2.0 are considered large. 44 Garver and Mentzer (1999) recommended that modification indices > 7.88 are considered large. 125 books such as Hair et al. (1998). Because the bootstrapping estimation process estimates the final parameters and their confidence estimates directly from multiple model estimations across separate samples, they do not rely on assumptions as to the statistical distribution of the parameters (Hair et al., 1998). Therefore the bootstrapping estimation process is employed in this study. The results in Table 5.31 were generated using bootstrapping estimation. Next to determine whether the effects of security effort on SCP are direct or indirect, a comparison was conducted between a model that has H5a and a model that does not. The results are shown in Table 5.32. Path H5a was found to be statistically insignificant and its inclusion in the model reduces the R 2 value of SCP. The inclusion of path H5a also renders path H5b statistically insignificant. Since the elimination of path H5a did not affect the model fit indices significantly, the decision was made to exclude path H5a in the model. Table 5.32: Comparison of model having path H5a and model not having H5a. Model Explanation Statistics H5a No H5a R2 \u00E2\u0080\u0094 SCP 0.500 0.530 Standardized Residuals* 0 0 Modification Indices** 2 2 Insignificant Parameters 13 11 Model Fit Statistics H5a No H5a Chi-Square (x2) (p-value) 99.816 (0.146) 99.949 (0.162) GFI 0.909 0.909 RMSEA 0.038 0.036 TLI/NNFI 0.988 0.989 CFI 0.991 0.992 IFI 0.992 0.992 number of standardized residuals greater than 2.0 4s . number of modification indices greater than 7.88 46 . 5.6.4 Model Evaluation The overall SEM model consists of two key components \u00E2\u0080\u0094 the measurement model(s) and the structural equation model. There are usually one or more measurement models and the final model is the structural equation model. The measurement models specify how the latent 45 Garver and Mentzer (1999) recommended that standardized residuals > 2.0 are considered large. 46 Garver and Mentzer (1999) recommended that modification indices > 7.88 are considered large. 126 Model Fit Indices: Chi-Square (p-value)^: GFI^ : RMSEA : TLI / NNFI^: CFI^ : IFI : 0.585 0.998 0.000 1.004 1.000 1.000 (0.444) Standadized coefficients and error terms (shown). Impact on Efficiency Impact on Time Impact on Reliability Impact on Availability Impact on Responsiveness 0.96 0.93 1-c.1^0.87 0 E3 0.86 0.90 O variables are measured in terms of the indicator variables as well as address the reliability and validity of the indicator variables in measuring the latent variables or hypothetical constructs (Wisner, 2003). The structural equation model provides an assessment of predictive validity, specifies the direct and indirect relations among the latent variables, and describes the amount of explained and unexplained variance in the model (Wisner, 2003). 5.6.4.1^Measurement Model Evaluation The evaluation of the measurement models is performed in two key stages. The first stage evaluates each measurement model that makes up the structural model. There are three measurement models in this model. One measurement model measures the Perceived Collateral Benefits (Figure 5.13), one other measures the SCP (Figure 5.14) and the last one measures the Security Effort (Figure 5.15). Figure 5.13: Perceived Collateral Benefits measurement model. 127 Figure 5.14: SCP measurement model. 0.65 ^\u00E2\u0096\u00BA Efficiency Time 0.22 o^0.55 Reliability CO cst O 1 c). \u00C2\u00B0 0.00 0.37 Responsiveness Availability 0.62 Model Fit Indices: Chi-Square (p-value)^: GFI^ : RMSEA : TLI / NNFI^: CFI : IFI^ : 0.020 1.000 0.000 1.040 1.000 1.000 (0.888) Standadized coefficients and error terms (shown). Model Fit Indices: Chi-Square (p-value) GFI RMSEA TLI / NNFI CFI IFI : : : : : : 1.289 0.994 0.000 1.023 1.000 1.015 (0.863) Standadized coefficients and error terms (shown). 0.68 0.49 0.48 Personnel Initiatives Information Initiatives Cargo Initiatives Mgt / Strategic Initiatives 0.48 Figure 5.15: Security Effort measurement model. Each measurement model is assessed for unidimensionality, reliability and validity. For a latent construct to possess construct validity, it must first be unidimensional and reliable (Garver and Mentzer, 1999). Unidimensionality Unidimensionality is an assumption underlying the calculation of reliability and is demonstrated when the indicators of a construct have acceptable fit on a single factor (one-dimensional) 128 model. An acceptable measurement of unidimensional constructs should reveal relatively small standardized residuals and modification indices. A large residual will be over 2.00 (Garver and Mentzer, 1999). A substantial modification index value is considered 7.88 (Garver and Mentzer, 1999). For all three measurement models, there are no standardized residual values larger than 2.00. The largest standardized residual values are 0.019, 0.031 and 0.366 for the Perceived Collateral Benefits, SCP and Security Effort model respectively. Similarly, there are no modification indices that are larger than 7.88. In fact, there are no modification indices for all three measurement models. In addition, the direction/sign (+, -), magnitude and statistical significance of the parameter estimates between indicators and latent variables are inspected and evaluated. The directions of all the parameter estimates are consistent with theory and existing literature. All estimated parameters are also statistically significant at the 0.05 level of significance. Next, Garver and Mentzer (1999) suggests that the magnitude of the standardized parameter estimates should be at least 0.70 to ensure construct unidimensionality. As can be seen from Figures 5.13, 5.14 and 5.15, all the standardized parameter estimates are greater than 0.70 except for three parameters: (1) Responsiveness for SCP, (2) Cargo Initiatives for Security Effort and (3) Management/Strategic Initiatives for Security Effort. Although less than 0.70, all these three parameters are marginally close enough to 0.70 to be accepted. Moreover, Savalei and Bentler (2006) suggested that a parameter value greater than 0.60 is a rather good estimate especially for exploratory studies such as this. Reliability Cronbach's alpha is still the most commonly used index of scale reliability and in general scales that receive alpha scores over 0.70 that are considered to be reliable. Table 5.33 shows the Cronbach's alpha values for each of the three latent constructs. Table 5.33: Cronbach's alpha values for each measurement model. Measurement Model Cronbach's Alpha Perceived Collateral Benefits 0.908 SCP 0.865 Security Effort ^ 0.827 129 Although commonly used, Cronbach's alpha has three limitations (Garver and Mentzer, 1999). Firstly, Cronbach's alpha tends to underestimate scale reliability or become artificially inflated if there is a large number of items in the scale. Secondly, it does not measure consistency. Thirdly, it assumes that all items have equal reliabilities. In order to overcome these limitations, Baumgarter and Homburg (1996) and Garver and Mentzer (1999) propose two additional SEM construct reliability measures: Construct Reliability = (a)2 / [(a)2 + E(1 - X,J 2 )] Variance Extracted^=^[E1,2 E(1 - xj 2 )] Where: X, is the standardized parameter estimate between a latent construct and each of its indicators. (1 - X 2) is the measurement error for each indicator. The construct reliability index does not assume that individual items have equal reliabilities and the acceptable reliability value is 0.70 or greater (Garver and Mentzer, 1999). Complementary to the Construct Reliability, the Variance Extracted measure measures the total amount of variance in the indicators accounted for by the latent variable (Garver and Mentzer, 1999). An acceptable reliability value for variance extraction is 0.50 or greater. The construct reliability and variance extracted measures are calculated for all three measurement models and all of them have construct validity values greater than 0.80 and variance extracted values greater than 0.50 (see Table 5.34). Table 5.34: SEM construct reliability measures for each measurement model. Measurement Model Construct Validity Variance Extracted Perceived Collateral Benefits 0.981 0.914 SCP 0.868 0.636 Security Effort 0.808 0.596 130 Validity There are three key aspects of validity: convergent, discriminant and predictive. Convergent Validity: Convergent validity is tested by determining whether the items in a scale converge or load together on a single construct in the measurement model. A reasonable benchmark value of substantial magnitude of the parameter estimate indicating convergent validity is 0.70. As mentioned above, majority of the standardized parameter estimates (i.e. loadings) in the measurement models are greater than 0.70. For those parameter estimates that are not, they are at least greater than 0.60. As mentioned earlier, Savalei and Bentler (2006) concluded loading values greater than 0.60 as good loadings. This therefore also implies convergent validity in the three constructs (Dunn et al., 1994). Moreover, Table 5.35 shows that the correlations values among observed variables measuring the same latent construct are significantly higher than the correlation values with other observed variables measuring another latent construct. These results provide clear support for convergent validity for all the measurement models. Table 5.35: Observed variables item-to-item correlation matrix. C )4 o 2 \"r3 co co^5a E E w C .44 o = 46 :5 m 2a. E E>< C^U) o &) t c al^ci,a _ 52 so O. S re ca E i- c0 ..., g O. E - c .4, 0 = t :5 a .5 E r (a (an, c .g), 2 0 0.(atore 24, = :5 As 40-> < .4.., =:a .5 elw a) E i= >.g \u00E2\u0080\u00A2 a) a LLI .0^U) ED a? 2 ..r., E 4,'-3 to' '5 0) 2 U) a? ...-3 2 CI 0 P.fa c.) Z U)c^g.) 5 ..r. 4,'-3 ca 5 C U).o^a? 16' ..r. E :(.1.1, 8 Z .4- C Impact on Efficiency 1 Impact on Availability 0.909 1 Impact on Responsiveness 0.929 0.945 1 Impact on Time 0.941 0.92 0.933 1 Impact on Reliability 0.914 0.86 0.896 0.902 1 Responsiveness 0.212 0.195 0.214 0.198 0.22 1 Availability 0.27 0.248 0.273 0.252 0.279 0.443 1 Reliability 0.282 0.26 0.285 0.264 0.292 0.447 0.547 1 Time 0.296 0.273 0.299 0.277 0.307 0.603 0.593 0.675 1 Efficiency 0.301 0.277 0.304 0.281 0.312 0.459 0.584 0.61 0.641 1 Mgt/Strategic Initiatives 0.321 0.297 0.322 0.302 0.328 0.195 0.248 0.259 0.272 0.277 1 Cargo Initiatives 0.301 0.278 0.301 0.283 0.307 0.183 0.232 0.243 0.255 0.259 0.71 1 Personnel Initiatives 0.375 0.347 0.376 0.353 0.383 0.228 0.29 0.303 0.318 0.323 0.564 0.529 1 Information Initiatives 0.325 0.301 0.326 0.306 0.332 0.198 0.251 0.263 0.276 0.28 0.489 0.458 0.572 1 Discriminant Validity: Discriminant validity verifies that scales developed to measure different constructs are indeed measuring different constructs. In contrast to convergent validity, discriminant validity is the 131 extent to which the items representing a latent construct discriminate that construct from the other items representing other constructs (Garver and Mentzer, 1999). Table 5.36 shows the correlations between each observable variable and each latent construct. It can be seen that the highest correlation value each observable variable has with a latent construct is with the latent construct that it is suppose to be measuring. This provides clear support for discriminant validity. Table 5.36: Variables (Items) to latent constructs correlation matrix. Perceived Collateral Benefits Security Effort SCP Impact on Efficiency 0.983 0.925 0.946 0.957 0.93 0.462 0.373 Impact on Availability 0.427 0.344 Impact on Responsibility 0.463 0.377 Impact on Time 0.434 0.349 Impact on Reliability 0.472 0.386 Mgt/Strategic Initiatives 0.34 0.695 0.651 0.812 0.704 0.343 Cargo Initiatives 0.319 0.321 Personnel Initiatives 0.398 0.401 Information Initiatives 0.345 0.347 Responsiveness 0.227 0.281 0.569 0.723 0.756 0.794 0.807 Availability 0.288 0.357 Reliability 0.302 0.373 Time 0.316 0.392 Efficiency 0.322 0.398 Predictive Validity: Predictive validity estimates whether or not the construct of interest predicts or covaries with constructs that it is supposed to predict or covary. This can be assessed by correlating constructs to other constructs that they should predict. The correlations between these two constructs should be substantial in magnitude and statistically significant (Garver and Mentzer, 1999). The correlations between the following pairs of latent constructs were performed and they are all statistically significant at the 0.05 level (see Table 5.37). This shows that the measurement models all satisfy the predictive validity requirement. Table 5.37: Correlations between measurement models. Measurement Model Pairs Correlation Significance Perceived Collateral Benefits - Security Effort 0.477 < 0.001 Perceived Collateral Benefits - SCP 0.249 0.023 Security Effort - SCP 0.508 < 0.001 132 Model Fit The individual measurement models are lastly evaluated for their model fit indices. There are three types of goodness-of-fit measures: (1) absolute fit measures which assess only the overall model fit (both structural and measurement models collectively) without adjustment for the degree of \"overfitting\" that might occur, (2) incremental fit measures which compare the proposed model to another model specified by the researcher, or (3) parsimonious fit measures which \"adjust\" the measures of fit to provide a comparison between models with differing numbers of estimated coefficients. Assessing the goodness-of-fit of a model is more a relative process than one with absolute criteria. Multiple fit indices should be examined and reported when evaluating practical fit of a model (Savalei and Bentler, 2006). Garver and Mentzer (1999) recommended using the (1) Tucker-Lewis index or Non-normed fit index (TLI or NNFI), (2) the comparative fit index (CFI) and (3) the root mean squared approximation of error (RMSEA). These indices are all scaled to a pre-set continuum (0 to 1) for easy interpretation and are all relatively independent of sample size effects. Wisner (2003) used the (1) x2 statistic, (2) Goodness-of-fit Index (GFI), (3) Normed fit index (NFI), (4) CFI, (5) Incremental fit index (IFI) and (6) Hoelter's N (CN). Savalei and Bentler (2006) recommends the use of CFI and RMSEA. However, Arbuckle and Wothke (1998) are not convinced by Hoelter's arguments in favor of the 200 cutoff for Hoelter's N. And Savalei and Bentler (2006) highlighted the NFI's dependence on sample size and the fact that NFI tends to be too small for models based on fewer observations. Therefore, in evaluating the model fit for each of the measurement models in the Supply Chain Security structural model, the six model fit statistics shown in Table 5.38 are used. Table 5.38: Supply Chain Security measurement models fit evaluation. Type Indices Acceptable Level Measurement Models Perceived Collateral Benefits SCP Security Effort Absolute fit RMSEA < 0.08 (preferably < 0.05) 0.000 0.000 0.000 X2 (p-value) Small x2 Large p-values (> 0.2) 0.585 (0.444) 0.020 (0.888) 1.289 (0.863) GFI > 0.90 0.998 1.000 0.994 Incremental fit TLI / NNFI > 0.90 1.004 1.040 1.023 CFI > 0.90 1.000 1.000 1.000 IFI > 0.90 1.000 1.000 1.015 133 Chi-Square (x 2): It is important to note that although the x2 statistic is the most common method of evaluating fit, this fit index is highly sensitive to sample size and significance tests can be misleading (Garver and Mentzer, 1999; Arbuckle and Wothke, 1995). Hair et al. (1998) recommends that the use of X2 statistic is appropriate for sample sizes between 100 and 200 and that a minimum value of 0.1 or 0.2 for the significance level should be exceeded before non-significance is confirmed. The sample size for this study is 111 and the p-values for all the x2 statistics for all three measurement models are greater than 0.20. The use of x2 statistic is therefore appropriate. The x2 statistics for all three measurement models have corresponding p-values greater than 0.05, indicating good fit. They are also greater than the 0.2 level recommended by Hair et al. (1998). GFI: This index represents the overall degree of fit but does not adjust for the degrees of freedom. The higher the value of GFI, the better the fit and Wisner (2003) recommends a greater than 0.90 GFI value as acceptable. The GFI for all three measurement models are greater than 0.90, indicating good fits. RMSEA: This index measures the discrepancy between observed and estimated input matrices per degree of freedom. The value is representative of the goodness-of-fit that could be expected if the model were estimated in the population. A value of the RMSEA of about 0.05 or less would indicate a close fit of the model in relation to the degrees of freedom (Arbuckle and Wothe, 1995). The RMSEA values for all three measurement models are less than 0.05, indicating very good fits. TLI (NNFI): This index combines a measure of parsimony into a comparative index between the proposed and null models, resulting in typical values ranging from 0 to 1.0 but it is not limited to this range. A value greater than 0.90 and close to 1.0 indicates a very good fit (Arbuckle and Wothe, 1995). The TLI values for all three measurement models are greater than 0.90 and close to 1.0, indicating very good fits. 134 CFI and IFI: Both the CFI and IFI indices represent comparison between the estimated model and a null or independence model. The values lie between 0 and 1.0 with larger values indicating higher levels of goodness-of-fit. Values close to 1.0 indicate very good fit. The CFI has been found to be more appropriate in a model development strategy or when a smaller sample is available. The CFI values for all three measurement models are greater than 0.90, indicating very good fits. And the IFI values for all three measurement models are greater than 0.90, also indicating very good fits. In summary, all six model fit indices achieve their recommended thresholds or benchmarks thus indicating good if not very good fits of the data to all the three proposed measurement models. 5.6.4.2^Structural Model Evaluation The structural model for supply chain security is now put together, and the parameters estimated and assessed for goodness-of-fit (see Figure 5.16). The first step in evaluating the results of the Supply Chain Security model is an initial inspection for \"offending estimates\". Once the model is established as providing acceptable estimates, the standardized residuals and modification indices can be evaluated and thereafter the indices for goodness-of-fit must then be assessed. Offending estimates refer to (1) negative error variances or non-significant error variances for any construct, (2) standardized coefficients exceeding 1.0 or (3) very large standard errors associated with any estimated coefficient. Standardized Coefficients The AMOS output for Supply Chain Security model contains no negative error variances or non- significant error variances for any construct. There are also no standardized coefficients larger than 1.0. All standard errors are also small with the largest value being only 0.198. 135 Model Fit Indices: Chi-Square (p-value)^: GFI^ : RMSEA : TLI / NNFI^: CFI^ : IFI : 99.949 0.909 0.036 0.989 0.992 0.992 (0.162) Standadized coefficients and error terms (shown). Security Performance Impact on Efficiency O0.97 0.65 Efficiency^4 ^co 0 O0.92 r\u00CC\u0082 Impact on Time 0 .63 Time ^4^ 0.89 4^Responsiveness Personnel Initiatives Information Initiatives Cargo Initiatives 0.32 0.44 0.11 0.58 Al Security Effort 0.73^0.53 r Nr^01^LO^N1- N CN066 6 6 Perceived Security Impact 0.79 Perceived Collateral Benefits Impact on Reliability 0.57 Reliability Impact on AvailabilityCr) O 0.52 o co O Availability 0.06 O O 0.66 0.50 0.42 Impact on Responsiveness 0.32 Mgt / Strategic Initiatives 0.48 0.47 Figure 5.16: Supply Chain Security SEM model. Note: E's and O's are \"error' variables that represent factors that affect the variable that it is pointing to, that are not captured in the survey. 136 Table 5.39: Standardized residuals matrix for Supply Chain Security model. Security Impact SCP _Resp Security _Pert Eff _Impact Available _Impact Resp _Impact Time Impact SCP Available SCP _Reliable SCP _Time SCP _Eff Mgt/Strat Jnit Cargo _Init. Personnel _Mit Info !nit Reliable Impact Security_Impact -0.003 SCP_Resp -0.571 0 Security_Perf 0.089 -1.021 0 Eff Impact 0.002 -1.713 0.285 0 Available Impact -0.001 -0.872 0.357 -0.001 0.001 Resp_Impact -0.004 -0.931 -0.011 0 0 0 Time_Impact -0.001 -1.297 023 0 0 0.001 0 SCP_Available -0.443 0 -0.039 -0.923 -0.762 -1.211 -1.296 0 SCP_Reliable 0.4 0.001 0.133 -0.123 0.22 -0.011 -0.203 0.017 0 SCPTime -0.025 0 -0.116 -1.569 -1.043 -1.117 -1.569 0.003 0 0 SCP_Eff -0.051 0.322 0.179 -1.082 -1.03 -0.921 -1.541 0.113 -0.145 -0.049 0 Mgt/Strat_Init -0.315 -1.837 0.26 0.089 0.568 0.343 0.457 -0.56 -0.062 0.657 0.501 -0.309 Cargo_lnit 0.339 0.116 -0.167 0.713 1.337 1.085 1.289 -0.362 0.135 0.657 0.192 -0.045 0.198 Personnel Ina -0.225 -0.844 -0.189 -0.097 0.548 0.193 -0.064 -0.739 -0239 -0.205 -0.741 -0.494 0.061 -0259 Info_Init 0.451 0.872 -0213 -0.321 0.262 0 -0.279 0.696 1.691 1.495 0.737 0.055 0.355 0.332 0.504 Reliable_Impact -0.003 -1.428 0.169 0.002 -0.003 -0.002 -0.001 -1.271 0.593 -0.994 -1.088 -0.111 0.787 -0.708 -0.421 0 Table 5.40: Modification indices for Supply Chain Security model. Covariances: (Security Model - Default model M.I. Par Change E10 <-> E14 13.379 -0.141 E13 <-> E10 4.675 0.075 E12 <-> 01 4.258 0.07 E3 <-> E8 6.975 0.06 Variances: (Security Model - Default model) M.I.^Par Change' Regression Weights: (Security Model - Default model M.I. Par Change SCP_Responsiveness <-- E14 9.795 -0.349 SCP_Responsiveness <-- Support_Initiatives_l 7.465 -0.164 SCP_Reliability <-- Avg_Reliable_Impact 4.658 0.152 SCP_Time <-- E14 4.323 0.207 SCP_Time <-- Support_Initiatives_I 4.009 0.107 Support_Initiatives_I <-- SC P_Responsiveness 7.46 -0.21 Info_Initiatives_I <-- SCP_Responsiveness 4.036 0.121 Info_Initiatives_I <-- SCP_Reliability 5.2 0.116 137 Standardized Residuals The standardized residuals are examined next. From the standardized residuals matrix (see Table 5.39), it can be seen that half of the residuals are negative and half are positive, indicating a good degree of randomness. The majority of their values are also small with the largest standardized residual value being 1.691 which is lower than the cutoff of 2.00 recommended by Garver and Mentzer (1999) and makes this model acceptable in terms of explaining the covariances and correlations among the variables very well. Modification Indices The modification indices are examined next (see Table 5.40). They are helpful in determining whether and how a model can or should be modified because they point specifically to paths whose addition to the model would result in the biggest improvement in the overall x2 value. Table 5.40 shows that there are two modification indices that are greater than the recommended cutoff level of 7.88 suggested by Garver and Mentzer (1999). These modification indices suggest that the corresponding pairs of variables should be allowed to correlate. The first value is 13.379, between the error term for responsiveness performance (El 0) and the error term for management/strategic initiatives (E14). Theoretically, the factors that affect an organization's motivation to implement support type initiatives such as the amount of upstream and downstream control (i.e. how integrated) it has, the nature of its operating environment and business partners can be expected to be the same as those that affect the organization's performance in terms of responsiveness. Therefore El 0 and E14 should correlate. But when these two variables are allowed to correlate, their covariance value is negative, which does not make theoretical sense. As such, this modification to the model is not made. The second value is 9.795, between responsiveness performance and the error term for management/strategic initiatives (E14). E14 represents those factors that affect an organization's adoption of management/strategic initiatives. These factors can include the management's attitude towards security, general trends in its industry and extent of government regulations. These factors cannot be directly related to an organization's responsiveness performance because an organization can and would have appropriate strategies in place to ensure that they are able to respond to customers' deliveries and requirements effectively and efficiently given these operation constraints/challenges and hence, this modification to the model is also not made. 138 Goodness-of-fit Indices Next, we assess the overall goodness-of-fit for the Supply Chain Security model. The goodness- of-fit indices used are the same as those used for evaluating the goodness-of-fit of the measurement models (see Table 5.41). Table 5.41: Supply Chain Security model fit evaluation. Type Indices Acceptable Level / Cutoff Security Model Values Absolute fit RMSEA < 0.08 0.036 (preferably < 0.05) X2 Small x2 99.949 (p-value) Large p-values (> 0.2) (0.162) GFI > 0.90 0.909 Incremental fit TLI / NNFI > 0.90 0.989 CFI > 0.90 0.992 IFI > 0.90 0.992 The absolute fit indices all indicate good fit for the Supply Chain Security model. The RMSEA is 0.036, indicating good fit as it is smaller than 0.05. The p-value for x2 is 0.162, larger than the significance level of 0.05. This means that the departure of the data from the model is insignificant at the 0.05 a level, indicating good fit. The GFI is 0.909, greater than the acceptable level of 0.90, indicating good fit. The incremental fit indices also indicate good fit for the Supply Chain Security model. The values for all the three indices \u00E2\u0080\u0094 TLI/NNFI, CFI and IFI, are greater than the acceptable level of 0.90, at 0.989, 0.992 and 0.992 respectively, indicating very good fit. Structural Model Statistical Power Statistical power is defined as the probability of correctly rejecting the null hypothesis when it is false and this can be affected by factors such as the significance criterion (a), sample size, number of groups or levels, effect size and number of dependent variables (McQuitty, 2004). McQuitty (2004) notes that if one is concerned about the validity of measures contained in structural equation models and the interpretation of model fit, then one should evaluate the associated statistical power in order to place fit indices in an appropriate context. Using the method proposed by MacCallum et al. (1996) for estimating the power associated with the test of an entire structural equation model with known sample size (N) and degrees of 139 freedom (di), McQuitty (2004) provides a table of the minimum sample size required to achieve a desired level of power for a range of df. The statistical power for the Supply Chain Security Model is assessed using the McQuitty (2004) table (Table 5.42). Table 5.42: Minimum sample size required to achieve specified power (test of close fit). df Power = 0.60, N Power = 0.70, N z Power = 0.80, N Power = 0.90, N 5 885 1132 1463 1994 10 486 613 782 1050 15 350 436 550 732 20 280 346 435 572 30 207 254 314 410 40 168 205 252 325 50 145 175 214 274 75 111 133 168 204 100 92 110 132 165 125 80 95 114 142 150 72 85 101 125 200 61 71 84 104 250 53 62 74 90 300 48 56 66 81 400 41 48 56 68 Source: McQuitty (2004). The N and df values for the Supply Chain Security model are 113 and 87 respectively. From Table 5.42, the power of the Supply Chain Security model is approximately 0.70. This is a desirable level of statistical power. And we can reasonably and safely conclude that the Supply Chain Security model is adequate in shining light on the concepts it seeks to explain. 5.6.5 Interpreting Parameters Now that we have a model that fits the data well, we proceed to assess the statistical significance of the parameter estimates and interpret them. Table 5.43 shows the standardized estimates for the final parameters in the Supply Chain Security model. Significant estimates are marked \"\"*\" beside their respective p-values. 140 Table 5.43: Parameter estimates for Supply Chain Security model. Standardized Regression Weights: (Security Model - Default model Estimate S.E. C.R. P Security Effort <--- Avg_Security_Impact 0.478 0.080 3.162 0.002*** Security Effort <--- Perceived_Collateral Benefits 0.112 0.083 0.734 0.463 Performance in_Security <--- Avg_Security_Impact 0.419 0.097 2.789 0.005*** Performance in_Security <-- Security Effort 0.440 0.196 2.744 0.006*** SCP <--- Performance in_Security 0.728 0.198 4.162 *** Info_Initiatives_I <-- Security Effort 0.704 Personnel_Initiatives_I <-- Security Effort 0.812 Cargo_Initiatives_I <-- Security Effort 0.651 Support_Initiatives_I <--- Security Effort 0.695 Personnel_Initiatives_I <--- El 1 0.584 Support_Initiatives1 <-- E14 0.719 Avg_Time_Impact <--- Perceived_Collateral Benefits 0.957 0.039 26.967 *** Avg_Reliable_Impact <--- Perceived_Collateral Benefits 0.930 0.045 21.328 *** Avg_Available_Impact <-- Perceived_Collateral Benefits 0.925 0.034 29.199 *** Avg_Resp_Impact <--- Perceived_Collateral Benefits 0.946 Avg_Eff Impact <--- Perceived_Collateral Benefits 0.983 0.044 24.381 *** SCP_Reliability <--- SCP 0.756 0.156 7.235 *** SCP_Availability <--- SCP 0.723 0.129 7.274 *** SCP_Time <--- SCP 0.794 0.161 7.214 *** SCP_Efficiency <--- SCP 0.807 SCP_Responsiveness <-- SCP 0.569 0.136 5.266 *** Correlations: (Security Model - Default model Estimate S.E. C.R. P Avg_Security_Impact <--> Perceived_Collateral Benefits 0.791 0.111 6.342 *** E13 <--> E14 0.472 0.049 3.65 *** E3 <--> Avg_Security_Impact 0.093 0.027 1.169 0.242 E4 <--> Avg_Security_Impact -0.144 0.021 -2.503 0.012*** E7 <--> E8 0.187 0.071 1.105 0.269 E7 <--> El 0 0.304 0.068 1.99 0.047*** E9 <--> E10 0.057 0.056 0.456 0.648 E8 <--> El 0 0.031 0.064 0.24 0.810 E5 <--> E4 0.567 0.019 3.602 *** E2 <--> Avg_Security_Impact -0.247 0.024 -2.907 0.004*** E3 <--> E5 0.133 0.012 1.228 0.219 E2 <--> E4 0.312 0.018 1.896 0.058 E2 <--> E5 0.295 0.018 1.533 0.125 E3 <--> E2 0.112 0.015 0.76 0.448 E7 <--> E9 0.046 0.055 0.331 0.741 E1 <--> Avg_Security_Impact -0.219 0.025 -1.536 0.124 All parameter estimates are significant except: 1. Security Effort^Perceived Collateral Benefits 2. E3 f.4 Average Security Impact 3. E7 E-4 E8 4. E9 E--) E10 5. E8 <-4 E10 6. E3^E5 141 7. E2 E--) E4 8. E2 <-4 E5 9. E3 <- E2 10. E7 E--> E9 11. El E--) Average Security Impact When a non-significant path exists in an otherwise well fitting model, we ask whether the model would fit the data equally well or about as well if we were to omit this path entirely. We can answer this question by means of a X2 difference test (Table 5.44). Table 5.44: Goodness-of-fit indices for x2 difference tests. Path Eliminated RMSEA x2 (p-value) GFI TLI / NNFI CFI IFI R2 - SCP Original 0.036 94999'949(0.162) 0.989 0.992 0.992 0.530 Security Effort f. Collateral Benefits 0.036 100.489 (0.171) 0.909 0.989 0.992 0.992 0.533 E3^.--> Average Security Impact 0.037 101.333 (0.157) 0.908 0.989 0.992 0.992 0.530 E7^.-.> E8 0.037 101..184(0.159) 0.907 0.989 0.992 0.992 0.514 E9^4 El 0 0.035 100.159(0.177) 0.908 0.990 0.992 0.993 0.521 E8 <-^El0 0.035 100.007(0.180) 0.908 0.990 0.993 0.993 0.526 E3 <-4 E5 0.037 101. 479(0.154) 0.907 0.989 0.992 0.992 0.530 E2 <--> E4 0.040 103.675.(0.122) 0.905 0.987 0.990 0.990 0.529 E2 E-4 E5 0.038 102.256.(0.142) 0.906 0.988 0.991 0.991 0.530 E3^.-.> E2 0.036 100.528(0.170) 0.908 0.989 0.992 0.992 0.530 E7^.-> E9 0.035 100.059(0.179) 0.909 0.990 0.992 0.993 0.525 El (--> Average Security Impact 0.038 102.409 (0.140) 0.906 0.988 0.991 0.991 0.530 Table 5.44 shows that the elimination of each of the non-significant paths does not alter the goodness-of-fit of the model by much. The x2 differences range between 0.11 and 3.726 with 1 degree of freedom. The path that yields the largest x2 difference is E2 E--> E4. E2 is the error term for average time impact and E4 is the error term for the average availability impact. The resulting modified model still fits the data well but we note that the squared multiple correlation value (R2) has decreased very slightly from 0.530 to 0.529. However, as there is strong 142 theoretical and logical support for this relationship between the unaccounted factors that affects the perceived impact on time and the perceived impact on availability performance, this path is retained in the final model. The rest of the non-significant paths yielded relatively smaller x2 differences. Although the elimination of these paths does not significantly alter the model's goodness-of-fits, their corresponding R2 values either remain the same or decreased. However, this is with the exception of the path - Security Effort <-- Perceived Collateral Benefits. The R 2 value has increased very slightly from 0.530 to 0.533. However, as there is strong theoretical support for the relationship between perceived collateral benefits and security effort (i.e. the extent of adoption of security initiatives), this path is also retained in the final model. Note also that Garver and Mentzer (1999) pointed out that the x2 test is highly sensitive to sample size and significance testing can be misleading. As such, even though these parameters or paths are not statistically significant, they are retained in the model because their directions (i.e. sign) and magnitudes demonstrate some of the interesting existing hypotheses around supply chain security. A bigger sample size might be able to detect this relationship (Savalei and Bentler, 2006). 5.6.6 Analysis of Structural Model The sections that follow will discuss the findings from the SEM model results. However, first and foremost, it is important to highlight the concept of nonidentifiability and how it has been addressed in the SEM model. It is essential to note that the Std Errors, Critical Ratios and P-Values are blank for those regression weights that are pre-specified with a value (typically \"1\") to fix the problem of model nonidentifiablility (Arbuckle and Wothke, 1995), Model nonidentifiability refers to the situation where the number of parameters to be estimated exceeds the number of distinct sample moments (i.e. negative degrees of freedom). To illustrate with an example, there is simply not enough information to determine both the price of each button and the number purchased by only knowing that one bought $10 worth of buttons. 143 According to Arbuckle and Wothke (1995), any one single-headed arrow leading away from each unobserved variable can be chosen and its regression weight fixed to \"1\". The regression weights that are fixed at \"1\" are: \u00E2\u0080\u00A2 Impact on Responsiveness E- Perceived Collateral Benefits (for the unobserved variable \"Perceived Collateral Benefits) \u00E2\u0080\u00A2 SCP_Efficiency SCP (for the unobserved variable \"SCP\") In addition, specifically for the measurement model Security Effort, there is a need to compensate for the assumption that the four groups of initiatives predicting Security Effort are parallel with same-sized common variance components and equal-sized error variances. This is because the number of groups of initiatives included under each of the four headings is different. \"Info Initiatives\" and \"Cargo Initiatives\" each consists of two of the ten groups whereas \"Personnel Initiatives\" and \"Mgt/Strategic Initiatives\" each consists of three of the ten groups. As such the regression weights for all four observed variables that predict Security Effort are specified. Since \"Personnel Initiatives\" and \"Mgt/Strategic Initiatives\" have 50% more items in their group than the other two, the weight for regressing these observed variables on the unobserved variable Security Effort is 1.5 times the weight for regressing \"Info Initiatives\" and \"Cargo Initiatives\" on Security Effort. Similarly, given equal variances for each of these observed variables, the (fixed) regression weight for the error terms for \"Personnel Initiatives\" and \"Mgt/Strategic Initiatives\" is Ni1.5 = 1.22 times as large as the (fixed) regression weights for the error terms for \"Info Initiatives\" and \"Cargo Initiatives\". Since these regression weights are pre-specified, AMOS does not calculate their corresponding Std Errors, Critical Ratios and P-Values. Security Effort The statistical relationship between perceived security impact and security effort is significant with a standardized parameter estimate of 0.478 (see Table 5.41). This statistically significant relationship (p-value < 0.001) supports the hypothesis (H1) that an organization will undertake a security effort that is perceived to have a positive impact on the security performance of its supply chain operations. 144 The statistical relationship between perceived collateral benefits and security effort is however not significant with a standardized parameter estimate of 0.112 (see Table 5.41). Although this statistical relationship is not significant (p-value > 0.05) in this model, the positive sign between the two latent constructs supports the common viewpoint that the more collateral benefits a security investment is perceived to bring, the more motivated an organization will be to undertake the security investment. Next, it is interesting to note the large difference in the magnitudes of these two standardized parameter estimates. The parameter value between perceived collateral benefits and security effort is 0.366 (i.e. \u00E2\u0080\u0094 77%) smaller than the parameter value between perceived security impact and security effort. This illustrates that currently, organizations place more emphasis on the actual resulting security performance improvements rather than traditional SCP improvements when deciding whether or not to undertake security improvement initiatives. Both the perceived security impact and perceived collateral benefits speaks to an organization's self-interest behavior. However, recall from Figures 5.10 and 5.11 that there is also a strong indication of an out-of- compliance behavior from the private sector. This means that the private sector is undertaking security efforts as a result of the need to comply with public regulations rather than self- interests. These findings are consistent with that from the field interviews where interviewees indicated that they see their current efforts in security improvements as a result of complying with regulations and trade movement requirements such as C-TPAT and FAST. Figure 5.17 illustrates the structure of these motivators for security efforts. Figure 5.17: The motivators of security efforts. Self-Interest Behavior .--.---...-1\u00E2\u0080\u00A2,-----.-.. Perceived Security Benefits Perceived Collateral Benefits Security Effort Out-of-Compliance Behavior 145 Security Effort and Security Performance The statistical relationship between security effort and security performance is also significant with a standardized parameter estimate value of 0.440 (see Table 5.41). This significant statistical relationship (p-value < 0.05) answers the third research question of interest and also supports the hypothesis (H3) that undertaking security efforts will improve security performance. This result reflects that despite a lack of objective KPIs for security performance, responding organizations are confident that whatever they are doing towards improving security performance are indeed doing what they are supposed to. This is consistent with the findings from the field interviews and this observation could be due to a simply logical expectation of a positive outcome from security effort since security performance is a paradoxical concept where an improved outcome can only be measured when something bad happens. To understand specifically how each type of initiative affects security performance between respondent types, each initiative is cross-tabulated against the self-rated performance in security. The results show statistically significant positive relationships between seven of the ten groups of security initiatives and security performance (see Table 5.45). Significance is determined using the Pearson x2 statistic where a p-value smaller than 0.05 is considered significant. Detailed results of the cross-tabulation analyses can be found in Appendix G. Table 5.45: Cross-tabulation results for security initiatives and security performance. Security Initiatives P-Value Entire Sample Shipper Service Provider Security/Operations related certifications 0.005*** 0.027*** 0.055\"* Business Partner Requirements 0.020*** 0.028*** 0.448 Container/Trailer/ULD Security 0.061 0.086 0.322 Advanced Data 0.000*** 0.007*** 0.002*** Physical Security and Access Control 0.002*** 0.028*** 0.027*** Procedural Security 0.129 0.108 0.858 Tracking and Monitoring 0.109 0.125 0.536 Security Training 0.049*** 0.093 0.172 Personnel Security 0.001*** 0.001*** 0.210 Management Support 0.008*** 0.066 0.058 ***^Significant p-values at the 0.05 level of significance. Taken as a whole, these results show that the organizations that have implemented one or more of the seven groups of security initiatives below perceive their security performance to be significantly better than organizations that have not. These seven groups of initiatives are (1) 146 security/operations related certifications, (2) business partner requirements, (3) advanced data, (4) physical security and access control, (5) security training, (6) personnel security and (7) management support and sponsorship. It is also important to recall that advanced data, personnel security, physical security and security/operations related certifications are the four most popularly implemented security initiatives to date. Therefore, like an effort justification behavior 47, organizations that have implemented these initiatives due to compliance actually see these initiatives as having a significant positive effect on their security. However, when the sample is split into shipper and service provider clusters, we can see that shippers and service providers differ in their opinions on two of these seven groups of significant initiatives. These two groups of initiatives are (1) business partner requirements and (2) personnel security. The significant difference in opinions about their impact on security performance comes mainly from the shipper cluster. The service providers in the sample are somewhat neutral about the effectiveness of instituting business partner requirements and personnel security on security performance. The division on opinions on business partner requirements is consistent with findings gathered from field interviews. During the field interviews, service provider organizations such as the 3PLs, port operators and ocean carriers expressed that although they see security improvement as a holistic effort among different stakeholders in the supply chain, shippers (i.e. ultimate owners of the cargo) should be taking the lead in these efforts. The division on opinions on personnel security training could be due to the fact that service providers typically employ more temporary workers compared to shippers as a result of the nature of their operations. As such, some of the examples of personnel security efforts such as background checks and security awareness training may be seen as being less effective to service providers. The statistical relationship between perceived security impact and security performance is also significant with a standardized parameter estimate value of 0.419 (see Table 5.41). The 47 Effort justification behavior refers to the tendency to reduce dissonance by finding reasons for why a person has devoted time, effort, or money for something turned out to be unpleasant or disappointing to the person (Gilovich et al., (2005). 147 statistically significant relationship (p-value < 0.05) between perceived security impact and security performance supports the fourth hypothesis (H4) that in the absence of objective security performance KPIs, organizations who perceive a security initiative (be it a mandatory one or voluntary one) as having strong impact on security performance will also perceive their performance in security to have improved after implementing the initiative (i.e. again an effort justification behavior). At this point, it is important to recall that the data supported that current private sector security efforts are made primarily out-of-compliance rather than self-interests. Thus, it follows that in view of the positive relationships among perceived security impact, security effort and self-rated security performance, if there is no objective way of evaluating the effectiveness of security efforts, we can expect the effects of effort justification behaviour to kick-in. It is also important of note that neither the shipper nor the service provider groups perceive any significant impact container/trailer/ULD security measures has on security performance. This is consistent with the findings from Langhoff et al. (2005), which found that most technologies for container security are not commercially viable in the near future because they do not function properly (i.e. they have less then 99.9% reliability), do not improve security or are too expensive. The study tested every major technology group that could possible be applied to a container: eSeals, container security devices (CSDs), cellular devices, GPS, and sensors (radiation, biological, chemical, etc.). International jurisdiction and frequency ranges also remain an issue especially for remote sensors and monitoring devices such as CSDs. Security Effort and SCP Via the impact on security performance, security effort also has a positive effect on traditional SCP. The statistical relationship between security performance and traditional SCP is significant with a very large standardized parameter estimate value of 0.728. This supports the fifth hypothesis (H5) and reflects the sentiments that organizations support the notion that in today's environment, an improvement in security performance will bring about a net positive improvement in traditional SCP. To understand if there are specific groups of security initiatives that are contributing to these effects on traditional SCP, we conducted cross-tabulation analyses to identify any significant relationships between each group of security initiative and their corresponding impact on 148 various aspects of SCP 48 . Statistical significance is determined using the x2 test with p-values smaller than 0.05 considered as significant. Table 5.46 shows the p-values with the significant ones marked with \"\"*\". Table 5.46: Cross-tabulation results for security initiatives and traditional SCP. Aspects of SCP Security/Operations Related Certification (P-Value) Entire Sample Shipper Service Provider Efficiency 0.255 0.087 0.277 Time 0.218 0.111 0.650 Reliability 0.208 0.161 0.950 Availability 0.159 0.111 0.906 Responsiveness 0.293 0.264 0.950 Aspects of SCP Business Partner Requirements (P-Value) Entire Sample Shipper Service Provider Efficiency 0.126 0.025*** 0.153 Time 0.004*** 0.004*** 0.662 Reliability 0.121 0.058 0.376 Availability 0.062 0.171 0.236 Responsiveness 0.001*** 0.005*** 0.376 Aspects of SCP Container/Trailer/ULD Security Shipper (P-Value) Service ProviderEntire Sample Efficiency 0.226 0.310 0.386 Time 0.045*** 0.124 0.151 Reliability 0.121 0.100 0.872 Availability 0.023*** 0.046*** 0.257 Responsiveness 0.088 0.193 0.139 Aspects of SCP Advanced Data (P-Value) Shipper Service ProviderEntire Sample Efficiency 0.067 0.279 0.075 Time 0.010*** 0.040*** 0.151 Reliability 0.154 0.530 0.005*** Availability 0.222 0.266 0.762 Responsiveness 0.024*** 0.035*** 0.872 Aspects of SCP Physical Security & Access Control (P-Value) Entire Sample 0.211 Shipper 0.028*** Service Provider 0.047***Efficiency Time 0.004*** 0.068 0.011*** Reliability 0.182 0.403 0.106 Availability 0.022*** 0.068 0.177 Responsiveness 0.019*** 0.090 0.106 48 Respondents' answers on impact on various aspects of SCP are used instead of their self rating on SCP in Section A of the survey because SCP performance was self-rated at the very beginning of the survey which means that the respondents' answer could have been influenced by many other things other than security efforts. 149 Table 5.46 (continued): Cross-tabulation results for security initiatives and traditional SCP. Aspects of SCP Procedural Security (P-Value) Entire Sample Shipper Service Provider Efficiency 0.100 0.128 0.977 Time 0.101 0.125 0.849 Reliability 0.026*** 0.059 0.341 Availability 0.069 0.060 0.735 Responsiveness 0.060 0.128 0.341 Aspects of SCP Tracking & Monitoring P-Value) Entire Sample Shipper Service Provider Efficiency 0.064 0.212 0.144 Time 0.002*** 0.064 0.009*** Reliability 0.282 0.439 0.463 Availability 0.065 0.200 0.166 Responsiveness 0.024*** 0.212 0.053 Aspects of SCP Security Training (P-Value) Entire Sample Shipper Service Provider Efficiency 0.003*** 0.004*** 0.437 Time 0.001*\" 0.001\"* 0.530 Reliability 0.001 *** 0.003*** 0.072 Availability 0.002*** 0.001*** 0.340 Responsiveness 0.001*** 0.000*** 0.613 Aspects of SCP Personnel Security (P-Value) Entire Sample Shipper Service Provider Efficiency 0.069 0.278 0.212 Time 0.006*** 0.047*** 0.060 Reliability 0.280 0.370 0.708 Availability 0.010*** 0.130 0.014*** Responsiveness 0.010*** 0.178 0.002*** Aspects of SCP Management Support & Sponsorship (P-Value) Entire Sample Shipper Service Provider Efficiency 0.006*** 0.041 0.054 Time 0.016*** 0.018*** 0.478 Reliability 0.009\"* 0.092 0.025*** Availability 0.030*** 0.066 0.250 Responsiveness 0.015*** 0.041 *** 0.308 Which security initiatives have significant impacts? As seen from Table 5.46, it is interesting to note that probably one of the most widely implemented security initiatives - security/operations related certification, is not perceived to have statistically significant impacts on any aspects of SCP. None of the p-values are statistically significant and the conclusion does not change when the respondent type (i.e. Shipper vs Service Provider) variable is added as a control variable. This clearly reflects the out- of-compliance nature of getting paper certifications such as C-TPAT and FAST. 150 Of the other four more popularly implemented initiatives (i.e. Business Partner Requirements, Advanced Data, Physical Access and Control and Personnel Security), all of them are perceived to have significant impact on time and responsiveness but only two of them (i.e. Physical Access and Control and Personnel Security) are perceived to have significant impacts on availability. Security initiatives that seek to enhance supply chain visibility (i.e. Tracking and Monitoring) are perceived to have significant impacts on the time and responsiveness aspect of SCP. This is logically since the increased in ability to get information about the whereabouts of an organization's cargoes enables the organization to respond rapidly and effectively to chances in demand or routing. However, recall from Figure 5.11 that this is the least popularly implemented group of security initiatives. The majority of the other less popularly implemented initiatives such as procedural security, security training and management support and sponsorship, are also perceived to have significant impact on reliability. Two of these initiatives (Security Training and Management Support) are in fact perceived to have significant impact all aspects of SCP. Considering that these groups of security initiatives are relatively more complex to implement compared to the popular/mandatory ones such as Physical Access and Control, Business Partner Requirements and Security Certification, it is evident why they are less widely adopted despite their perceived collateral benefits. It is because security is yet viewed as a strategic driver for supply chain management and again, this result alludes to the fact that security initiatives are currently implemented out of compliance instead of self-interest. What are the aspects of SCP that are impacted? As can be seen from Table 5.46, the aspect of SCP that is impacted by the most number of groups of security initiatives is Time and Responsiveness, followed by Availability, then Reliability and finally Efficiency. It is evident why respondents perceive Time and Responsiveness to be the most impacted aspect of SCP. Most of the security initiatives commonly implemented today including those that are mandatory (such as advanced manifest rule) requires additional operation times to be spent on inspecting and checking, thus lengthening processing time. It follows that as a result of a \"longer\" supply chain and the increased risk of cargo being held at customs check points for inspections, organizations may opt to hold more inventories in order to remain responsive to their customers and ensure that their products and/or services are always available when 151 demanded. Those who do not or cannot will perceive security efforts as having a negative impact on their responsiveness and availability performance. Reliability and Efficiency are two aspects of SCP that are perceived to be the least impacted by security efforts. Recall that many of the security technologies are \"promoted\" as being able to make one's supply chain more reliable and efficient. If this is not what the users (i.e. Shippers and Service Providers) perceive, then the marketing message may not have been the most appropriate. Next notice from Figure 5.16 that respondents perceive that the impact security efforts have on security performance has unfavorable impacts on the efficiency, time and availability aspect of SCP. The regression weights between Perceived Security Impact and Impact on Efficiency, Time and Availability are negative with values of -0.22, -0.25 and -0.14 respectively. The relationship between Perceived Security Impact and Time and Availability are statistically significant meaning that security efforts that are perceived to bring about an improvement in security are perceived to bring about deteriorations in an organization's supply chain's on-time performance and ability to ensure availability of their products and services. This is consistent with the sentiments gathered from the field interviews. Theoretically, we can also see why this is so. Physical access and control and other procedural security initiatives that add checkpoints and inspections along the cargo movement process also add non-value adding delays to the supply chain, causing organizations to perceive a negative impact on their time performance. A lengthened supply chain brings about additional operations uncertainties. Additional checks and balances, more thorough and lengthy cargo handling procedures and inspections can also affect an organization's ability in ensuring that their products and services will always be available to their customers. As such it is not surprising organizations perceive a negative impact of enhanced security on their availability performance. These observations are very logical considering that the most popular security improvement initiatives currently are personnel security, physical security and access control and obtaining security related certifications which typically add additional checks and balances along the cargo movement process. Although the relationship between Perceived Security Impact and Efficiency Impact is not statistically significant, the direction of the relationship does serve to illustrate a common sentiment found during the field interviews \u00E2\u0080\u0094 security improvement initiatives are cost items. 152 Security initiatives such as physical access and control and C-TPAT certifications, costs money and do not have an immediate ROI. As such, organizations adopting these measures will perceive a negative impact on their supply chain efficiency. It is often claimed that enhanced supply chain visibility can lead to other collateral benefits such as allowing an organization to be more responsive to changing business environment and enabling an organization to use of limited resources more effectively and efficiently in order fulfilment. Since security initiatives such as Tracking and Monitoring, which have the potential to improve an organization's visibility of its supply chain operations, is the least implemented group of security initiatives, it is small wonder again why respondents feel that the security efforts taken have a negative impact on their time, availability and efficiency performance. And in light of Figure 5.10 where respondents consistently rank Tracking and Monitoring as the group of security initiatives with the greatest impact on all aspects of SCP, it is very evident that the private sector is currently adopting security initiatives only when mandated. The concept of collateral benefits is not enough to entice private organizations to adopt particular security improvements just yet. However, notice from Figure 5.16 that organizations do perceive that security efforts that bring about an increase in security will bring about improvements in the reliability performance aspect of SCP. The regression weight between the Perceived Security Impact and Impact on Reliability is positive with a value of 0.093. Again, although this relationship is not statistically significant, it serves to illustrate a logical theory that a secured supply chain is also a more reliable\" supply chain. Are there any differences between Shippers and Service Providers? The significant differences for the more popular security initiatives such as Advanced Data, Physical Access and Control, Personnel Security and Management Sponsorship and Support, come from the service provider cluster of respondents. Business Partner Requirements on the other hand, has significant differences accounted for by respondents in the shipper cluster. This is consistent with findings from field interviews where interviewees especially service provider organizations such as 3PLs, ocean carriers and port operators expressed that the ultimate 49 \"Reliable\" being defined as consistency and dependability of supply chain operations. 153 cargo owners (i.e. Shippers) should take the lead in the holistic effort towards improving security. The Insights In conclusion, security efforts are perceived to have positive impacts on supply chain security performance and opinions between the shipper and service provider cluster are similar. Specifically, the five most popularly implemented security initiatives \u00E2\u0080\u0094 personnel security, physical security and access control, security/operations related certification, advanced data and business partner requirements, are perceived to have the greatest impact on security performance. This could be a genuine feedback or an effort justification behavior or a combination of both. But these same initiatives are not perceived to have significant impacts on SCP. This is especially the case for security/operations related certification. This group of initiatives is not perceived to have significant impact on any of the aspects of SCP. Two of the ten groups of initiatives \u00E2\u0080\u0094 security training and management support are also perceived to have significant impacts on security performance. They are also perceived to have significant impacts on all aspects of SCP, but they are currently two of the three least implemented initiatives; the other being tracking and monitoring. Tracking and Monitoring type of security initiatives are also perceived to have relatively wider impacts on SCP but is similarly not widely implemented. The fact that organizations are not implementing initiatives that they perceive to have positive impacts on their SCP reflects very strongly the reality that the private sector is currently adopting security initiatives out of compliance instead of self-interest. The overall net perceived impact on traditional SCP is also positive. Results support Willis and Ortiz (2004) preliminary conclusions that supply chain efficiency and security are distinct but interconnected. However, the private sector does perceive that security efforts will bring about unfavorable impacts to the time, availability and efficiency aspects of SCP. The longer cycle time of the supply chain due to longer delays in getting goods through the global supply chain threatens supply chain practices such as Just-in-Time and lean inventory processes (Lee, 2004); Just-in-Time and lean inventory processes are proven supply chain strategies for improving supply chain performance especially operations efficiency and product availability. 154 Additional checks and inspections along the cargo movement process also add delays which are not necessarily value-adding. Those security initiatives that are touted to bring about collateral benefits (e.g. enhanced availability of products and on-time performance of deliveries) as a result of improved supply chain visibility, such as Tracking and Monitoring, are however least widely implemented. As such, it is little wonder that organizations responding to this study perceive these negative effects of security efforts on their SCP. Taking all operating factors into consideration, security efforts and improvements are perceived to have a net positive impact on SCP. Specifically, instituting the right procedures, training personnel appropriately and ensuring higher level management support, are the ways to go in ensuring reliability in an organization's supply chain operations in this increasingly uncertain environment. It is also apparent that these initiatives are much more long-term in nature and affects a more fundamental level of business operations than physical security and access control, personnel security, obtaining security certifications and transmitting shipment information in advance. Results from this study also clearly illustrate the industry's opinions about the need for security efforts to be holistic. Instituting business partner requirements is not only perceived to have a significant impact on security performance, it is also perceived to be beneficial to the overall responsiveness of the supply chain. And the community expects the ultimate cargo owner (i.e. the shipper) to take the lead on this. 155 CHAPTER 6 CONCLUSION This Chapter concludes the study and addresses the contributions and limitations of the study, final thoughts and potential future research directions. This study attempted to increase the understanding of supply chain security management and provide useful insights to managers seeking to improve security performance of their supply chain. While the data in this study should not be considered as any type of industry average, the findings do demonstrate the key ideas and concepts in managing security in supply chain operations as described in the rest of this chapter. This study provides a major step and springboard for further research in the area of supply chain security management and performance evaluation. 6.1 Undertaking Security Effort The results from this study clearly show the positive effects that security improvements have on overall supply chain performance. As such, undertaking security investments should not be omitted from an organization's overall supply chain strategic plan, if the organization endeavours to improve their overall supply chain operations performance. The Motivation/Drivers The field interview and empirical results from this study show that security is not yet a strategic driver in supply chain management. These sentiments do not differ significantly between the Shipper and Service Provider community. They also do not differ among organizations with different cargo nature, typical shipment sizes, organization size and scope of supply chain control/influence. The current motivation/drivers behind the private sector's implementation of security initiatives are found to be very much due to a pressure to comply with public sector regulations and/or simply the ease of implementation. This is consistent with current literature on security such as Willis and Ortiz (2004), Wolfe (2004), Langhoff et al. (2005), Rice and Spayd (2005), Peleg- Gillai et al. (2006). 156 Support for this observation comes from the fact that respondents in this study place more weight on perceived security impact compared to perceived collateral benefits when determining the extent or amount of security efforts to undertake. The empirical results of this study also show that the most widely implemented security initiatives are not the ones perceived to have the greatest positive impact on SCP (i.e. collateral benefits). In fact, on the contrary, those security initiatives that are widely implemented are the ones perceived to have little or no collateral benefits. To entice private organizations to undertake security investments out of self-interests, it is then logical for one to look to the concept of collateral benefits. That is, using collateral benefits as a catalyst to entice private sector investments in security improvements. The results from this study shows that although private organizations are cognizant of the collateral benefits that can come along with investments in security, they are not really basing their security investment decisions on collateral benefits right now. Their out-of-compliance behaviour in this context clearly shows the relative importance they see security in managing their supply chain. These observations together mean that there is much work required to market the concept of collateral benefits. It also means that it is equally important to sell the idea of security as a potential competitive advantage in supply chain management in the future. Types of Effort and Their Effectiveness on Security Improvement Not all security initiatives are viewed equal however. Based on the ten groups of security initiatives outlined in the CBP's (2006) catalog of supply chain security best practices, the initiatives that are perceived to have significant impacts on security performance are (not in order of importance) 5\u00C2\u00B0 . \u00E2\u0080\u00A2 Obtain security/operations related certifications \u00E2\u0080\u00A2 Institute business partner requirements \u00E2\u0080\u00A2 Comply with advanced data requirements \u00E2\u0080\u00A2 Establish physical security and access controls \u00E2\u0080\u00A2 Conduct security training for personnel 50 However, it is important to be cognizant that these are also some of the most popularly implemented security initiatives. As such this could either be a genuine feedback or an effort justification behavior or a combination of both. 157 \u00E2\u0080\u00A2 Implement personnel security measures \u00E2\u0080\u00A2 Garner management support Empirical results show that the Service Provider group tends to place more importance in the effectiveness of initiatives such as obtaining certifications, complying with advanced data requirements and instituting physical security and access controls. This observation is not surprising considering the widespread outsourcing environment today, where service providers are the ones handling the physical cargo storage and movement and the associated shipping documentation for their clients. The Shipper group on the other hand, also places more importance on externally oriented initiatives such as establishing business partner requirements. This observation is encouraging for the holistic approach to improving supply chain security. Many of the service providers interviewed during the field interviews have expressed the appropriateness for customers to lead the holistic effort in improving supply chain security. It is also interesting to note that neither the shipper nor the service provider groups perceive container/trailer/ULD security measures to have any significant impacts have on security performance. This is consistent with the findings from current literature which found that most technologies for container security are not commercially viable in the near future because they do not function properly (i.e. they have less then 99.9% reliability), they do not improve security or they are too expensive. The study tested every major technology group that could possible be applied to a container: eSeals, container security devices (CSDs), cellular devices, GPS, and sensors (radiation, biological, chemical, etc.). Types of Efforts and Their Collateral Benefits In terms of collateral benefits, security efforts in general are perceived to have significant impacts on time and availability and the perceived impacts are negative. Efficiency is also found to be negatively impact by a tightening of security within the supply chain but the empirical results of this study for this is not statistically significant. These observations are not surprising considering there are widespread theoretical and logical support for the negative effects that security initiatives such as additional inspections and checkpoints have on lengthening the supply chain and increase the amount of uncertainties in cargo movement. 158 The reliability aspect of SCP on the other hand, is found to be positively impacted by a tightening of security within the supply chain. This is what security improvements are supposed to do anyways and it is encouraging that the private sector holds this same view. However, again not all security initiatives are viewed the same when it comes to the idea of collateral benefits. Certain groups of initiatives are perceived to have more significant impacts on various aspects of SCP than others. Table 6.1 ranks the ten groups of security initiatives based on their popularity of implementation and lists their corresponding collateral benefits (i.e. aspects of SCP that are found to be statistically significantly different between those respondents who have implemented that initiative and those who have not). Table 6.1: Ranking security initiatives by implementation popularity with no. of SCP aspects that are statistically significant. Security Initiatives (Ranked by Popularity of Implementation) Significant SCP Aspects Affected Personnel security Time Availability ResponsivenessPhysical security & access control Operations/security related certifications None Advanced data compliance Time Responsiveness Business partner requirements Container/ULD security Time Availability Procedural security Reliability Security training & outreach programs Efficiency Time Availability Reliability Responsiveness Management support & sponsorship Tracking & monitoring Time Responsiveness It is interesting to note that of all the security initiatives, Tracking and Monitoring is the least implemented security initiative but is at the same time, perceived by respondents to be the one that can bring about a relatively good amount of collateral benefits in terms of time and 159 responsiveness performance. The other two least implemented initiatives \u00E2\u0080\u0094 security training and management support, are also perceived to have significant positive impacts on SCP. On the contrary, one of the more widely implemented security initiatives - Security Related Certifications, is perceived to bring about little or no collateral benefits. This finding again reflects very strongly the reality that the private sector is currently adopting security initiatives out of compliance instead of self-interest. Shippers Should Lead the Holistic Effort Shippers and service providers also differ in their opinions on the effectiveness of instituting business partner requirements. The service providers in the sample are somewhat neutral about the effectiveness of instituting business partner requirements and personnel security on security performance but shippers feel otherwise. These results support the findings from the field interviews where service provider organizations such as the 3PLs, port operators and ocean carriers expressed that although they see security improvement as a holistic effort among different stakeholders in the supply chain, shippers (i.e. ultimate owners of the cargo) should be taking the lead in these efforts. 6.2 Evaluating the Effectiveness of Security Effort Although not perceived to be a competitive advantage/supply chain driver in the near term, industry practitioners, shippers and service providers alike, do see security as a component of overall SCP. Results from this study indicate that KPIs for security performance are indeed a subset of traditional SCP from the industry practitioners' point of view. Results from this study together with existing literature on SCP suggest that traditional SCP evaluation is made up of six key components: \u00E2\u0080\u00A2 Efficiency (utilization of resources including time, money, people and infrastructure) \u00E2\u0080\u00A2 Reliability (on-time, speed) \u00E2\u0080\u00A2 Accuracy \u00E2\u0080\u00A2 Availability (business planning effectiveness) \u00E2\u0080\u00A2 Responsiveness (agility and flexibility) 160 \u00E2\u0080\u00A2 Security Specifically, security performance measurements can be further classified into four key components that are very similar to the components of supply chain management: \u00E2\u0080\u00A2 those measuring the accuracy and reliability of information \u00E2\u0080\u00A2 those measuring the effectiveness of physical breaches prevention \u00E2\u0080\u00A2 those measuring the cost of security initiatives \u00E2\u0080\u00A2 those measuring the safety of operations and personnel Results from this study also indicate that industry practitioners perceive security performance to have implications on not only one but many aspects of traditional SCP, especially in terms of timeliness, reliability, availability and efficiency. 6.3 Managerial Implications of Results Security Investments Should be Viewed as Any Other Supply Chain Investments It is essential for private organizations to recognize that security investments, like any other supply chain investments, bring about supply chain tradeoffs. What is more important is that at the end of the day, there should be a net positive impact on overall supply chain performance. Specifically, instituting the right operating procedures with sound checks and balances, training personnel appropriately and ensuring higher level management support, is the way to go in ensuring reliability in an organization's supply chain operations in this increasingly uncertain environment. And it is apparent why this is so. These initiatives are much more long-term in nature and affect a more fundamental level of business operations than physical security and access control, personnel security, obtaining security certifications and transmitting shipment information in advance. What to Invest? An extension of Table 6.1, Table 6.2 shows the corresponding ranking of security initiatives based on perceived SCP impacts (i.e. collateral benefits) and their perceived impact on security itself. 161 Based on the insights and experience of the maritime supply chain community and the findings in this study, Figure 6.1 illustrates a route that private organizations can take in improving the security of their supply chain. It seems then that the way to go in improving supply chain security is to kick start the security efforts with appropriate investments in physical security and access control mechanisms. Simple and easy to implement measures include restricting access to sensitive areas, reviewing and renewing (if needed) employee identification system and using uniforms to distinguish between staff and visitors, establishing a visitor logging system and monitoring all pickups and deliveries. Table 6.2: Ranking security initiatives. Collateral Benefits Statistically Significant impacts on Security (Table 5.41) Rank based on \"Perceptions\" (Figure 5.10) Rank based on \"Actual Experience\" (Table 5.42) 1.Tracking & Monitoring (5.39) 2. Management Support (5.21) 3. Physical Security and Access Control (5.18) 4. Business Partner Requirements (5.17) 5. Security Training (5.13) 6. Container Security (5.05) 7. Procedural Security (5.03) 8.Advanced Data (5.02) 9. Personnel Security (5.00) 10.Security Related Certification (4.78) All Aspects: Security Training Management Support (Efficiency, Time, Reliability, Availability, Responsiveness) Security Related Certification Business Partner Requirements Advanced Data Physical Security & Access Control Security Training Personnel Security Management Support 3 Aspects: Personnel Security Physical Security and Access Control (Time, Availability, Responsiveness) 2 Aspects: Tracking & Monitoring Advanced Data Business Partner Requirements (Time, Responsiveness) 2 Aspects: Container Security (Time, Availability) 1 Aspect: Procedural Security (Reliability) None: Security Related Certifications 162 E.g. Business partner requirements E.g. Tracking and monitoring E.g. Personnel security and personnel security training E.g. Physical access controls Low Figure 6.1: The route to improving supply chain security. Implementation Complexity The next step would be to establish procedures to ensure personnel security and conduct security training to all personnel. Initiatives such as conducting pre-employment background checks and proper employment termination procedures can be established as a start to ensure personnel security. Once that is done, it is important to permeate the importance of security to the entire organization through training and awareness building. An organization is ultimately about its people. Next, one can look to instituting appropriate technologies that seeks to improve the visibility of one's supply chain operations. Tracking and monitoring types of projects will improve an organization's visibility of its supply chain and thereby allow a more agile response to disruptions. It will also enable an organization to more efficiently and effectively utilise its order fulfilment resources. After taking care of internal security matters, the next step is to bring the overall security effort to other stakeholders in the supply chain. The supply chain is made up of many sequential and simultaneous events/tasks that are necessary to move products from where they originate to where they are desired. And many stakeholders are involved along the way, thereby creating many handoffs and many different ways of doing things. It is therefore of no good for only any one of the components to be secure and the rest not. Similar to the concept where a supply 163 lc+ .;)0 \u00E2\u0080\u00A21io 0\u00E2\u0080\u00B9, co,) do . 43 % / t.9^0^ow^6,/, op ), 1:e.. 1)0, co sco4c\ ;)/ \"t>)^4\u00C2\u00B0 .co )) d' \c\u00E2\u0080\u00A2 ck9 chain is only as efficient as its weakest link, a supply chain is only as secure as it's least secure component. The need for the different stakeholders to collaborate on security efforts thus cannot be over- emphasised. Externally-oriented security initiatives such as instituting business partner requirements and security related requirements can be negotiated and established with business partners to ensure a minimum level of security mechanisms in the supply chain. Organizations in the private sector that were interviewed for this study have echoed the importance of a holistic effort for any security effort to be effective. Last but not least, it is important to bear in mind that security improvements are long term investments and similar to other long term major business endeavours, it is essential to garner top management endorsement for any security efforts. When Evaluating Security Investments, Look to Four Key Components When evaluating security efforts, an organization can look at four key aspects \u00E2\u0080\u0094 Information, Cost, People and Cargo (Figure 6.2) to determine the appropriate KPIs to be used. The set of KPIs that an organization should pick or use to evaluate their security investments and initiatives should include at least one from each of these four areas for comprehensiveness as well as to capture any potential trade-offs. Figure 6.2: Security efforts evaluation framework. 164 Figure 6.2 provides examples of KPIs in each area that organizations can utilize to evaluate their security performance. In terms of information, examples of KPIs to assess the accuracy of information sent and received include (1) number of EDI re-transmissions for shipment manifests and (2) number of re-issued bills-of-lading as a result of errors. Examples of KPIs to assess the reliability of information sent and received such as completeness and consistency in information transmission performance include (1) percentage of EDI re-transmissions and (2) percentage of incomplete bills-of-lading or booking forms received from shippers. In terms of cost, examples of KPIs to assess the total cost of investment include (1) total initial outlay for security equipment and/or headcount, (2) cost of conducting security training and (3) cost of obtaining security certification. Examples of KPIs to assess the costs of errors and re- work include (1) cost per man hour x the number of hours spent on re-working documents or correcting errors and (2) value of lost sales due to overages, shortages and damages. In terms of people, examples of assessing and monitoring the safety performance of operations include (1) number of safety accidents and near incidents and (2) number of illegal and attempted unauthorised entries into restricted areas. Examples of KPIs for assessing the amount and quality of security training programs include (1) personnel average assessment grade for security awareness programs and (2) number of security related training programs. In terms of cargo, examples of KPIs for monitoring cargo thefts and pilferages include (1) the amount and number of cargo thefts and pilferages and (2) the amount and frequency of overages, shortages and damages. The frequency of cargo overages, shortages and damages are good indicators of loop holes in the cargo movement process and indicates the potential for cargo tampering. This study does not endeavour to provide an exhaustive list of KPIs for each of the above categories. This is because the KPIs in each of the above categories will differ between any two organizations. For instance, a KPI for pilferage for an organization handling apparel may not be appropriate or the same for another organization handling precious metals. The organization handling apparel may be interested in capturing and monitoring the number of incidents beyond what is allowed for shrinkage but the organization handling precious metals will want to 165 measure the value of pilferage with no shrinkage amount allowed. Another example, an organization handling chemicals will be interested in the number of spill incidents as an indication of the level of safety in its operations but this will not be relevant for an organization handling fast moving consumer products. Therefore, it is important for an organization endeavouring to use the above framework, to recognise the need to identify KPIs that are relevant to its own business operations. The important thing is to ensure that the set of KPIs should include indicators from each of the four areas. 6.4 Limitations of Study The findings from this study are interesting and are definitely a springboard for further research in the realm of supply chain security management. There are nevertheless some limitations that we have to be cognizant of. Sample Size The sample size for the survey was obtained from the membership databases from CSCMP Canada, China, Hong Kong, Singapore and U.S., the Canadian Transportation & Logistics weekly e-newsletter and the Supply Chain Logistics Council (SCL) Canada. Thus, the results of the study are only generalizable to the extent that these members resemble the population of the maritime supply chain community that is involved in cargo movement between Asia and North America and are knowledgeable about their organization's supply chain management and security management efforts. Considering the sensitivity and complexity of the subject matter, this sample size obtained is considered reasonable. Although sufficient for the analytical techniques used in this study, the sample size can certainly be larger to achieve better model fits and power. The results from this study endeavours to reflect industry opinions, therefore the larger the sample size, the better the results will be able to serve its purpose. Common Method Variance for Factor Analysis Measures of a construct have variance due to the construct being measured as well as variance due to measurement error. This measurement error is made up of two components \u00E2\u0080\u0094 random 166 error and systematic error (the error due to method effect). Measurement error is omnipotent and its confounding influences on research findings cannot be avoided and this study is no exception. The amount of construct, method and random error variance can be estimated for Common Factor method of extraction but not Principal Component method. This is because the Principal Component method derives factors that contain small proportions of unique variance and in some instances, error variances (that include variance due to method and variance due to random error). This is different from the Common Factor method which derives factors based only on common variance (i.e. variance that is shared with all other variables in the analysis). It is recognized that the method effect is present in this study as with any other empirical study. And although not calculated, it is important to note that the method effect does not appear to be an issue in the study. This is because there is not a single factor that accounts for more than 50% of the total variance explained. Figures 5.8 and 5.9 show the scree plots for the SCP and SP factor analyses respectively. The amount of variance explained by the first factor for SCP and SP is 26.80% and 35.96% respectively. Self-Rated Performance In view of the issue of confidentiality that most private organizations have over performance type information and to encourage more responses, self-rated performance data instead of truly objective KPI performance data were asked. The performance data are therefore subjected to the limitation of individual respondent's judgement and interpretation of level of performance. Operational Characteristics Not Covered The survey instrument used in this study has tried to capture as much information as possible about an organization's operational characteristics without compromising the rate of response. There is however some data items that have to left out due to scope limitation and concerns over the negative impact on response rate. These include items that can be used as indicators for an organization's degree of overseas sourcing and the extent of implementation of each security initiatives. The degree of overseas sourcing especially from countries that are generally known to be less secure in terms of cargo movement infrastructure, may impact the degree of importance that 167 organizations place on security management and the types of security efforts that they may undertake and the extent to which they would take them. The extent of the implementation of a security initiative will also affect the amount of impact it will have on security performance and supply chain performance (i.e. collateral benefits). 6.5 Future Research Next, we examine the scope for future research in this topic area. It is hoped that the findings from this study will spark off further quantitative research in this topic area. Below are some potential future research directions. Other Organizational Characteristics Future research efforts in this topic area should include further studies including other potential business factors that can affect security efforts and their impacts on security performance and supply chain performance. These potential business factors can include an organization's extent of overseas sourcing and an organization's corporate culture. Other Trade Routes Different geographical areas create different operating environments that breed different operational practices and behaviours. These factors are expected to produce different attitudes and behaviours towards security management. As such, other trade routes can be studied to identify and understand the differences (if any) in private organizations' opinions and behaviour towards security efforts and performance evaluation. Other Supply Chains This study focused on the stakeholders in the maritime supply chain. 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The study aims to identify the best practices and key performance measurements used in securing the marine container supply chain All information obtained from this interview is regarded as confidential and will be used solely for the purpose of this study only. Your kind cooperation will be highly appreciated. PART A - INTERVIEWEE & ORGANIZATION INFORMATION Date of Interview: Name of Organization: Name of Person Interviewed: Designation & Responsibilities: Al. What is your organization type? A2. What is(are) your organization's main trade route(s)? Tick all that is applicable. ^ Intra Asia (Incl. Indian sub-continent and Australasia) ^ Intra Americas^ ^ Intra Europe ^ Trans Pacific (Asia-North America) ^ Trans Pacific (Asia-South America) ^ Asia Europe (Asia-Europe) ^ Trans Atlantic (North America-Europe) ^ Trans Atlantic (South America-Europe) ^ Asia Middle East/Africa (Asia-ME/Africa) ^ N.A. Middle East/Africa (N.A.-ME/Africa) ^ Europe Middle East/Africa (EU-ME/Africa) ^ Others. Please indicate: ^ Trans Pacific (North America-Asia) ^ Trans Pacific (South America-Asia) ^ Asia Europe (Europe-Asia) ^ Trans Atlantic (Europe-North America) ^ Trans Atlantic (Europe-South America) ^ Asia Middle East/Africa (ME/Africa-Asia) ^ N.A. Middle East/Africa (ME/Africa-N.A.) ^ N.A. Middle East/Africa (ME/Africa-EU.) 179 A3. What is your organization's annual revenue for 2005 (in US$)? ^ less than US$20 million^^ US$500 million to US$1 billion ^ US$20 million to US$100 million^^ more than US$1 billion ^ US$100 million to US$500 million Estimate: ^ A4. How many employees are there in your organization globally? ^ less than 100 ^ ^ 1,000 to 5,000 ^ 100 to 500 ^ more than 5,000 ^ 500 to 1,000 Estimate: ^ A5. What is your scope of control or influence over your supply chain? Aspects of Supply Chain Not Controlled In-house Outsourced Choice of suppliers (i.e. manufacturers) Trucking / other inter-modal move from factory to origin port Warehousing / freight consolidation at origin Customs clearance at origin Choice of port of loading Choice of terminal at origin Choice of carriers (i.e. freight contracts) Choice of port of destination Choice of terminal at destination Customs clearance at destination Warehousing / freight deconsolidation at destination Trucking / other inter-modal move to final destination For Shippers Only A6. Do you see supply chain management as a competitive advantage for your business? ^ Yes ^ No If yes, what is your organization's logistics and supply chain strategy or value proposition? ^ Efficiency / Cost of fulfillment ^ Timeliness of product and service delivery ^ Responsiveness to customer needs (Flexibility) ^ Availability of products and services (e.g. minimum backorders, maximum fill rates) ^ Reliability of operations (e.g. accuracy and recovery from disruptions) ^ Others. Please indicate: If no, what is your organization's value proposition? That is, what (e.g. research and development, marketing) gives your business the competitive edge over your competitors? For Service Providers Only A6.What is your organization's value proposition to your customers? 180 PART B - SUPPLY CHAIN PERFORMANCE Note: Please respond to the following questions based on the scope of the supply chain that your company has control over or assumes responsibility for. This is established in A5. B1.What KPIs does your company use to evaluate the performance of your supply chain operations? And how would you rate your performance in each of them relative to competition? Prompts: E.g., what KPIs do you use to measure performance in terms of efficiency, reliability of service, responsiveness to customers' needs, ensuring availability of products /services and timeliness of product/service delivery? Performance Measurements Rating Efficiency performance ... Poor Excellent 1 2 3 4 5 Poor Excellent I 1 2 3 4 i 5 Timeliness performance ... Poor Excellent 1 1 2 3 4 5 Poor Excellent I 1 2 3 4 I 5 Responsiveness performance ... Poor 1 Excellent 1 2 3 4 I 5 Poor I Excellent 1 2 3 4 i 5 Availability of products & services performance ... Poor 1 Excellent i 1 2 3 4 5 Poor F Excellent I 1 2 3 4 5 Poor Excellent Reliability of operations performance ... I I I I 1 1 2 3 4 5 Poor Excellent 1 2 3 4 5 Note : If you need more space, please do not hesitate to use a separate sheet of paper. B2. Is there an overall measure(s) that you use to measure supply chain performance? ^ Yes ^ No If yes, please indicate what this measure(s) is and how would you rate your performance? If this overall measure has already been identified above, please mark it with \"*\". Overall Supply Chain Performance Measurement Rating Poor I Excellent 1 2 3 4 5 181 PART C \u00E2\u0080\u0094 SUPPLY CHAIN SECURITY PERFORMANCE . Is ensuring security in your supply chain important to you? ^ Extremely important. Go to Question C2.^^ Not so important. Go to Question C2. ^ Very important. Go to Question C2.^^ Not at all. Go to Question C3. ^ Quite important. Go to Question C2. C2. How do you think each of the aspects of supply chain performance contribute to overall supply chain performance? Supply Chain Performance Aspect Not at all Relatively insignificant Not sure Relatively substantial Very substantial Responsiveness/Flexibility Timeliness Efficiency Resiliency/ Availability Reliability Security C3.What KPIs does your company use to evaluate the security performance of your supply chain? And how would you rate your performance in each of them? Performance Measurements Rating Poor Excellent 1 2 3 4 1 5 Note : If you need more space, please do not hesitate to use a separate sheet of paper. C4. Is there an overall measure that you use to measure supply chain security performance? If there is, please indicate what this measure is and how would you rate your performance? ^ Yes ^ No If there is, please indicate what this measure is and how would you rate your performance? If this overall measure has already been identified above, please mark it with \"*\". Overall Security Performance Measurement Rating Poor I Excellent 1 2 3 4 5 PART D \u00E2\u0080\u0094 SUPPLY CHAIN SECURITY INITIATIVES D1 .Has your organization made any investments (past and present) or planning to make investments in security-related initiatives such as applying for CT-PAT certification, deploying tracking systems and more stringent personnel checks and organizational changes etc. to ensure your shipments, personnel and infrastructure are secured? ^ Yes ^ No 182 If yes, what are they? And please indicate if they were made before or after 9/11. B = Before 9/11^A = After 9/11^F = Future Check: 1 very low impact, 3 average impact, 5 very high impact Supply Chain Security Initiatives B A F Impact on Security Performance Impact on Supply Chain Performance 1 2 3 4 5 NA 1 2 3 4 5 NA Business Partner Requirements Such as ... ^ Require certification such as C-TPAT ^ Contractual obligations ^ Audits and compliance manuals for partners ^ Collaboration ^ Partner selection procedures ^ Customer outreach ^ Others: Container/Trailer/ Unit Load Device Security Such as ... ^ Inspections ^ Seals ^ Tracking ^ Inventory/storage practices ^ Others: Conveyance Security Such as ... ^ En-route inspections ^ Parking assignment ^ Monitoring / Security escorts ^ Route design ^ Spot checks ^ Others: 183 Physical Access Controls Such as ... ^ Biometric technology ^ Monitoring access patterns ^ Restricting access to certain areas ^ Multiple check points ^ Visitor pre-clearance ^ Driver waiting area ^ Escalation matrix ^ Others: Personnel Security Such as ... ^ Pre-employment background checks ^ Termination procedures ^ Code of conduct ^ Others: Procedural Security Such as ... ^ Written procedures ^ Measuring and monitoring incidents ^ Protect/control use of company stationery ^ RFID / EDI ^ Staff rotation ^ Others: Security Training Such as ... ^ Awareness ^ Outreach ^ Incentives ^ Incident reporting ^ Others: 184 Physical Security Such as ... ^ Fencing / Gates ^ Security guards and patrol ^ Locking mechanisms ^ Lighting ^ Surveillance ^ Others: IT Security Such as ... ^ Internal access restrictions ^ External access restrictions ^ User / usage policies and procedures ^ Recovery plans ^ Others: If no, please indicate the reason(s) why. D2.How is your ability to secure the supply chain in your part of the process affected by actions of your upstream and downstream supply chain partners? D3. 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AfrAitiq- idltAkW4AMIgli 1411f1V-MIITVY\u00C2\u00B1}iffiiltil-RVIVtinFl=ii[ifri**CT -PATiENI'sittA, 1-11- Vhsg_%-iari r\u00E2\u0080\u00A2 V24IntAtYltiL aft-tfAlgfr.4A -Rfo,^ ANC.P. iiiiAW9J1a#NFIA341\u00C2\u00B1Ailk'WZA911$421041k'Z'4: Pit B = 911$4tZA A = 911 -T4t^F =^1 = ,IR ,J , (11 M/Vrirn1, 3 = ^/VP, 5 = 'fkffsVotiVworq iMiitaWMA B A F n-T-AgliktiVXAM,/ Ilfr\u00CC\u0080J RITIAM3M3s5iM41/L'uffii 1 2 3 4 5 NA 1 2 3 4 5 NA AAHAfffiisTM*^t/ri..- ^ II-1X-*t(nur-PATiE-175 ^ WigSC* ^ *iffil*4*I'F'Rit-WAN417- IFi It ^ HP ^ 4)(4filfffiT1 ^ )'='4gi141 ^ 44th: 0 -ic-VAf*/f 12, u Vi-Mji O3.G.VgA/TiTY, ^ MV3Li- 1F o Itt 190 Itilig--Wait- Of* c^tin.-\u00E2\u0080\u00A2 ^ ilitit=1=1W-ctl ^ lowilwvf ^ raR/igyzIZA ^ i_itt,TMI -R -it / '4tIt'AA ^ At *ffiA1,1.$1.111,A^An... ^ ti4N4R ^ mw,ffimiAa / ;--li,L)..i-' 0 1 1-31V14'AAM D -ih'-k-V-L / 7ti1410.12 ^ __LAIIII-Rfitil 0 At AY: J7^MITI X '' ''IR P'^0... ^ WIII-M14:1 -1,14A o tiLifiMfili-t; ^ RATA% o At fi'FffirrmIX'i-KIMA^0.-. ^ la'irr9f,FM-t; ^ - 4A\"RigEiRt44 ^ RI'\u00C2\u00B1i/1.$0_;q-, r)30,-infliffl ^ RFID / EDI ^ AY., AM o At 191 %11^PO- ci Zig al^N'iJ ^ t tAIMfilif ^ A IftselligrAl(-^0... ^ iNt./11 ^ Ng-KAY:fniMfitiT: o RgafflinfILVI ^ ):IYE ^ ftlas ^ Aft qi-Z13FIffi^tlii--. ^ Pk]SitTIIMPInil ^ ki-M-itTlIORM ^ IfJP/)=1]An*panurf o MV ^ Mt 02.^A^12_^u^> w (Secure as in the probability of your supply chain being compromised in terms of pilferages, thefts, damages, terrorism and other crimes such as smuggling, contraband etc.) A3.On a scale of 1 to 7 where [1=Not Acceptable and 7=Excellent], please rate how well you think 1 2 3 4 5 6 7 your logistics/supply chain operations are performing in the following aspects. 1. Efficiency (including cost of fulfillment, productivity) 1 1 11 2 3 1 4 1 5 1 6 1 7 2. Timeliness of product delivery (including speed and on-time performance) 1 1 1 1 1 1 11 2 3 4 5 6 7 3. Reliability of operations (including accuracy and recovery from disruptions) 1 11 1 1 1 11 2 3 4 5 6 7 4. Availability of products 1 1 1 1 1 1 11 2 3 4 5 6 7 5. Responsiveness to customers' needs (including flexibility and agility) 1 1 1 1 11 2 3 4 5 1 6 1 7 Section B. Organization Profiling B1. To what main industrial sector does your organization belong? (Check all that apply). ^ Buyer (Importer)^ ^ Shipper (Exporter)^^ Others, please specify: ^ 194 B2. What supply chain(s) does your organization belong to? (Check all that apply). ^ Fast Moving Consumer Goods (FMCG) ^ ^ Electronics / High Tech Products^^ Perishables / Food Products ^ Automotive^ ^ Pharmaceuticals ^ ^ Chemicals ^ Heavy Machinery ^ Aerospace ^ Others, please specify: ^ B3. Does your organization handle hazardous cargo? ^ No ^ Yes, what OA B4. Does your organization ship full container loads? ^ No ^ Yes, what B5. What is(are) your organization's main trade route(s)? (Check no more than 3). ^ Intra Asia^ ^ Infra Americas (within N.A. and S.A.)^^ Intra Europe ^ Trans Pacific (Asia 4 N.A.) ^ ^ Trans Pacific (N.A. 4 Asia) ^ Trans Pacific (Asia 4 S.A.) ^ Trans Pacific (S.A. 4 Asia) ^ Asia Europe (Asia 4 Europe) ^ Trans Atlantic (N.A. 4 Europe) ^ Trans Atlantic (S.A. 4 Europe) ^ Asia 4 Middle East/Africa ^ N.A. 4 Middle East/Africa ^ S.A. 4 Middle East/Africa ^ Europe 4 Middle East/Africa ^ Asia Europe (Europe 4 Asia) ^ Trans Atlantic (Europe 4 N.A.) ^ Trans Atlantic (Europe 4 S.A.) ^ Middle East/Africa 4 Asia ^ Middle East/Africa 4 N.A. ^ Middle East/Africa 4 S.A. ^ Middle East/Africa 4 Europe ^ Others. please specify: ^ Legend :^N.A.: North America and Central America (includes Panama and all countries north of Pananma) S.A.: South America (all countries south of Panama) B6. What is your organization's annual revenue for 2005 (in 1_15$)? Please select a range from below. ^ less than US$20 million^ ^ US$500 million to US$1 billion ^ US$20 million to US$100 million^^ more than US$1 billion ^ US$100 million to US$500 million 195 B7. Which of the following supply chain activities do you directly select/make final decisions for? Please indicate \"X\" under \"Make Final Decisions\" column against each activity that you select/make final decision for. Please indicate \"X\" under \"Outsource Final Decision Making\" column against each activity that you do not make final decision for. For those activities that are not applicable to your organization, please indicate \"X\" under the \"Not Applicable\" column. Aspects of Supply Chain Outsource Final Decision Making Make Final Decisions In-house Not Applicable Choice of suppliers (e.g. manufacturers) Trucking or other inter-modal transportation from factory to origin port Warehousing at origin Freight consolidation at origin Customs clearance at origin Cross-border trucking to origin port or final destination (if required) Choice of port of loading Choice of terminal at origin Choice of carriers (i.e. freight contracts) Choice of port of destination Choice of terminal at destination Customs clearance at destination Cross-border trucking from destination port to final destination (if required) Warehousing at destination Freight deconsolidation / break bulk at destination Trucking or other inter-modal transportation to final location at destination 196 B8. If your organization considers supply chain management as part of your business value proposition/competitive advantage, please indicate the strategic importance of the following supply chain drivers for your organization. [1=Not at all Important, 2=Sliohtiv Important, 3=Somewhat Important, 4=Moderatelv Important, 5=Important, 6=Very Important, 7=Extremelv Important]. Supply Chain Drivers Not Important Somewhat Important Very Important 1. Efficiency (including cost of fulfillment, productivity) / 1 1 1 1 1 1 2 3 4 5 6 7 2. Timeliness of product delivery (including speed and on-time performance) 1 1I. I 1 1 1 1 2 3 4 5 6 7 3. Reliability of operations (including accuracy and recovery from disruptions) 1 1 1 1 1 1 I 1 2 3 4 5 6 7 4. Availability of products / 1 1 1 1 1 I 1 2 3 4 5 6 7 5. Responsiveness to customers' needs (including flexibility and agility) 1 1 1 1 1 1 2 3 1 4 5 6 1 7 6. Security 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Section C. Key Performance Indicators (KPIs) Cl. In your opinion, should there be KPIs for security performance/efforts? ^ Yes ^ No ^ Unsure/Undecided C2. Next, using a 3-point scale: fl=lnappropriate, 2=lndifferent/Unsure, 3=Appropriatel, please indicate under the relevant \"Appropriateness\" scales, the degree to which you think that each KPI below is an appropriate indicator for Supply Chain Performance and Security Performance. Key Performance Indicators (KPI) Appropriateness For Supply Chain Performance^For Security Performance Inappropriate^Indifferent^Appropriate^Inappropriate^Indifferent^Appropriate 1.Asset utilization (e.g. production capacity, containers, trucks). I^I^I I1 2 3 1 2 3 2. Results from a random security audit. I I I 1 2 3 1 2 3 3.Operations efficiency (e.g. labour productivity, cases picked per hour). F F I1 2 3 1 2 3 4. Number of security policy violations. I I I I I I 1 2 3 1 2 3 197 Key Performance Indicators (KPI) Appropriateness For Supply Chain Performance^For Security Performance Inappropriate^Indifferent^Appropriate^Inappropriate^Indifferent^Appropriate 5. Level of insurance premiums for cargo and/or operations. 1 1 2 3 1 2 3 6. Level of inventory (in warehouses or in pipeline). I I I 1 2 3 1 2 3 7. Number/frequency of customs inspections. I 1 2 3 1 2 3 8. Logistics costs as a percentage (%) of sales or per product unit. 1 I I I 1 I 1 2 3 1 2 3 9.On-time transmission of shipment information. I 1 2 3 1 2 3 10.Number of unauthorized entry incidents. 1 I I I I 1 2 3 1 2 3 11.Order fulfillment lead times (e.g. order-to-cash cycle time). IF I I I I1 2 3 1 2 3 12.On-time delivery (e.g. % on-time order delivery, information transmission). I1 2 3 1 2 3 13.Length of time to deliver expedited orders. I 1 2 3 1 2 3 14.Customs clearance lead-time (import and/or export). F I I I 1 2 3 1 2 3 15.Accuracy rate of shipment information (e.g. manifest transmission). F f I I1 2 3 1 2 3 16.Number/frequency of service errors and failures. F I I 1- I1 2 3 1 2 3 17.Results from periodic safety audit. 1-1 2 3 1 2 3 18.Accuracy rate of inventory records (e.g. cycle counting variance). I 1 2 3 1 2 3 19.Accuracy rate of invoicing. F I I F I I 1 2 3 1 2 3 20. Number/frequency of pilferage/theft/security incidents. 1 2 3 1 2 3 21.Amount of freight claims and/or freight loss (in monetary terms). F I I 1 2 3 1 2 3 22. Number/frequency of personnel safety accidents. I I I I I I 1 2 3 1 2 3 23. Amount/frequency of overages, shortages and damages (OS&D). F 1 1 I I I 1 2 3 1 2 3 198 Key Performance Indicators (KPI) Appropriateness For Supply Chain Performance^For Security Performance Inappropriate^Indifferent^Appropriate^Inappropriate^Indifferent^Appropriate 24.Amount/frequency of operations deviations (e.g. capacity deviations). I^1^I1^2 3 1 2 3 25.Number/frequency of back orders. I^I I I I I1^2 3 1 2 3 26.Number/frequency of order cancellations/ rejections. I- I I I I1^2 3 1 2 3 27.Average time taken to respond to client problems. I I I1^2 3 1 2 3 28.Average time taken to resolve client problems. I^I I I I I1^2 3 1 2 3 29.Results from customer service satisfaction / feedback survey. I^I I I I I1^2 I^I 3 1 2 3 30.Order fill rate. I I I I1^2 3 1 2 3 31.Number and type of special requests satisfied. I^I I I I I1^2 I-^I 3 I 1 2 3 32.Number and type of customer complaints resolved. I I I1^2 3 1 2 3 33.Others: I I I I1^2 3 1 2 3 34.Others: I1^2 3 1 2 3 35.Others: I^I I I I I1^2 3 1 2 3 Section D. Supply Chain Security Initiatives For each type/group of security initiative below, please indicate whether your organization is currently Implementing / Implemented (I), Planning to implement (P) or Not implementing (N) that initiative. Also, for each initiative currently Implementing / Implemented (I) or Planning to Implement (P), please indicate under \"Impact on Supply Chain Performance\", how the initiative has impacted or will impact your supply chain performance, using a 7-point scale: [1=Extremelv Negative, 2=Very Negative,. 3=Moderatelv Negative, 4=Unsure/Neutral, 5=Moderately Positive, 6=Very Positive s 7=Extremelv Positive). 199 Impact on Supply Chain Performance Security Initiatives Implementation Status a) a)z -o O 2 a) coO is O a) Oa_ a)E\u00C2\u00B02 w I^P N Efficiency: 11 I I I I I1 2 3 4 5 6 7 Timeliness: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Reliability: 1 1 11 1 1 1 1 2 3 4 5 6 7 Availability: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Responsiveness: I I I I I 1 I 1 2 3 4 5 6 7 Security: 1 1 1 11 1 1 1 2 3 4 5 6 7 I^P N Efficiency: 1 1 1 1 1 11 2 3 4 5 1 6 7 Timeliness: 1 1 11 1 1 1 1 2 3 4 5 6 7 Reliability: 1 1 1 11 1 1 1 2 3 4 5 6 7 Availability: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Responsiveness: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Security: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 1. Operations/Security Related Certifications. Internationally recognized certifications for operations excellence including security and risk assessment. Examples:- \u00E2\u0080\u00A2 Customs-Trade Partnership Against Terrorism (C-TPAT) (U.S.). \u00E2\u0080\u00A2 Partners-In-Protection (PIP) (Canada). \u00E2\u0080\u00A2 Secure-Trade-Partnership (STP) (Singapore). \u00E2\u0080\u00A2 Free and Secure Trade (FAST) (U.S. and Canada). \u00E2\u0080\u00A2 Transported Asset Protection Association (TAPA). \u00E2\u0080\u00A2 International Ship and Port Facility Security (ISPS). 2. Advanced Data. Compliance to data submission programs through secure information transmission technology. Examples:- \u00E2\u0080\u00A2 24-hours Advance Manifest Rule & Automated Commercial Environment (ACE) (U.S.). \u00E2\u0080\u00A2 Advanced Commercial Information (ACI) (Canada). \u00E2\u0080\u00A2 Traceable/secure electronic data transmissions. \u00E2\u0080\u00A2 Advanced shipping notices (ASNs). 200 ->a^P 2 0_8 . N^>,. w \u00E2\u0080\u00A2^ 7^N^ 2o I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 F I^I^I^I^I^I 1^2 F^I 1^2 1^2 1^2 Efficiency: Timeliness: Reliability: Availability: Responsiveness: Security: 3^4^5^6^7 I^I^I^I^I 3^4^5^6^7 3^4^5^6^7 1-111111 3^4^5^6^7 Impact on Supply Chain Performance Implementation Security Initiatives^ Status 3. Business Partners Requirements. Working with business partners to ensure security measures are in place and adhered to. Examples:- Towards Manufacturer/Supplier/Vendor \u00E2\u0080\u00A2 Contractual obligations. \u00E2\u0080\u00A2 Factory certification requirements. \u00E2\u0080\u00A2 Supplier code of conduct. Towards Service Provider \u00E2\u0080\u00A2 Representative at overseas office. \u00E2\u0080\u00A2 Prohibit subcontracting. \u00E2\u0080\u00A2 Require background clearances for personnel. \u00E2\u0080\u00A2 Contractual obligations/procedures for selection. Towards Customer \u00E2\u0080\u00A2 Prevent misuse of products through education. \u00E2\u0080\u00A2 Verify business references, credit checks. \u00E2\u0080\u00A2 Establish routine pickup/drop-off points. 4. Security Training & Outreach Programs.^ I P N^Efficiency: I-^1 1^2 Examples:-^ Timeliness: \u00E2\u0080\u00A2 Use alert levels^ 1^2 \u00E2\u0080\u00A2 Communicate terrorism information to employees.^ Reliability:1111111 \u00E2\u0080\u00A2 Periodic training, specialized training in handling breaches,^ 1 conducting investigations, inspections etc.^ Availability:^1 \u00E2\u0080\u00A2 Train business partners.^ 1 \u00E2\u0080\u00A2 Provide incentives for incident reporting. Responsiveness: \u00E2\u0080\u00A2 Collaborate with local law enforcement.^ 1 2^3^4^5^6^7 II^II^I^I 2^3^4^5^6^7 Security: [mill 1^2^3^4^5^6^7 201 I P N 1^1^1^1^1 3^4^5^6^7 1- 111111 3^4^5^6^7 1^1^1^1^1^1 2^3^4^5^6^7 -I Impact on Supply Chain Performance a)co a)al z CU a)CU a) z a) a) Implementation EU) z a) Security Initiatives Status cC.; 02 5. Procedural Security. I^P^N Efficiency: 1 1 1 Incorporate security into business practices through accountability 1 2 3 and a system of checks and balances. Timeliness: 1 1 1 1 2 3 Examples:- Reliability: 1 1 1 Risk Assessment & Incident Management 1 2 3 \u00E2\u0080\u00A2 Establish internal security personnel network Availability: 1 1 1 \u00E2\u0080\u00A2 Establish incident database and procedures to handle suspicious 1 2 3 activities, incident reporting and response. Responsiveness: 1 1 1 \u00E2\u0080\u00A2 Emergency and evacuation plans. 1 2 3 Cargo Handling Security: 1 1 1 \u00E2\u0080\u00A2 Barcode/RFID scanning to detect discrepancies and ensure only manifested cargo is loaded. 1 2 3 \u00E2\u0080\u00A2 Use carton tape imprinted with company's name. \u00E2\u0080\u00A2 Rotate shipping/receiving personnel. 6. Physical Security and Access Control. I^P^N Efficiency: 1 I I Prevent unauthorized entry to facilities, maintain control of personnel 1 2 3 and protect company assets. Timeliness: 1 1 1 1 2 3 Examples:- Reliability: 1 1 1 \u00E2\u0080\u00A2 24-hours security guard and/or police patrol 1 2 3 \u00E2\u0080\u00A2 Fence/gate with magnetic sensors, alarm systems. Availability: 1 1 1 For Employees 1 2 3 \u00E2\u0080\u00A2 Biometric technology, color-coding uniforms. Responsiveness: 1 1 1 \u00E2\u0080\u00A2 Photo ID cards and password controlled locks. 1 2 3 For Visitors & Deliveries/Cargo Pickup (Including Mail) Security: 1 1 1 \u00E2\u0080\u00A2 ID verification and exchange for visitor's badge. 1 2 3 \u00E2\u0080\u00A2 Schedule pickups and establish driver waiting area. \u00E2\u0080\u00A2 Screen/random inspect incoming packages/vehicles. 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 I I 1 4 5 6 7 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 1 1 1 1 4 5 6 7 202 Security Initiatives Implementation Status Impact on Supply Chain Performance a) )^2u)'Ws^ co o) a)^a) oa)^> z CLZ t'73^>,, >.>,^CD CD^Z^a^a)a) a) E^Z^115 1 -3 i';^71 a) o^-ao N2. i 1^> 2 rat^2 I P N I P N 7. Tracking & Monitoring (Conveyance Security). Inspect, secure and track conveyance to ensure mode of transport is not used to facilitate terrorism or illegal acts. Examples:- Trucking/Drayage \u00E2\u0080\u00A2 Monitor \"unusual\" requests and time lags for container turnaround time on premises. \u00E2\u0080\u00A2 Global Positioning System (GPS), truck transponders, online shipment visibility tool, CCTVs. \u00E2\u0080\u00A2 Utilize panic buttons, security escorts/travel in convoys. \u00E2\u0080\u00A2 Designate routes and establish alternate routes \u00E2\u0080\u00A2 Examine fuel consumption to detect route deviations. \u00E2\u0080\u00A2 Staff rotation to prevent internal conspiracies. Ocean Carriers \u00E2\u0080\u00A2 Control use of equipment \u00E2\u0080\u00A2 Satellite monitoring, remote surveillance and detect stowaways 8. Personnel Security. Examples:- \u00E2\u0080\u00A2 Pre-employment background checks. \u00E2\u0080\u00A2 Termination procedures. \u00E2\u0080\u00A2 Employee handbook for internal code of conduct. \u00E2\u0080\u00A2 Employee security awareness training. Efficiency: Timeliness: Reliability: Availability: Responsiveness: Security: Efficiency: Timeliness: Reliability: Availability: Responsiveness: Security: I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I-1 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 I I^I^I^I^I^I 1^2^3^4^5^6^7 203 I I 1 I 1 2 3 4 5 6 1 1 1 1 1 1 1 2 3 4 5 6 1 1 1 1 1 1 1 2 3 4 5 6 1 1 1 1 1 1 1 2 3 4 5 6 1 1 1 1 1 1 1 2 3 4 5 6 1 1 1 1 1 1 1 2 3 4 5 6 I P N Efficiency: Timeliness: Reliability: Availability: Responsiveness: Security: Impact on Supply Chain Performance Security Initiatives Implementation Status a) C) CDz a) 1:1 9. Container/Trailer/Unit Load Device (ULD) Security. Container inspection, storage, tracking, seal control, issuance and verification. Examples:- Trucking/Drayage \u00E2\u0080\u00A2 Exterior inspection, container and seal condition, and seal no. verification and seal issuance controls. \u00E2\u0080\u00A2 Secure empty containers and less-than-truckloads. Ocean Carriers & Container Seals \u00E2\u0080\u00A2 Seals on every container on board and checks at every hand-off. \u00E2\u0080\u00A2 E-seals, other advanced container locking technology. \u00E2\u0080\u00A2 \"Smart Box\" \u00E2\u0080\u0094 container with heavy-duty seal and electronic security device that communicates evidence of tampering, register every legitimate and unauthorized opening of container. 10. Management support and sponsorship. Senior management's involvement in organization's supply chain security program and dedicating necessary resources to the efforts. Examples:- Domestic \u00E2\u0080\u00A2 Establish security committee and conduct periodic briefings \u00E2\u0080\u00A2 Incorporate security into \"Continuous Improvement\" philosophy and mission statement \u00E2\u0080\u00A2 Top management maintains high level of familiarity with overseas business partners, their practices and affiliations and ensures all subsidiaries develop and implement a sound security plan Worldwide \u00E2\u0080\u00A2 Establish security directors and global security council to formulate global security guidelines, methods for assessment I^P N Efficiency: IIIIII 1 2 3 4 5 6 Timeliness: 1 1 1 1 1 1 1 2 3 4 5 6 Reliability: 1 1 1 1 -1 1 2 3 4 5 6 Availability: 1 1 1 1 -1 1 1 2 3 4 5 6 Responsiveness: 1 1 1 1 -I 1 2 3 4 5 6 Security: I I I 1 1 1 1 2 3 4 5 6 I 7 1 7 1 7 1 7 1 7 1 7 7 1 7 7 1 7 7 -I 1 -I 1-1 7 204 Section E. Respondents' Information El. How did you get to know about this survey? ^ Canadian Supply Chain Logistics Association ^ Canadian Transportation Magazine ^ SecuritySurvey2007@freightsecurity.ubc.ca ^ A personal contact ^ Others, please specify: ^ E2. Where is your physical location? ^ Canada^ ^ Singapore ^ China ^ United States of America ^ Hong Kong ^ Others, please specify: ^ E3. What is your title/position in your organization? E4.What is the name of your organization? (Optional). E5.Please indicate the country whose culture influences your business perspectives, thoughts, ideas and opinions the most. E6. If you are interested in receiving an executive summary of the findings, please provide us with your email address below. 205 * SERVICE PROVIDER * ENGLISH VERSION Section A. Self Performance Appraisal Al. For the following survey, are you answering the questions for your entire firm or for your division/strategic business unit? ^ Entire firm^ ^ My division or strategic business unit (SBU) Score / Rating A2.On a scale of 1 to 7 where (1=Not Acceptable and 7=Excellent , please rate how secure you think your supply chain is. (Secure as in the probability of your supply chain being compromised in terms of pilferages, thefts, damages, terrorism and other crimes such as smuggling, contraband etc.) A3.On a scale of 1 to 7 where r1=Not Acceptable and 7=Excellent , please rate how well you think your logistics/supply chain operations are performing in the following aspects. 1.Efficiency (including cost of fulfillment, productivity) 2. Timeliness of product delivery (including speed and on-time performance) 3. Reliability of operations (including accuracy and recovery from disruptions) 4.Availability of products 5. Responsiveness to customers' needs (including flexibility and agility) Section B. Organization Profiling a)_ow 0.^,-a) 0 C.)^o o\u00C2\u00B0^CI) \u00E2\u0080\u00A2 ' ' t)^CL 0 C^775^ ; (^....a 0 7: (1'^ TD `k)z > 0_ u_^> w I I^I^I^I^I^-I 1 2 3 4 5 6 7 1 1 1 1 1 1 1 1 2 3 4 5 6 7 1 1 1 1 1 1 1 1 2 3 4 5 6 7 1 1 1 1 1 1 1 2 3 4 5 6 7 1 1 1 1 1 1 1 1 2 3 4 5 6 7 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Bl. To what main industrial sector does your organization belong? (Check all that apply). ^ Port Authority^ ^ Terminal Operators^ rd Party Logistics Provider ^ Ocean Carrier ^ Customs Broker ^ Customs Authority ^ Trucking / Inter-modal Company^^ Freight Consolidator ^ Freight Forwarder ^ Others, please specify: ^ 206 B2. What industry/sector does your organization serve the most? (Check no more than 3). ^ Fast Moving Consumer Goods (FMCG) ^ ^ Electronics / High Tech Products ^ ^ Perishables / Food Products ^ Automotive^ ^ Pharmaceuticals ^ ^ Chemicals ^ Heavy Machinery ^ Aerospace ^ Others, please specify: ^ B3. Does your organization handle hazardous cargo? ^ No ^ Yes, what B4. Does your organization ship full container loads? ^ No ^ Yes, what B5. What is(are) your organization's main trade route(s)? (Check no more than 3). ^ Intra Asia^ ^ Intra Americas (within N.A. and S.A.) OA Ok ^ Intra Europe ^ Trans Pacific (Asia 4 N.A.) ^ Trans Pacific (Asia 4 S.A.) ^ Asia Europe (Asia 4 Europe) ^ Trans Atlantic (N.A. 4 Europe) ^ Trans Atlantic (S.A. 4 Europe) ^ Asia 4 Middle East/Africa ^ N.A. 4 Middle East/Africa ^ S.A. 4 Middle East/Africa ^ Europe 4 Middle East/Africa ^ Not Applicable ^ Trans Pacific (N.A. 4 Asia) ^ Trans Pacific (S.A. -9 Asia) ^ Asia Europe (Europe 4 Asia) ^ Trans Atlantic (Europe -9 N.A.) ^ Trans Atlantic (Europe 4 S.A.) ^ Middle East/Africa 4 Asia ^ Middle East/Africa 4 N.A. ^ Middle East/Africa 4 S.A. ^ Middle East/Africa 4 Europe ^ Others. please specify: ^ Legend :^N.A.: North America and Central America (includes Panama and all countries north of Pananma) S.A.: South America (all countries south of Panama) 207 B6. What is your organization's annual revenue for 2005 (in US$)? Please select a range from below. ^ less than US$20 million ^ US$20 million to US$100 million ^ US$100 million to US$500 million ^ US$500 million to US$1 billion ^ more than US$1 billion B7. Which of the following supply chain activities do you directly select/make final decisions for? Please indicate \"X\" under the \"Make Final Decisions\" column against each activity that you select/make final decision for. Please indicate \"X\" under \"Outsource Final Decision Making\" column against each activity that you do not make final decision for. For those activities that are not applicable to your organization, please indicate \"X\" under the \"Not Applicable\" column. Aspects of Supply Chain Outsource Final Decision Making Make Final Decisions In-house Not Applicable Trucking or other inter-modal transportation from factory to origin port Warehousing at origin Freight consolidation at origin Customs clearance at origin Cross-border trucking to origin port or final destination (if required) Choice of port of loading Choice of terminal at origin Choice of carriers (i.e. freight contracts) Choice of port of destination Choice of terminal at destination Customs clearance at destination Cross-border trucking from destination port to final destination (if required) Warehousing at destination Freight deconsolidation / break bulk at destination Trucking or other inter-modal transportation to final location at destination 208 B8. If Please indicate the strategic importance of the following supply chain drivers for your organization. (1=Not at all Important, 2=Slightiv Important, 3=Somewhat Important, 4=Moderately Important, 5=Important, 6=Very Important, 7=Extremelv Important]. Supply Chain Drivers Not Important Somewhat Important Very Important 1. Efficiency (including cost of fulfillment, productivity) 1 1 1 1 1 1 2 3 4 5 1 6 1 7 2. Timeliness of product delivery (including speed and on-time performance) / 1 1 1 1 1 1 1 1 2 1 3 1 4 1 5 6 7 3. Reliability of operations (including accuracy and recovery from disruptions) 1 1 1 1 2 3 4 5 6 7 4. Availability of products 1 1 1 1 1 1 -1 1 2 3 4 5 6 7 5. Responsiveness to customers' needs (including flexibility and agility) l\u00E2\u0080\u00A2 1 1 1 1 1 1 1 1 2 1 3 4 1 5 6 7 6. Security 1 1 1 1 1 2 3 4 5 6 7 Section C. Key Performance Indicators (KPIs) Cl. In your opinion, should there be KPIs for security performance/efforts? ^ Yes ^ No ^ Unsure/Undecided C2. Next, using a 3-point scale: 11=Inappropriate, 2=lndifferentlUnsure, 3=Appropriatel, please indicate under the relevant \"Appropriateness\" scales, the degree to which you think that each KPI below is an appropriate indicator for Supply Chain Performance and Security Performance. Appropriateness For Supply Chain Performance^For Security Performance Key Performance Indicators (KPI) 1.Asset utilization (e.g. vessel, containers, trucks). 2. Results from a random security audit. 3. Operations efficiency (e.g. control crane rate, warehouse productivity). 4. Number of security policy violations. Inappropriate Indifferent Appropriate^Inappropriate Indifferent Appropriate I I\u00CC\u0082^I^ F I^I 1^2^3 1^2^3I I^I 1 I^I 1^2^3 1^2^3 I I^I 1- 1^1 1^2^3 1^2^3 F I^I 1^2^3 1^2^3 209 Key Performance Indicators (KPI) 5. Level of insurance premiums for cargo and/or operations. Appropriateness For Supply Chain Performance^For Security Performance Inappropriate^Indifferent^Appropriate^Inappropriate^Indifferent^Appropriate I 1 I 2 I 3 I 1 I 2 -I 3 6. Level of inventory (in warehouses). I I I1 2 3 1 2 3 7. Number/frequency of customs inspections. I 1 2 3 1 2 3 8. Logistics costs as a percentage (%) of sales or per product unit. I I I I I I 1 2 3 1 2 3 9.On-time transmission of shipment information. F I I I i1 2 3 1 2 3 10.Number of unauthorized entry incidents. I I I I I -I1 2 3 1 2 3 11. Service fulfillment lead times (e.g. truck/permit turnaround time). 1 1 -I 1 2 3 1 2 3 12. On-time service delivery (e.g. berth-on-arrival, information transmission). I I I I I 1 2 3 1 2 3 13.Length of time to deliver expedited orders. I I I I I I 1 2 3 1 2 3 14.Customs clearance lead-time (import and/or export). F I I I I I 1 2 3 1 2 3 15.Accuracy rate of shipment information (e.g. manifest transmission). I I I I I 16.Number/frequency of service errors and failures. 1 2 3 1 2 3 i 1 2 3 1 2 3 17.Results from periodic safety audit. I I I F I 1 2 3 1 2 3 18.Accuracy rate of inventory records (e.g. cycle counting variance). I I 1 2 3 1 2 3 19.Accuracy rate of invoicing. F I I F I I 1 2 3 1 2 3 20. Number/frequency of pilferage/theft/security incidents. I. I I 1 2 3 1 2 3 21.Amount of freight claims and/or freight loss (in monetary terms). I I I F I I 1 2 3 1 2 3 22. Number/frequency of personnel safety accidents. I I I I- I I 1 2 3 1 2 3 23. Amount/frequency of overages, shortages and damages (OS&D). I I I 1 2 3 1 2 3 210 Key Performance Indicators (KPI) 24.Amount/frequency of operations deviations (e.g. capacity deviations). Appropriateness For Supply Chain Performance^For Security Performance Inappropriate^Indifferent^Appropriate^Inappropriate^Indifferent^Appropriate 1 2 3 1 2 3 25.Number/frequency of \"back orders\" (e.g. container rolls, delivery delays). 1 2 3 1 2 3 26.Number/frequency of order cancellations/ rejections. 1 2 3 1 2 3 27.Average time taken to respond to client problems. 1 2 3 1 2 3 28.Average time taken to resolve client problems. 1 2 3 1 2 3 29.Results from customer service satisfaction / feedback survey. 1 2 3 1 2 3 30.Order fill rate. I 1 2 3 1 2 3 31.Number and type of special requests satisfied. 1 2 3 1 2 3 32.Number and type of customer complaints resolved. 1 2 3 1 2 3 33.Others: 1 2 3 1 2 3 34.Others: 1 2 3 1 2 3 35.Others: 1 2 3 1 2 3 Section D. Supply Chain Security Initiatives For each type/group of security initiative below, please indicate whether your organization is currently Implementing / Implemented (I), Planning to implement (P) or Not implementing (N) that initiative. Also, for each initiative currently Implementing / Implemented (I) or Planning to Implement (P), please indicate under \"Impact on Supply Chain Performance\", how the initiative has impacted or will impact your supply chain performance, using a 7-point scale: [1=Extremelv Negative, 2=Very Negative, 3=Moderatelv Negative, 4=Unsure/Neutral, 5=Moderatelv Positive, 6=Very Positive,. 7=Extremelv Positivel. 211 da a , Security Initiatives Status z^2 >, a N^Z^UI^y^>, ;2 E 213w r< 2 w Implementation^Impact on Supply Chain Performance I^P N Efficiency: I I I I I I -11 2 3 4 5 6 7 Timeliness: 1111111 1 2 3 4 5 6 7 Reliability: 1111111 1 2 3 4 5 6 7 Availability: 1111111 1 2 3 4 5 6 7 Responsiveness: 1111111 1 2 3 4 5 6 7 Security: 1111111 1 2 3 4 5 6 7 I^P N Efficiency: 1111111 1 2 3 4 5 6 7 Timeliness: 1111111 1 2 3 4 5 6 7 Reliability: 1111111 1 2 3 4 5 6 7 Availability: 1111111 1 2 3 4 5 6 7 Responsiveness: 11111-11 1 2 3 4 5 6 7 Security: 111111-1 1 2 3 4 5 6 7 1. Operations/Security Related Certifications. Internationally recognized certifications for operations excellence including security and risk assessment. Examples:- \u00E2\u0080\u00A2 Customs-Trade Partnership Against Terrorism (C-TPAT) (U.S.). \u00E2\u0080\u00A2 Partners-In-Protection (PIP) (Canada). \u00E2\u0080\u00A2 Secure-Trade-Partnership (STP) (Singapore). \u00E2\u0080\u00A2 Free and Secure Trade (FAST) (U.S. and Canada). \u00E2\u0080\u00A2 Transported Asset Protection Association (TAPA). \u00E2\u0080\u00A2 International Ship and Port Facility Security (ISPS). 2. Advanced Data. Compliance to data submission programs through secure information transmission technology. Examples:- \u00E2\u0080\u00A2 24-hours Advance Manifest Rule & Automated Commercial Environment (ACE) (U.S.). \u00E2\u0080\u00A2 Advanced Commercial Information (ACI) (Canada). \u00E2\u0080\u00A2 Traceable/secure electronic data transmissions. \u00E2\u0080\u00A2 Advanced shipping notices (ASNs). 212 Security Initiatives 3. Business Partners Requirements. Implementation Status Impact on Supply Chain Performance a) ^ a)>^w>^-.= >^a) ,=. al F-- >as a)^al^w iea)^a)^a) )... o^o)a) z^5^a_ a)^0z^i^>,^a) E^a_Z^>,^>>,^0)^a) W c0 >, E^W fZ^..6^a) ^T.^2 fi^EE.,^Z, 6 ^-1:3 = a)^ 0 cn^'V E,1<^>^\u00C2\u00A7^c 0^a)^->('w D^2 >^w Working with business partners to ensure security measures are in place and adhered to. I P N Efficiency: I I12 3 4 I 5 I 6 1 7 Timeliness: I I 1 1 1 I Examples:- 2 3 4 5 6 7 Towards Manufacturer/SupplierNendor Reliability: 1 1 1 1 1 1 \u00E2\u0080\u00A2 Contractual obligations. 2 3 4 5 6 7 \u00E2\u0080\u00A2 Factory certification requirements. Availability: 1 1 1 1 1 1 \u00E2\u0080\u00A2 Supplier code of conduct. 2 3 4 5 6 7 Towards Service Provider Responsiveness: 11 1 I 1 1 \u00E2\u0080\u00A2 Representative at overseas office. 2 3 4 5 6 7 \u00E2\u0080\u00A2 Prohibit subcontracting. Security: 1 1 1 1 1 1 \u00E2\u0080\u00A2 Require background clearances for personnel. 2 3 4 5 6 7 \u00E2\u0080\u00A2 Contractual obligations/procedures for selection. Towards Customer \u00E2\u0080\u00A2 Prevent misuse of products through education. \u00E2\u0080\u00A2 Verify business references, credit checks. \u00E2\u0080\u00A2 Establish routine pickup/drop-off points. 4. Security Training & Outreach Programs. I P N Efficiency: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Examples:- Timeliness: 11 I 1 I 1 1 \u00E2\u0080\u00A2 Use alert levels 1 2 3 4 5 6 7 \u00E2\u0080\u00A2 Communicate terrorism information to employees. Reliability: 11 1 1 1 1 1 \u00E2\u0080\u00A2 Periodic training, specialized training in handling breaches, conducting investigations, inspections etc. Availability: 1 2 3 4 5 6 7 1 1 1 1 1 1 1 \u00E2\u0080\u00A2 Train business partners. 1 2 3 4 5 6 7 \u00E2\u0080\u00A2 Provide incentives for incident reporting. Responsiveness: II I I I I I \u00E2\u0080\u00A2 Collaborate with local law enforcement. 1 2 3 4 5 6 7 Security: 1 11 1 1- 1 1 1 2 3 4 5 6 7 213 214 Implementation Impact on Supply Chain Performance a)a)^..e>^a)> -Csi^ > w1^a w^a)^0a) >^z '5^0_^a)z a) co T z^\u00E2\u0080\u00BA,^le\u00E2\u0080\u00BA,^cs)^cu^...... (7) coG7 E 12 a)z 2 a) 17 2 7 )u - a)0 Pi o Security Initiatives Status w (Cs> o 2 c D o 2 Cs) > 5. Procedural Security. I^P N Efficiency: F111-111 Incorporate security into business practices through accountability 1 2 3 4 5 6 and a system of checks and balances. Timeliness: 1111111 1 2 3 4 5 6 Examples:- Reliability: 1111-111 Risk Assessment & Incident Management 1 2 3 4 5 6 \u00E2\u0080\u00A2 Establish internal security personnel network Availability: 1111111 \u00E2\u0080\u00A2 Establish incident database and procedures to handle suspicious 1 2 3 4 5 6 activities, incident reporting and response. Responsiveness: 1111111 \u00E2\u0080\u00A2 Emergency and evacuation plans. 1 2 3 4 5 6 Cargo Handling Security: 1-111-111 \u00E2\u0080\u00A2 Barcode/RFID scanning to detect discrepancies and ensure only manifested cargo is loaded. 1 2 3 4 5 6 \u00E2\u0080\u00A2 Use carton tape imprinted with company's name. \u00E2\u0080\u00A2 Rotate shipping/receiving personnel. 6. Physical Security and Access Control. I^P N Efficiency: 1111111 Prevent unauthorized entry to facilities, maintain control of personnel 1 2 3 4 5 6 and protect company assets. Timeliness: 111 1 11 1 1 2 3 4 5 6 Examples:- Reliability: 1111111 \u00E2\u0080\u00A2 24-hours security guard and/or police patrol 1 2 3 4 5 6 \u00E2\u0080\u00A2 Fence/gate with magnetic sensors, alarm systems. Availability: 1111111 For Employees 1 2 3 4 5 6 \u00E2\u0080\u00A2 Biometric technology, color-coding uniforms. Responsiveness: 1111111 \u00E2\u0080\u00A2 Photo ID cards and password controlled locks. 1 2 3 4 5 6 For Visitors & Deliveries/Cargo Pickup (Including Mail) Security: 1111111 \u00E2\u0080\u00A2 ID verification and exchange for visitor's badge. 1 2 3 4 5 6 \u00E2\u0080\u00A2 Schedule pickups and establish driver waiting area. \u00E2\u0080\u00A2 Screen/random inspect incoming packages/vehicles. 7 7 7 7 7 7 7 7 7 7 7 7 Implementation^Impact on Supply Chain Performance Security Initiatives Status a)CU z E w CU co z O 2 cp O E w\u00E2\u0080\u00A2 I^P N Efficiency: 1111111 1 2 3 4 5 6 7 Timeliness: 1111111 1 2 3 4 5 6 7 Reliability: 1111111 1 2 3 4 5 6 7 Availability: 1111111 1 2 3 4 5 6 7 Responsiveness: IIIIII 1 2 3 4 5 6 7 Security: 1111111 1 2 3 4 5 6 7 I^P N Efficiency: 1111111 1 2 3 4 5 6 7 Timeliness: 1111111 1 2 3 4 5 6 7 Reliability: 1111111 1 2 3 4 5 6 7 Availability: 1111111 1 2 3 4 5 6 7 Responsiveness: 1111111 1 2 3 4 5 6 7 Security: 1111111 1 2 3 4 5 6 7 7. Tracking & Monitoring (Conveyance Security). Inspect, secure and track conveyance to ensure mode of transport is not used to facilitate terrorism or illegal acts. Examples:- Trucking/Drayage \u00E2\u0080\u00A2 Monitor \"unusual\" requests and time lags for container turnaround time on premises. \u00E2\u0080\u00A2 Global Positioning System (GPS), truck transponders, online shipment visibility tool, CCTVs. \u00E2\u0080\u00A2 Utilize panic buttons, security escorts/travel in convoys. \u00E2\u0080\u00A2 Designate routes and establish alternate routes \u00E2\u0080\u00A2 Examine fuel consumption to detect route deviations. \u00E2\u0080\u00A2 Staff rotation to prevent internal conspiracies. Ocean Carriers \u00E2\u0080\u00A2 Control use of equipment \u00E2\u0080\u00A2 Satellite monitoring, remote surveillance and detect stowaways 8. Personnel Security. Examples:- \u00E2\u0080\u00A2 Pre-employment background checks. \u00E2\u0080\u00A2 Termination procedures. \u00E2\u0080\u00A2 Employee handbook for internal code of conduct. \u00E2\u0080\u00A2 Employee security awareness training. 215 Implementation^Impact on Supply Chain Performance a)a)^> -.0 =.. a 0^ 0) Z >,^ .\u00C2\u00AB.> Z,^CO^CD 7) 2 ZCD 15 a0 2^2,^-0 c%.'Security Initiatives^ Status^ L5 >(T) 0 > O > z cll I^P N Efficiency: I I I I I I I 1 2 3 4 5 6 7 Timeliness: I I I I I I I 1 2 3 4 5 6 7 Reliability: II I I I I 1 1 2 3 4 5 6 7 Availability: I I I I I I -1 1 2 3 4 5 6 7 Responsiveness: 1 II 1 I 1 I 1 2 3 4 5 6 7 Security: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 I^P N Efficiency: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Timeliness: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Reliability: 1 1 1 1 1 1 1 1 2 3 4 5 6 7 Availability: 1 1 11 1 1 1 1 2 3 4 5 6 7 Responsiveness: 11 1 1 1 1 1 2 3 4 5 6 7 Security: 1 11 1 1 1 1 1 2 3 4 5 6 7 9. Container/Trailer/Unit Load Device (ULD) Security. Container inspection, storage, tracking, seal control, issuance and verification. Examples:- Trucking/Drayage \u00E2\u0080\u00A2 Exterior inspection, container and seal condition, and seal no. verification and seal issuance controls. \u00E2\u0080\u00A2 Secure empty containers and less-than-truckloads. Ocean Carriers & Container Seals \u00E2\u0080\u00A2 Seals on every container on board and checks at every hand-off. \u00E2\u0080\u00A2 E-seals, other advanced container locking technology. \u00E2\u0080\u00A2 \"Smart Box\" \u00E2\u0080\u0094 container with heavy-duty seal and electronic security device that communicates evidence of tampering, register every legitimate and unauthorized opening of container. 10. Management support and sponsorship. Senior management's involvement in organization's supply chain security program and dedicating necessary resources to the efforts. Examples:- Domestic \u00E2\u0080\u00A2 Establish security committee and conduct periodic briefings \u00E2\u0080\u00A2 Incorporate security into \"Continuous Improvement\" philosophy and mission statement \u00E2\u0080\u00A2 Top management maintains high level of familiarity with overseas business partners, their practices and affiliations and ensures all subsidiaries develop and implement a sound security plan Worldwide \u00E2\u0080\u00A2 Establish security directors and global security council to formulate global security guidelines, methods for assessment 216 Section E. Respondents' Information El. How did you get to know about this survey? ^ Canadian Supply Chain Logistics Association ^ Canadian Transportation Magazine ^ SecuritySurvey2007@freightsecurity.ubc.ca ^ A personal contact ^ Others, please specify: ^ E2. Where is your physical location? ^ Canada^ ^ Singapore ^ China ^ United States of America ^ Hong Kong ^ Others, please specify: ^ E3. What is your title/position in your organization? E4.What is the name of your organization? (Optional). E5.Please indicate the country whose culture influences your business perspectives, thoughts, ideas and opinions the most. E6. f you are interested in receiving an executive summary of the findings, please provide us with your email address below. 217 *3/ffifA * A. Al. iiiRSAI;t4 -1- t-nTIATIMaiallifg,4? kfAt M.Volk-C)1 MA*Milat *Ik^.t:}}k^117C 1111111 1^2^3^4^5^6^7 A2. -1WHILtilAAlElJtatitigIzflzffilYi*Ntinfeio \"1\" j \"aX\" Ai \"7\" \"Ka\" ]. (Nyzfoigzsul-T-f&iAnt-fusq-Ascag -rnot&vpimm: 1) 'xyA 2) An- 3)Wyl 4) ,t`J.** 5) IVEIXtinitfik. fZ,40 ) [ \"1\" \"tRA\" gl \"7\" \"Ra\" ]o 1. ,, t(t4Vrr%/13R-P4EiXA*) 2. AltnEiVIIIItt^AA) 3. 3.11/Frr9To-a-ft (i .11`fil9ftfrAft, 4. AltfYITIAlt (#1M1411 -1 1AWKAFrl-M4 -1TV-M*) 5. 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PfiAlgElka\u00E2\u0080\u0094t-ffVSAMO4M--1, AlEittPft_LIMEIITOIRitAtto 241 APPENDIX C KPI Definitions LIST OF KPIs AssetUtilize^Asset utilization SecurityAudit Results from a periodic security audit OpsEfficiency^Operations efficiency PolicyViolations Frequency of violations of security policies InsurancePremiums^Insurance premiums InventoryLevel^Level of inventory in warehouse InspectionCost Costs of customs inspections LogCostSavings^Logistics costs savings amount Shipmentlnfo On-time transmission of shipment information UnauthorizedEntry^Frequency of unauthorized entry into restricted areas/zones FulfillmentLT^Fulfillment lead-time OTDelivery On-time delivery ExpeditedOrders^Frequency of expedited orders CustomsLT Customs clearance lead-time InfoAccuracy^Accuracy of information ServiceErrors Frequency of service errors SafetyAudit^Results from periodic safety audit InventoryAccuracy^Accuracy of inventory records InvoiceAccuracy Accuracy of invoices Pilferage^ Pilferage amounts and frequency FreightClaims Amount and frequency of freight claims SafetyAccidents^Frequency of safety related accidents OSD^ Cargo overages, shortages and damages OpsDeviation^Deviation in operations capacity BackOrders Percentage of backorders Cancellations^Percentage of order cancellations ProblemResponse^Problem response lead-time ProblemResolution^Problem resolution lead-time FeedbackSurvey Results from periodic customers' feedback survey FillRate^ Percentage of orders filled on first instance SpecialRequests^Ability to handle customers' special requests Complaints Frequency of customers' complaints 243 APPENDIX D Citations of Studies Used in Determining SCP KPIs Citations of Studies from Keller et al. (2002): Brown, James R., Robert F. Lusch, and Laurie P. Smith (1991), \"Conflict and Satisfaction in an Industrial Channel of Distribution,\" International Journal of Physical Distribution and Logistics Management, Vol. 21, No. 6, pp. 15-26. Crosby, Leon and Stephen A. LeMay (1998), \"Empirical Determination of Shipper Requirements for Motor Carrier Services: SERVQUAL, Direct Questioning, and Policy Capturing Methods,\" Journal of Business Logistics, Vol. 19, No. 1, pp. 139-153. Daugherty, Patricia J., Matthew B. Myers, and Chad W. Autry (1999), \"Automatic Replenishment Programs: An Empirical Examination,\" Journal of Business Logistics, Vol. 20, No. 2, pp. 63-82. Daugherty, Patricia J., Theodore P. Stank, and Alexander E. Ellinger (1998), \"Leveraging Logistics/Distribution Capabilities: The Effect of Logistics Service on Market Share,\" Journal of Business Logistics, Vol. 19, No. 2, pp. 35-51. Emerson, Carol J. and Curtis M. Grimm (1996), \"Logistics and Marketing Components of Customer Service: An Empirical Test of the Mentzer, Gomes, and Krapfel Model,\" International Journal of Physical Distribution and Logistics Management, Vol. 26, No. 8, pp. 29-42. Fawcett, Stanley E., Roger Calantone, and Sheldon R. Smith (1996), \"An Investigation of the Impact of Flexibility on Global Reach and Firm Performance,\" Journal of Business Logistics, Vol. 17, No. 2, pp. 167-196. Fawcett, Stanley E. and Sheldon R. Smith (1995), \"Logistics Management and Performance for United States-Mexican Operations Under NAFTA,\" Transportation Journal, Vol. 34, No. 3, pp. 25-34. Fawcett, Stanley E., Sheldon R. Smith, and M. Bixby Cooper (1997), \"Strategic Intent, Measurement Capability, and Operation of Success: Making the Connection,\" International Journal of Physical Distribution and Logistics Management, Vol. 27, No. 7, pp. 410-421. Gassenheimer, Jule B., Jay U. Sterling, and Robert A. Robicheaux (1989), \"Long-term Channel Member Relationships,\" International Journal of Physical Distribution and Materials Management, Vol. 19, No. 12, pp. 15-28. Goldsby, Thomas J. and Theodore P. Stank (2000), \"World Class Logistics Performance and Environmentally Responsible Logistics Practices,\" Journal of Business Logistics, Vol. 21, No. 2, pp. 187-208. Lambert, Douglas M. and Thomas C. Harrington (1989), \"Establishing Customer Service Strategies Within the Marketing Mix: More Empirical Evidence,\" Journal of Business Logistics, Vol. 10, No. 2, pp. 44-60. Maloni, Michael and W. C. Benton (2000), \"Power Influences in the Supply Chain,\" Journal of Business Logistics, Vol. 22, No. 1, pp. 49-73. 245 Matear, Sheelagh and Richard Gray (1993), \"Factors Influencing Freight Service Choice for Shippers and Freight Suppliers,\" International Journal of Physical Distribution and Logistics Management, Vol. 23, No. 2, pp. 25-35. McGinnis, Michael A. (1979), \"Shipper Attitudes Toward Freight Transportation Choice: A Factor Analytic Study,\" International Journal of Physical Distribution and Materials Management, Vol. 10, No. 1, pp. 25-34. McGinnis, Michael A. (1990), \"The Relevant Importance of Cost and Service in Freight Transportation Choice: Before and After Regulation,\" Transportation Journal, Vol. 30, No. 1, pp. 12-19. McGinnis, M., T. M. Corsi, and M. J. Roberts (1981), \"A Multiple Criteria Analysis of Modal Choice,\" Journal of Business Logistics, Vol. 2, No. 2 McGinnis, Michael A. and Johnathan W. Kohn (1990), \"A Factor Analytical Study of Logistics Strategy,\" Journal of Business Logistics, Vol. 11, No. 2, pp. 41-63. Menon, Mohan K., Michael A. McGinnis, and Kenneth B. Ackerman (1998), \"Selection Criteria for Providers of third-Party Logistics Services: An Exploratory Study,\" Journal of Business Logistics, Vol. 19, No. 1, pp. 121-137. Mentzer, John T., Daniel J. Flint, and John L. Kent (1999), \"Developing a Logistics Service Quality Scale,\" Journal of Business Logistics, Vol. 20, No. 1, pp. 9-32. Mentzer, John T. and Brenda P. Konrad (1991), \"An Efficiency/Effectiveness Approach to Logistics Performance Analysis,\" Journal of Business Logistics, Vol. 12, No. 1, pp. 33-62. Monczka, Robert M., Thomas J. Callahan, and Ernest L. Nichols, Jr. (1995), \"Predictors of Relationships Among Buying and Supplying Firms,\" International Journal of Physical Distribution and Logistics Management, Vol. 25, No. 10, pp. 45-59. Novack, Robert A., Lloyd M. Rinehart, and C. John Langley, Jr. (1994), \"An Internal Assessment of Logistics Value,\" Journal of Business Logistics, Vol. 15, No. 1, pp. 113-152. Pearson, J. N. and J. Semeijn (1999), \"Service Priorities in Small and large Firms Engaged in International Logistics,\" International Journal of Physical Distribution & Logistics Management, Vol. 29, No. 3, pp. 181. Raghunathan, T. S., Prabir K. Bagchi, and Edward J. Bardi (1998), \"Motor Carrier Services: The U.S. Experience,\" International Journal of Physical Distribution and Materials Management, Vol. 18, No. 5, pp. 3-7. Scannell, Thomas V., Shawnee K. Vickery, and Cornelia L. DrOge (2000), \"Upstream Supply Chain Management and Competitive Performance in the Automotive Supply Industry,\" Journal of Business Logistics, Vol. 21, No. 2, pp. 23-48. Semeijn, Jake (1995), \"Service Priorities in International Logistics,\" International Journal of Logistics Management, Vol. 6, No. 1, pp. 27-36. 246 Sharma, Arun and Douglas M. Lambert (1990), \"Segmentation of Markets Based on Customer Service,\" International Journal of Physical Distribution and Logistics Management, Vol. 20, No. 7, pp. 19-27. Stank, Theodore P., Patricia J. Daugherty, and Alexander E. Ellinger (1996), \"Information Exchange, Responsiveness and Logistics Provider Performance,\" International Journal of Logistics Management, Vol. 7, No. 2, pp. 43-57. Stank, Theodore P., Scott B. Keller, and Patricia J. Daugherty (2001), \"Supply Chain Collaboration and Logistical Service Performance,\" Journal of Business Logistics, Vol. 22, No. 1, pp. 29-48. Stank, Theodore P. and Charles W. Lackey, Jr. (1997), \"Enhancing Performance Through Logistical Capabilities in Mexican Maquiladora Firms,\" Journal of Business Logistics, Vol. 18, No. 1, pp. 91-123. Sterling, J. U. and D. M. Lambert (1987), \"Establishing Customer Service Strategies Within the Marketing Mix,\" Journal of Business Logistics, Vol. 8, No. 1, pp. 1. Supply Chain Council (2006), Supply-Chain Operations Reference-model, Version 8.0. Zinn, Walter and Peter C. Liu (2001), \"Consumer Response to Retail Stockouts,\" Journal of Business Logistics, Vol. 22, No. 1, pp. 49-71. Citations of Recent Studies on Supply Chain Security: Banomyong, R. (2005), \"The Impact of Port and Trade Security Initiatives on Maritime Supply- Chain Management,\" Maritime Policy and Management, Vol. 32, No. 1, pp. 3-13. Blake, Marilyn A. (2003), \"Safety: It's No Accident,\" Rural Telecommunications, Vol. 22, No. 3, pp. 52. European Conference of Ministers of Transport (ECMT) (2005), Container Transport Security Across Modes. Koch, R. (2004), \"A Secure Supply Chain Blueprint,\" Unisys White Paper Series. Langhoff, T., N. Pillai, and R. Koch (2005), \"Secure Commerce Roadmap - The Industry's View for Securing Commerce,\" Unisys Technical White Paper Series. Peleg-Gillai, B., G. Bhat, and L. Sept (2006), \"Innovators in Supply Chain Security,\" The Manufacturing Innovation Series, The Manufacturing Institute. Price, W. (2004), \"Reducing the Risk of Terror Events at Seaports,\" Review of Policy Research, Vol. 21, No. 3, pp. 329. Rice, J. B. Jr. and P. W. Spayd (2005), \"Investing in Supply Chain Security: Collateral Benefits,\" IBM Center for the Business of Government, Special Report Series. 247 Sheffi, Y. (2001), \"Supply Chain Management Under the Threat of International Terrorism,\" The International Journal of Logistics Management, Vol. 12, No. 2, pp. 1-11. Willis, H. H. and D. S. Ortiz (2004), \"Evaluating the Security of the Global Containerized Supply Chain,\" RAND Technical Report Series. Wolfe, Michael (2004), \"The Dynamics of Supply Chain Security,\" The Monitor (Center for International Trade and Security (CITS)), Vol. 10, No. 2, pp. 15-20. 248 APPENDIX E Responses Gathered from Field Interviews Variable Company A Company B Company C Company D Company E Company F Company G Location Singapore Singapore Singapore Shanghai Shanghai Shanghai Shanghai Organization Type Terminal Operator Freight Consolidator/ Forwarder 3PL Dealing with / handling customs matters Port Freight Consolidator/ Forwarder 3PL Port Terminal Operator Interviewee's Key Role & Responsibilities Handle container security initiatives, regulations, ITS and commercial services Handle Asia & Middle East operations and security projects Develop & implement security related matters Oversee and manage all import and export activities Lead security solutions (system, manpower and procedures) and investigation Manage personnel and port safety and security department. Vessel security inspection / certification. Security incidents investigation & resolution. Key Trade Routes Asia-Europe Infra Asia Asia-N.America Asia-Europe Intra-Asia US, China and Japan Intra-Asia (60%) Asia-Europe (30%) Asia-N. America (10%) Intra-Asia Asia-Europe Asia-North America Intra-Asia Asia-N.America Intra-Asia Asia-N.America 2006 Annual Revenue (US$) > 1 billion > 1 billion > 1 billion 100 - 500 million > 1 billion Cannot disclose Cannot disclose Global Employee Count > 5,000 500 \u00E2\u0080\u0094 1,000 100 \u00E2\u0080\u0094 500 100 \u00E2\u0080\u0094 500 1,000 \u00E2\u0080\u0094 5,000 > 5,000 500 \u00E2\u0080\u00941,000 Span of Supply Chain Control Narrow Wide Not Applicable Average Wide Narrow Narrow Value Proposition Connectivity Efficiency Timeliness Responsiveness Operations competency People & knowledge Timeliness Integrity Commitment Responsiveness Cannot disclose Network coverage People & knowledge Efficiency Safety and security Service reliability Efficiency (e.g. turnaround time) Trust & integrity Security as a Business Driver? Yes Maybe Yes No Maybe Yes Yes Importance of Security Very Important Very Important Very Important Not so Important Very Important Very Important Very Important 250 Variable Company A Company B Company C Company D Company E Company F Company G SCP KPIs - Efficiency Vessel rate Control crane rate Container utilization Receiving Supplier pricing productivity Space utilisation Picking productivity # moves per man hour - Timeliness Berth on arrival Transit times Document flow Warehouse turnaround time Truck turn time On-time delivery Permit turnaround time On-time delivery Container loading and unloading Berth on arrival On time departure Turnaround time within 24hours - Responsiveness Service failures 24hrs respond guideline # of service failures Compliment- complaint ratio Responsiveness to problems. Ability to propose solutions/ recommendation s # customer complaints -Availability Accommodating volumes during peak season. Order fill rate - Reliability Accuracy of information Claims per PO Post shipment sampling checks Accuracy of paperwork submission # accidents per employee Cycle counting variance Tally checks/ Info accuracies - Document discrepancies Accuracy of loading # of safety incidents SCP Overall Measure Throughput Contribution margin Traders' satisfaction index - - - - Security KPIs # incidents Random audit checks # incidents # personnel trained for security Facility audit results Collateral benefits # of inspections Customs clearance time # thefts / pilferage Amount of damage Security guards performance survey Property/cargo loss # supplier security incompliance Security training attendance. Pilot testing results of technology # of unauthorised personnel # of accidents within port # of complaints from customers Safety audit results from Ministry of Transport. # of incidents / personnel accidents (commented security is part of safety) 251 Variable Company A Company B Company C Company D Company E Company F Company G Current Security Initiatives Certifications with voluntary programs such as C-TPAT. E-seals testing. Biometrics for access control. Transponders for truckers. Drivers ID card. Monitor truck turnaround time. Police patrol. 24hr CCTV monitoring. Pre-employment checks. Fencing / gates / locks. Certifications Biometrics for access control GPS and cell phone communications for truckers. CCTV monitoring. Pre-employment checks. Termination procedures. Fencing / gates / locks. Written procedures. Handbook for vendors and business partners. Personnel security training. Not applicable Insurance purchase. Pre-employment background checks. Security escorts. TAPA certification Instituting security procedures Tracking system Security escorts for certain products Route design Restricting access to certain areas Visitor pre- clearance ISPS certification Access controls for employees and visitors Dedicated trucker waiting area Port entrychecking procedures Own dedicated trucks for draying containers within port area (mention that as long as an initiative is recognised by international standards, the organisation will look into adoption) ISPS certification H986 inspection Scanning 24hr CCTV Police boat patrol Joint security drills and contingency plans with marine police Increase security staff strength ID access card IF cards for all certified container trucks Monitor truck turnaround time within port GPS patrol cars Infra-red fencing Procedures for checking seal # discrepancies Certifying ship supplies suppliers Future Security Initiatives Employee awareness and outreach. Gamma rays inspections E-seals RFID Connect monitoring systems among terminal, port and carrier. Security as a holistic effort? Yes Yes Yes Yes Yes Yes Yes How to influence channel partners in security effort? Engage legislative counterparts. Use security as a competitive edge over competitors. Require certifications from all partners. Train partners for cecomplian . Participate in industry-led security programs. Develop and institutet security programs. Part of basic requirements to do business. Require equivalent certification. Sharing experiences and communicate Employ legal punishment for non-complying shippers. Participate in development of security legislation. Communications and joint programs with carriers Contractual obligations 252 Variable Company H Company I Company J Company K Company L Company M Company N Location Shanghai Shanghai Shanghai Shanghai Shanghai Singapore Singapore Organization Type Freight Consolidator / Forwarder 3PL Shipper Shipper Shipper Shipper Shipper Ocean Carrier Interviewee's Key Role & Responsibilities North China consolidation operations to N.America General manager Export and importmanager Export and import supervisor Vessel President Supply chain manager operations and security Key Trade Routes Asia-N. America Asia-Europe N. America-Asia Asia-N. America (Exports) Intra-Asia (Imports) Asia-N. America Asia-Europe Asia-N. America (majority FOB Shanghai) Europe-Asia N. America-Asia Infra Asia Intra-Asia Asia-N. America Asia-Europe 2006 Annual Revenue (US$) 100 \u00E2\u0080\u0094 500 million > 1 billion 20 \u00E2\u0080\u0094 100 million billion 100 \u00E2\u0080\u0094 500 million 500 million \u00E2\u0080\u0094 1 > 1 billion > 1 billion Global Employee Count 100 - 500 500 \u00E2\u0080\u00941,000 1,000 \u00E2\u0080\u0094 5,000 1,000 \u00E2\u0080\u0094 5,000 100 - 500 > 5,000 > 5,000 Span of Supply Chain Control Wide Wide Average Narrow Wide Average Narrow Value Proposition One-stop shop Skills and knowledge Global network and capabilities Quality Environmentalism Quality Production scale capability and production experience Quality Price Customer service SCM People and knowledge IT system Quality and cost Innovation and scale flexibility SCM Operations reliability Innovation / R&D. IT automation Service reliability Security as a Business Driver? Yes No No No Maybe No Yes Importance of Security Quite Important Very Important Quite Important Quite Important Quite Important Very Important Extremely Important 253 Variable Company H Company I Company J Company K Company L Company M Company N SCP KPIs - Efficiency CBM per headcount Overtime Customer cost savings Production time per piece of apparel Production time per piece of apparel Production throughput Manufacturing defect rate Cycle time of order delivery Container moves per hour Fuel consumption - Timeliness On-time documents pouching / transmission of info / billing Delivery lead times Delive ry precision On-time completion of orders On-time completion of orders Order completion on time Delivery on-time performance (based on schedules) BL timeliness Trans it t ime Vessel turnaround time Depot delay time - Responsiveness Respond to customer enquires within 48 hrs # customer claims Promise to delivery date Respond to customer complaints Respond to customer complaints Responsiveness to customer enquiries Responsiveness to customer enquiries - Availability Capacity planning with carriers Availability of packaging Inventory availabilities such as back orders and order fill rate. Equipment availability Ship stoppage # detentions at port # ship accidents - Reliability AMS accuracy Suppliers exception management Invoicing accuracy Deviation management Quality checks and controls Quality checks and controls Quality checks and controls SCP Overall Measure Contribution margin Customer satisfaction survey Customer satisfaction survey Customer satisfaction survey Business volume growth Customer satisfaction survey Security KPIs Periodic audit results (commented # of pilferage and thefts are too rare to be effective KPIs for security) Periodic operations and safety audit Freight loss / damage (only if cause can be identified) Audit results # safety incidents. Commented that security is similar to safety. Certifications # of accidents / disasters # of thefts # of strikes Freight loss by forwarder # security incidents Vessel security audit results # detentions at port Vessels spot inspection results 254 Variable Company H Company I Company J Company K Company L Company M Company N Current Security Initiatives On-route tracking via GPS/cell Trucker ID checks Monitor truck turnaround time Visitor log/badge Pre-employment checks Written procedures for employees truckers Awareness training Monthly security broadcasts Fencing and locks Security guard patrols Separate parking area for private vehicles Password change every 45 days Virus protection firewall ISPS certification Safety and security procedures for terminals and operations Safer container locks Cargo tracking system GPS equipped local delivery vehicles Employee ID cards Visitor pre- clearance Driver safety measures and practices CCTVs for 24hours monitoring. ID card access. Security checks and inspections for trucks entering factories. Rely on local logistics service providers on security certifications. Safety and fire prevention procedures, awareness training and drills. Basic locks and fencing. ID card access Gate at factory Security guard patrols at factory Basic security for personnel and cargo such as CCTVs, security patrol, ID card access, visitor control log. Internal control procedures such as invoice checks , no lending of export licenses, accounting audits and compliance with government regulations. Commented that measures are more reactive than preventive now due to low frequency of occurrence. Basic company security such as ID card access and employee procedural handbook. Ensure safety standards within company is stricter than international requirements. Background checks on delivery vehicles and drivers but this is more for safety purposes rather than security. C-TPAT, ISPS certification Participation in security initiatives such as CSI, SFI. Survelliance cameras IMO required panic buttons on board all vessels Security SOP Gangway watch Visitor escorts Single entry to vessel at berth Visitor pre- clearance Ensure security certification for chartered ships Automatic Identification System (AIS) on board all vessels Security training Future Security Initiatives Depends on customers' requests but will only comply with reasonable ones Depends on customers' requests but will only comply with reasonable ones Depends on customer requirements 24 hours monitoring Other certification programs and probably RFID Security as a holistic effort? Yes Yes Yes Yes Yes Yes Yes How to influence channel partners in security effort? Formalize as contractual obligations Periodic audits Communications and education to change mindset For suppliers: set up security requirements as pre-requisites to doing business. Communications and cooperation but customers should drive the initiatives. Unless proven measurable impacts, it will be tough for his industry to readily adopt any out of self-interests. Institute security as business requirements Communicate and participate in security activities. 255 Variable Company 0 Company P Company Q Company R Company S Company T Company U Location Singapore Singapore Singapore Vancouver Vancouver Vancouver Vancouver Organization Type Shipper 3PL 3PL Shipper Shipper Terminal Operator Shipper Interviewee's Key Role & Responsibilities Internal Security Consultant Business development and account management - US military supply in Iraq and weaponry reverse logistics Regional Security Manager, Asia Pacific i Logistics Analyst handling import customs operations Marine Transportation Manager + Transportation Analyst VP Operations + Manager, Security and Labour Relations Director - Warehousing + Transportation Analyst Key Trade Routes Intro-Asia Asia-Europe All Asia-N. America Infra N. America Only mail orders are international. N. America-Asia (Japan and China) N. America- Europe (UK) 6 Services: West Coast to Asia Within Canada (65%) USA (20%) Asia (esp China) (15%) 2006 Annual Revenue (US$) > 1 billion > 1 billion 100 - 500 million 100 - 500 million > 1 billion 20 \u00E2\u0080\u0094 100 million > 1 billion Global Employee Count > 5,000 > 5,000 1,000 \u00E2\u0080\u0094 5,000 500 \u00E2\u0080\u0094 1,000 > 5,000 100 \u00E2\u0080\u0094 500 > 5,000 Span of Supply Chain Control Wide Wide Wide Wide Wide Narrow Wide Value Proposition SCM \u00E2\u0080\u0094 Reliability and timeliness Assets Flexibility of service offering Good dollar value for customers SCM \u00E2\u0080\u0094 Timeliness of delivery and reliability of service SCM \u00E2\u0080\u0094 Timeliness and availability of supply Handling capacity Efficiency and customer service SCM \u00E2\u0080\u0094 Timeliness and efficiency of fulfillment Security as a Business Driver? Maybe Yes Yes Not at the moment Not at the moment Not at the moment Not at the moment Importance of Security Very Important Extremely Important Very Important Very Important Very Important Very Important Very Important 256 Variable Company 0 Company P Company Q Company R Company S Company T Company U SCP KPIs - Efficiency Logistics cost per unit Warehouse productivity measures # case pick/ orders/receipts per man hour Fuel consumption Space utilisation Pallet occupancy rate unable to go into specific details Freight cost per unit Mill productivity Container moves per hour Crane control rate Insurance premiums Cost per case handled Cases handled per hour % Overtime vs Regular Time - Timeliness Delivery lead time Delivery on time % On time delivery % Truck turnaround time unable to go into specific details % On-time orders Order cycle time Truck turnaround time Rail dwell time On time arrival of inbound orders/ vessels/ delivery to store - Responsiveness # customer complaints unable to go into specific details Customer satisfaction survey Keep track of occurrence of customers' \"Nos \u00E2\u0080\u009E Personnel customer service - Availability Order fill rate Order fill rate unable to go into specific details Order fill rate Supply rate from mills Manages most out of stock situations as exceptions - Reliability Forecast accuracy Quality control checks Inventory accuracy (cycle counting) unable to go into specific details Claim history Safety statistics Safety statistics such as loss time incident frequency Accuracy of orders received Quality checks SCP Overall Measure Net profit Order fill rate Inventory turns Cost per case / unit handled Security KPIs Losses # of accidents/ security incidents ROI on security investments (return calculated as the potential savings from potential losses) # of truck kidnaps / loss / blowups # of personnel casualties Trade Compliance Staff awareness training OS&D Pilferages/thefts Freight risk assessment -> insurance premiums Customs clearance lead time. Thefts/claims/losses are usually more due to human errors and therefore cannot be used to indicate security. # container crimes # security incidents such as thefts, illegal site entry # inspections by guard force Compliance with security procedures Safety is a good indication of security # & frequency of accidents Safety audit results Loss/damage/theft Claims Shrinkages Insurance premiums 257 Variable Company 0 Company P Company Q Company R Company S Company T Company U Current Security Initiatives Basic security such as CCTVs, security guard patrol, control card access, visitor pre- clearance and visitor pass. C-TPAT compliant Periodic audits Decentralised security department Partner selection procedures Contractual obligations RFID seals GPS trucks US convoy escorts 24hr monitoring at CCTVs Security patrols Security SOPs Personnel crisis training Pre-employment checks Double fencing - with barbed wire Alarm system for break-ins All of the initiatives mentioned in the questionnaire. All gates and access doors to DC are securely locked after hours. All visitors to report to receiving office. All access doors monitored.. Adequate lighting. Alarm system. PIP certification Contractual obligations for truckers to be WCB certified Security procedures Container checking procedures during Survelliance cameras Mandatory visitor pre-clearance Mandatory safety gear and safety officer Fencing and gates ISO 28000 Vessel safety inspection Security declaration by all incoming vessels CCTVs Alarm systems 24/7 guard patrol Mobile patrol Driver ID cards Security procedures Corporate endorsed security manuals Staff awareness training FAST/GPS truckers Container inspections Controlled key access seals Spot checks Track truck turnaround time Gating over weekend/night hrs Mobile security Employee bag check at end of day CCTVs Inventory yard check Vehicle monitoring system - black box Drivers safety training Future Security Initiatives Depends on operating environment, product type and cost is a huge consideration. Mention that cost of basic security can be borne by service provider but beyond that should be the responsibility of the customer. New DC will have fencing, CCTVs, security swipe cards for entry. staff on dutyN allowed to bring in/take out any items. Security procedures Inbound goods inspected and verified against shipping docs. C-TPAT certification by end of the year so depends on what the requirements are. C-.TPAT certification by end of the year so depends on what the requirements are. Security as a holistic effort? Yes Yes Yes Yes Yes Yes Yes How to influence channel partners in security effort? Set up contractual obligations and build relationship building. Education and communications. Higher management involvement Education and communications Join trade associations Obtaining internationally recognized certifications. Education and communications. Really depends on market dynamics. 258 APPENDIX F SPSS Cross Tabulation Results for Attitudes Towards Supply Chain Security Cross-tabulation results for entire sample for security driver ranking with two variables - annual revenue and Firm/SBU. Annual_Revenue * Security_Driver * Firm_or SBU Crosstabulation Firm_ Or_ SBU Security Driver TotalNot Important Moderately Important Very Important Entire Annual_ < 20 mil Count 0 3 11 14 Firm Revenue % within Annual_Revenue .0% 21.4% 78.6% 100.0% 20 mil - 100 mil Count 1 1 15 17 % within Annual_Revenue 5.9% 5.9% 88.2% 100.0% 100 mil - 500 Count 0 3 11 14 mil % within Annual_Revenue .0% 21.4% 78.6% 100.0% 500 mil - 1 bil Count 1 1 5 7 % within Annual_Revenue 14.3% 14.3% 71.4% 100.0% > 1 bil Count 0 5 31 36 % within Annual_Revenue .0% 13.9% 86.1% 100.0% Total Count 2 13 73 88 % within Annual_Revenue 2.3% 14.8% 83.0% 100.0% SBU Annual_ < 20 mil Count 1 0 3 4 Revenue % within Annual_Revenue 25.0% .0% 75.0% 100.0% 20 mil - 100 mil Count 0 0 8 8 % within Annual_Revenue .0% .0% 100.0% 100.0% 100 mil - 500 Count 0 1 16 17 mil % within Annual_Revenue .0% 5.9% 94.1% 100.0% 500 mil - 1 bil Count 0 0 6 6 % within Annual_Revenue .0% .0% 100.0% 100.0% > 1 bil Count 2 5 33 40 % within Annual_Revenue 5.0% 12.5% 82.5% 100.0% Total Count 3 6 66 75 % within Annual_Revenue 4.0% 8.0% 88.0% 100.0% Chi-Square Tests Firm_or_SBU Value df Asymp. Sig. (2-sided) Entire Firm^Pearson Chi-Square 8.921a 8 .349 Likelihood Ratio 7.799 8 .453 Linear-by-Linear Association .154 1 .695 N of Valid Cases 88 SBU^Pearson Chi-Square 8.814b 8 .358 Likelihood Ratio 8.917 8 .349 Linear-by-Linear Association .289 1 .591 N of Valid Cases 75 260 Cross-tabulation results for entire sample for security driver ranking with two variables - annual revenue and respondents' physical location. Annual_Revenue * Security_Driver * Physical_Loc Crosstabulation Physical_ Location Security Driver TotalNot Important Moderately Important Very Important North Annual_ < 20 mil Count 1 2 7 10 America Revenue % within Annual_Revenue 10.0% 20.0% 70.0% 100.0% 20 mil - 100 mil Count 1 0 16 17 % within Annual_Revenue 5.9% .0% 94.1% 100.0% 100 mil - 500 Count 0 1 19 20 mil % within Annual_Revenue .0% 5.0% 95.0% 100.0% 500 mil - 1 bil Count 1 0 5 6 % within Annual_Revenue 16.7% .0% 83.3% 100.0% > 1 bil Count 1 6 40 47 % within Annual_Revenue 2.1% 12.8% 85.1% 100.0% Total Count 4 9 87 100 % within Annual_Revenue 4.0% 9.0% 87.0% 100.0% Asia Annual_ < 20 mil Count 0 0 3 3 Revenue % within Annual_Revenue .0% .0% 100.0% 100.0% 20 mil - 100 mil Count 0 0 3 3 % within Annual_Revenue .0% .0% 100.0% 100.0% 100 mil - 500 Count 0 1 3 4 mil % within Annual_Revenue .0% 25.0% 75.0% 100.0% 500 mil - 1 bil Count 0 0 3 3 % within Annual_Revenue .0% .0% 100.0% 100.0% > 1 bil Count 1 1 10 12 % within Annual_Revenue 8.3% 8.3% 83.3% 100.0% Total Count 1 2 22 25 % within Annual_Revenue 4.0% 8.0% 88.0% 100.0% Chi-Square Tests Physical_Loc Value df Asymp. Sig. (2-sided) Canada^Pearson Chi-Square 9.787a 8 .280 Likelihood Ratio 11.033 8 .200 Linear-by-Linear Association .156 1 .693 N of Valid Cases 100 China^Pearson Chi-Square 3.504b 8 .899 Likelihood Ratio 4.081 8 .850 Linear-by-Linear Association .822 1 .365 N of Valid Cases 25 261 Cross-tabulation results for entire sample for security driver ranking with two variables \u00E2\u0080\u0094 hazardous cargo nature and respondent type. Hazardous * Security_Driver * Respondent_Type Crosstabulation Respondent _Type Security Driver TotalNot Important Moderately Important Very Important Shipper Hazardous No Count 3 8 57 68 % within Hazardous 4.4% 11.8% 83.8% 100.0% Yes Count 0 8 37 45 % within Hazardous .0% 17.8% 82.2% 100.0% Total Count 3 16 94 113 % within Hazardous 2.7% 14.2% 83.2% 100.0% Service Hazardous No Count 1 2 19 22 Provider % within Hazardous 4.5% 9.1% 86.4% 100.0% Yes Count 1 1 26 28 % within Hazardous 3.6% 3.6% 92.9% 100.0% Total Count 2 3 45 50 % within Hazardous 4.0% 6.0% 90.0% 100.0% Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Shipper^Pearson Chi-Square 2.685a 2 .261 Likelihood Ratio 3.733 2 .155 Linear-by-Linear Association .101 1 .751 N of Valid Cases 113 Service Provider^Pearson Chi-Square .712b 2 .700 Likelihood Ratio .711 2 .701 Linear-by-Linear Association .336 1 .562 N of Valid Cases 50 262 Cross-tabulation results for entire sample for security driver ranking with two variables \u00E2\u0080\u0094 hazardous cargo nature and Firm/SBU. Hazardous * Security_Driver * Firm_or SBU Crosstabulation Firm_ or_ SBU Security_ Driver TotalNot Important Moderately Important Very Important Entire Hazardous No Count 2 7 44 53 Firm % within Hazardous 3.8% 13.2% 83.0% 100.0% Yes Count 0 6 29 35 % within Hazardous .0% 17.1% 82.9% 100.0% Total Count 2 13 73 88 % within Hazardous 2.3% 14.8% 83.0% 100.0% SBU Hazardous No Count 2 3 32 37 % within Hazardous 5.4% 8.1% 86.5% 100.0% Yes Count 1 3 34 38 % within Hazardous 2.6% 7.9% 89.5% 100.0% Total Count 3 6 66 75 % within Hazardous 4.0% 8.0% 88.0% 100.0% Chi-Square Tests Firm_or_SBU Value df Asymp. Sig. (2-sided) Entire Firm^Pearson Chi-Square 1.542a 2 .463 Likelihood Ratio 2.246 2 .325 Linear-by-Linear Association .135 1 .713 N of Valid Cases 88 SBU^Pearson Chi-Square .381b 2 .827 Likelihood Ratio .387 2 .824 Linear-by-Linear Association .286 1 .593 N of Valid Cases 75 263 Cross-tabulation results for entire sample for security driver ranking with two variables \u00E2\u0080\u0094 hazardous cargo nature and respondents' physical location. Hazardous * Security_Driver * Physical_Loc Crosstabulation Physical_ Location Security Driver TotalNot Important Moderately Important Very Important North Hazardous No Count 3 5 47 55 America % within Hazardous 5.5% 9.1% 85.5% 100.0% Yes Count 1 4 40 45 % within Hazardous 2.2% 8.9% 88.9% 100.0% Total Count 4 9 87 100 % within Hazardous 4.0% 9.0% 87.0% 100.0% Asia Hazardous No Count 1 0 9 10 % within Hazardous 10.0% .0% 90.0% 100.0% Yes Count 0 2 13 15 % within Hazardous .0% 13.3% 86.7% 100.0% Total Count 1 2 22 25 % within Hazardous 4.0% 8.0% 88.0% 100.0% Chi-Square Tests Physical_Loc Value df Asymp. Sig. (2-sided) Canada^Pearson Chi-Square .681a 2 .711 Likelihood Ratio .720 2 .698 Linear-by-Linear Association .493 1 .483 N of Valid Cases 100 China^Pearson Chi-Square 2.841b 2 .242 Likelihood Ratio 3.883 2 .143 Linear-by-Linear Association .119 1 .730 N of Valid Cases 25 264 Cross-tabulation results for entire sample for security driver ranking with two variables \u00E2\u0080\u0094 shipment size and respondent type. FCL * Security_Driver * Respondent_Type Crosstabulation Respondent _Type Security Driver TotalNot Important Moderately Important Very Important Shipper FCL No Count 1 1 16 18 within FCL 5.6% 5.6% 88.9% 100.0% Yes Count 2 15 78 95 % within FCL 2.1% 15.8% 82.1% 100.0% Total Count 3 16 94 113 within FCL 2.7% 14.2% 83.2% 100.0% Service FCL No Count 0 1 12 13 Provider % within FCL .0% 7.7% 92.3% 100.0% Yes Count 2 2 33 37 % within FCL 5.4% 5.4% 89.2% 100.0% Total Count 2 3 45 50 % within FCL 4.0% 6.0% 90.0% 100.0% Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Shipper^Pearson Chi-Square 1.882a 2 .390 Likelihood Ratio 2.029 2 .363 Linear-by-Linear Association .079 1 .778 N of Valid Cases 113 Service Provider^Pearson Chi-Square .797b 2 .671 Likelihood Ratio 1.294 2 .524 Linear-by-Linear Association .342 1 .559 N of Valid Cases 50 265 Cross-tabulation results for entire sample for security driver ranking with two variables \u00E2\u0080\u0094 shipment size and Firm/SBU. FCL * Security_Driver * Firm_or_SBU Crosstabulation Firm_ Or_ SBU Security Driver TotalNot Important Moderately Important Very Important Entire FCL No Count 1 2 14 17 Firm % within FCL 5.9% 11.8% 82.4% 100.0% Yes Count 1 11 59 71 \u00C2\u00B0A within FCL 1.4% 15.5% 83.1% 100.0% Total Count 2 13 73 88 % within FCL 2.3% 14.8% 83.0% 100.0% SBU FCL No Count 0 0 14 14 % within FCL .0% .0% 100.0% 100.0% Yes Count 3 6 52 61 % within FCL 4.9% 9.8% 85.2% 100.0% Total Count 3 6 66 75 % within FCL 4.0% 8.0% 88.0% 100.0% Chi-Square Tests Firm or SBU Value df Asymp. Sig. (2-sided) Entire Firm^Pearson Chi-Square 1.338a 2 .512 Likelihood Ratio 1.082 2 .582 Linear-by-Linear Association .184 1 .668 N of Valid Cases 88 SBU^Pearson Chi-Square 2.347b 2 .309 Likelihood Ratio 3.992 2 .136 Linear-by-Linear Association 2.028 1 .154 N of Valid Cases 75 266 Cross-tabulation results for entire sample for security driver ranking with two variables \u00E2\u0080\u0094 shipment size and respondents' physical location. FCL * Security_Driver * Physical_Loc Crosstabulation Physical_ Location Security Driver TotalNot Important Moderately Important Very Important North FCL No Count 1 2 19 22 America % within FCL 4.5% 9.1% 86.4% 100.0% Yes Count 3 7 68 78 % within FCL 3.8% 9.0% 87.2% 100.0% Total Count 4 9 87 100 % within FCL 4.0% 9.0% 87.0% 100.0% Asia FCL No Count 0 0 2 2 % within FCL .0% .0% 100.0% 100.0% Yes Count 1 2 20 23 % within FCL 4.3% 8.7% 87.0% 100.0% Total Count 1 2 22 25 % within FCL 4.0% 8.0% 88.0% 100.0% Chi-Square Tests Physical Loc Value df Asymp. Sig. (2-sided) Canada^Pearson Chi-Square .023a 2 .989 Likelihood Ratio .022 2 .989 Linear-by-Linear Association .018 1 .894 N of Valid Cases 100 China^Pearson Chi-Square .296b 2 .862 Likelihood Ratio .534 2 .765 Linear-by-Linear Association .249 1 .618 N of Valid Cases 25 267 APPENDIX G SPSS Cross Tabulation Results for Security Initiatives Cross-tabulation results for entire sample with two variables. Security/Operations Related Certifications Crosstab Security Performance Binned) TotalLow Average High Certification^Not Implemented^Count 0 30 3 33 % within Certification .0% 90.9% 9.1% 100.0% Implemented^Count 2 48 30 80 % within Certification 2.5% 60.0% 37.5% 100.0% Total^ Count 2 78 33 113 % within Certification 1.8% 69.0% 29.2% 100.0% Chi -Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 10.515a 2 .005 Likelihood Ratio 12.450 2 .002 Linear-by-Linear Association 6.629 1 .010 N of Valid Cases 113 Business Partner Requirements Crossta b Security Performance (Binned) TotalLow Average High Partner_Requirements^Not Implemented^Count 1 30 4 35 % within Partner_ Requirements 2.9% 85.7% 11.4% 100.0% Implemented^Count 1 48 29 78 % within Partner_ Requirements 1.3% 61.5% 37.2% 100.0% Total^ Count 2 78 33 113 % within Partner Requirements 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 7.870a 2 .020 Likelihood Ratio 8.781 2 .012 Linear-by-Linear Association 7.626 1 .006 N of Valid Cases 113 269 Container/Trailer/Unit Load Device Security Crosstab Security_Performance_ Binned) TotalLow Average High Container_Security^Not Implemented^Count 1 29 5 35 % within Container_Security 2.9% 82.9% 14.3% 100.0% Implemented^Count 1 49 28 78 % within Container Security 1.3% 62.8% 35.9% 100.0% Total^ Count 2 78 33 113 % within Container Security 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 5.608a 2 .061 Likelihood Ratio 6.079 2 .048 Linear-by-Linear Association 5.490 1 .019 N of Valid Cases 113 Advanced Data Crosstab Security Performance (Binned) TotalLow Average High Advanced_Data^Not Implemented^Count 0 41 3 44 % within Advanced_Data .0% 93.2% 6.8% 100.0% Implemented^Count 2 37 30 69 % within Advanced_Data 2.9% 53.6% 43.5% 100.0% Total^ Count 2 78 33 113 % within Advanced_Data 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 19.731a 2 .000 Likelihood Ratio 23.043 2 .000 Linear-by-Linear Association 12.945 1 .000 N of Valid Cases 113 270 Physical Access and Control Crosstab Security Performance ABinned) I^High TotalLow Average Physical_Security^Not Implemented^Count 1 34 3 38 % within Physical_Security 2.6% 89.5% 7.9% 100.0% Implemented^Count 1 44 30 75 % within Physical_Security 1.3% 58.7% 40.0\u00C2\u00B0/0 100.0% Total^ Count 2 78 33 113 % within Physical_Security 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 12.610a 2 .002 Likelihood Ratio 14.586 2 .001 Linear-by-Linear Association 11.896 1 .001 N of Valid Cases 113 Procedural Security Crosstab Security_ Performance (Binned) TotalLow Average High Procedure^Not Implemented^Count 1 18 3 22 % within Procedure 4.5% 81.8% 13.6% 100.0% Implemented^Count 1 60 30 91 % within Procedure 1.1% 65.9% 33.0% 100.0% Total^ Count 2 78 33 113 % within Procedure 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 4.104a 2 .129 Likelihood Ratio 4.257 2 .119 Linear-by-Linear Association 3.885 1 .049 N of Valid Cases 113 271 Tracking and Monitoring Crosstab Security Performance (Binned) TotalLow Average High Tracking^Not Implemented^Count 1 52 15 68 % within Tracking 1.5% 76.5% 22.1% 100.0% Implemented^Count 1 26 18 45 within Tracking 2.2% 57.8% 40.0% 100.0% Total^ Count 2 78 33 113 % within Tracking 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 4.442a 2 .109 Likelihood Ratio 4.394 2 .111 Linear-by-Linear Association 3.382 1 .066 N of Valid Cases 113 Security Training Crosstab Security Performance (Binned) TotalLow Average High Training^Not Implemented^Count 1 7 1 9 % within Training 11.1% 77.8% 11.1% 100.0% Implemented^Count 1 71 32 104 within Training 1.0% 68.3% 30.8% 100.0% Total^ Count 2 78 33 113 % within Training 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 6.026a 2 .049 Likelihood Ratio 3.968 2 .138 Linear-by-Linear Association 3.111 1 .078 N of Valid Cases 113 272 Personnel Security Crosstab Security Performance (Binned) TotalLow Average High Personnel_Security^Not Implemented^Count 1 33 2 36 % within Personnel_ Security 2.8% 91.7% 5.6% 100.0% Implemented^Count 1 45 31 77 % within Personnel_ Security 1.3% 58.4% 40.3% 100.0% Total^ Count 2 78 33 113 % within Personnel_ Security 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 14.343a 2 .001 Likelihood Ratio 17.291 2 .000 Linear-by-Linear Association 13.576 1 .000 N of Valid Cases 113 Management Support Crosstab Security Performance (Binned) TotalLow Average High Mgt_Support^Not Implemented^Count 1 44 8 53 % within Mgt_Support 1.9% 83.0% 15.1% 100.0% Implemented^Count 1 34 25 60 % within Mgt_Support 1.7% 56.7% 41.7% 100.0% Total^ Count 2 78 33 113 % within Mgt_Support 1.8% 69.0% 29.2% 100.0% Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 9.643a 2 .008 Likelihood Ratio 10.045 2 .007 Linear-by-Linear Association 8.539 1 .003 N of Valid Cases 113 273 Cross-tabulation results for Shipper and Service Provider with three variables. Security/Operations Related Certifications Crosstab Respondent Type Security Performance (Binned) TotalLow Average High Shipper Certification Not Implemented Count 0 19 1 20 % within Certification .0% 95.0% 5.0% 100.0% Implemented Count 2 33 17 52 % within Certification 3.8% 63.5% 32.7% 100.0% Total Count 2 52 18 72 % within Certification 2.8% 72.2% 25.0% 100.0% Service Provider Certification Not Implemented Count 11 2 13 % within Certification 84.6% 15.4% 100.0% Implemented Count 15 13 28 % within Certification 53.6% 46.4% 100.0% Total Count 26 15 41 % within Certification 63.4% 36.6% 100.0% Chi-Square Tests Respondent Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 7.189b 2 .027 Likelihood Ratio 9.086 2 .011 Linear-by-Linear Association 3.546 1 .060 N of Valid Cases 72 Service Provider^Pearson Chi-Square 3.688c 1 .055 Continuity Correction3 2.471 1 .116 Likelihood Ratio 4.015 1 .045 Fisher's Exact Test .084 .055 Linear-by-Linear Association 3.598 1 .058 N of Valid Cases 41 Business Partner Requirements Crosstab Respondent_Type Security Performance (Binned) TotalLow Average High Shipper Partner Requirements Not Implemented Count 1 24 2 27 % within Partner_ Requirements 3.7% 88.9% 7.4% 100.0% Implemented Count 1 28 16 45 % within Partner_ Requirements 2.2% 62.2% 35.6% 100.0% Total Count 2 52 18 72 % within Partner_ Requirements 2.8% 72.2% 25.0% 100.0% Service Provider Partner Requirements Not Implemented Count 6 2 8 % within Partner_ Requirements 75.0% 25.0% 100.0% Implemented Count 20 13 33 % within Partner_ Requirements 60.6% 39.4% 100.0% Total Count 26 15 41 % within Partner_ Requirements 63.4% 36.6% 100.0% 274 Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 7.143b 2 .028 Likelihood Ratio 8.155 2 .017 Linear-by-Linear Association 6.396 1 .011 N of Valid Cases 72 Service Provider^Pearson Chi-Square .575c 1 .448 Continuity CorrectiorP .122 1 .727 Likelihood Ratio .601 1 .438 Fisher's Exact Test .687 .373 Linear-by-Linear Association 561 1 .454 N of Valid Cases 41 Container/Trailer/Unit Load Device Security Crosstab Respondent Type Security Performance (Binned) 111^High TotalLow Average Shipper Container_Security Not Implemented Count 1 20 2 23 % within Container Security 4.3% 87.0% 8.7% 100.0% Implemented Count 1 32 16 49 % within Container_Security 2.0% 65.3% 32.7% 100.0% Total Count 2 52 18 72 % within Container Security 2.8% 72.2% 25.0% 100.0% Service Provider Container Security Not Implemented Count 9 3 12 % within Container Security 75.0% 100.0%25.0% Implemented Count 17 12 29 % within Container_Security 58.6% 100.0%41.4% Total Count 26 15 41 % within Container_Security 63.4% 100.0%36.6% Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 4.909b 2 .086 Likelihood Ratio 5.585 2 .061 Linear-by-Linear Association 4.662 1 .031 N of Valid Cases 72 Service Provider^Pearson Chi-Square .981c 1 .322 Continuity CorrectiorP .402 1 .526 Likelihood Ratio 1.018 1 .313 Fisher's Exact Test .480 .266 Linear-by-Linear Association . 958 1 .328 N of Valid Cases 41 275 Advanced Data Crosstab Respondent_ Type Security Performance (Binned) TotalLow Average High Shipper Advanced_Data Not Implemented Count 0 29 3 32 % within Advanced_Data .0% 90.6% 9.4% 100.0% Implemented Count 2 23 15 40 % within Advanced_Data 5.0% 57.5% 37.5% 100.0% Total Count 2 52 18 72 % within Advanced_Data 2.8% 72.2% 25.0% 100.0% Service Provider Advanced_Data Not Implemented Count 12 0 12 % within Advanced_Data 100.0% .0% 100.0% Implemented Count 14 15 29 % within Advanced_Data 48.3% 51.7% 100.0% Total Count 26 15 41 % within Advanced_Data 63.4% 36.6% 100.0% Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 9.926\u00C2\u00B0 2 .007 Likelihood Ratio 11.309 2 .004 Linear-by-Linear Association 4.105 1 .043 N of Valid Cases 72 Service Provider^Pearson Chi-Square 9.788c 1 .002 Continuity Correctiona 7.685 1 .006 Likelihood Ratio 13.682 1 .000 Fishers Exact Test .001 .001 Linear-by-Linear Association 9.549 1 .002 N of Valid Cases 41 Physical Access and Control Crosstab Respondent_Type Security Performance (Binned) TotalLow Average High Shipper Physical_Security Not Implemented Count 1 24 2 27 % within Physical_Security 3.7% 88.9% 7.4% 100.0% Implemented Count 1 28 16 45 % within Physical_Security 2.2% 62.2% 35.6% 100.0% Total Count 2 52 18 72 % within Physical_Security 2.8% 72.2% 25.0% 100.0% Service Provider Physical_Security Not Implemented Count 10 1 11 % within Physical_Security 90.9% 100.0%9.1% Implemented Count 16 14 30 % within Physical_Security 53.3% 46.7% 100.0% Total Count 26 15 41 % within Physical_Security 63.4% 36.6% 100.0% 276 Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 7.143b 2 .028 Likelihood Ratio 8.155 2 .017 Linear-by-Linear Association 6.396 1 .011 N of Valid Cases 72 Service Provider^Pearson Chi-Square 4.898 1 .027 Continuity Corrections 3.413 1 .065 Likelihood Ratio 5.693 1 .017 Fisher's Exact Test .033 .028 Linear-by-Linear Association 4.779 1 .029 N of Valid Cases 41 Procedural Security Crosstab Respondent_Type Security Performance (Binned) TotalLow Average High Shipper Procedure Not Implemented Count 1 14 1 16 % within Procedure 6.3% 87.5% 6.3% 100.0% Implemented Count 1 38 17 56 % within Procedure 1.8% 67.9% 30.4% 100.0% Total Count 2 52 18 72 % within Procedure 2.8% 72.2% 25.0% 100.0% Service Provider Procedure Not Implemented Count 4 2 6 % within Procedure 66.7% 33.3% 100.0% Implemented Count 22 13 35 % within Procedure 62.9% 37.1% 100.0% Total Count 26 15 41 % within Procedure 63.4% 36.6% 100.0% Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. 11-sided) Shipper^Pearson Chi-Square 4A51b 2 .108 Likelihood Ratio 5.202 2 .074 Linear-by-Linear Association 4.386 1 .036 N of Valid Cases 72 Service Provider^Pearson Chi-Square .032' 1 .858 Continuity Corrections .000 1 1.000 Likelihood Ratio .032 1 .857 Fisher's Exact Test 1.000 .620 Linear-by-Linear Association .031 1 .860 N of Valid Cases 41 277 Tracking and Monitoring Crosstab Respondent Type Security Performance (Binned) TotalLow Average High Shipper Tracking Not Implemented Count 1 39 9 49 % within Tracking 2.0% 79.6% 18.4% 100.0% Implemented Count 1 13 9 23 % within Tracking 4.3% 56.5% 39.1% 100.0% Total Count 2 52 18 72 % within Tracking 2.8% 72.2% 25.0% 100.0% Service Provider Tracking Not Implemented Count 13 6 19 % within Tracking 68.4% 31.6% 100.0% Implemented Count 13 9 22 % within Tracking 59.1% 40.9% 100.0% Total Count 26 15 41 % within Tracking 63.4% 36.6% 100.0% Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 4.153b 2 .125 Likelihood Ratio 4.000 2 .135 Linear-by-Linear Association 2.302 1 .129 N of Valid Cases 72 Service Provider^Pearson Chi-Square .383c 1 .536 Continuity Correctiona .086 1 .769 Likelihood Ratio .384 1 .535 Fisher's Exact Test .746 .386 Linear-by-Linear Association 373 1 .541 N of Valid Cases 41 Security Training Crosstab Respondent_Type Security Performance (Binned) TotalLow Average High Shipper Training Not Implemented Count 1 4 1 6 % within Training 16.7% 66.7% 16.7% 100.0% Implemented Count 1 48 17 66 % within Training 1.5% 72.7% 25.8% 100.0% Total Count 2 52 18 72 % within Training 2.8% 72.2% 25.0% 100.0% Service Provider Training Not Implemented Count 3 0 3 % within Training 100.0% .0% 100.0% Implemented Count 23 15 38 % within Training 60.5% 39.5% 100.0% Total Count 26 15 41 % within Training 63.4% 36.6% 100.0% 278 Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 4.755b 2 .093 Likelihood Ratio 2.604 2 .272 Linear-by-Linear Association 1.396 1 .237 N of Valid Cases 72 Service Provider^Pearson Chi-Square 1.867c 1 .172 Continuity Correctiona .554 1 .457 Likelihood Ratio 2.868 1 .090 Fisher's Exact Test .287 .244 Linear-by-Linear Association 1.822 1 .177 N of Valid Cases 41 Personnel Security Crosstab Respondent Type Security Performance (Binned) TotalLow Average High Shipper Personnel_Security Not Implemented Count 1 25 0 26 % within Personnel_ Security 3.8% 96.2% .0% 100.0% Implemented Count 1 27 18 46 % within Personnel_ Security 2.2% 58.7% 39.1% 100.0% Total Count 2 52 18 72 % within Personnel_ Security 2.8% 72.2% 25.0% 100.0% Service Provider Personnel_Security Not Implemented Count 8 2 10 % within Personnel_ Security 80.0% 20.0% 100.0% Implemented Count 18 13 31 % within Personnel_ Security 58.1% 41.9% 100.0% Total Count 26 15 41 % within Personnel_ Security 63.4% 36.6% 100.0% Chi-Square Tests Respondent Type Value df Asymp. Sig. 12-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 13.568b 2 .001 Likelihood Ratio 19.401 2 .000 Linear-by-Linear Association 11.940 1 .001 N of Valid Cases 72 Service Provider^Pearson Chi-Square 1.568c 1 .210 Continuity Correctiori3 .765 1 .382 Likelihood Ratio 1.677 1 .195 Fisher's Exact Test .277 .193 Linear-by-Linear Association 1.530 1 .216 N of Valid Cases 41 279 Management Support and Sponsorship Crosstab Respondent_Type Security Performance (Binned) TotalLow Average High Shipper Mgt_Support Not Implemented Count 1 31 5 37 % within Mgt_Support 2.7% 83.8% 13.5% 100.0% Implemented Count 1 21 13 35 % within Mgt_Support 2.9% 60.0% 37.1% 100.0% Total Count 2 52 18 72 within Mgt_Support 2.8% 72.2% 25.0% 100.0% Service Provider Mgt_Support Not Implemented Count 13 3 16 % within Mgt_Support 81.3% 18.8% 100.0% Implemented Count 13 12 25 % within Mgt_Support 52.0% 48.0% 100.0% Total Count 26 15 41 % within Mgt_Support 63.4% 36.6% 100.0% Chi-Square Tests Respondent_Type Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Shipper^Pearson Chi-Square 5.427b 2 .066 Likelihood Ratio 5.563 2 .062 Linear-by-Linear Association 4.279 1 .039 N of Valid Cases 72 Service Provider^Pearson Chi-Square 3.598C 1 .058 Continuity Correctiorfa 2.447 1 .118 Likelihood Ratio 3.791 1 .052 Fisher's Exact Test .097 .057 Linear-by-Linear Association 3.510 1 .061 N of Valid Cases 41 280 APPENDIX H Behavioral Research Ethics Board Approval Certificate The University of British Columbia Office of Research Services Behavioural Research Ethics Board Suite 102, 6190 Agronomy Road, Vancouver, B.C. V6T 1Z3 CERTIFICATE OF APPROVAL - MINIMAL RISK PRINCIPAL INVESTIGATOR: Garland Chow INSTITUTION / DEPARTMENT: UBC/Sauder School of Business UBC BREB NUMBER: H07-01313 INSTITUTION(S) WHERE RESEARCH WILL. BE CARRIED OUT: I^ institution^ I^ Sit. UBC Vancouver (excludes UBC Hospital) Other locations where the research will be conducted: field surveys at respondents premises or web surveys CO-INVESTIGATOR(S): Wal Leng Lake SPONSORING AGENCIES: TranAport Canada PROJECT TITLE: Simulation Model of Container Transport Security for the Vancouver Gateway (Approval of the pilot project for Kelly Loke's MSc thesis) CERTIFICATE EXPIRY DATE: April 17, 2009 DOCUMENTS INCLUDED IN THIS APPROVAL: DATE APPROVED: April 17, 2008 Document Name^ I^Version^I Date Questionnaire, Questionnaire Cover Letter. Tests: N/A^April 15, 2008 N/A April 15, 2008 N/A^April 15, 2008 N/A April 15, 2008 N/A^April 15, 2008 Field survey shippers Field interview service providers web survey service providers web survey shippers Letter of Initial Contact: Letter to potential respondents The application for ethical review and the document(s) listed above have been reviewed and the procedures were found to be acceptable on ethical grounds for research involving human subjects. Approval is issued on behalf of the Behavioural Research Ethics Board and signed electronically by one of the following: Dr. M. Judith Lynam. Chair^. Dr. Ken Craig, Chair Dr. Jim Rupert, Associate Chair Dr. Laurie Ford, Associate Chair Dr. Daniel Salhanl. Associate Chair Dr. Anita Ho. Associate Chair 282"@en . "Thesis/Dissertation"@en . "2008-05"@en . "10.14288/1.0066712"@en . "eng"@en . "Business Administration - Transportation and Logistics"@en . "Vancouver : University of British Columbia Library"@en . "University of British Columbia"@en . "Attribution-NonCommercial-NoDerivatives 4.0 International"@en . "http://creativecommons.org/licenses/by-nc-nd/4.0/"@en . "Graduate"@en . "An evaluation of the value of security in the international marine supply chain"@en . "Text"@en . "http://hdl.handle.net/2429/2519"@en .