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The adoption of internet banking : a model of decision factors 1999

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THE ADOPTION OF INTERNET B A N K I N G : A M O D E L OF DECISION FACTORS by STAN C H A N Diploma of Business Administration, Hong Kong Shue Yan College, 1988 M B A , The University of Central Oklahoma, 1990 A THESIS SUBMITTED IN PARTIAL F U L F I L M E N T OF THE REQUIREMENTS FOR THE D E G R E E OF M A S T E R OF SCIENCE in THE FACULTY OF GRADUATE STUDIES THE F A C U L T Y OF C O M M E R C E A N D BUSINESS ADMINISTRATION DIVISION OF M A N A G E M E N T INFORMATION SYSTEMS We accept this thesi^as conforming to the required stjandard THE UNIVERSITY OF BRITISH C O L U M B I A August 1999 ©Stan Chan, 1999 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Faculty of Commerce and Business Administration Division of Management Information Systems The University of British Columbia Vancouver, Canada Abstract This paper tests a model of Internet banking adoption, giving insight into issues that banks consider when adopting the Internet as a delivery channel. It also reveals how a bank's perception of these issues is related to the intent to adopt. The study has two parts. The qualitative study involved literature review and interviews with bank executives, leading to the identification of several potential decision factors and the formation o f a tentative adoption model. The quantitative research validated the proposed model by conducting a comprehensive survey targeted at senior bank executives in North America. The result has shown that the adoption decision was mainly determined by various issues such as strategic motivation, the perceived value o f Internet banking, customer demand, environmental influences, and operational context. However, only a few of them are able to discriminate the level o f adoption intent among banks. Keywords: Adoption of IT, Internet Banking, Decision Model , Empirical Study, Literature Review, Theory of Planned Behavior, Factor Analysis, Discriminant Analysis. u Table of Contents Abs t rac t i i L i s t o f Tab les v L i s t o f F igures v i L i s t o f A p p e n d i c e s v i i A c k n o w l e d g m e n t s v i i i Sec t ion 1 Int roduct ion: Strategic U s e o f IT i n B a n k i n g 1 Sec t ion 2 Strategic Imp l i ca t ions o f the Internet to B a n k i n g 1 Sec t ion 3 Resea r ch Perspect ives 4 Sec t ion 4 Research M e t h o d o l o g y 5 Sec t ion 5 P rev ious Research on T e c h n o l o g i c a l A d o p t i o n 6 Sec t ion 6 Fac tor Ident i f i ca t ion : A Qua l i t a t i ve S tudy 9 6.1 Strategic M o t i v a t i o n 9 6.2 V a l u a t i o n o f Internet B a n k i n g 10 6.3 Cus tomer D e m a n d 11 6.4 Env i r onmen ta l Inf luences 11 6.5 Opera t iona l Con tex t 13 Sec t ion 7 Const ruc t V a l i d i t y : Q-Sort A n a l y s i s 14 Sec t ion 8 Theore t i ca l Founda t ions 16 Sec t ion 9 Survey 18 Sec t ion 10 Survey Samp le 19 Sec t ion 11 Desc r ip t i ve Stat ist ics 2 0 11.1 Percept ion o f In i t ia l P red ic tors 20 11.2 L e v e l o f Intent to A d o p t Internet B a n k i n g 20 11.3 N o r m a t i v e Responses 21 Sec t i on 12 M o d e l V a l i d a t i o n : A Quant i ta t i ve A n a l y s i s 23 12.1 Fac tor A n a l y s i s on In i t ia l P red ic tors 23 12.1.1 Objec t i ves 23 12.1.2 Procedures 23 12.1.3 Resu l ts : 24 12.2 D i s c r i m i n a n t A n a l y s i s 25 12.2.1 Objec t i ves 25 12.2.2 Procedures 26 12.2.3 Resu l ts 28 Sec t ion 13 S u m m a r y 32 Sec t ion 14 C o n c l u s i o n s 34 Sec t ion 15 Research Cont r ibu t ions 37 Sec t ion 16 L im i t a t i ons 38 T a b l e 1: C o m p a r i s o n o f F i n d i n g s w i t h P rev ious Resea r ch 39 Tab l e 2: C l a s s i f i c a t i on o f B a n k i n g Func t ions i n the Internet 40 Tab l e 3: F requency D i s t r i bu t i on o f E va lua t i on Score on In i t ia l P red icators 41 Tab le 4: F r equency D i s t r i bu t i on o f L e v e l o f Intent to A d o p t Internet B a n k i n g Func t ions ... 42 Tab l e 5: F r equency D i s t r i bu t i on o f Responses to N o r m a t i v e Ques t ions 43 Tab l e 6: Percentage o f Va r i ance E x p l a i n e d b y P r o v i s i o n a l Factors 44 Tab l e 7: Fac tor L o a d i n g M a t r i x 45 Tab l e 8: F requency D i s t r i bu t i on o f M e a n Score i n Intent L e v e l 46 Tab l e 9: M e a n Scores in the D e f i n e d G r o u p s 48 F igu re 1: A Hypo thes i zed M o d e l o f D e c i s i o n Factors o f Internet B a n k i n g 49 F i gu re 2: The Theo ry o f P l anned B e h a v i o r ( T P B ) 50 F i gu re 3: The A d o p t i o n o f Internet B a n k i n g : A M o d e l o f D e c i s i o n Factors 51 A p p e n d i x 1: Strategic Advan tages o f Internet B a n k i n g 52 A p p e n d i x 2: In i t ia l Measu remen t Items 53 A p p e n d i x 3: Items P lacement M a t r i x o f Q-Sort A n a l y s i s 56 A p p e n d i x 4: A n a l y s i s o f the I tems P lacement M a t r i x 57 A p p e n d i x 5: Survey F o r m 58 A p p e n d i x 6: Procedures o f E va l ua t i ng S ign i f i cance o f D i s c r i m i n a n t Func t i ons 66 References 67 IV List of Tables Table 1: Comparison of Findings with Previous Research 39 Table 2: Classification of Banking Functions in the Internet 40 Table 3: Frequency Distribution of Evaluation Score on Initial Predicators 41 Table 4: Frequency Distribution of Level of Intent to Adopt Internet Banking Functions .... 42 Table 5: Frequency Distribution of Responses to Normative Questions 43 Table 6: Percentage of Variance Explained by Provisional Factors 44 Table 7: Factor Loading Matrix 45 Table 8: Frequency Distribution of Mean Score in Intent Level 46 Table 9: Mean Scores in the Defined Groups 48 v List of Figures Figure 1: A Hypothesized Model of Decision Factors of Internet Banking 49 Figure 2: The Theory of Planned Behavior (TPB) 50 Figure 3: The Adoption of Internet Banking: A Model of Decision Factors 51 v i List of Appendices Appendix 1: Strategic Advantages of Internet Banking 52 Appendix 2: Initial Measurement Items 53 Appendix 3: Items Placement Matrix of Q-Sort Analysis 56 Appendix 4: Analysis of the Items Placement Matrix 57 Appendix 5: Survey Form 58 Appendix 6: Procedures of Evaluating Significance of Discriminant Functions 66 Acknowledgments T h e author w o u l d l i k e to extend spec ia l thanks to J o h n T i l l q u i s t for his considerable assistance this study. T h e author w o u l d also l i k e to thank R i c h a r d A W a f e r , Sean P O ' S u l l i v a n , B o b M c G l a s h o n and M e i n i Icker t for their he lp i n the in te rv iews , I zak Benbasa t for h is va luab l e adv ice o n the research m e t h o d o l o g y , and those graduate students at the U n i v e r s i t y o f B r i t i s h C o l u m b i a for par t ic ipa t ing i n the Q-sor t A n a l y s i s . T h i s research was supported b y a C a n a d i a n research grant f r o m the S o c i a l Sc ience and H u m a n i t i e s Resea r ch C o u n c i l . viii Section 1 Introduction: Strategic Use of IT in Banking In business, the use of Information Technology (IT) is always widely adopted to support business strategies. The banking industry provides a very good example. It has always been the leader in innovative applications of IT and is very aggressive in aligning IT to support business strategies, particularly in the delivery of services and products. Many technical innovations have been developed and adopted in an effort to provide competitive advantages and channel efficiency. For example, "Back Office Automation" was enabled by Electronic Data Processing (EDP) in the 1960s, "Front Office Automation" and "Customer Interface Automation" by the EFT, A T M and POS networks in the 1970s, and geographic expansion by home banking, such as telephone and PC banking, in the 1980s. In recent years, the potential of the Internet has been widely recognized. Driven by Web technologies, the Internet has now become a major infrastructure providing an economical, quality, fast and, more importantly, a virtual medium for business transactions. It is also an impetus of today's ubiquitous electronic commerce, and its applications can be strategically aligned to business operations. For example, the Internet is now being used as a sales channel, a marketplace for buyers and sellers, an infrastructure of distribution network, an on-line catalogue, a customer support and a means of forming virtual corporations '(Kosiur, 1997). Its strategic implications, especially to banks, are very significant. Section 2 Strategic Implications of the Internet to Banking Competitive Implications. The Internet has changed the competitive landscape of the banking industry. In a way, it poses a threat to large banks for two reasons. First, since the Internet is size insensitive, small banks can have the opportunity to close the technology gap between them and large banks and offer on-line banking without having to make enormous investments in IT infrastructures such as the design of software applications, support of proprietary back-end systems and dial-in lines and modems for customers access. The burden of technical development has been shifted to such companies as Web browser developers and communication companies. Technically, all that is needed is the use of standard TCP/IP networking and a connection to the Internet (US Web Services, 1998). 1 Second , s ince the Internet is a lso geographic insens i t i ve , it can neutra l ize the compet i t i ve advantage o f hav ing the extensive b ranch ne twork that large banks have. Th i s extends the compet i t i on b e y o n d geographic boundar ies to become reg iona l or na t iona l . B y outsourc ing the Internet b a n k i n g operat ions to serv ice bureaus, such as F i se r v , E D S and In tegr ion 2 , sma l l banks can ma in ta in a f u l l t ransact ional webs i te to customers on a nat iona l bas is and project the same techno logy image that large banks have , at a l o w cost 3 ( M a r e n z i , 1998) . G i v e n this un l im i t ed geograph ic reach, the compet i t i ve d i f fe rent ia t ion between geograph ica l d i f ferences w i l l be g radua l l y e roded, subject o n l y to regulatory constraints ( B o o z , A l l e n & H a m i l t o n , 1997). Strategic Benefits. T o banks , the adopt ion o f the Internet as a de l i ve ry channe l is a strategic use o f I T to p rov ide channel e f f i c i ency . In this aspect, the Internet can p rom i se s ign i f i cant potent ia l benef i ts , i n c l u d i n g immedia te use o f a w i d e l y adopted set o f t echno logy standards, r ap id increases i n funct iona l i t y as standards evo l ve , integrated marke t ing and b a n k i n g content, and access to a large number o f customers and prospects at the lowest cos t 4 ( O o i et a l . , 1996, i v ) . Strategy Development. The impac t o f the Internet on banks i n f o rmu la t i ng strategy can be r e cogn i zed from several examples . F i rs t , banks are r ep lac ing ex i s t ing PC-based serv ices w i t h Internet b a n k i n g , l i ke the Toron to D o m i n i o n B a n k ' s conve rs ion i n 1999. It is a strategic m o v e enab led b y the evo lu t ion o f IT, i.e., the Internet and W e b technolog ies . Internet b a n k i n g has advantages over P C bank ing because the concept o f Internet b a n k i n g is ent i re ly based on open t echno logy standards, such as TCP/ I P and W e b browsers , i n w h i c h the unde r l y i ng t e l e commun i ca t i on ne twork is an open p l a t f o r m shared b y the pub l i c . T h i s a l l ows banks to escape the constraints o f expens ive propr ietary systems, such as those operated b y C h e c k F r e e and V i s a Interact ive, and spec ia l l y deve loped software and dial-up interface, such as Q u i c k e n and M o n e y ( Eng l and , 1998). The beauty o f Internet b a n k i n g is the use o f the cl ient-server p l a t f o r m to support the interact iv i ty between banks and customers , i n w h i c h customers r u n appl ica t ions that res ide at the b a n k ' s W e b server. B a n k s can therefore f u l l y cus tomize and dif ferent iate e lectronic interfaces, and have true b rand ident i ty that P C b a n k i n g cannot o f fe r ( O o i et a l . , 1996, i i i ; F i v e Pace , 1995; W e b T e c h , 1998). Kosiur in his book provides six innovative case studies of Web-based electronic commerce. 2 Integrion is a consortium found by some of the largest banks and financial institutions in North America. Its goal is to act as an outsourcer for the electronic banking needs of its members (Marenzi, 1998). 3 For example, initial set up cost is from US20K to $30K, plus $1.5Kper month for first 12,000 transactions, which is much lower than the cost in creating in house Internet banking. 2 Second, the Internet allows Internet-based or so-called virtual banks to appear as new competitors because it breaks the entry barrier created by the high set-up cost of branch network5. Internet- based competitors of this type have created a well-branded image and compete directly with traditional banks for time-pressed customers who demand any-time and anywhere banking services. Some traditional banks have responded by either creating a new business6 or acquiring a business7 of this type. Meanwhile, it was also suggested that the strategic issue for banks might no longer be how to integrate Internet banking into the portfolio of existing delivery channels, but to consider how and where to build a new barrier before this old barrier completely collapses (Li, 1997). But setting an entry barrier could also be considered as protectionism. "Keeping them (new competitors) out even though they got a better idea is a bad idea, ... what you (banks) need to do is find the way to win, as opposed to find the way to make the other lose" (McGlashon & Ickert, 1998). Third, the Internet is a force leading to strategic partnerships between banks and other organizations. With the use of the Internet, rich information can simultaneously reach a large number of prospects, thus breaking the traditional trade-off between richness and reach of information. This allows bank customers to navigate a full range of banking options and provides direct access to such financial service providers as credit card companies and mortgage lenders, without having to go through banks. The hierarchy of channels once controlled by banks has been broken (Evans & Wurster, 1997). To a great extent, the Internet is an enabler of disintermediation to the financial industry (McGlashon & Ickert, 1998). In order to maintain their role as a leading financial intermediary and to support a full menu of services that cannot be offered alone, banks are forming strategic partnerships with such companies as insurance and brokerage firms (Ogilve, 1996). Market Potential. Many studies have indicated that there is great potential in Internet banking. It was projected that 16 million US households, representing 16% of all US households, would use Internet banking by the year 20008 (Booz, Allen & Hamilton, 1996). In 1998, Online Banking Report estimated that there were about 4.5 million US households using Internet banking at least 4 Some other commonly recognized strategic advantages are summarized in Appendix 1. 5 Setting up an Internet-only bank costs only between US$1 to US$2 million, which is significantly lower than the costs involved in developing a branch network (Booz, Allen & Hamilton, 1997). 6 For example, Mbanx was created by the Bank of Montreal and Citizens Bank by Vancouver City Savings Credit Union. 7 For example, First Security Network Bank was acquired by the Royal Bank. 3 once a month. That number was expected to increase to 33.5 million by the year 2005 and would represent nearly 31% of all households (US Web Services, 1998). The Tower Group (1996), a consulting firm specializing in financial industry, expected that by the year 2000, 85% of US households with an account at a commercial bank would have that account at a bank offering Internet-based services. Therefore, household demand for Internet banking will be at a level that banks cannot afford to ignore. Worthy of note is the fact that most customers are willing to see more varieties of banking functions available through the Internet. In GVU's study (1997), the majority of surveyed consumers felt that having a variety of features and services (including bill payment) available on the Internet was important9, while in Ooi, Wei and Goh's survey (1996, i), both bill payment and transfer of funds were viewed as important categories of Internet banking services that should be provided. Section 3 Research Perspectives Research Motivation. From the above elaboration, it is reasonable to expect a high adoption rate of full functionality in banks' websites. However, research findings have shown that Internet banking functions adopted by banks varied significantly, and that only a minority of banks had offered advanced level functions such as bill payment and funds transfer (Diniz, 1998; Booz, Allen & Hamilton, 1997). In Diniz's study, only about 15% of bank sites studied provided services in bill payment and funds transfer10. Obviously, customer demand does not solely determine the adoption rate and there exist some important issues about providing Internet-based services and products. For banks, integrating the Internet into the existing business portfolio might require a completely different set of considerations that might not be encountered in the adoption of earlier technologies. However, many journals have tried to explain the adoption of Internet banking from the customers' perspective and attributed the slow growth to customer resistance because they are still not comfortable with the security of the Internet banking and prefer face-to-face interactions with branch tellers. As a result, many studies on Internet banking have been focused on the understanding of the relationship between customer behavior and adoption rate. For example, how the consumer usage of electronic channels was influenced by their needs and opportunity of using electronic channel (Ramaswami et al., 1998), what the user profile of Internet banking was 8 The analysis was based on the key factors affecting consumer demand, such as Internet usage, computer ownership and consumer acceptance. 9 Including both respondent groups that had and had not an Internet bank account. 4 and what factors were a f fec t ing their adopt ion dec i s i on ( G V U Center , 1997) , and what determinants ex is ted to affect cus tomers ' usage in tent ion o f Internet b a n k i n g serv ices ( O o i et a l . , 1996, i ) . B y compa r i son , studies i n the perspect ives o f banks o n l y have rece i ved l i t t le attent ion. Research Questions. Therefore , this study tries to e x p l a i n adopt ion o f Internet b a n k i n g f r o m the perspect ives o f banks . It intends to invest igate the p r i n c ip l e issues that banks cons ider w h e n p r o v i d i n g products and services through the Internet, and then to create and va l idate a m o d e l o f techno log i ca l adopt ion that reveals h o w these issues affect b a n k s ' intent to adopt. T h e p roposed m o d e l answers two research quest ions. 1. What are the factors that banks take into account when considering or implementing Internet banking? 2. How are these factors related to banks' level of intent to adopt Internet banking? Section 4 Research Methodology Qualitative Research. T h i s research was d i v i d e d into t w o phases. T h e f i rst phase started w i t h a qual i tat ive research b y r e v i e w i n g the l iterature o f re levant indust ry pub l i ca t ions and scho la r l y research w h i c h have ident i f i ed m a n y potent ia l factors l ead ing to the adopt ion o f the Internet as a de l i ve ry channe l , a lbeit i n p i ecemea l f o r m . These have been augmented b y semi-structured in terv iews w i t h bank execut ives o f several ma jo r f i nanc i a l inst i tut ions i n the V a n c o u v e r area. In the in te rv iews , respondents had been a l l o w e d to choose the issues they wanted to d iscuss before the prepared quest ions were asked. Factors from bo th sources were c o m b i n e d to generate 56 in i t i a l survey i tems and a tentative adopt ion m o d e l . Q-Sort Analysis. A Q-sort analys is on the in i t i a l su rvey i tems was conducted to test the construct v a l i d i t y o f the m o d e l , w h i c h was , spec i f i ca l l y , to m a k e sure that corre lated quest ions were grouped w i t h i n par t i cu lar categories and amb iguous quest ions e l im ina ted or rev i sed . A f t e r th is , the rev i sed survey i tems were incorporated into an 8-page survey , i n w h i c h quest ions measu r ing the respondents ' intent to add par t icu lar b a n k i n g funct ions to their f i r m s ' websi tes were a lso i n c luded . Quantitative Research. The second phase was a quant i tat ive research approach des igned to ana lyze the survey result against the proposed adopt ion m o d e l . The survey was des i red i n this study because factors ident i f i ed i n the qual i tat ive study d i d not have suf f i c ient emp i r i c a l The survey data was collected in October/November 1997. 5 foundat ion . T h e survey approach is able to p rov ide some stat ist ical s ign i f i cance to the f ind ings . T h e analys is was conduc ted i n three parts. F i rs t , factor ana lys is was used to study h o w measurement i tems c lustered around some unde r l y i ng c o m m o n factors. Second l y , d i s c r im inan t ana lys is was used to examine the re la t ionsh ip between the c o m m o n factors and the l eve l o f intent that bank managers had i n adopt ing par t icu lar Internet b a n k i n g funct ions . F i n a l l y , f i nd ings were eva luated and s u m m a r i z e d , l ead ing to the conc l u s i on o f what the c o m m o n factors were and h o w they d i f ferent iated the l eve l o f intent to adopt Internet b a n k i n g . Section 5 Previous Research on Technological Adoption A l t h o u g h there is a very l im i t ed quant i ty o f research spec i f i c a l l y f ocus ing on Internet b a n k i n g adopt ion f r o m a bank ' s perspect ive , research o n adopt ion o f other technolog ies b y organ iza t ions has been con t inuous l y emerg ing i n the IS l i terature. F o l l o w i n g are examples o f studies f o c u s i n g on adopt ion o f t echno logy that has s imi la r i t ies to Internet b a n k i n g , w h i c h m a y p rov ide some ins ights into the Internet b a n k i n g adopt ion dec i s ion . A l t h o u g h E l e c t ron i c D a t a Exchange ( ED I ) is an In terorganizat iona l Sys tem ( IOS ) be tween t w o organ izat ions , it is s t i l l s im i l a r to Internet b a n k i n g i n a w a y that they both are network-based e lectronic systems, des igned to improve channe l e f f i c i ency and to faci l i tate de l i v e r y o f serv ices and products from an organ iza t ion to its customers . There are m a n y studies i n t e chno log i ca l adopt ion us ing ( ED I ) as a uni t o f ana lys is , but their research focus o f adopt ion determinants va r i ed d i f ferent ly . F o r example , O ' C a l l a g h a n et a l . (1992) had studied the impac t o f relative advantage, compatibility " and external influences ( f r om t rad ing partners) to the E D I adopt ion i n insurance industry , and f o u n d that on l y the relative advantage was related to the adop t ion behav ior . B u t i n some later research, compa t ib i l i t y and external in f luence c o u l d a lso be in f luent ia l to adopt ion dec i s ion o f E D I . B a s e d on l iterature r e v i e w and case studies, I a covou et a l . (1995) invest igated the adopt ion o f E D I and f o u n d that factors i n f l uenc ing the adopt ion dec i s i on c o u l d be organ iza t iona l and inter - o rgan iza t iona l . Factors i n f l uenc ing the intent to adopt E D I were ident i f i ed as: the pe r ce i ved potent ia l advantages associated w i t h E D I imp lementa t ion (i.e., perceived benefits), the l e ve l o f f i nanc i a l and techno log i ca l resources o f the o rgan iza t ion (i.e., organizational readiness), and the 1 ' R e l a t i v e advantage and c o m p a t i b i l i t y are t w o o f the five f u n d a m e n t a l factors that can i n f l u e n c e the d i f f u s i o n o f i n n o v a t i o n . T h e other three factors are o b s e r v a b i l i t y , c o m p l e x i t y and t r i a l ab i l i t y ( R o g e r s , 1983) . 6 pressure from competitors and trading partners (i.e., external pressure). Later, this proposition was statistically validated by a survey approach (Chwelos et al., 1999). The role of organizational and interorganizational factors were also highlighted in other research. Hart and Saunders (1998) have examined the impact of the interorganizational relationship between the supplier and customer on EDI adoption. The results suggested that customer power and supplier trust could affect the use of EDI differently. In one study, Premkumar and Ramamurthy (1995, i) tested several factors against the decision mode for EDI adoption. It was found that two organizational factors, internal needs (i.e., need and relative advantage) and top management support, and two interorganizational factors, competitive pressure and exercise power of the trading partner, were important factors to differentiate the decision mode among organizations. In a separate study focusing on organizational factors (Premkumar and Ramamurthy, 1995, ii), they found that compatibility, relative advantage, championing, scope of use within the task environment, and being an early adopter determined the diffusion of EDI internally, while technical compatibility, top management support, and being an early adopter were key variables influencing the diffusion externally. Internet banking can be viewed as a customer-oriented strategic system (COSS) n , which is designed to link to customers and improves a bank's competitive edge. Therefore, insight of adoption of Internet banking can be drawn from a case research by Reich and Benbasat (1990). Reich and Benbasat have investigated eleven COSS and identified some factors that enabled an organization to be a first-mover in developing a strategic system. The results showed that factors influencing the speed with which an organization developed a strategic system were related to the characteristics of the industry (i.e., high competitive threat from existing competitors and new entrants, and customer bargaining power), the organization (i.e., proactive stance, CEO support and champion), IS function (i.e., proactive stance, high competence and previous COSS experience) and the system itself (i.e., high priority, high level of resources, full pilot test and avoidance of IS planning). Although Internet banking is more consumer-based13, to a certain extent it is also a customer- based interorganizational system (CIOS) because its purpose is to facilitate the link to the 1 2 As defined, COSS is an information system used to support or shape the competitive strategy of an organization and set up a link to customers. Under such definition, Internet banking can also be categorized as a COSS. 1 3 The scope of this study is limited to retailing banking. 7 cus tomer and to improve customer re la t ionsh ip . A d o p t i o n dec is ions o f C I O S were p roved to be fac i l i ta ted b y factors i n w ide range o f categories (Grover , 1995). T h e y were : support factor {i.e., top management support and championship), IOS factor (i.e., compatibility and complexity), p o l i c y factor {i.e., proactive role of IT and management risk-taking position), o rgan iza t iona l factor {i.e., organizational size, IS infrastructure and strategic planning), and env i ronmenta l factor {i.e., number of adaptable innovations). T e c h n o l o g i c a l adopt ion can also arise from organ iza t iona l in i t ia t ive and env i ronmenta l pressure. B u r k e (1996) used the adopt ion o f A T M b y banks to study the re la t ionsh ip between the strategic or ientat ion and techno log ica l adopt ion dec i s i on and to examine h o w this re la t ionsh ip was associated w i t h the env i ronmenta l constraints the organ iza t ion was f a c ing and the organ iza t iona l capab i l i t i es the organ iza t ion possessed. The results ind ica ted that b a n k s ' strategic orientations were re lated to the t i m i n g and extent o f adopt ion , that i s , banks aggress ive ly pu r su ing expans ion in to n e w markets adopted A T M s ign i f i can t l y ear l ier than banks w i t h conservat ive approach, w h i c h concentrated on ma in ta in ing their current compet i t i ve pos i t i on . T h e results have also s h o w n that the t im ing o f adopt ion w o u l d d i f f e r as a func t ion o f regulatory environment and organizational size. B a n k s operat ing i n a less restr ict ive env i ronment or h a v i n g a larger o rgan iza t iona l s ize w o u l d have an ear l ier adopt ion . A n E E C - s p o n s o r e d research project has iden t i f i ed some major barr iers to the adopt ion o f service- based I T appl ica t ions , w h i c h were in tended to improve customer re la t ionships and the qua l i ty o f serv ices and de l i ve ry (Barras, 1986). Bar r ie rs that m igh t inh ib i t the rate o f adopt ion were be l i e ved to have three categories. T h e y i n c l uded e c o n o m i c a l factors {i.e., cost barrier), soc i a l factors {i.e., fear of depersonalization 1 4 , customer resistance), po l i t i c a l factors (i.e., government regulations), ins t i tu t iona l f a c to r s 1 5 and lega l factors. T h e above d i scuss ion i l lustrates that t echno log i ca l adopt ion is a ve ry b road issue. Factors a f fec t ing the adopt ion dec i s ion m a y vary d i f ferent ly between types o f techno log ies . So , the unders tand ing o f the factors spec i f i c to Internet bank ing adopt ion s t i l l requires a thorough study o f l i terature spec i a l i z ing i n the b a n k i n g indust ry and the Internet techno logy . T h i s w i l l be d i scussed i n the next sect ion. The fear of deskilling of the work and loss of jobs. 1 5 For example, lack of standardization of procedures and consistency of organization structure. 8 Section 6 Factor Identification: A Qualitative Study T h i s study o n l y intends to focus on Internet bank ing-spec i f i c factors because a comprehens i ve m o d e l i n c l u d i n g a " c o m p l e t e " range o f var iab les as iden t i f i ed b y prev ious research w o u l d be d i f f i cu l t to manage and test (Grover , 1995). Potent ia l factors l ead ing to Internet b a n k i n g dec i s i on were m a i n l y ident i f i ed f r o m literature spec i a l i z i ng i n the subject and three in-depth in te rv iews w i t h senior execut ives o f major depos i tory inst i tut ions i n C a n a d a 1 6 . T h e re la t ionsh ip o f these factors w i t h the b a n k s ' intent to adopt Internet b a n k i n g was tested b y several hypotheses. H i g h l i g h t s o f the f ind ings , together w i t h the n u l l f o r m o f the hypotheses, are p r o v i d e d as f o l l o w s . 6.1 Strategic Motivation A d o p t i o n o f Internet b a n k i n g is a business strategy mot i va ted b y h o w it can sat isfy the business need, strategic mission and organizational goal. Some examples are f o u n d i n the banks in te rv i ewed . D u e to env i ronmenta l changes 1 7 , the B a n k o f M o n t r e a l ( B M O ) needed to re-define cus tomer re la t ionsh ip and become tota l ly c l ient-centr ic and serv ice-dr iven. W i t h Internet techno logy , the bank c o u l d differentiate the c l ient base and o f fe r appropriate serv ices for i n d i v i d u a l c l ients , so that their " segment o f o n e " marke t ing strategy c o u l d be suppor ted 1 8 . M e a n w h i l e , the l aunch o f M b a n x was mos t l y a b rand ing strategy requ i red because B M O had a l o w name recogn i t ion i n N o r t h A m e r i c a . The object ive o f b e c o m i n g a future b a n k i n g b rand , as c lea r l y stated i n an internal document , translated into the goa l o f be ing a dist inct o rgan iza t ion and a l ead ing force for i nnova t ion i n N o r t h A m e r i c a ( M c G l a s h o n & Ickert, 1998; B a r c l a y , 1998; K i n s l e y , 1998; C h i s h o l m , 1998). O n the other hand , cons idera t ion o f Internet b a n k i n g i n H o n g k o n g B a n k G r o u p o f C a n a d a ( H K B a n k ) was mot i va ted b y the need for a l o w cost de l i v e r y channe l . A s commen ted ( O ' S u l l i v a n , 1998), the bank " cannot compete , at least w i t h a certa in segment i n the customer base, b y o n l y o f f e r ing a h igher cost d i s t r ibut ion channe l " . F o r V a n C i t y , Internet b a n k i n g c o u l d per fec t l y f i t into their m i s s i o n o f be i ng at the l ead ing edge o f t echno logy based de l i ve ry (Wafer , 1998). The strategic l aunch o f C i t i zens B a n k for V a n C i t y on the other hand was intended to sat isfy the need o f a sma l l g roup o f customers w h o shared the interest i n techno logy or customer serv ices (Barc lay , 1998). Therefore HI: The degree to which Internet banking satisfies the business needs is not related to banks' adoption intent 1 6 Richard A Wafer, V P Information Systems, Vancouver City Savings Credit Union (VanCity); Sean P O'Sullivan, VP Distribution Systems, Hongkong Bank Group of Canada (HK Bank); Bob McGlashon, Senior V P & Meini Ickert, Senior Manager Sales, the Bank of Montreal (BMO). B M O is one of the largest banks, and VanCity and H K Bank respectively are the largest credit union and foreign bank in Canada. 1 7 Democratization of information, globalization, social and demographic shifts, and deregulation of financial industry (Chisholm, 1998). 1 8 It is to make customers feel valued as a market segment of one. 9 ( r< l0 .3 l ) 1 9 . H2: The degree to which Internet banking matches the declared missions is not related to banks' adoption intent (r < 10.31). H3: The degree to which Internet banking meets the organizational goals is not related to banks' adoption intent ( r<l0.3l) . 6.2 Valuation of Internet Banking Characteristics of Internet Banking. Percept ions o f Internet b a n k i n g , as represented b y the e f f i c i ency and s ign i f i cance o f the Internet as a de l i ve ry channe l , can affect Internet b a n k i n g dec i s i on . A study has found that banks seeing the Internet as the mos t important de l i ve ry channe l had sites w i t h more advanced funct iona l i t y than banks r a n k i n g t radi t ional b ranch as a major de l i ve ry channe l ( B o o z , A l l e n & H a m i l t o n , 1997). It indicates that banks v i e w i n g the Internet as a future ma ins t ream channe l w i l l have more incent ives fo r a more advanced webs i te . Cur ren t l y , Internet bank ing m a y s t i l l be v i e w e d as a strategic advantage, but this oppor tun i ty is c l o s i n g r a p i d l y because it w i l l soon f o l l o w the same path as A T M . It w i l l change f r o m a strategic advantage to a strategic necess i ty , a l though m u c h faster ( U S W e b Serv ices , 1998). B a n k i n g on the Internet w i l l soon become a bas ic and expected b a n k i n g serv ice . A s one banker commen ted , Internet bank ing "does not differentiate y o u (the bank ) , it jus t a l l ows y o u to be a bank . I f y o u don ' t o f fer this stuff, y o u do not get to a bank a n y m o r e " (Tress lar , 1997). Hence H4: The perceived significance o f the Internet as a delivery channel for banking services is not related to banks ' adoption intent (r < lo.31). E f f i c i e n c y is m a i n l y about economies , secur i ty , and the access ib i l i t y and conven ience that the Internet can p rov ide as a de l i ve ry channe l . A m o n g these, secur i ty is s t i l l pe r ce i ved as a b i g issue w h e n banks cons ider Internet bank ing . W h e n Toron to D o m i n i o n B a n k and C a n a d i a n Imper ia l B a n k o f C o m m e r c e f i rst cons ide red Internet b a n k i n g , it was the secur i ty conce rn that de layed the f u l l imp lementa t ion (G reen , 1996). O n the other hand , V a n C i t y cons idered the secur i ty issue as a pure l y emot iona l b ias , and par t ly because o f that, they became one o f the ear ly adopters o f Internet b a n k i n g i n C a n a d a (Wafer , 1998). Therefore H5: The perceived efficiency o f the Internet as a delivery channel for banking services is not related to banks' adoption intent (r < lfj.3l). Business Opportunity. It is w i d e l y be l i e ved that imp l emen t i ng Internet b a n k i n g is an oppor tun i ty fo r business deve lopment , w h i c h m a y lead to an ear ly adopt ion dec i s i on . B a n k i n g w i t h the Internet is l i k e l y to become just one component o f an integrated system, w h i c h inc ludes not o n l y 9 The magnitude of coefficient of correlation ( r) will be discussed in the subsequent section. 10 b a n k i n g funct ions , but a lso a var ie ty o f non-bank ing act iv i t ies , such as E-commerce and b i l l presentment (Wafer , 1998). A n d through this sys tem, banks can keep track o f cus tomers ' act iv i t ies and target spec i f i c products to spec i f i c customers , p r o v i d i n g a bus iness oppor tun i ty (Tresslar , 1997). A d d i t i o n a l l y , this business oppor tun i ty a lso means deve lopment o f techn ica l k n o w - h o w and manager ia l sk i l l s w i t h i n the o rgan iza t ion . F o r examp le , b y exper iment ing w i t h Internet b a n k i n g , M b a n x has become a center for creat iv i ty and i nnova t i on that w i l l fac i l i tate p r o b l e m so l v i ng and innova t ing th i nk ing at a l l o rgan iza t iona l leve ls ( K i n s l e y . 1998). H e n c e H6: The degree to which Internet banking is perceived as a business opportunity is not related to banks ' adoption intent ( r<l0.3l) . 6.3 Customer Demand Manage r s i n a survey have a cknow ledged the d i f f i cu l t i es i n p red i c t ing w h e n , and at what rate, the usage l eve l o f Internet b a n k i n g b y customers w o u l d start to g row . Th i s uncerta inty made it ha rd for banks to c o m m i t s ign i f i cant investment to Internet b a n k i n g (Dan i e l & Storey, 1997). There fore , it is ve ry c o m m o n that banks w i l l conduct extens ive market research w h e n m a k i n g their Internet b a n k i n g dec i s ion . A certainty o f cus tomer demand is not jus t a s t imulus , but a lso a requi rement to adopt ion dec i s i on . In consensus, customers' behavior, demographics and technical capabilities o f us ing the Internet m a y be g o o d ind icators o f customer demand . T h e understanding o f cus tomer behav io r is important because it a l l ows banks to understand cus tomers ' preferences towards us ing the Internet to access b a n k i n g serv ices. D e m o g r a p h i c d is t r ibut ion can s h o w what market segments w i l l generate demand fo r Internet b a n k i n g . O n the contrary , cus tomers ' l a ck o f requ i red sk i l l s , hardware , software and connec t i v i t y i n us ing the Internet w i l l negat i ve l y affect the demand ( O 'Su l l i van , 1998; B a r c l a y , 1998; W a f e r , 1998). There fore H7: The perceived influence o f customer behavior to the demand o f Internet banking is not related to banks ' adoption intent (r < lfj.3l). H8: The perceived influence o f customer demographics to the demand o f Internet banking is not related to banks ' adoption intent (r < l0.3l). H9: The perceived influence o f customers' capabilities o f using the Internet to the demand o f Internet banking is not related to banks' adoption intent (r < l0.3l). 6.4 Environmental Influences Market Competition. A d o p t i o n m a y be a response to compet i t i ve threats c o m i n g f r o m banks (e.g., C i t i z ens B a n k ) or non-bank compet i tors (e.g., I N G ) , wh i cheve r can of fer l o w cost alternatives to the customers. B a n k s nowadays are f i n d i n g it d i f f i cu l t to compete b y o n l y o f f e r i ng a h igher cost de l i ve ry channe l ( O ' S u l l i v a n , 1998). T i m i n g o f entry into Internet b a n k i n g marke t is 11 also important because ear ly adopters can a lways secure a market share. V a n C i t y has opted fo r this o f fens ive strategy because they be l i e ved that be ing late i n the market w o u l d m a k e it d i f f i cu l t for them to " ca t ch up and d r a g " the customers f r o m compet i tors (Wafer , 1998). B a n k s i n the future w i l l be subject to s ign i f i cant ne twork pressure i n adopt ion o f Internet b a n k i n g . T h e T o w e r G r o u p (1996) est imated that b y the year 1999, 9 0 % o f the top 50 U S banks w o u l d o f fe r f u l l serv ice v i a Internet access. The group a lso wa rned that banks w o u l d lose 1 0 % o f their customers i n five years i f they fa i l ed to of fer on-line b a n k i n g , i n c l u d i n g the Internet. P r o v i s i o n o f Internet b a n k i n g to a great extent w i l l become a customer retent ion strategy. Hence H10: The perceived competitive threats are not related to banks ' adoption intent (r < l0.3l). Regulatory Constraints. Regu la to ry requirements a lso constra in large-scale Internet b a n k i n g imp lementa t ion , at least temporar i l y . There were lega l and comp l i ance issues that jus t c o u l d not be done i n the Internet env i ronment such as p r o v i s i o n o f comple te i n fo rma t ion and issues o f signature (Ba rc lay , 1998). Gahtan & G r a h a m (1997) have h igh l igh ted some o f the issues f a c ing banks i n connec t ion w i t h the p r o v i s i o n o f f i nanc i a l services through the Internet. T h e y i nc lude the di f ferences i n p r o v i n c i a l and internat ional lega l requi rements , r i s k i n authent icat ion, l ega l i t y o f contractua l b i n d i n g and potent ia l l i ab i l i t y from exp i r ed i n fo rmat ion posted o n the Internet. T o avo id the poss ib i l i t y o f v i o l a t i ng the j u r i sd i c t i on o f another country , some banks m a y even choose to restr ict their cus tomer base to certain countr ies . F o r example , Secur i ty F i r s t N e t w o r k B a n k o n l y accepts accounts for U S and Canad i an nat iona ls (Reed, 1997). Therefore H i t : Regulatory challenges associated wi th Internet banking are not related to banks ' adoption intent ( r<l0.3l) . Technological Complexity20. There are techn ica l cha l lenges i n us ing Internet t echno logy , w h i c h m a y defer adopt ion dec i s i on . M a n y o f t hem are related to the front-end cont ro l such as incompa t ib i l i t y be tween system conf igurat ions and browsers , immature p r o g r a m m i n g languages and the connec t ion qua l i t y o f the Internet. These are the th ings that banks do not have m u c h cont ro l over because improvemen t o f Internet t echno logy is dependent on other in termediar ies such as Java, M i c r o s o f t and Netscape (Wafer , 1998). "Technological Complexity" was not hypothesized because the result from Q-sort analysis suggested merging its measurement items into other factor categories. 12 6.5 Operational Context Channel Management21. M a n y operat ional issues co l la tera l to imp lemen t ing Internet b a n k i n g m a y a lso exist as cha l lenges. F i rs t , there are cha l lenges i n manag ing mu l t ip l e channels . A d d i n g the Internet into the mu l t i p l e channe l sys tem w i thou t r educ ing t radi t ional costs s i m p l y means an add i t ion o f overhead. So the key cha l lenge l ies i n re-engineer ing and o p t i m i z i n g the t rad i t iona l n e t w o r k 2 2 ( N e h m z o w , 1997), w h i c h means that banks need to re-define the ro le o f each channe l , espec ia l l y the branches. It m a y not be necessary to reduce the number o f branches as one study f o u n d that on l y 1 0 % o f the surveyed banks in tended to reduce the number o f branches because Internet b a n k i n g was o f fe red ( Rob inson , 1998). Rather , it is h o w to in f luence cus tomers ' behav io r b y encourag ing them to use the Internet for rout ine and non-prof i table transact ions, so that higher-cost channe l can handle the more prof i tab le customers w h o demand more h u m a n attention ( O ' S u l l i v a n 1998; D a n i e l , 1997). Product and Service Development. Internet b a n k i n g is more than just m a p p i n g ex i s t ing serv ices and products into the Internet env i ronment . It a lso requires some sort o f t rans format ion capac i ty , such as b r i n g i n g into the Internet some serv ices that cannot be done at b ranch . A s such , Internet b a n k i n g can di f ferent iate, cus tomize and persona l ize the products ( M c G l a s h o n & Ickert , 1998) . F o r examp le , before M b a n x was l aunched, a lot o f w o r k had gone into the conceptua l i za t ion o f products and services o f fered , m a k i n g M b a n x a dist inct bus iness , not just an add-on serv ice to the ex i s t ing serv ice por t fo l i o (Barc lay , 1998). B a n k i n g i n the Internet shou ld be more than just b a n k i n g , mean ing that some other non-bank ing funct ions , such as E-commerce , t i cket purchase and c o m m u n i t y event, must be added (Wafer , 1998). Even tua l l y , b a n k i n g serv ices on their o w n m a y not be c o m p e l l i n g enough to increase the usage rate o f Internet bank ing . There must be a c r i t i ca l mass o f other wo r thwh i l e services that users can access (Dan ie l & Storey, 1997). H e n c e Hi2: The issues in developing appropriate services and products on the Internet environment are not related to banks' adoption intent (r <l0.3l). Management Support. A s f ound i n one survey , the l a ck o f commi tmen t and awareness at senior l e ve l was the b iggest issue hamper ing the on-l ine deve lopment . A h igher l eve l o f management support w o u l d p rov ide the team w o r k i n g on Internet b a n k i n g deve lopment w i t h a h igher o rgan iza t iona l status (Dan ie l & Storey, 1997). W i t h o u t management support , there m a y be a l a ck 2 1 "Channel Management" was not hypothesized because the result from Q-sort analysis suggested that its measurement items were too ambiguous to fit into any factor category. Items have been eliminated or merged into other factor categories. 2 2 For large banks, integrating the Internet with existing delivery systems will be much more expensive than setting up an Internet bank from scratch. 13 o f resources for Internet b a n k i n g deve lopment , i n c l u d i n g capi ta l and IT support ( O ' S u l l i v a n , 1998). O n the other hand , management ins ight and fores ight w i l l fac i l i tate exper imenta t ion o f Internet b a n k i n g , hence l ead ing to an ear ly adopt ion dec i s ion (Wafer , 1998). Therefore H13: Level of management support to Internet banking implementation is not related to banks' adoption intent (r<l0.3l). Technical Context. T e c h n i c a l d i f f i cu l t i es can a lso be found i n operat ing Internet b a n k i n g . A s the n u m b e r o f channels prol i ferates, banks m a y f i n d it d i f f i cu l t to integrate the Internet w i t h the ex i s t ing systems. Integrat ion issue has di f ferent facets. It m a y be about ma in t a in ing the f l ex ib i l i t y , in teroperab i l i ty and c o m m u n i c a b i l i t y 2 3 o f the entire system (Wafer , 1998), about ba l anc ing the trade-off between the c o m p l e x i t y o f integrat ion and the potent ia l for incons is tent systems data ( T o w e r G r o u p , 1996), about ach i ev ing the cons is tency o f i n t e r f a c e s 2 4 ( R o b i n s o n , 1998), or even about de f i n ing the respons ib i l i t y for ma in ta in ing the websi te . T w o survey f ind ings have s h o w n that respons ib i l i t y for websi te maintenance va r i ed from marke t i ng department to I T department (Grant Tho rn ton L L P 1996; B o o z , A l l e n & H a m i l t o n , 1997). H e n c e H14: Technical challenges from Internet banking implementation are not related to banks' adoption intent (r<l0.3l). Section 7 Construct Validity: Q-Sort Analysis B a s e d on the factors ident i f i ed , 56 in i t i a l survey i tems measur ing h o w bank execut ives w o u l d perce i ve these factors were deve loped ( A p p e n d i x 2) . These i tems were des igned to tap into va r ious aspects o f the factors. In order to ve r i f y the convergent and d i sc r im inant v a l i d i t y 2 5 o f the survey i tems, a Q-Sort A n a l y s i s was conducted . Spec i f i c a l l y , the ana lys is was in tended to ensure that i tems i n the survey were cons is tent ly g rouped w i t h i n par t i cu lar factor categor ies, and amb iguous ( f i t t ing into more than one factor category) or indeterminate ( f i t t ing into no factor category) i tems e l iminated . In the procedure , each i t em was pr in ted on a ca rd and a l l cards were then shuf f l ed into r a n d o m order. T e n j u d g e s 2 6 were asked independent ly to sort the cards into d i f ferent categories and g ive them labels . A s an attempt to m i n i m i z e the potent ia l o f 2 3 Flexibility means that addition or removal o f channels will not require the replacement o f the entire system. Interoperability and communicability mean that when a new channel is added, all it needs is to define the communication protocols, so that it can channel communication between the outside world and the existing internal network. 2 4 A lot o f Internet and voice responses are developed and maintained by different departments, and when they update their records, there is no consistency. 2 5 A n item is considered to demonstrate convergent validity with the related construct, and discriminant validity with the others if it is consistently placed within a particular category (Moore & Benbasat, 1991). 14 " i n t e r p r e t a t i o n a l c o n f o u n d i n g " , j u d g e s w e r e n o t t o l d w h a t t h e u n d e r l y i n g f a c t o r s w e r e . I n s t e a d t h e y w e r e a s k e d t o d e f i n e t h e i r o w n l a b e l s ( M o o r e & B e n b a s a t , 1 9 9 1 ) . R e s u l t s o f t h e Q - S o r t A n a l y s i s a r e s u m m a r i z e d i n a n I t e m s P l a c e m e n t M a t r i x , w h i c h s h o w s h o w m e a s u r e m e n t i t e m s w e r e g r o u p e d a n d l a b e l e d b y t h e j u d g e s ( A p p e n d i x 3 ) . D i a g o n a l e n t r i e s i n t h e m a t r i x s h o w t h e n u m b e r o f i t e m s t h a t w e r e p l a c e d w i t h i n t h e t a r g e t e d c a t e g o r i e s , w h i l e t h e l a s t c o l u m n g i v e s t h e p e r c e n t a g e o f c o r r e c t p l a c e m e n t s . A h i g h p e r c e n t a g e c a n b e c o n s i d e r e d as a h i g h d e g r e e o f c o n s t r u c t v a l i d i t y . O f f - d i a g o n a l e n t r i e s o n t h e o t h e r h a n d a r e t h e n u m b e r o f i t e m s t ha t w e r e p l a c e d o u t s i d e t a r g e t e d c a t e g o r i e s . I f o f f - d i a g o n a l e n t r i e s s h o w c l u s t e r i n g o f i t e m s , t h e r e i s p o t e n t i a l t ha t i t e m s w e r e m i s - c l a s s i f i e d . T h e s e i t e m s s h o u l d t h e n b e r e - e x a m i n e d a n d r e - c l a s s i f i e d . I f s c a t t e r i n g o f i t e m s o c c u r s , i t e m s s h o u l d b e r e w o r d e d o r e l i m i n a t e d a s t h e y a r e t o o i n d e t e r m i n a t e o r a m b i g u o u s t o f i t i n t o a n y p a r t i c u l a r c a t e g o r i e s . T h e r e s u l t o f t h e Q - s o r t A n a l y s i s i s s o m e w h a t e n c o u r a g i n g , n o t o n l y b e c a u s e s o m e c a t e g o r i e s h a v e a v e r y h i g h p e r c e n t a g e o f c o r r e c t p l a c e m e n t s , b u t a l s o b e c a u s e f o r t h o s e c a t e g o r i e s t ha t h a v e a l o w p e r c e n t a g e o f c o r r e c t p l a c e m e n t s , t h e p r o b l e m s w e r e c o n s i s t e n t l y c a u s e d b y s o m e p a r t i c u l a r i t e m s . T h e s e i t e m s w e r e r e p h r a s e d o r e l i m i n a t e d from t h e s u r v e y . E x a m i n a t i o n o f t h e I t e m s P l a c e m e n t M a t r i x h a s l e d t o s o m e c h a n g e s t o t h e s u r v e y i t e m s , a s e x p l a i n e d i n A p p e n d i x 4 . A s a r e s u l t , o n l y 4 5 i t e m s w e r e r e t a i n e d as p o t e n t i a l f a c t o r s t o I n t e r n e t b a n k i n g d e c i s i o n a n d as initial predictors o f t h e i n t e n t t o a d o p t I n t e r n e t b a n k i n g . T h e y h a v e b e e n h y p o t h e s i z e d i n t o 14 m a i n antecedent factors, a s p r e s e n t e d i n t h e f o l l o w i n g t a b l e . B a s e d o n t h e s e c h a n g e s , a s u r v e y w a s p r o d u c e d a n d d i s t r i b u t e d a c c o r d i n g l y . A l l judges are graduate students of University of British University, specializing in MIS and having certain degree of knowledge in construct validity. 2 7 "Interpretational confounding occurs as the assignment of empirical meaning to an unobserved variable (e.g., factor) other than the meaning assigned to it by an individual priori to estimating unknown parameters (Moore & Benbasat, 1991, P.200)." 15 Hypothesized Category Hypothesized Antecedent Factor Number of Survey Questions Strategic Mot iva t ion 1. Business Needs 2 2. Strategic Fi t 2 3. Goa l Congruence 2 Valuat ion o f Internet 4. Perceived Eff ic iency as Del ivery 4 Bank ing Channel 5. Perceived Significance as 3 Del ivery Channel 6. Business Opportunities 3 Customer Demand 7. Customer Behavior 4 8. Customer Demographics 4 9. Technical Capabili t ies o f Us ing 3 the Internet Environmental Influences 10. Market Competi t ion 4 11. Regulatory Constraints 3 Operational Context 12. Service and Product 3 Development 13. Management Support 3 14. Technical Challenges 5 Section 8 Theoretical Foundations The discussion in the above sections has led to the formulation of the tentative research model as depicted in Figure 1, which focuses on the identification of the antecedent factors of Internet banking decision and on how these antecedent factors are affecting the intent level of adopting Internet banking. In context, this model draws on the theoretical framework of Theory of Planned Behavior (TPB) and integrates the concept of intention-based behavior. An Application of TPB: The factors tested in this paper can be thought of as the constructs in a TPB-based model, as depicted in Figure 2 (Ajzen, 1988). T P B asserts that one's actual behavior is based on the behavioral intention and that behavioral intention is formed by three basic determinants: the attitude towards behavior, subjective norm and perceived behavioral control. The attitude towards behavior is defined as how the individual evaluates {i.e., feeling of favorableness or unfavorableness) performing the target behavior, while subjective norm refers to the individual's perception that most people who are important to him think he should or should not perform the behavior in concern. Perceived behavioral control is the perception of the ease of or difficulty in performing the behavior, which reflects the individual's perception of internal and external constraints or facilitators on the behavior. Generally speaking, an individual has a stronger intention to perform a behavior when he evaluates it positively, believes that significant 16 others th ink he shou ld pe r f o rm it, and perce ives a h i g h cont ro l over the factors that m a y prevent the behav ior . A s such, the factors i n this study can be mapped to T P B constructs as f o l l ows . TPB Constructs Model Constructs Of This Study Actual Behavior Ac tua l adoption decision o f Internet banking Behavioral Intention Intent to adopt Internet banking Attitude Towards Behavior Strategic Mot iva t ion (i.e., Business Needs, Strategic Fi t , G o a l Congruence) Valuat ion o f Internet Bank ing (i.e., Channel Eff ic iency, Business Opportunity) Subjective N o r m Channel Significance Marke t Competi t ion Customer Demand (i.e., Customer Behavior , Demographics and Technical Capabilit ies) Perceived Behavior Control Regulatory Constraints Operational Context (i.e., Product and Service Development, Management Support, Technical Challenge) T h e strategic mot i va t i on and va luat ion o f Internet bank i n g (except the perce i ved s i gn i f i cance o f Internet bank ing) are equated to the attitude towards behav io r because they represent h o w Internet bank i ng is eva luated i n terms o f pe rce i ved benef its and compat ib i l i t y w i t h ex i s t ing needs, strategies and goals. Pe r ce i ved s ign i f i cance o f Internet bank ing , market compet i t i on and cus tomer demand are aspects o f subject ive n o r m because they are the s ign i f i cant referents and pressures that urge banks to of fer Internet bank ing . Regu la to ry constraints and operat ional d i f f i cu l t i e s are pa ra l l e l to pe rce i ved behav io r cont ro l because they are the pe rce i ved imped iments and obstacles to Internet bank i ng imp lementat ion . A s a matter o f fact, the factors demonstrated i n p rev ious research to be s ign i f i cant factors o f techno log i ca l adopt ion can also be incorporated into the T P B f ramework , and related to the m o d e l constructs i n this study. Tab le 1 compares these factors to the m o d e l constructs i n this paper. Individual Intention and Organizational Decision. In this analys i s , bank execut ives were targeted as study subjects. In a fash ion, the study is t r y i ng to use the adopt ion intent ion o f the ind i v idua l s to pred ict the intent ion at an organ izat iona l l e ve l . Th i s approach is based on the premise that these bank execut ives have p r i v i l eged access to the organ izat ion i n fo rmat ion and are the salient actors i n Internet bank ing adopt ion decis ions. T h e y share a c o m m o n set o f o rgan i z i ng 17 principles about their roles, their organizations and the industry. Under such a shared system, they act with collective goals, visions and ideas in mind in a specific area, for example, about adoption of the Internet as a delivery channel. Their individual perspectives towards Internet banking directly influence their intent to act, which then translates into individual adoption decision. Such a collective intent to act w i l l result in collective action, which eventually shapes the acts that are subscribed to the organization. Independent Variable. In the qualitative study, 45 initial predictors were identified as the determinants o f the Internet banking decision. They were also expected to have predictive power on the dependent variables, the adoption intent. However, they have not been directly measured against the dependent variables. Instead, they have been grouped into a smaller number o f common antecedent factors that ultimately represented the independent variables of the model. In a statistical context, the model is exploratory because it intends to identify the actual factor structure by estimating the extent (i.e., factor loadings) to which the speculated initial predictors are related to the common antecedent factors, and generating '•'•factor scores" to represent initial predictors on the common antecedent factors. This was achieved by factor analysis. Dependent Variable. The "intent to adopt" Internet banking functions is the dependent variable o f the model. The model was developed in such a way that it could discriminate the level o f intent based on the independent variables, the antecedent factors. It was also speculated that the level o f intent might vary with how the Internet would be adopted in business operations, which has been classified into five functional categories or "feature sets" o f banking functions. That is, how the Internet can be used as an information delivery medium, a marketing tool, a value-added service, an account transaction platform, and an electronic commerce opportunity. In the analysis, the relationship between each feature set and the antecedent factors was examined. Section 9 Survey The survey was designed mainly to measure bank managers' perceptions of the decision factors of Internet banking and their level of intent to adopt Internet banking functions (Appendix 5). The level of intent was measured in Section 1. For each feature set, the level o f adoption intent was estimated by several measurement items, each representing a banking function that can be offered via the Internet, as shown in Table 2. The classification scheme emerged from a consolidation o f studies in functionality o f Internet banking (Diniz, 1998; Booz, A l l en & Hamilton Ltd. ; Meridien Research Ltd . & M i l l e r Freeman, 1997). Measurement items in Section 2 to Section 6 were 18 concerned with the decision factors. They all have been designed to find out how the initial predictors identified in qualitative study were perceived by bank managers. Section 7 was intended to solicit background information of the respondents, in which an item verifying respondents' knowledge in Internet banking development within their organization was also included. As an effort to supplement the analysis on the decision factors, several "normative questions" were also included in each section of the survey, with the exception of Section 7. Responses to these questions were intended to provide a higher-level perspective of decision factors by identifying who it is who plays significant roles in "framing" the issues behind the factors. These questions were intended to uncover the influences that shaped bank managers' perceptions of the decision factors. Specifically, they were intended to identify who determines, regulates or polices the domain of issues associated with each factor. However, choices were restricted to those parties who the author believed to be influential elements in the issue domain28, including respondents' organization, the banking industry, government, financial intermediaries and customers. Section 1 0 Survey Sample Sample Size. Based on a leading financial directory (Thomson Financial Publishing, 1997), a mailing list of 1237 individual banks or depository institutions was compiled as the survey sample, 246 from Canada and 991 from the USA. The 246 Canadian institutions included almost all the registered banks and depository institutions in Canada. They included domestic banks, foreign banks, credit unions and trust companies. Since the banking industry in the U S A is characterized by the large number of banks of various sizes, only banks from the 1000-list were selected29. Targeted respondents were those senior bank executives who have the perceptive necessary to serve as knowledgeable informants about Internet banking development within their organization. This was verified by one question included in the survey. Survey Response. The original surveys were first distributed in late February of 1999, which gave a response rate of about 10%. Follow-up letters were sent one month later, increasing the initial response rate by 1%. Because of this insignificant difference, an analysis of non-response bias has 2 8 The selection was based on the personal judgement of the author in consideration of materials studied in qualitative study. 19 not been conducted. Of the 1237 surveys sent, 55 could not be delivered because of unknown addresses or unknown recipient, meaning that only 1182 surveys could be successfully delivered. Of the 1182 surveys sent, 132 responses were received, giving a response rate of 11%. However, of all the received responses, only 104 were usable. Reasons for non-usable responses mainly are: respondents' insufficient knowledge in Internet banking and respondents' refusal to participate. Response statistics are summarized as follows. Del ivered Responses Response Usable Non-usable Surveys Rate Responses Responses Canada 231 56 24%. 1 42 14 U S A 951 76 8% 62 14 Total 1182 132 11% 104 28 Section 11 Descriptive Statistics 11.1 Perception of Initial Predictors The statistics in Table 3 provide an understanding of how the factors identified in the qualitative study were perceived by bank managers. Overall, the mean scores are very high in that most of them have a value greater than 3.5. This can be interpreted in a way that these factors will, to a fairly significant extent, influence the Internet banking decision in the way they have been believed to. Therefore, in a sense, these factors do exist as factors that bank managers consider when implementing Internet banking. Some relatively higher scores have been reported in "Business Need", "Strategic Fit" and "Goal Congruence", meaning that implementing Internet banking could significantly satisfy a bank's business need, declared mission and organizational need. This suggests that the implementation of Internet banking is strategically motivated. The finding also suggests that the Internet is widely believed as an efficient channel in delivery banking services because the factor mean scores under "Perceived Efficiency" are also very high. Conversely, the factors under the category of "Regulatory Constraints" have a relatively lower mean score (i.e., less than 3), implying that regulatory and legal issues relatively are not as much of a barrier as they were believed to be. 11.2 Level of Intent to Adopt Internet Banking Table 4 summarizes the level of intent bank managers had in adopting particular Internet banking functions. As anticipated, the Internet has already been widely used as an "Information Delivery Several banks in the top-1000 list were not included in the sample because their addresses were not provided. 20 M e d i u m " because a s ign i f i cant numbe r o f respondents have c o n f i r m e d that the Internet is be i ng used as a m e d i u m to p rov ide i n fo rma t i on about their o rgan iza t ion and b ranch loca t ion . There are a lso a fa i r l y large number o f adopters o f funct ions i n the feature set o f " M a r k e t i n g T o o l " , i nd i ca t ing that the Internet is a lso c o m m o n l y adopted as a ma rke t i ng too l . F o r those non-adopters i n this feature set, the l eve l o f adopt ion intent is rather m i x e d and there is no dominan t score. O f a l l funct ions under the category o f "Va lue-added Se rv i ces " , those c o m m o n funct ions l i ke E-mai l , hot- l inks and ca lcu la tor mos t l y have a l ready been p rov ided . O f those funct ions that have not been o f fe red , search engine, d i s cuss ion group and software d o w n l o a d have rece i ved a ve ry l o w score o f adopt ion intent. A n o t h e r important f i nd i ng is that today more banks are o f f e r ing more advanced funct ions th rough the Internet. M o r e than 4 0 % o f banks surveyed i n this study have a l ready p r o v i d e d services i n b i l l payment and fund transfer th rough the Internet. T h i s contradicts p rev ious research ( D i n i z , 1997) where o n l y about 1 5 % o f s tudied banks had of fe red these two func t ions . M e a n t i m e , a m o n g those banks that do not have these funct ions on their websi te , the ma jor i t y o f t hem have ind ica ted a ve r y h i g h l eve l o f adopt ion intent. It m a y be an ind i ca t ion that, i n the near future, funct ions o f these types w i l l become bas ic features o f Internet b a n k i n g . F i n a l l y , Internet-based e lect ron ic c o m m e r c e i n banks is p roved to be at an ear ly stage because the n u m b e r o f adopters i n this area is s t i l l v e r y ins ign i f i cant . O n l y a sma l l percentage o f respondents ind i ca ted a ve ry h i g h l eve l o f adopt ion intent. 11.3 Normative Responses Tab l e 5 summar izes the responses to the normat i ve quest ions. E v a l u a t i o n o f the result is based on the phys i c a l count o f cho ices made i n the normat i ve quest ions o f each sect ion. It is pa lpab le that f i nanc i a l intermediar ies and government , i n general , do not have m u c h in f luence i n the issue d o m a i n associated w i t h the dec i s ion factors, and the in f luence o f the b a n k i n g indust ry is mos t l y re la ted to the issues i n external env i ronment . T o a very great extent, these responses a lso indicate that customers and the bank i t se l f are the ones w h o w i l l mos t in f luence wha t issues w o u l d be cons ide red w h e n imp l emen t i ng Internet b a n k i n g . Internet Banking Functionality. In regard to the func t iona l i t y o f f e red through the Internet, customers were mos t l y r e cogn i zed as the ones w h o w o u l d most in f luence the type o f services that shou ld be of fered through the Internet (q2, q 3 ) 3 0 . M e a n w h i l e , the bank was be l i e ved to be the one Bracketed is the measurement item number of the survey. 21 w h o a s s u m e d t h e r o l e i n r e g u l a t i n g t h e b a n k i n g a c t i v i t i e s , m a k i n g s u r e t h a t I n t e r n e t b a n k i n g f u n c t i o n a l i t y w a s a p p r o p r i a t e l y s e l e c t e d ( q 4 ) . Strategic Motivation. I t w a s a l s o b e l i e v e d t ha t c u s t o m e r s w o u l d m o s t i n f l u e n c e b a n k s ' I n t e r n e t b a n k i n g s t r a t e g y b e c a u s e i n t h e b e l i e f o f b a n k m a n a g e r s , I n t e r n e t b a n k i n g s t r a t e g y s h o u l d b e c o n s i s t e n t w i t h t h e n e e d s o f c u s t o m e r s ( q l 1, q l 2 ) . D e s p i t e t h i s , t he b a n k w a s s t i l l t h e o n e w h o d e t e r m i n e d h o w t h e I n t e r n e t b a n k i n g s h o u l d b e s t r a t e g i c a l l y i m p l e m e n t e d ( q l 3 ) . Valuation of Internet Banking. T h e r e s u l t s s u g g e s t t ha t e v a l u a t i o n o f I n t e r n e t b a n k i n g i s s t r o n g l y i n f l u e n c e d b y c u s t o m e r s . T h a t i s t o s a y , t h e v a l u e o f I n t e r n e t b a n k i n g c a n b e r e a l i z e d o n l y i f i t i s v a l u a b l e t o c u s t o m e r s ( q l 7 ) . E v e n t h o u g h the b a n k i n g i n d u s t r y w a s b e l i e v e d t o b e t h e m a j o r s o u r c e o f i d e a s o n i m p r o v i n g t h e v a l u e o f I n t e r n e t b a n k i n g ( q l 8 ) , i t w a s s t i l l t h e c u s t o m e r s w h o p r o v i d e d t h e n e c e s s a r y f e e d b a c k f o r i m p r o v e m e n t o f I n t e r n e t b a n k i n g s e r v i c e s ( q l 9 ) . Customer Demand. O v e r w h e l m i n g l y , t h e b a n k i t s e l f w a s b e l i e v e d t o t h e o n e w h o w o u l d d e t e r m i n e w h i c h I n t e r n e t b a n k i n g s e r v i c e s c o u l d m e e t c u s t o m e r d e m a n d a n d h o w t h e y m i g h t d o t h a t ( q 2 3 , q 2 4 ) . B u t w h e n b a n k m a n a g e r s w e r e a s k e d w h o w o u l d d e c i d e i f t h e I n t e r n e t b a n k i n g s e r v i c e s p r o v i d e d c o u l d m e e t c u s t o m e r s ' e x p e c t a t i o n s , t h e i r c h o i c e s w e r e s p l i t b e t w e e n c u s t o m e r s a n d b a n k s ( q 2 5 ) . Environmental Influences. I n t h i s a r e a , t h e r e s p o n s e s w e r e m i x e d . T h e b a n k i n g i n d u s t r y a n d c u s t o m e r s w e r e b e l i e v e d t o b e i n f l u e n t i a l e l e m e n t s i n t h e e x t e r n a l e n v i r o n m e n t t h a t b a n k s s h o u l d c o n s i d e r w h e n m a k i n g a n I n t e r n e t b a n k i n g d e c i s i o n ( q 2 8 ) . W i t h r e g a r d t o t h e p a r t y t ha t w o u l d b e a b l e t o p r o v i d e i n f o r m a t i o n o n h o w t o b e s t o p e r a t e I n t e r n e t b a n k i n g , t h e b a n k i n g i n d u s t r y , c u s t o m e r s a n d b a n k s t h e m s e l v e s w e r e a l l b e l i e v e d t o h a v e t h i s a b i l i t y ( q 2 9 ) . A s t o the c h o i c e o f t h e b e s t i n d i c a t o r o f p r o b l e m s i n t h e e x t e r n a l e n v i r o n m e n t , t h e b a n k i n g i n d u s t r y a n d c u s t o m e r s w e r e m o s t l y c h o s e n ( q 3 0 ) . Operational Context. I t w a s b e l i e v e d t ha t t h e b a n k i n g i n d u s t r y , i n c l u d i n g b a n k s t h e m s e l v e s , w a s q u i t e c a p a b l e i n i d e n t i f y i n g o p e r a t i o n a l f a c t o r s t ha t w o u l d a f f e c t I n t e r n e t b a n k i n g d e c i s i o n ( q 3 4 ) . B u t i t w a s the b a n k s t h e m s e l v e s w h o w o u l d f i g u r e o u t a n d d e t e r m i n e h o w t h e I n t e r n e t b a n k i n g s i t e s h o u l d b e o p e r a t e d ( q 3 5 ) . I n d e t e r m i n i n g i f t h e I n t e r n e t b a n k i n g s i t e w a s b e i n g o p e r a t e d i n a n e f f e c t i v e w a y , c u s t o m e r s c o u l d d o s o as w e l l ( q 3 6 ) . 22 Section 12 Model Validation: A Quantitative Analysis 12.1 Factor Analysis on Initial Predictors 12.1.1 Objectives There are three objectives for conducting a factor analysis. First, the qualitative study has produced a fairly large number of survey items (45), each of them could be treated as an initial predictor variable to the intent to adopt. So it makes sense to describe this large set of predictor variables in terms of a small number of factors for further analysis. Second, in order to study the individual contribution of each predictor variable in explanation of variance of dependent variables, factor analysis was used to mitigate possible multicollinearity among the initial predictor variables. A new set of uncorrelated independent variables was generated using factor analysis. Third, initial predictors identified in the qualitative study were pre-hypothesized into different groups based on the logical judgement of the author. Factor analysis was used to verify the clustering of the initial predictors. 12.1.2 Procedures Approach. The approach of factor analysis in this study is exploratory in a sense that it is intended to identify the actual factor structure of Internet banking decision. It is a theory- generating study, rather than a theory-testing study. It is not a confirmatory study because predictor variables were identified based on literature review rather than on empirical foundation. The analysis attempts to determine how many common antecedent factors are present to affect the Internet banking decision, as well as the pattern of relationship between the common factors and the predictor variables. Extraction of Provisional Factors. Principal component analysis, was adopted to extract a set of uncorrelated provisional factors required by the factor analysis. In determining the number of significant factors that should be retained for further analysis, Kaiser's criterion was employed. In that, only factors with eigenvalues greater than 1 were retained. Rotation Method. Orthogonal rotation was used because rotated new factors could remain significantly uncorrelated. Again, uncorrelated factors were desired in this study because of the intention of assessing contribution of individual factors to the dependent variables. Of all the orthogonal rotation methods, Kaiser's Varimax was adopted because this would allow factors to 3 1 References on factor analysis are from Manly (1986) and Stevens (1996). 23 load high on a small number of predictor variables and low on other predictor variables. Quartimax was not chosen because it would make each predictor variable load mainly on one single factor and interpretation of factors would be more difficult (Stevens, 1996). 12.1.3 Results Factor Structure. Eleven common factors were extracted from factor analysis. These common factors can be treated as empirically proved antecedent factors that bank managers will consider when implementing Internet banking. Output of the analysis is summarized in Tables 6 and 7. Table 6 presents the percentage of variance in predictor variables that is explained by the extracted provisional factors. As seen, these provisional factors in total can account for 70% of the total variance. The Factor Loading Matrix as given in Table 7 shows how the common factors have loaded into the predictor variables. Factor loadings in the matrix represent the correlation between the predictor variables and the common factors. High loading indicates that the predictor variable is highly related to the factor. Reliability of the factors extracted was also examined. It was suggested that factors with 4 or more loadings above 0.6 in absolute value were reliable, regardless of sample size (Stevens, 1996). Even though there are several factors that just have 3 loadings, the author still concludes that they are reliable because their loadings are very high, and some of them have loading greater than 0.8. However, Factor 11 is still considered unreliable because it only has 2 loadings. Overall, about 80% of all the highest loadings has a value greater than 0.6 (many of them even have loading greater 0.8), indicating that the common factors are reliable in representing the predictor variables. Furthermore, the communality of most predictor variables is very high, with a mean of 0.73. That is to say, most of the variance of the predictor variables can be accounted for by these eleven common factors. It can be concluded that these eleven common factors effectively represent the predictor variables and can be used as the independent variables for further analysis. Examination of the result has also led to the conclusion that the grouping of predictor variables to a great extent is consistent with the way they were pre-grouped initially. For example, measurement items from q6 to qlO in the survey were grouped to measure "Strategic Motivation", which now cluster together and tap into the common Factor 1; measurement items from q27a to q27c, which were pre-grouped as "Regulatory Constraints", now are represented by the common Factor 7; all measurement items (q32a to q32c) under the group of "Management Support" now hang around the common Factor 8. This confirms the initial factor structure from 24 the proposed model. The final grouping o f the predictor variables and labeling o f the obtained common factors are now concluded in the following table. Predictor Variable Common Label (Measurement Items) Factor Loaded q6-q!0, ql5c, q ! 6 a - S l 6 c Factor 1 Strategic Motivation and Business Opportunity q ! 4 a - q l4d Factor 2 Perceived Efficiency of Internet Banking q21a-q21d, q20c- Factor 3 Customers' Demographics, Perceived Usefulness and Ease of q20d Use oflnternet Banking q33a - q33e Factor 4 Technical Challenge q22a - q22c Factor 5 Customers' Technical Capabilities of Using the Internet q l 5 a - q l 5 b , q26d Factor 6 Perceived Significance of Internet Banking, Timing of Market Entry q_27a - q27c Factor 7 Regulatory Constraints q32a - q32c Factor 8 Management Support q31 a - q31 c Factor 9 Service and Product Development q26a - q26c Factor 10 Market Competition q20a - q20b Factor 11 Customers' Prior Experiences in Using the Internet and Perceived Risk in Using Internet Banking Factor Scores: In order to make the results of factor analysis usable as independent variables for further analysis, factor scores for each observation have also been estimated 3 2. Factor score is an indication of relative importance of the factor to each observation. Higher value represents higher importance. They were used as the independent variables in discriminant analysis as discussed in the subsequent section. The estimated factor scores have also been proved to be uncorrelated and normally distributed 3 3. Uncorrelated factor scores allow the assessment o f contribution o f individual factors to the intent to adopt Internet banking functions. Normality is an underlying assumption required by discriminant analysis. 12.2 Discriminant Analysis34 12.2.1 Objectives In discriminant analysis, factor scores estimated from factor analysis were used as independent variables to discriminate bank managers' intent level to adopt Internet banking. Specifically, it achieves two objectives. In an explanatory context, it determines which of the common factors have contributed most to discriminating among groups o f "intent to adopt". This is concerned with identifying certain linear discriminant functions that separate groups with different levels o f intent to adopt Internet banking. In a predictive context, the result of the discriminant analysis w i l l allow assignment of new observations to one o f the "intent to adopt" groups based on observations' resultant factor scores. Estimation of factor scores involves matrix transformation that is usually handled by statistical software. SPSS was used in this study. 3 3 For correlation, Pearson and Spearman tests were used. For normality, Normal Probability Plot was used. 25 12.2.2 Procedures Underlying Assumption. The optimality of discriminant analysis is conditional upon two assumptions. The first is the multivariate normality of independent variables. In definition, when the independent variables being studied appear to be normally distributed, then it is assumed that the joint distribution is also multivariate normal (Manly, 1986). Fulfillment of this requirement has already been confirmed in factor analysis, it so will not be discussed in the following sections. The second assumption is the equal within-group covariance matrix. That is, the covariance matrix of the dependent variables in each group must be identical, meaning that group dispersion structure across groups must be equal. To test this requirement, the Box's M Test has been used in this study, in which the null hypothesis is equal covariance matrices between groups. Prior Grouping of "Intent to Adopt". Discriminant analysis involves deriving linear combinations of independent variables that will discriminate between the "prior defined" groups. Therefore, as a preliminary procedure to the analysis, each observation has to be assigned into a mutually exclusive group. In this study, groups have been defined according to the "response category" respondents would assign to each item measuring their level of intent to adopt Internet banking. The response categories were represented by a rank of scores in a 5-point Likert-scale, in which scores of 1 and 5 respectively represented a very low and very high level of intent. Since it was also expected that some banking functions might have already been adopted by the respondent's organization, an extra score of 6 was created to represent such a group. It must be noted that scores used here only represent the level of "intent to adopt" ranked by respondents, and that this 6-categorical-score is not an interval scale. No conclusion can be drawn about the meaning of distance between scale positions, and it can only be interpreted in a way that, for example, score 6 represents an intent level higher than that of all other scores, but not indicating how much higher it is. It is simply an ordinal scale that allows respondents to rank their intent to adopt. It is also because of that a respondent's scores could be totaled, i.e., "summated rating scale" (Moser, 1972), and averaged to give a mean rank that represented its attitude towards Internet banking adoption. In such a measuring process, the respondents' overall responses to each feature set of Internet banking functions (e.g., "Marketing Tool") were measured by their "total score", which was the sum of the scores of the categories they had endorsed for each of the measurement items in the feature set. The total score then was averaged, References on discriminant analysis are from Marcoulides & Hershberger (1997), Manly (1986), Dillon & Goldstein (1984), and Pedhazur (1982). 26 producing a mean score ranging from 1 to 6. Based on this mean score, the categorical group of intent of the observation for each feature set could be decided. Categorical Groups of Intent. In the original plan, responses would be categorized into 5 groups because respondents' mean scores could fall into one of the five equal intervals between 1 and 6. However, in the analysis, respondents were classified into three groups in such a way that each group would have roughly an equal number of observations. There were two reasons for not having five categorical groups of intent level. First, the number of survey responses was not large enough (about 100) to produce sufficient number of observations for all groups of intent. Second, the mean scores obtained were not evenly distributed between 1 and 6. For example, in the feature set of "Account Transaction Platform," there was no score falling into the interval between 2 and 3, while the interval between 5 and 6 had 49 observations (i.e., about 49% of total number of observations). Details of frequency distribution of mean scores can be referred to in Table 8. This uneven distribution in the number of observations would easily violate the assumption of equal within-group covariance matrices35. Having an equal number of observations in each group will increase the chance of having equal covariance matrices. Grouping Procedure. The grouping procedure placed all observations according to their mean scores, so that each of them would be assigned a percentile position. Based on the percentile position, observations could be assigned into different groups. The first group then was defined in such a way that it would include all the observations whose percentile position was in the first 33 percentile. In other words, the first group would have all observations with lowest self- assessed mean scores. The second group was defined similarly so that it would have all observations positioned between the 33rd and the 67th percentile. Eventually, the third group had the remaining observations. The definition of the final three groups is given as follows. Categorical Group Definition Group 1 Observations whose ranked position was in the first 33 percentile Group 2 Observations whose ranked position was between the 33rd percentile and the 67th percentile Group 3 Observations whose ranked position was in the last 33 percentile. An attempt had been made to run a discriminant analysis on 5 intent groups, but was not successful because the requirement of equal covariance matrices has been seriously violated. No discriminant functions could be significantly derived. 27 Tab le 9 summar izes the range o f mean scores that has been i n c l uded i n each o f the def ined groups. It is ve ry important to note that the mean score on l y represents the l e ve l o f intent self - assessed b y the respondents, and is a " response ca tego ry " ass igned b y the respondents themselves. Number of Discriminant Functions. T h e m a i n goal o f d i s c r im inant analys i s is to construct severa l ordered and uncorre lated d i sc r im inant funct ions o f independent var iables, w h i c h can account for the d i f ferences i n the dependent var iables. O f a l l the funct ions, the f irst funct ion w i l l account for most o f the group dif ferences. The second func t i on w i l l capture as m u c h as poss ib le o f the group dif ferences not captured b y the f irst funct ion. T h e th i rd func t ion w i l l account for mos t o f the res idua l group d i f ferences not exp la ined b y the f irst two funct ions, and so forth. H o w e v e r , on l y those funct ions that can s i gn i f i cant l y account fo r the group d i f ferences w i l l be retained. In this study, Wilks' Lambda Test was used to determine what funct ions shou ld be retained. A b r i e f descr ipt ion o f this test procedure is i n c l uded i n A p p e n d i x 6. 12.2.3 Results T h e result o f the B o x ' s M Test and W i l k s ' L a m b d a Test are s ummar i zed i n the f o l l o w i n g table. Feature set of Banking Function Box's M Test Wilks' Lambda Test Test Result * Significance Level Test Result * Significance Level % of variance DF explains Information Delivery Medium Ho is rejected; Insufficient evidence to support that covariance matrices are the same 0.014 Ho is accepted at the l s l step; No discriminant function is retained; Insufficient evidence to support that at least one DF is significant 0.107 No significant discriminant function. Marketing Tool Ho is accepted; Insufficient evidence to support that covariance matrices differ 0.545 Ho is accepted at the Is1 step; No discriminant function is retained; Insufficient evidence to support that at least one DF is significant 0.232 No significant discriminant function. Value-added Services Ho is accepted; Insufficient evidence to support that covariance matrices differ 0.860 Ho is rejected only at the 1 s t step; Only the 1st discriminant function is significant to describe group differences. 0.003 93% Account Transaction Platform Ho is accepted; Insufficient evidence to support that covariance matrices differ 0.124 Ho is rejected only at the 1st step; Only the 1st discriminant function is significant to describe group differences. 0.001 77% Electronic Commerce Opportunity Ho is accepted; Insufficient evidence to support that covariance matrices differ 0.839 Ho is rejected only at the I s ' step; Only the 1 st discriminant 0.002 76% function is significant to describe group differences. (* tested at an alpha level of significance of 0.05) 28 Evaluating Equality of Covariance Matrices. The underlined and bolded significance value in B o x ' s M Test indicates that the null hypothesis is accepted, meaning that there is insufficient evidence to suggest that covariance matrices are different. In other words, the group covariance matrices are assumed to be the same. Among all the tests, only the one for "Information Delivery Med ium" could not satisfy the requirement of equal covariance matrices. It can be explained by the fact that the majority of respondents had already adopted Internet banking functions in this feature set, making even distribution o f the number of observations in each group impossible. Details o f the frequency distribution can be found in Table 8. Evaluating Significance of Discriminant Function. The underlined and bolded significance value in W i l k s ' Lambda Test indicates that the null hypothesis is rejected, meaning that there is insufficient evidence to support that all discriminant functions are not significant. In other words, at least one discriminant function is significant. The test results show that discriminant function can only be derived for the feature set o f "Value-added Services", "Account Transaction Platform" and "Electronic Commerce Opportunity". This finding has indicated well that the antecedent factors identified do not discriminate bank mangers' level of intent to adopt the Internet as an "Information Delivery Medium " and a "Marketing Tool". One possible explanation is that these two feature sets have already been widely adopted by banks as basic and undifferentiated features, regardless of how they perceive Internet banking. On the contrary, the antecedent factors are able to discriminate bank managers' level of intent to adopt the Internet as "Value-added Services ", an "Account Transaction Platform " and an "Electronic Commerce Opportunity ". It is also clear that for al l of these feature sets, there exists only one discriminant function that can significantly discriminate the intent to adopt, which in al l cases can explain a very high portion of group differences. The lowest percentage is 76% while the highest reaches 93%. Evaluating Individual Contribution. Assessment of individual contribution of antecedent factors to the level of intent is based on the respective "discriminant loadings", which are represented by the coefficients of structure matrix produced from discriminant analysis. Discriminant loading is the simple correlation between each independent variable and the discriminant function, and an indication o f relative importance of the antecedent factors on the discriminant function. H i g h discriminant loading means that the factor contributes significantly to the discriminant function. Wi th respect to the concern of how large a discriminant loading should be considered as 29 meaningful, it is only a matter of opinion. However, as suggested by Pedhazur (1982), only loadings equal to or greater than 0.3 should be treated as meaningful. As discussed above, based on the antecedent factors, discriminant analysis was unable to discriminate the group differences in level of adoption intent for the feature sets of "Information Delivery Medium" and "Marketing Tool". Therefore, analysis of the individual contribution of the factors was only carried out on the remaining three feature sets. The obtained structure matrices of these three feature sets are now consolidated into one matrix, as depicted in the following table. Consolidated Structure Matrix Discriminant Loading Antecedent Factor Account Electronic Value-added Transaction Commerce Services Platform Opportunity (p< 0.003) (p< 0.001) (p< 0.002) 1. Strategic Motivation and Business Opportunity -0.091 -0.248 0.221 2. Perceived Efficiency of Internet banking -0.024 0.252 -0.060 3. Customers' Demographics and Perceived Usefulness and Ease of Use of Internet Banking -0.115 -0.069 0.155 4. Technical Challenge -0.241 -0.381 -0.074 5. Customers' Technical Capabilities of Using the Internet -0.041 -0.168 -0.193 6. Perceived Significance of Internet Banking & Timing of Market Entry 0.244 0.340 0.453 7. Regulatory Constraints -0.120 -0.204 -0.043 8. Management Support 0.214 0.255 0.385 9. Service and Product Development 0.604 0.265 0.448 10. Market Competition 0.223 0.193 0.054 11. Customers' Prior Experiences in Using the -0.199 -0.233 -0.147 Internet and Perceived Risk in Using Internet Banking Discriminant loadings with an absolute value greater than 0.3 are underlined and bolded. In the feature set of "Value-added Services", there is a high loading (0.604) in the antecedent factor of "Service and Product Development", indicating that this factor significantly contributes to the discrimination. That is, the issues of product and service development are critical to discriminating the intent to adopt the Internet to provide more value-added services to customers. For the feature set of " Account Transaction Platform", "Technical Challenge", "Perceived Significance of Internet Banking" and "Timing of Market Entry" all have mild influence in discriminating the level of intent, but differently. The negative value in "Technical Challenge" is interpreted in a way that the technical issues will negatively affect the degree of adoption intent, thus existing as a barrier to the adoption. This suggests that the higher the challenge the technical issue is perceived to present, the lower the intent bank managers have in adopting the Internet as a 3 0 platform for account transactions. This is quite reasonable because the support of account transactions through the Internet requires a relatively higher level of interactivity and a higher security standard. Loadings in perceived significance of Internet banking and timing of market entry suggest that bank managers will have a higher intent to adopt the Internet to support account transactions on-line i f they perceive the Internet as a significant channel or believe that being an early adopter of Internet banking is strategically important. For the feature set of "Electronic Commerce Opportunity", three antecedent factors contribute to the differences in the level of intent. They are "Service and Product Development", "Perceived Significance and Timing of Market Entry" and "Management Support". Their influence in discriminating the intent level is much higher than that of other factors, with a loading of 0.448, 0.453 and 0.385 respectively. Loadings in "Management Support" suggest that participation in electronic commerce requires stronger support and commitment from management. It may be because electronic commerce for banks is still at an experimental stage and its benefits in the near future are yet to be realized. The more management support provided in this area, the higher the intent level bank managers have. Evaluating Classification Accuracy. This study uses the hit rate to evaluate classification accuracy, which is simply the proportion of the observations correctly classified into the group they come from. Two methods have been used. The first is a straightforward approach, which is simply to re-substitute all observations' resultant factor scores into the discriminant functions obtained. However, this method tends to have a bias in favor of allocating observation to the group that it really comes from because the observation has helped determine that mean score of the group. Therefore, classification of this type always gives a slightly higher number of correct classifications than the other, which is called cross-validation method. Cross-validation classification is a "leave-one-out" approach, in which the discriminant functions are derived N times, each time leaving out one observation. The discriminant functions derived without using this observation are used to classify the observation. The hit rate then is the percentage that the "left-out" cases are correctly assigned. This method can provide a relatively unbiased estimate of classification accuracy because the observation classified has been held out from estimation of the discriminant functions. Classification results from both methods are summarized in the following table. 31 Classification Result Percentage (hit rate) and number of correct classification Feature Set Straightforward Classification Group 1 Group2 Group 3 Total Group 1 Cross-validation Group 2 Group 3 Total Value-added Services 63.6% (21/33) 54.8% (17/31) 66.7% (22/33) 61.9% (60/97) 48.5% (16/33) 29% (9/31) 57.6% (19/33) 45.4% (44/97) Account Transaction Platform 80% (24/30) 63% (17/27) 52.5% (21/40) 63.9% (62/97) 60% (18/30) 29.6% (8/27) 47.5% (19/40) 46.4% (45/97) Electronic Commerce Opportunity 70% (21/30) 45.2 (14/31) 64.7% (22/34) 60% (57/95) 56.7% (17/30) 32.3 (10/31) 47.1% (16/34) 45.3 (43/95) The straightforward method provided satisfactory discriminating power of the discriminant function because the average hit rate for all feature sets is equal to or greater than 60%. The classification accuracy is lower i f the cross-validation method is adopted. Although the perception of an acceptable hit rate is rather subjective, the hit rate obtained by straightforward option is generally acceptable. The rate in cross-validation is somewhat lower, but still higher than in random choice. Section 13 Summary What are the antecedent factors? The descriptive statistics in Table 3 suggests that all the potential factors identified in the qualitative study are significant factors that bank managers will consider when making Internet banking decisions, except those under the category of "Regulatory Constraints", which are relatively less important when compared to others. The factor analysis also confirms that these potential factors can be well represented by eleven unique and major factors, namely 1) strategic motivation and business opportunity, 2) perceived efficiency of Internet banking, 3) customers' demographics, and perceived usefulness and ease of use of Internet banking, 4) technical challenge, 5) customers' technical capabilities of using the Internet, 6) perceived significance of Internet banking and timing of market entry, 7) regulatory constraints, 8) management support, 9) service and product development, 10) market competition, and 11) customers' prior experiences and perceived risk in using the Internet. How are the antecedent factors related to adoption intent? Despite the conclusion that there are eleven major factors influencing bank managers' Internet banking decisions, not all of them are able to discriminate their level of intent to adopt particular Internet banking functions. As found, only several factors, i.e., product and service development, management support, technical difficulties, and perceived significance of Internet banking and timing of market entry, have the 32 discriminating power. The findings also show that the influences of these few factors to the discriminating power vary according to the types of Internet banking functions that are intended to be offered via the Internet. Individual influence of these factors to the intent level is shown in the following table. Degree of Discriminating Power Feature Set of Internet Banking Functions Antecedent Factor Valued-added Account Transaction Electronic Services Platform Commerce Perceived Significance of Internet Banking & Timing of Market Entry Insignificant Moderate Moderate Service & Product Development Strong Insignificant Moderate Management Support Insignificant Insignificant Moderate Technical Challenge Insignificant Moderate Insignificant Hypotheses Conclusion. The results from discriminant analysis suggest that, at an alpha level of significance of 0.05, there is insufficient evidence to support the proposed hypothesis H4, H10, H12, H13 and H14, leading to the following conclusions. • (H4): The perceived significance of the Internet as a delivery channel is influential to banks' intent to adopt the Internet as a platform for account transactions (r = 0.34, p< 0.001) and an electronic commerce opportunity (r = 0.45, p< 0.002), • (H10): The timing of market entry into the internet banking market, which is a form of competitive threat, is influential to banks' intent to adopt the Internet as an account transaction platform (r = 0.34, p< 0.001) and an electronic commerce opportunity (r = 0.45, p< 0.002), • (H12): The issues of service and product development on the Internet environment are influential to banks' intent to adopt the Internet as value-added services (r = 0.60, p< 0.003) and an electronic commerce opportunity (r = 0.45, p< 0.002), • (H13): The level of management support is influential to banks' intent to adopt the Internet as a business opportunity in electronic commerce (r = 0.39, p< 0.002), • (H14): Technical issues are influential to banks' intent to adopt the Internet as a platform for account transactions (r= -0.38, p< 0.001). On the other hand, the results do not provide sufficient evidence to reject the hypothesis that the strategic motivation (HI, H2, H3), the perceived efficiency of the Internet as a delivery channel (H5), the perceived business opportunity Internet banking can provide (H6), customer demand (H7, H8, H9), and regulatory challenges (Hll) are not influential to banks' intent to adopt the Internet as an information delivery medium, a marketing tool, value-added services, an account transaction platform and an electronic commerce opportunity. 33 A revised model. To translate the findings into graphical presentation, a revised model of Internet banking adoption is created, as depicted in Figure 3. This revised model shows how the antecedent factors are related to the intent to adopt particular feature sets of Internet banking functions, in which the degree of relationship is indicated by the coefficient of correlation. Section 14 Conclusions Interference of Adoption Intent. A mapping of the factors in the revised model and the TPB constructs (as shown in the following table) reveals that discrimination of adoption intent of Internet banking is not a function of attitudinal factors, and only the subjective norm and the perceived behavioral control have the discriminating power. TPB Construct Discriminating Factor Non-discriminating Factor* Attitude Towards Behavior Nil Strategic Fit, Business Need, Goal Congruence, Perceived Efficiency, Business Opportunity Subjective Norm Timing of Market Entry, Perceived Significance Customer Demand Perceived Behavior Control Product and Services Development, Management Support, Technical Challenges Regulator Constraints * Factors that do not discriminate the adoption intent This is a very surprising result because factors parallel to attitude towards behavior are all non- discriminating factors. These factors indeed are the perceived value of Internet banking and can be directly equated to the relative advantage and compatibility with the existing organizational values. This contrasts with the findings of many studies (O'Callaghan et al., 1992; Grover, 1995; Iacovou et al., 1995; Premkumar & Ramamurthy, 1995, i & i i ; Chwelos et al., 1999) and the fundamental diffusion theory (Roger, 1985) that the perceived relative advantage and compatibility are two basic determinants of adoption behavior. One possible indication for such a situation is that the benefits of Internet banking and its consistency with strategic vision have already been recognized by banks, and have generally become primary initiatives in Internet banking adoption. But such adoption intent is interfered by the perception of the external pressure (i.e., subjective norm) and the perceived obstacles in Internet banking implementation (i.e., perceived behavior control). 34 In subjective consideration, external pressure plays a role in recognizing the significance and the legitimacy o f the Internet as an integral component of delivery system, and the importance o f being an early adopter o f Internet banking. In other words, Internet banking is being institutionalized in the banking delivery system, just like what happened to A T M . A s indicated, the greater the perceived market pressure, the greater the intent to adopt. In perceived behavior control, banks' adoption intent is disrupted by some factors that are beyond their control. The level of intent w i l l depend on such factors as the requisite resources in Internet banking implementation. These factors are specific to the difficulties in developing appropriate products and services on the Internet environment, to the technical challenges associated with the implementation and to the lack o f support from the senior management. Subject to these obstacles, banks are unlikely to form a strong behavior intention to adopt even i f they hold a favorable attitude towards Internet banking. So, it leads to a conclusion that for adoption intent o f Internet banking, attitudinal considerations are relatively less important than normative considerations and behavioral control factors. Significant and Discriminating Factors: It is necessary to point out that the results do not suggest that non-discriminating factors are not significant to banks' Internet banking decisions. For example, Table 3 reveals that almost all bank managers believed that Internet banking could significantly satisfy business need (more than 90% of respondents assigned scores o f 4 or 5 in this factor), indicating that such a belief has already become a common attitude towards Internet banking. But, based on this, it is difficult to discriminate banks' adoption intents. What really discriminates the adoption intent is the relative importance o f other factors (i.e., discriminating factor) that vary from one bank to another. The significance and discriminating power o f a factor in adoption behavior so are two different perspectives. The distinction is very important because the number of factors identified in the banking literature is so large that it is hard to draw conclusions on which factors can explain the differences in adoption behavior among banks. The distinction helps clear up such confusion by revealing what factors really exist as barriers or facilitators in adoption intent. Therefore the results should be interpreted in a way that the discriminating and non-discriminating factors together explain the importance o f the factors to Internet banking decisions, while the discriminating factors mediate the effect o f non- discriminating factors and explain the differences in the level of adoption intent among banks. 35 Competitive Differentiation. It is also surprising to see that strategic motivation fails to explain the difference in adoption intent, even though a significant majority of banks believed that Internet banking could satisfy business needs, strategic missions and organizational goals. A deeper analysis leads to the explanation that these benefits are now considered to be basic expectation from offering Internet banking. This confirms that Internet banking is no longer a competitive advantage, but a competitive necessity, and has evolved from a strong "competitive differentiator" to a basic and expected service (US Web Services, 1997). Offering Internet banking does not sharpen a bank's competitive edge, but not offering it will be a competitive disadvantage. However, this is not the end of the story. The competitive implication of Internet banking is still changing. It is not a simple matter of whether or not banks should adopt the Internet as a delivery channel, but a consideration of how to appropriately and creatively apply technology (the Internet) into operations, thus meeting the needs of customers in the changing environment, exploring more market opportunities, and creating a new set of competitive advantages. For example, making use of the inherent capabilities of the Internet in building a sophisticated customer base and tracking customer's banking behavior, thereby developing a better system that can be efficiently adjusted to the changing need of customers. These capabilities will be where banks can develop competitive differentiation and advantages. Again, examples given here do not suggest that they can always differentiate one bank from another because a differentiated product today will soon become a commodity product tomorrow. It is the ability to best use technology that allows a bank to create competitive advantages. Implications for Practitioners. An interesting issue that surfaced in the results is the importance of operational issues (i.e., product and service development, technical challenges and management support) to adoption intent. It may be a good indication that one major impediment to Internet banking adoption indeed exists within a bank's internal environment. Therefore, it will be useful to probe deeper into the aspects of these issues and study the factors that inhibit the adoption of Internet banking. As revealed, difficulty in product and service development does not emerge from account transaction activities, but is about services extended beyond traditional banking activities. This may indicate that banks are more concerned with the development of non-banking services and products than core-banking activities, such as funds transfer, balance inquiry and bill payment. It is likely because core-banking activities are standard features in a traditional service menu that they do not provide much potential for differentiation. Therefore, product differentiation does not 36 come from the core-banking activities, but is achieved through non-banking services. Perhaps it is these services that lead to the competitive differentiation and make Internet banking more valuable and attractive to customers. Accepting this premise, it can be concluded that what differentiates a bank from others in competitive context is not the technology itself (the Internet). Rather, it is the way the bank applies technology to product development. A closer look into survey responses on "Technical Challenges" reveals that security of the Internet is still a significant fear that banks have. In the author's opinion, security issues of Internet banking should be addressed as a psychological obstacle rather than a technical challenge because security technology (e.g., the use of 128-bit encryption, firewall and digital certificate) in the past few years has already greatly advanced. Banking transactions conducted through the Internet are now very secured. So, the fear is not particularly realistic, and it is likely to be the case that banks have little information about the issues. Therefore, when considering Internet banking, banks may first need to deal with the psychological fear of security issues, but not the security risk itself. This psychological barrier can be removed if more awareness of the security of Internet banking is generated among banks, not just customers. In the light that management support is a crucial element in adoption intent, top management should be more aware that their involvement, commitment and vision about Internet banking may encourage an earlier adoption decision. As noted earlier, research has proved that early technological adoption could be traced to the critical role played by champions (Reich & Benbasat, 1990; Premkumar. and Ramamurthy, 1995, i & i i ; Grover, 1995). This therefore suggests that it is imperative to develop initiatives at senior management level. The more management support given to the Internet banking implementation, the fewer obstacles bank managers will anticipate, leading to a stronger adoption intent. Section 15 Research Contributions This study is distinctive in several ways. First, it demonstrates that in addition to customer demand, Internet banking decision is also based on strategic, perceptual, environmental and operational considerations. This helps explain the low adoption rate of full functionality of Internet banking despite the promising customer demand in the future. Second, the study provides some perspectives into the influences of the supply side (i.e., the bank) on Internet banking adoption, hence supplementing and consolidating previous studies in the demand side (i.e., the customer). Third, the model reveals the pattern of relationship between the adoption intent and 37 decision factors of Internet banking, giving insights into the current barriers and facilitators in Internet banking implementation. It also suggests that adoption rate of Internet banking will be increased if banks are provided with solutions to the operational difficulties collateral to implementing Internet banking. Finally, since the adoption of Internet banking is a business decision enabled by IT (e.g., adopting the Internet as a strategy of marketing banking products and services), the model in a way correlates the adoption of IT with business strategy, advancing scholarly knowledge in notions of "fit" between IT adoption and business strategy. That is, what factors are governing the application of IT to business operations. Section 16 Limitations Some limitations of this study have to be noted. First, the response rate of the survey was rather low, giving a fairly small number of observations for quantitative analysis. This makes it difficult to differentiate the results between banks of different sizes. That is, it is unable to identify the influence of organizational size on adoption intent of Internet banking. In this aspect, it has to be pointed out that organizational size may also be a strong predictor of technological adoption because it may imply differentiation of resource availability. Second, the scope of the study is limited to the retail banking sector. Adoption of the Internet as a delivery channel in corporate banking was not examined. As believed, adoption decision for corporate banking may require a different set of considerations because corporate banking is relatively more customer-relationship emphasized and corporate clients may demand more custom-developed services and products. Third, the study is unable to differentiate the results between adopters and non-adopters of Internet banking because it is difficult to generalize a respondent as an adopter or non-adopter, unless the respondent has adopted either none or all of the Internet banking functions as represented in this study. Among all the responses received, there is a very limited number of cases indicating that the respondent is not offering any Internet banking function, and no case that the respondent is providing all Internet banking functions. Finally, there is a danger that some significant factors have not been included in the model because all model factors were mainly based on literature review specifically related to the banking industry. Factors identified in previous research, although conducted in other industries, may also play a critical role in the adoption of Internet banking and could be model constructs. 38 T a b l e 1: C o m p a r i s o n o f F i n d i n g s w i t h P r e v i o u s R e s e a r c h TPB Constructs Model Factor Factor Supported from Previous Research Attitude Towards • Business Needs • Relative Advantage (O'Callaghan et al., Behavior • Strategic Fit 1992; Premkumar & Ramamurthy, 1995, • Goal Congruence ii) • Channel Efficiency • Perceived Benefits (Iacovou et al., 1995; • Business Opportunity Chwelos et al., 1999) • Internal Needs (Premkumar & Ramamurthy, 1995, i) • Compatibility (Premkumar & Ramamurthy, 1995, i i ; Grover, 1995) Subjective Norm • Channel Significance • External Pressures (Iacovou et al., 1995; • Market Competition Chwelos et a l , 1999) • Customer Demand (i.e., • Customer Power and Supplier Trust (Hart Customer Behavior, & Saunders, 1998) Demographics and • Competitive Pressure, Exercise Power of Technical Capabilities) Trading Partners (Premkumar & Ramamurthy, 1995, i) • Being an early adopter (Premkumar & Ramamurthy, 1995, ii) • Competitive Threat, Customer Bargaining Power (Reich & Benbasat, 1990) • Customer Resistance, Depersonalization Fear (Barras, 1986) Perceived Behavior • Regulatory Constraints • Economical, Regulatory, Legal, Control • Operational Context (i.e., Institutional, Political Barrier (Barras, Product and Service 1986) Development, Management • Regulatory Environment (Burke, 1996) Support, Technical • Organizational Readiness (Iacovou et al., Challenge) 1995; Chwelos et al., 1999) • Top Management Support, Championship (Premkumar & Ramamurthy, 1995, i & i i ; Reich & Benbasat, 1990; Grover, 1995) 39 Table 2: Classification of Banking Functions in the Internet Feature Set of Functionality Definition Measurement Item Information Del ivery M e d i u m ' Offer ing general information o f the organization Corporate information Press release Branch location Market ing Too l Value-added Services Account Transaction Plat form Offer ing product information or launching promotional campaign Prov id ing extra services to create, maintain or improve customer relationship A l l o w i n g customers to access account information and conduct banking transactions on-l ine Electronic Commerce Opportunity Offer ing Web-based businesses Advert isement Offers announcement Loans, investment & account appl ication E-mai l & suggestion forms Search engine Hot l inks to other sites Discussion group Calculator Investment Adv i so r Software download Balance inquiry Statement request Transaction history B i l l Payment Funds Transfer Stock & mutual fund trading Electronic Cash B i l l presentment Smart Card Dig i ta l Certi f icate Remarks: Classification of banking functions is defined in consideration of the following 3 studies. 1. Diniz (1998): 121 bank sites from the USA were studied. About 20% were banks with assets greater than $10 billion, more than 30% between $500 million and $10 billion, and 47% below $500 million. 2. Booz, Allen & Hamilton (1997): 1240 retail banking sites around the world were visited. 3. Meridien Research (1997): over 50 of the top brokerages, banks and insurance companies in the USA were surveyed. Recruitment form was also a measurement item in the survey, but was dropped because it is irrelevant to customers' banking activities. 40 Table 3: Frequency Distribution of Evaluation Score on Initial Predicators Score Initial Predictors/ Measurement Item No. 1 Count % 2 Count % 3 Count % 4 Count % 5 Count % Mean Score Business Need q6 1 0.97 1 0.97 9 8.74 29 28.16 63 61.17 4.48 Strategic Fit q8 2 1.94 0 0 13 12.62 32 31.07 56 54.37 4.36 Goal Congruence qlO 1 0.96 4 3.85 11 10.58 37 35.58 51 49.04 4.28 Perceived Efficiency as delivery Channel ql4_a 1 0.96 6 5.77 9 8.65 50 48.08 38 36.54 4.13 ql4_b 2 1.92 0 0 7 6.73 33 31.73 62 59.62 4.47 ql4_c 1 0.96 0 0 7 6.73 42 40.38 54 51.92 4.42 ql4_d 3 2.88 9 8.65 27 25.96 25 24.04 40 38.46 3.87 Perceived Significance as Delivery Channel ql5_a 4 3.85 27 25.96 27 25.96 33 31.73 13 12.5 3.23 q!5_b 1 0.96 7 6.73 22 21.15 49 47.12 25 24.04 3.87 ql5_c 1 0.96 1 0.96 9 8.65 38 36.54 55 52.88 4.39 Business Opportunity ql6_a 2 1.92 5 4.81 22 21.15 42 40.38 33 31.73 3.95 ql6_b 4 3.88 6 5.83 25 24.27 51 49.51 17 16.5 3.69 ql6_c 5 4.85 10 9.71 41 39.81 33 32.04 14 13.59 3.4 Customer Behavior q20_a 3 2.94 10 9.8 16 15.69 46 45.1 27 26.47 3.82 q20_b 3 2.94 9 8.82 31 30.39 29 28.43 30 29.41 3.73 q20_c 2 1.96 1 0.98 20 19.61 48 47.06 31 30.39 4.03 q20_d 2 1.96 3 2.94 21 20.59 40 39.22 36 35.29 4.03 Customer Demographics q21_a 5 4.81 11 10.58 37 35.58 38 36.54 13 12.5 3.41 q21_b 2 1.92 6 5.77 28 26.92 50 48.08 18 17.31 3.73 q21_c 2 1.92 8 7.69 33 31.73 50 48.08 11 10.58 3.58 q21_d 1 0.96 12 11.54 29 27.88 48 46.15 14 13.46 3.6 Customers' Technical Capabilities q22_a 6 5.83 17 16.5 23 22.33 29 28.16 28 27.18 3.54 q22_b 2 1.94 19 18.45 23 22.33 42 40.78 17 16.5 3.51 q22_c 3 2.91 19 18.45 32 31.07 35 33.98 14 13.59 3.37 Market Competition q26_a 3 2.88 11 10.58 35 33.65 32 30.77 23 22.12 3.59 q26_b 3 2.91 14 13.59 28 27.18 37 35.92 21 20.39 3.57 q26_c 3 2.88 10 9.62 21 20.19 45 43.27 25 24.04 3.76 q26_d 8 7.69 34 32.69 36 34.62 17 16.35 9 8.65 2.86 Regulatory Constraints q27_a 26 26 34 34 21 21 14 14 5 5 2.38 q27_b 19 19 26 26 32 32 16 16 7 7 2.66 q27_c 13 13 26 26 31 31 21 21 9 9 2.87 Service & Product Development q31_a 0 0 1 0.96 13 12.5 44 42.31 46 44.23 4.3 q31_b 0 0 5 4.81 20 19.23 43 41.35 36 34.62 4.06 q31_c 4 3.85 17 16.35 31 29.81 33 31.73 19 18.27 3.44 Management Support q32_a 4 3.85 14 13.46 33 31,73 29 27.88 24 23.08 3.53 q32_b 2 1.94 13 12.62 25 24.27 40 38.83 23 22.33 3.67 q32_c 1 0.97 11 10.68 27 26.21 43 41.75 21 20.39 3.7 Technical Challenge q33_a 2 1.94 10 9.71 23 22.33 47 45.63 21 20.39 3.73 q33_b 3 2.91 8 7.77 14 13.59 32 31.07 46 44.66 4.07 q33_c 4 3.88 13 12.62 33 32.04 37 35.92 16 15.53 3.47 q33_d 3 2.91 10 9.71 31 30.1 43 41.75 16 15.53 3.57 q33 e 5 4.9 21 20.59 35 34.31 31 30.39 10 9.8 3.2 Score 1: very low Score 5: very high 41 Table 4: Frequency Distribution of Level of Intent to Adopt Internet Banking Functions Score Banking Functions 1 Count % 2 Count % 3 Count % 4 Count % 5 Count % 6 Count % Information Delivery Medium Corporate Information 4 3.92 3 2.94 5 4.9 5 4.9 7 6.86 78 76.47 Press Release 12 11.88 9 8.91 9 8.91 9 8.91 6 5.94 56 55.45 Branch Location 4 3.88 1 0.97 3 2.91 2 1.94 14 13.59 79 76.7 Marketing Tool Advertisement 6 6.06 3 3.03 9 9.09 13 13.13 9 9.09 59 59.6 Offers Announcement 10 10.1 6 6.06 10 10.1 15 15.15 8 8.08 50 50.51 Loans, Investment & account application 5 5.05 3 3.03 12 12.12 18 18.18 27 27.27 34 34.34 Value-added Services E-mail & suggestion form 5 4.85 4 3.88 8 7.77 10 9.71 9 8.74 67 65.05 Search Engine 24 25.53 18 19.15 22 23.4 7 7.45 3 3.19 20 21.28 Hot Links to other sites 11 10.78 13 12.75 16 15.69 9 8.82 7 6.86 46 45.1 Discussion groups 52 55.32 30 31.91 5 5.32 3 3.19 4 4.26 0 0 Calculator 12 11.54 2 1.92 9 8.65 17 16.35 15 14.42 49 47.12 Investment Advisor 15 15.46 19 19.59 18 18.56 19 19.59 9 9.28 17 17.53 Software download 40 40.4 22 22.22 8 8.08 3 3.03 5 5.05 21 21.21 Account Transaction Platform Balance inquiry 7 6.86 1 0.98 3 2.94 9 8.82 32 31.37 50 49.02 Statement request 7 6.93 3 2.97 4 3.96 11 10.89 32 31.68 44 43.56 Transaction history 7 6.8 2 1.94 3 2.91 10 9.71 31 30.1 50 48.54 Bill payment 10 9.71 0 0 2 1.94 12 11.65 32 31.07 47 45.63 Funds transfer 7 6.8 4 3.88 3 2.91 12 11.65 28 27.18 49 47.57 Electronic Commerce Opportunity Stock & mutual fund trading 24 24.24 17 17.17 17 17.17 13 13.13 13 13.13 15 15.15 Electronic Cash 27 27.84 20 20.62 17 17.53 18 18.56 11 11.34 4 4.12 Bill presentment 16 16 20 20 16 16 21 21 22 22 5 5 Smart Card 31 31.31 21 21.21 19 19.19 15 15.15 12 12.12 1 1.01 Digital Certificate 31 31.96 15 15.46 20 20.62 13 13.4 12 12.37 6 6.19 Score 1: very low intent Score 5: very high intent Score 6: function already adopted 4 2 Table 5: Frequency Distribution of Responses to Normative Questions Measurement Item No. Your Firm The Banking Govrnment Financial Customers Industry Intermediaries Count % Count % Count % Count % Count % Functionality of Internet Banking q2 17 16.30% 21 20.20% 0 0 6 5.80% 57 54.80% q3 32 30.80% 15 14.40% 0 0 7 6.70% 47 45.20% q4 60 57.70% 9 8.70% 22 21.20% 3 2.90% 4 3.80% Strategic Motivation qll 36 34.60% 17 16.30% 0 0 4 3.80% 45 43.30% ql2 16 15.40% 6 5.80% 0 0 3 2.90% 74 71.20% ql3 56 53.80% 7 6.70% 15 14.40% 11 10.60% 5 4.80% Valuation of Internet banking ql7 13 12.50% 17 16.30% 0 0 4 3.80% 68 65.40% ql8 17 16.30% 42 40.40% 0 0 12 11.50% 29 27.90% ql9 6 5.80% 7 6.70% 0 0 3 2.90% 84 80.80% Customer Demand q23 74 71.20% 5 4.80% 1 1.00% 5 4.80% 18 17.30% q24 95 91.30% 3 2.90% 3 2.90% 3 2.90% q25 44 42.30% 0 0 1 1.00% 2 1.90% 55 52.90% Environmental Influences q28 7 6.70% 31 29.80% 16 15.40% 13 12.50% 35 33.70% q29 30 28.80% 28 26.90% 5 4.80% 15 14.40% 21 20.20% q30 6 5.80% 38 36.50% 5 4.80% 13 12.50% 38 36.50% Operational Context q34 35 33.70% 35 33.70% 3 2.90% 21 20.20% 6 5.80% q35 75 72.10% 4 3.80% 1 1.00% 11 10.60% 10 9.60% q36 52 50.00% 0 0 1 1.00% 3 2.90% 42 40.40% 43 Table 6: Percentage of Variance Explained by Provisional Factors Provisional Factor Eigenvalue % of Variance Cumulative % 1 8.33 19.82 19.82 2 5.62 13.38 33.20 3 3.23 7.69 40.89 4 2.35 5.58 46.48 5 1.97 4.69 51.17 6 1.74 4.13 55.31 7 1.59 3.78 59.09 8 1.42 3.39 62.48 9 1.23 2.94 65.42 10 1.18 2.82 68.23 11 1.06 2.52 70.75 11 provisional factors were retained after the principal component analysis. These 11 provisional factors all have eigenvalue greater than 1, and together they will account for about 70% of the total variance of the original predictor variables. It can be noted that the first 2 components are relatively more important than the others because they together can account for 33% of the total variance of the predictor variables. 44 Table 7: Factor Loading Matrix Measurement C o m m o n Factor Item 1 2 3 4 5 6 7 8 9 10 11 Communali t ies q6 0.72 0.17 -0.04 -0.06 -0.01 -0.06 0.05 0.07 0.07 0.22 0.25 0.71 q8 0.74 0.30 0.06 -0.04 -0.13 -0.08 0.06 0.08 0.16 0.16 0.00 0 .74 qlO 0.64 0.33 0.11 0.10 -0.04 -0.02 0.10 0.20 0.17 0.09 -0.15 0.65 q14_a 0.18 0.65 0.03 -0.32 -0.11 -0.02 -0.15 0.09 , 0.06 0.16 0.21 0.68 q l4_b 0.35 0.77 0.16 -0.03 0.04 0.13 0.07 0.17 0.14 0.06 0.04 • 0.81 q l 4 c 0.33 0.79 0.12 -0.05 0.08 0.07 -0.07 0.10 0.08 0.03 -0.10 0 .80 q l 4 _ d 0.30 0.55 -0.06 -0.04 0.18 0.30 -0.16 0.25 -0.10 0.05 -0.01 0.67 q l5_a -0.02 0.23 -0.09 -0.05 -0.11 0.70 -0.06 0.22 0.11 0.06 -0.04 0 .64 q l5_b 0.12 0.12 0.01 -0.22 -0.07 0.69 0.04 0.13 0.12 0.20 0.08 0.68 q l5_c 0.42 0.39 0.26 -0.14 -0.05 0.26 -0.15 0.04 0.22 0.31 0.14 0.71 q l6_a 0.64 0.12 0.02 -0.10 -0.13 0.42 -0.20 0.20 0.16 0.05 0.02 0.73 ql6_b 0.69 0.14 0.06 -0.19 0.04 0.41 0.03 0.06 0.18 0.00 0.07 0 .77 q l6_c 0.57 0.15 0.03 0.00 0.06 0.51 0.17 -0.03 0.13 -0.07 0.21 0.78 q20_a 0.03 0.20 0.12 0.07 0.08 0.02 0.13 0.01 0.08 0.02 0.76 0.69 q20_b 0.16 -0.24 0.16 0.17 0.17 0.05 0.11 0.12 -0.04 -0.04 0.73 0.78 q20_c 0.21 0.26 0.53 -0.01 0.13 0.00 0.06 0.04 0.37 0.01 0.39 0.73 q20_d 0.13 0.33 0.41 0.11 0.08 0.11 0.08 0.02 0.47 -0.07 0.24 0.70 q21_a -0.05 -0.09 0.45 0.21 0.37 0.01 0.09 -0.10 -0.14 0.05 -0.01 0.61 q21_b 0.02 0.05 0.75 0.02 0.30 -0.06 0.07 -0.02 0.04 0.00 0.14 0 .74 q21_c 0.07 0.05 0.89 0.05 0.15 -0.01 0.03 0.02 -0.03 0.01 0.03 0.82 q21_d 0.01 0.10 0/77 0.11 -0.04 0.03 0.24 0.10 -0.18 0.03 0.06 0.82 q22_a -0.01 0.15 0.07 0.05 0.85 -0.11 -0.04 0.07 0.01 0.04 0.05 0.82 q22_b -0.10 0.00 0.19 0.09 0.88 -0.09 0.06 -0.03 0.00 0.00 0.03 0.84 q22_c -0.01 -0.08 0.19 0.17 0.77 0.03 0.15 -0.12 -0.06 -0.10 0.23 0.85 q26_a 0.21 0.14 0.04 0.02 -0.07 0.20 -0.01 -0.09 0.19 0.72 -0.03 0.68 q26_b 0.15 0.08 0.06 -0.17 -0.10 0.23 0.09 -0.04 0.48 0.53 0.05 0 .70 q26_c 0.07 0.02 -0.02 0.11 0.08 0.09 0.22 -0.11 -0.13 0.79 -0.02 0.75 q26_d 0.14 -0.21 0.08 0.15 -0.08 0.60 0.09 0.07 0.31 0.27 -0.03 0 .64 q27_a 0.20 -0.08 -0.02 0.15 0.11 0.14 0.79 -0.08 0.15 0.00 0.06 0.78 q27_b 0.01 -0.02 0.16 0.15 0.05 0.01 0.87 -0.14 0.02 0.12 0.15 0 .87 q27_c -0.09 -0.07 0.18 0.18 -0.01 -0.09 0.81 0.00 -0.01 0.13 0.04 0 .77 q31 a 0.24 0.14 -0.10 0.06 -0.08 -0.07 -0.15 0.11 0.59 0.32 0.18 0.62 q31_b 0.20 0.05 -0.10 -0.13 -0.04 0.27 0.10 0.18 0.74 0.00 -0.03 0 .74 q31_c 0.17 0.01 -0.01 0.03 0.05 0.35 0.16 0.03 0.62 -0.07 -0.07 0.63 q32_a 0.15 0.07 0.01 -0.02 -0.04 0.19 -0.02 0.82 0.00 -0.21 -0.03 0.81 q32_b 0.02 0.21 0.11 0.04 -0.01 0.05 -0.16 0.83 0.04 -0.04 0.04 0.78 q32_c 0.20 0.05 -0.06 -0.09 -0.03 0.12 -0.04 0.80 0.20 0.04 0.10 0.77 q33_a 0.05 0.04 -0.06 0.61 0.06 -0.10 0.16 -0.02 -0.05 0.33 0.00 0.54 q33_b -0.03 -0.31 0.16 0.47 0.20 -0.25 0.11 0.26 0.02 0.25 0.01 0.59 q33_c -0.07 -0.15 0.14 0.64 0.35 -0.18 0.02 -0.04 -0.21 0.03 0.02 0.72 q33_d -0.08 -0.09 0.07 0.86 0.09 0.03 0.12 -0.06 -0.02 -0.09 0.03 0 .80 q33_e -0.08 -0.04 0.08 0.83 -0.04 0.03 0.17 -0.02 0.10 -0.09 0.16 0.78 Factor Loading • Highest factor loading for each measurement item is underlined and bolded in the matrix, showing which factor has most significantly loaded on the predictor variables. • Factor loading is an indication of the correlation between the common factor and the predictor variable. It can be seen that the highest loading in measurement item q6 to qlO is with Factor 1 . They so are highly correlated with Factor 1. Similarly, measurement item q22a to q22c are significantly associated with Factor 5 because their factor loadings with Factor 5 are highest. Other measurement items can be interpreted in the same way. • The way predictor variables are grouped is roughly consistent with the way they were theoretically grouped. But there are also some minor deviations: "Business opportunity" (ql6a to ql6c) is grouped together with the "Strategic Motivation" (q6 to q 10) as one common factor, Factor 1 ; Predictors in "Customer Behavior" (q20a to q20d) are grouped into different factors. Communality • Communality of the predictor variable shows the part of its variance that is related to the factors extracted. The value of communality must be between 0 and 1. The higher the communality is, the more its variance is accounted for by the extracted factors. • For example, communality for measurement q6 is 0.71, indicating that 71% of its variances can be explained by the 11 common factors. And, the most significant factor in explaining the variance is the one with highest loading, i.e., Factor 1. • From the table, it can be seen that communalities are fairly high. Most of them are greater than 0.7, with a mean of 0.73. That is to say, most of the variance of the predictor variables is accounted for by the 1 1 common factors derived. 45 Table 8 : Frequency Distribution of Mean Score in Intent Level Mean Score Frequency Percent Cumulative Percent Information Delivery Medium 1.33 1 1.0 1.0 2.00 1 1.0 2.0 2.50 1 1.0 3.0 2.67 1 1.0 4.0 3.00 1 1.0 5.0 3.33 2 2.0 6.9 3.67 5 5.0 11.9 4.00 4 4.0 15.8 4.33 11 10.9 26.7 4.67 8 7.9 34.7 5.00 8 7.9 42.6 5.33 4 4.0 46.5 5.67 1 1.0 47.5 6.00 53 52.5 100.0 Total 100 100 Marketing Tool 1.00 1 1.0 1.0 1.67 1 1.0 2.0 2.33 3 3.0 5.0 2.67 3 3.0 8.0 3.00 1 1.0 9.0 3.33 4 4.0 13.0 3.50 1 1.0 14.0 3.67 8 8.0 22.0 4.00 9 9.0 31.0 4.33 9 9.0 40.0 4.50 1 1.0 41.0 4.67 7 7.0 48.0 5.00 10 10.0 58.0 5.33 5 5.0 63.0 5.67 10 10.0 73.0 6.00 27 27.0 100.0 Total 100 100.0 Value-added Services 1.14 1 1.0 1.0 1.29 2 2.0 3.0 1.43 1 1.0 4.0 1.57 1 1.0 5.0 1.86 2 2.0 6.9 2.00 2 2.0 8.9 2.14 2 2.0 10.9 2.29 3 3.0 13.9 2.43 2 2.0 15.8 2.50 1 1.0 16.8 2.57 4 4.0 20.8 2.71 3 3.0 23.8 2.86 4 4.0 27.7 3.00 3 3.0 30.7 3.14 3 3.0 33.7 3.17 2 2.0 35.6 3.29 7 6.9 42.6 3.43 3 3.0 45.5 3.57 3 3.0 48.5 3.71 3 3.0 51.5 3.86 6 5.9 57.4 4.00 7 6.9 64.4 4.14 6 5.9 70.3 4.29 3 3.0 73.3 4.33 1 1.0 74.3 4.50 2 2.0 76.2 4.57 3 3.0 79.2 4.71 3 3.0 82.2 4.86 4 4.0 86.1 5.00 3 3.0 89.1 5.14 1 1.0 90.1 5.17 1 1.0 91.1 5.29 2 2.0 93.1 5.43 1 1.0 94.1 5.57 1 1.0 95.0 6.00 5 5.0 100.0 Total 101 100.0 46 Mean Score Frequency Percent Cumulative Percent Account Information Platform 1.00 6 5.9 5.9 1.80 1 1.0 6.9 3.20 1 1.0 7.9 3.60 2 2.0 9.9 3.80 3 3.0 12.9 4.00 9 8.9 21.8 4.20 2 2.0 23.8 4.40 2 2.0 25.7 4.60 1 1.0 26.7 4.80 4 4.0 30.7 5.00 ' 21 20.8 51.5 5.20 1 1.0 52.5 5.60 2 2.0 54.5 5.80 5 5.0 59.4 6.00 41 40.6 100.0 Total 101 100.0 e Opportunity 1.00 8 8.1 8.1 1.20 5 5.1 13.1 1.40 2 2.0 15.2 1.60 5 5.1 20.2 1.80 2 2.0 22.2 2.00 7 7.1 29.3 2.20 3 3.0 32.3 2.40 5 5.1 37.4 2.50 1 1.0 38.4 2.60 4 4.0 42.4 2.80 3 3.0 45.5 3.00 8 8.1 53.5 3.20 7 7.1 60.6 3.40 4 4.0 64.6 3.60 6 6.1 70.7 3.67 1 1.0 71.7 3.80 7 7.1 78.8 4.00 3 3.0 81.8 4.20 4 4.0 85.9 4.40 2 2.0 87.9 4.50 1 1.0 88.9 4.60 2 2.0 90.9 4.80 1 1.0 91.9 5.00 5 5.1 97.0 5.40 2 2.0 99.0 6.00 1 1.0 100.0 Total 99 100.0 *There were missing values in some observations, making the number of observations for analysis less than the total number of received responses (i.e., 104). 47 Table 9: Mean Scores in the Defined Groups Mean Rank Frequency % Cumulative % Classified Group Information Delivery Medium 1 -4.34 27 27% 27% 1 4.341-5.67 21 21% 48% 2 5.671 -6 53* 52% 100% 3 Marketing Tool 1 -4 31 31% 31% 1 4.001-5.34 32 32% 63% 2 5.341-6 37* 37% 100% 3 Value-added Services 1 - 3.144 34 33% 33% 1 3.145-4 31 31% 64% 2 4.001 - 6 36* 36% 100% 3 Account Transaction Platform 1 - 4.8 31 31% 31% 1 4.801-5.8 29 29% 60% 2 5.801 -6 41* 40% 100% 3 Electronic Commerce Opportunity 1-2 .2 32 32% 32% 1 2.201 - 3 . 4 32 32% 64% 2 3.401 - 6 35 36% 100% 3 * Slightly higher percentage could not avoided due the averaging effect of mean score of 6 (adopter) 48 Figure 1: A Hypothesized Model of Decision Factors of Internet Banking Antecedent Factors Strategic Motivation • Business Need (H1) • Strategic Fit (H2) • Goal Congruence (H3) Internet Banking Valuation • Channel Significance (H4) • Channel Efficiency (H5) • Business Opportunity (H6) Customer Demand • Customer Behavior (H7) • Demographics (H8) w • Technical Capabilities (H9) Environmental Influences • Market Competition (H10) • Regulatory Constraints (HI 1) Intent to Adopt Information Delivery Medium Market Tool Value-added Services Adoption Decision Account Transaction Platform Electronic Commerce Opportunity Operational Context • Service & Product Development (HI2) • Management Support (HI3) • Technical Challenge (H14) 49 Figure 2 : The Theory of Planned Behavior (TPB) (Adopted from Ajzen, 1988) Attitudinal Attitude Beliefs and Towards Evaluations Behavior w Normative Subjective Beliefs and Norm Motivation to Comply w Behavioral Actual Intention Behavior w Control Perceived Beliefs and Behavioral Perceived Control Facilitation w 50 Figure 3: The Adoption of Internet Banking: A Model of Decision Factors Antecedent Factors: Subjective Norm Perceived Significance of Internet Banking & Timing of Market Entry (H4,H 10) Antecedent Factors: Perceived Behavior Control Product & Service Development (HI2) Management Support (H13) Technical Challenges (HI 4) Intent to Adopt Value-added Services Account Transaction Platform Adoption Decision Electronic Commerce Opportunity r= -0.38 * denotes significance at the p< 0.003 level ** denotes significance at the p< 0.001 level *** denotes significance at the p< 0.002 level 51 Appendix 1: Strategic Advantages of Internet Banking • It increases customer satisfaction by offering alternative and convenient access to banking services at any time and any place, so as to serve as a means of building and strengthening customer relationship. • It expands product offerings such as brokerage, mutual funds and insurance, either directly or indirectly by setting a Web link with partner organizations. Branches usually do not have the opportunity to "co-brand" offerings of these financial products. • It increases customer retention because in many cases customers loss is due to the their relocation from one area to another. • It extends geographic reach and allows banks to gain new market share by expanding customer base. • It allows banks to cross-sell services. Internet tracking software allows a bank to keep track of transactions conducted through the Web, which so forms a database that allows banks to target selling and identify profitable customers. • It reduces overall cost mainly in 2 ways: the transaction cost and cost in physical branch operation. • It allows banks to experiment with the technology and assess future impact on business. Source: Booz, Allen & Hamilton, 1997; US Web Services, 1998; Daniel & Storey, 1997; Tower Group, 1996; Ooi et al., 1996, (ii). 52 Appendix 2: Initial Measurement Items Initial survey questions are designed to tap into factors identified. Strategic Motivation 1. Does Internet banking satisfy one or more business opportunities for your firm? 2. Does Internet banking solve one or more existing business problems for your firm? 3. How well does Internet banking meet the following needs for your firm? • Improving your firm's name recognition • Re-defining customer relationship • Serving unique market segments (e.g. customers who have interests in technology or needs global access to banking services) • Developing cost-efficient delivery channels • Serving customers who cannot be reached by branch network 4. How important are the following to your firm's strategic mission? • Cost savings • Maintaining or increasing market share • Increased revenue • Innovation leadership 5. To what extent does Internet banking enable the following business drivers for your firm? • Cost savings • Maintaining or increasing market share • Increased revenue • Innovation leadership 6. Which of the following do you believe most closely matches your firm's strategic mission? (Please check one box only) • Branding strategy of improving or maintaining your firm's brand image • Technology adoption strategy of experimenting with the technology and assessing its future impact on business • Customer-oriented strategy of creating or improving customer relationship • Market-coverage strategy of widening the geographic-reach without having to extend the branch network 7. How closely does Internet banking support your firm's mission statement? 8. To what extent do the following match your strategic expectations about Internet banking? • Improving or maintaining brand image • Experimenting with technology and assessing its future impact on business • Creating or improving customer relationship • Widening the geographic-reach to customers • Being cost competitive by developing lower cost delivery channels 9 . Which of the following do you believe most closely matches your firm's organizational goals? (Please check one box only) • Being positioned as a distinctive and innovative organization and having a well-branded image • Development of expertise in technology-based service delivery • Creation or improvement of customer relationship • Widened market coverage and expanded accessibility to banking services • Expansion or retention of market share • Having cost advantage by reducing transaction and branch operation cost 10. To what degree do you believe that Internet banking meets the following goals? • Being positioned as a distinctive and innovative organization and having a well-branded image • Development of expertise in technology-based service delivery • Creation or improvement of customer relationship • Widened market coverage and expanded accessibility to banking services • Expansion or retention of market share • Having cost advantage by reducing transaction and branch operation cost 53 Va lua t i on of Internet B a n k i n g 11. To what extent do you believe that banking transactions conducted over the Internet are highly secured? 12. To what extent do you believe that the Internet expands the accessibility to banking services? 13. To what extent do you believe that the Internet is a convenient service channel for bank customers? 14. To what extent do you believe that the Internet is a less-expensive channel for delivering banking services? 15. To what extent do you believe that the Internet wil l become the mainst ream delivery channel for banking services? 16. To what extent do you believe that Internet banking has migrated from a strategic advantage to a strategic necessity? 17. To what extent do you believe that Internet banking wil l lay the foundation for your firm's future business development in Electronic Commerce (e.g. bill presentment, E-cash, digital certificate, smart card etc.)? 18. To what extent do you believe that more banking services must be added to make Internet banking successful? 19. To what extent do you believe that other non-banking services must be added to make Internet banking successful? 20. To what extent do you believe that implementing Internet banking will allow your firm to develop technical expertise for future business developments? 21. To what extent do you believe that implementing Internet banking wil l allow your firm to develop managerial skill for future business developments? Customer Demand 22. How much does ease of motivating customers to use Internet-based banking services affect the demand for your Internet banking services? 23. How much does customers' prior experience in using the Internet affect the demand for your Internet banking services? 24. How much does customers' perceived risk of the Internet affect the demand for your Internet banking services? 25. How much does customers' perceived usefulness of Internet banking affect the demand for your Internet banking services? 26. How much does customers' perceived ease of using Internet affect the demand for your Internet banking services? banking 27. How much does age of your firm's customers affect the demand for your Internet banking services? 28. How much does educational level of your firm's customers affect the demand for your Internet banking services? 29. How much does income level of your firm's customers affect the demand for your Internet banking services? 30. How much does the degree of financial sophistication of your firm's customers affect the demand for your Internet banking services? 31. How much does customers' lack the required hardware, software, or connectivity in using the Internet affect demand for your Internet banking services? 32. How much do Customers' lack experience and technical knowledge in using Internet affect demand for your Internet banking services? 54 Env i ronmenta l Influences 33. How would you characterize your firm's competitive threat from other banks and credit unions? 34. How would you characterize the threat of losing market share to non-bank competitors (e.g. mortgage firms or credit card companies) 35. How would you characterize your firm's pressure to keep up with other financial institutions that have already adopted Internet banking? 36. How would you characterize the threat of not having 'first-mover' advantages in Internet banking services? 37. To what degree do you believe that the differences in government regulation or legal requirement wil l delay your implementation of Internet banking? 38. To what degree do you believe that the lack of legal control and recourse for business conducted on the Internet wil l delay your implementation of Internet banking? 39. To what degree do you believe that the potential liability from downtime, unauthorized access, or expired information will delay your implementation of Internet banking? 40. To what extent do you believe that Security of Internet banking transactions will delay your implementation of Internet banking? 41. To what extent do you believe that Lack of control over Internet technology (e.g. third party control over browsers,) will delay your implementation of Internet banking? 42. To what extent do you believe that the setting of Internet standards (e.g. compatibility between system configurations) will delay your implementation of Internet banking? 43. To what extent do you believe that Immature programming and scripting languages wi l l delay your implementation of Internet banking? Opera t iona l Context 44. To what degree do you believe that it is important to influence customers to use Internet banking services (e.g. differential pricing policy)? 45. To what degree do you believe that it is important to re-define branch banking when Internet banking is offered? 46. To what degree do you believe that it is important to maintain face-to-face contact with customers in managing multiple service channels? 47. To what degree do you believe that it is important to decide what existing services can be put into Internet environment? 48. To what degree do you believe that it is important to make Internet banking as a distinct business entity (i.e., not just an add-on service to the existing service portfolio)? 49. To what degree do you believe that it is important to differentiate, customize and personalize services offered through the Internet? 50. To what degree do you believe that it is important to align Internet banking with the firm's overall Electronic Commerce development? 51. To what degree do you believe that your firm's management support and commitment to Internet banking are sufficient (e.g. finance, human resources and technology)? 52. To what degree do you believe that your firm's upper management understands the technological development issues? 53. To what degree do you believe that it is prestigious to be a team member working on Internet banking development? 54. To what degree do you believe that Integration of the Internet into the existing IT infrastructure, including operating system and people represent a challenge to operations in Internet banking? 55. To what degree do you believe that Integration of Internet banking with the existing channels (e.g. communicability and interoperability of channel systems, and consistency of data) represent a challenge to operations in Internet banking? 56. To what degree do you believe that Definition of line of responsibility for development of Internet banking operation (e.g. marketing or IT department) represent a challenge to operations in Internet banking? 5 5 ? to > CD CD 3 3 ON a- cb cr 3 o 3 0) T J 9 S CQ CD <5 r ? £ CD CD o .5 CD CD 91 = 5 31 ~ 73 Oi GO ro N» CO T otal | T ech n ical C o n text J  [M an ag em en t S u p p o rt j S ervce &  P ro d u ct D evelo p m en t C h an n el M an ag em en t O P E R A T IO N A L  C O N T I [T ech n ical C o m p lexity 1 L eg al C o n strain t iM arket C o m p etitio n  E N V IO R N M E N T A L  IN F  T ech n ical C ap ab ilities of C u sto m er C u sto m er D em o g rap h ics I C u sto m er B eh au o r j C U S T O M E R  D E M A N D  B u sin ess O p p o rtu n ity C h aracteristics a s  D eli\ery C h an n el V A L U A T IO N  O F  IN T E R  JG oal C o n g ru en ce | [strateg ic F it | [B u sin ess N eed  | S T R A T E G IC  M 0 T IV IA 1  Theoretical C ategory - J w L U E N C E  :N E T  B A I O l H O N  N eed  Ui ro o ro M K IN G  - J S. 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Issu es (G en eral) 9 CO CD -si CO Oi 00 ro ro M is c . rHERS cn ro ro ? > Ol CO O CO o CO O o CO o o CO O o ro o o Ol O Ol o CD o ro o CO o O l o T o ta l O l CO o - J - J cn o -̂ o tvs 00 5? o CO sp cv- | 100% | CD o CD o CD O •.p 0 s 00 00 p •b. OD ^ i 0 s •vi o -si CO Gi o 5? %  O f Hit > fD P a R' w » rs n B <v a p *» B" o O </) O a 3 Appendix 4: Analysis of the Items Placement Matr ix 10 judges have participated in the Q-sort Analysis and examination of the Items Placement Matrix suggests some major changes to the survey, as summarized as follows. Strategic Motivation • Measurement items in "BUSINESS N E E D " were too ambiguous because some of them were consistently targeted within the category of "PERCEIVED V A L U E " . However, this might indicate well for potential measurement consistency because they showed clustering, rather than a scattering of items. So items were reconstructed to specifically refer to the business need and its match with Internet banking. • Placements in "STRATEGIC FIT" and " G O A L C O N G R U E N C E " were considered acceptable, so no change was recommended. Valuation of Internet Banking • Some judges identified question 11 as a technical issue. It might be due to the word "secured" because "security" is always recognized as a technical issue. It so was changed to "reliable" as a measure to reduce the possibility of confusion. • Many measurement items clustered around the category of "SERVICE A N D PRODUCT D E V E L O P M E N T " . So, the following modifications were be made. 1. Some measurement items were reworded to specifically refer to the perceived value of Internet banking. Any references to "services" were dropped, so as to avoid confusion with the category of "SERVICE A N D PRODUCT D E V E L O P M E N T " . For example, service channel wil l be reworded as delivery channel. 2. Question 18 and 19 were mostly labeled as "SERVICE A N D PRODUCT D E V E L O P M E N T " because they were referring to Internet banking services. These items so were moved to the category of "SERVICE A N D PRODUCT D E V E L O P M E N T " . Customer Demand A very high percentage of measurement items was placed within theoretical constructs, indicating a high degree of construct validity. So no change was recommended. (Remarks: items clustering around "SERVICE A N D PRODUCT D E V E L O P M E N T " were all labeled by one particular judge) Environment Influences • Except those items in the " T E C H N O L O G I C A L C O M P L E X I T Y " , the majority of measurement items was placed within theoretical constructs. Therefore, only the ' T E C H N I C A L C O M P L E X I T Y " needed to be reconstructed. • Items in the " T E C H N O L O G I C A L C O M P L E X I T Y " were too ambiguous because most of them were identified either as " T E C H N I C A L C O N T E X T " (a dimension of " O P E R A T I O N A L CONTEXT") or just as " T E C H N O L O G I C A L ISSUE" in general. They so were merged into the category of " T E C H N I C A L CONTEXT" , becoming a dimension of " O P E R A T I O N A L C O N T E X T " . Operational Context • There was scattering of measurement items in " C H A N N E L M A N A G E M E N T " and no clustering around any particular category, indicating that they were too ambiguous and could fit in the same category. They were be eliminated or merged into other factor categories. • There was also potential of measurement inconsistency in "SERVICE & PRODUCT D E V E L O P M E N T " because items were scattering around. However, examination of items placement shows that the scattering was mainly due to the question 48 and 50. These two items were dropped. • Measurement items in " M A N A G E M E N T SUPPORT" also showed clustering around "PERCEIVED V A L U E " . Examination of the item placement indicated that the clustering was mainly formed by question 53. Confusion might be due to word of "prestigious". This item were be reworded. • " T E C H N I C A L C O N T E X " was be renamed as " T E C H N I C A L C H A L L E N G E " and included all items related to technical issue. 57 Section 1: FUNCTIONALITY OF INTERNET BANKING This section asks about information on the type of banking functions you intend to provide through the Internet 1. How would you rate your intention to add the following banking activities to your firm's Web site? Please check the box or code one number per row Corporation information Press release Recruitment form Branch location Advertisement Offers announcement Loans, investment and account application E-mail & suggestion forms • Search engine Hot links to other sites Discussion groups • Calculator Investment advisor Software download Balance inquiry Statement request Transaction history Bill payment Funds transfer Stock & mutual fund trading Electronic cash Bill presentment Smart card Digital certificate Already offered | (1: Very Low— 5: Very High) • 1 2 3 4 $ • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 S • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 • 1 2 3 4 5 Your Firm Please check one box per row The Financial Banking Inter- industry Government mediaries Customers 3. Who most influences the type of services you expect to offer through Internet banking? Who most influences how you define the market for Internet banking services? Who is the strongest regulator of Internet banking activities in your firm's Web site? • • • • • • • • • • • • • • • KSE3 '••«&»- The Umvcisily of British Columbia 2 o f S 59 Section 2: STRATEGIC MOTIVATION This section evaluates the degree to which Internet banking is perceived consistent with your firm's strategic vision. 2.1 Business Need Definition: the degree to which Internet banking satisfies problems or opportunities associated with key business needs. Needs are drivers to strategic missions and may be generated from all kinds of stimuli ranging from the change of organizational policy to the change of environmental factors (eg: evolution of IT, trends in the financial industry, demographic shift and competition structure). 5. Which of the following is the major business need of your firm? {Please one box only) • Improving name recognition • Re-defining customer relationship • Serving unique market segments (e.g. customers who have interests in technology or need global access to banking services) • Serving customers who cannot be reached by branch network • Developing cost-efficient delivery channels • Being innovation leader Please circle one number per row (1: Very Utile 5: Very Much t To what extent do you believe that Internet banking enables the following business drivers for your firm? a. Improving name recognition b. Re-defining customer relationship c. Serving unique market segments (e.g. customers who have interests in technology or need global access to banking services) d. Serving customers who cannot be reached by branch network . . . e. Developing cost-efficient delivery channels f. Beina innovation leader 4 5 4 5 4 5 4 5 4 5 4 5 2.2 Strategic Fit Definition: the degree to which the strategic features associated with Internet banking support your firm's stated strategic mission. 7. Which of the following is the major strategic mission of your firm? (Please one box only) • Branding strategy: improving or maintaining your firm's brand image • Customer-oriented strategy: creating or improving customer relationship • Market-coverage strategy: widening the geographic-reach without having to extend the branch network • Cost-saving strategy: developing lower cost alternatives for services delivery and making your firm cost competitive • Technology adoption strategy: experimenting with the technology and assessing its future impact on business To whai extent do the following match your strategic expectations about Internet banking? a. Improving or maintaining brand image b. Creating or improving customer relationship c. Widening the geographic-reach to customers d. Being cost competitive by developing lower cost delivery channels Please circle one number per row (I: Ver/ Little 5: i'erv Much I 1 2 3 - 1 5 1 2 3 4 5 1 2 3 ^ 5 3 of 8 nc University o f Brit ish C o l u m b i a 60 e. Experimenting with technology and assessing its future impact • ^ ^ ^ on business 2.3 Goal Congruence Definition: the degree to which Internet banking produces benefits that can achieve the declared organizational goals. 9. Which of the following is the major organizational goal of your firm? (Please one box only) • Being positioned as a distinctive and innovative organization and having a well-branded image • Creation or improvement of customer relationship • Widened market coverage and expanded accessibility to banking services I • Having cost advantage by reducing transaction and branch operation cost • Development of expertise in technology-based service delivery 10. To what degree do you believe that Internet banking meets the following organizational goals? a. Being positioned as a distinctive and innovative organization and having a well-branded image b. Creation or improvement of customer relationship c. Widened market coverage and expanded accessibility to banking services d. Having cost advantage by reducing transaction and branch operation cost e. Development of expertise in technology-based service delivery Please circle one number per row (1: Very Little __ 5: Very Much) Please check one box per row 11. What most influences your Internet banking strategy? 12. Your Internet banking strategy is most consistent with the needs of , 13. What constrains strategic innovation in Internet banking in your firm? Your Firm The Banking Industry Government Financial Inter- mediaries Customers • d • • • • • • • • • • • • • Section 3: VALUATION OF INTERNET BANKING This section evaluates the perceived value of delivery channel characteristics and business opportunities represented by Internet banking. 3.1 Perceived Efficiency as Delivery Channel Definition: the degree to which the Internet is perceived as being an efficient delivery channel. Please circle one number per row 14. TO What extent do you believe that... (hVeryUttle 5: Very Much) a. banking transactions conducted over the Internet are highly reliable? 1 2 3 b. the Internet expands the accessibility to banking services? 1 2 3 4 c. the Internet is a convenient delivery channel for bank customers? 1 2 1 4 d. the Internet is a less-expensive delivery channel? 1 2 3 4 3.2 Perceived Significance as Delivery Channel Definition: the degree to which the Internet is perceived as being a significant delivery channel. ' The University of British Columbii 4 of 8 61 15. To what extent do you believe that... a. the Internet will become the mainstream delivery channel? b. Internet banking has migrated from a strategic advantage to a strategic necessity? c. the Internet is an integral part of multiple-delivery system? Please circle one number per row (I: Very Littk— 5: Very Much) 3.3 Business Opportunity Definition: the degree to which Internet banking is perceived as being an opportunity for development of future business, managerial skill and technical "know-how". 16. To what extent do you believe that... a. Internet banking will lay the foundation for your firm's future business development in Electronic Commerce (eg. bill presentment, E-cash, digital certificate, smart card etc.)? b. implementing Internet banking will allow your firm to develop technical expertise for future business developments? c. implementing Internet banking will allow your firm to develop managerial skill for future business developments? Please circle one number per row (1: Very LimeS: Very Much) Please check one box per row 17. From where do you realize the value for Internet banking? 18. Where do you get ideas to improve your firm's Internet banking site? 19. From where do you get feedback on Internet banking services? Your Firm The Banking Industry Government Financial Inter- mediaries Customers • • • • • • • • • • • • • • • Section 4: CUSTOMER DEMAND This section evaluates the degree to which customer demand is perceived significant for the Internet banking decision in your firm. 4.1 Customer Behavior Definition: the degree to which customers' behavior and perception to the Internet influence their acceptance of Internet banking 20. How much do the following affect the demand for your firm's Internet circle one number per row , . • „ (1: Very Utile... 5: Very Much) banking services? a. Customers' prior experience in using the Internet ' 2 3 4 * b. Customers' perceived risk of the Internet ' 2 3 4 5 c. Customers'perceived usefulness of Internet banking . ' 2 3 4 5 d. Customers' perceived ease of using Internet banking 1 2 3 4 5 4.2 Customer Demographics Definition: the importance of the demographics of existing and potential customers to the projection of customer demand. 5 of 8 '^j&s The University of British Columbia 62 21. How much do the following affect the demand for your firm's Internet banking services? a. Age of your firm's customers b. Educational level of your firm's customers c. income level of your firm's customers d. The degree of financial sophistication of your firm's customers Please circle one number per row (I: Very Utile..- 5: Very Much) 2 3 ~* ~ 2 3 4 5 •2 3 4 5 2 3 4 5 4.3 Technical Capabilities of Customer Definition: the degree to which customers' capabilities to use the Internet affect their demand for Internet banking. 22. How much do the following affect the demand for your firm's Internet banking services? _ a. Customers lack the required hardware, software, or connectivity in using the Internet - b. Customers lack experience in using the Internet 1 2 c. Customers lack technical knowledge in using the Internet _ 1 2 Please circle one number per row (1: VeryLiale.„ 5: VeryMuch) 4 5 4 5 4 5 Please check one box per row 23. Who decides what services will address customer demand? 24. Who determines how to deploy Internet banking to meet customer demand of your firm? 25. Who decides if your firm's Internet banking activities meet customers' demand? , Your Firm The Banking Industry Government Financial Inter- mediaries Customers • • • • • • • • • • • • • • • Section 5: ENVIRONMENTAL INFLUENCES This section evaluates the degree to which the adoption decision {i.e. the timing and extent of adoption decision) is affected by the external environment. 5.1 Market Competition Definition: the degree to which your firm's competitive pressure is critical to adoption decision. Please circle one number per row ! I: Very Little 5: VeryMuch) 26. How would you characterize your firm's competitive threat in Internet banking? a. Competitive threat from other banks and credit unions 1 b. Threat of losing market share to non-bank competitors (e.g. mortgage firms or credit card companies) c. Pressure to keep up with other financial institutions that have already adopted Internet banking d. Threat of not having 'first-mover' advantages in Internet banking services 1 The University o f Bri t ish Columbia 6of8 6 3 5.2 Regulatory Constraints Definition: the degree to which regulatory and legal constraints associated with Internet banking hinder adoption. 27. To what degree do you believe that the following legal or regulatory issues will delay your implementation of Internet banking? a. Differences in government regulation or legal requirement b. Lack of legal control and recourse for business conducted on the Internet _ c. Potential liability from downtime, unauthorized access or expired information Please circle one monier per row fl: Very Little._ 5: Very Much) I 2 3 Please check one box per row 28. What is the most influential element in the external environment for Internet banking services? 29. Who informs you how to best operate within the external environment? 30. Where are your best indicators of external environmental problems? Your Firm The Banking Industry Government Financial lnter~ mediants Customers • • • • • • • • • • • • • • • Section 6: OPERATIONAL CONTEXT This section evaluates the degree to which the adoption decision is affected by operational issues collateral to implementing Internet banking. 6.1 Service and Product Development Definition: the degree to which developing appropriate services and products on the Internet is perceived important to Internet banking implementation. Please circle one number per row 31. To what degree do you believe that it is important to ... " : VeryLi"u Very Much) a. decide what existing services can be put into Internet environment? 1 2 3 4 5 b. differentiate, customize and personalize services and products offered through the Internet? 1 2 3 4 5 d. add non-banking services to make Internet banking successful? 1 2 3 4 5 6.2 Management Support Definition: the degree to which the levei of management support is perceived important to the implementation of Internet banking. Please circle one number per row 32. To what degree do you believe that ... ( 1 : v « y L i i l l e S : KryMuch) a. your firm's management support and commitment to Internet banking are sufficient (e.g. finance, human resources and technology)? , 2 } 4 } b. your firm's upper management understands the Internet banking development issues? ' 2 3 4 5 c. the team working on Internet banking development has a high organizational status? 1 2 3 4 5 F = 7ofS 'rtSF The University of Brit ish Co lumbia 64 6 .3 Technical Challenge Definition: the degree to which the technical complexity impacts the pace of Internet banking implementation. 33. To what degree do you believe that the following technical issues represent a challenge to operations in Internet banking? a. Integration of the Internet into the existing IT infrastructure (e.g. communicability and interoperability of channel systems, and data consistency) b. Security of Internet banking transactions c. Lack of control over Internet technology (eg. third party control over browsers) d. The setting of Internet standards ( eg. compatibility between system configurations) Immature programming and scripting languages Please circle one number per row (I: Very Utile - . . 5: Very Much ) e. 34. From where do you find out about the operational factors that affect Internet banking decision? 35. Who is most influential in organizing Internet banking within your firm's Web site? 36. Who judges the effectiveness of your firm's operations in Internet banking services? Please check one box per row Your Firm The Banking Industry Government Financial Inter- mediaries Customers • • • • • • • • • • • • • • • Section 7: BACKGROUND INFORMATION • How familiar are you with the development of Internet banking within your Please circle one number per row (I: Very Little 5: Very Much) firm? What is the name of your firm: What is your position title: • If you would like to receive the summarized report of the survey, please provide the following information Contact name: E-mail address: Mail Address: Please use the enclosed stamped envelope to return the completed survey or mail directly to Dr. John Tillquist Division of Management Information Systems Faculty of Commerce and Business Administration University of British Columbia, 2053 Main Mall, HA462 Vancouver, B.C. Canada V6TIZ2 Again, we thank you very much for your time and effort to support this study. S of S The University ol" British Columbia 65 Appendix 6: Procedures of Evaluating Significance of Discriminant Functions Wilks' Lambda Test in this study was used in discriminant analysis to examine which of the discriminant functions should be retained. The testing procedure is a residualization approach, which has steps as follows. 1. A l l the discriminant functions are tested simultaneously: the null hypothesis is that all discriminant functions are equal to 0, meaning that no discriminant function can describe group differences; and the alternative is that at least one is significant, meaning that there is at least one discriminant function that can describe group differences. 2. If the null hypothesis is rejected (indicating that at least one discriminant function is significant), then the largest (i.e., the first discriminant function because it explains most of the variance) discriminant function is removed and a test is made on the remaining functions (i.e., the residual) to determine i f they are significant. 3. At this stage, the null hypothesis is, only one (i.e., the largest) function differs from 0 3 7 ; the alternative is, more than one function is significant. If the null hypothesis is accepted, the procedure stops and it can be concluded that only one (i.e., the largest) function is required to describe group differences. It is because when null hypothesis is accepted, it means that all the residual functions cannot describe any group differences. 4. If the null hypothesis is rejected again, a second residual is created by removing the first 2 functions. Similarly, the next null hypothesis is, only 2 functions are significant; the alternative hypothesis is, more than 2 functions are significant. 5. The testing procedure wil l continue until either the residual becomes insignificant (i.e., null hypothesis is accepted) or one runs out of functions to test. It must be noted that in this procedure significance of any individual discriminant function cannot be determined. Only the retained functions as a whole can be proved significant. It is because the largest discriminant function has already been removed. The next null hypothesis is also that all discriminant functions are insignificant. If accepted, it means that only the removed largest discriminant function is significant. 66 References 1. Ajzen, I., "Attitudes, Personality, and behavior," Chapter 6, 1988. 2. Barras, Richard, "New Technology and The New Services: Towards An Innovation Strategy for Europe," Futures, December 1996, p.748-772. 3. Barclay, Donald W, "The Launch of Mbanx," Richard Ivey School of Business, October 1998. 4. Booz, Allen & Hamilton, "Millions Of Consumers To Use Internet Banking Booz Allen & Hamilton Study Indicates," July 8, 1996, http://www.bah.corn/press/net_banking.html. 5. Booz, Allen & Hamilton Inc., "Global Internet Banking Report: An Asia - Pacific - Japan Perspective," April 1997. 6. Burke, Lee, "Technology Adoption Strategy in Banking: Applying Miles and Snow to the Domain of Innovation," University of Washington University, paper presented in Virtual Proceedings 1996 for the Eastern Academy of Management (EAM), http ://blue .temple .edu/burke .html. 7. Chwelos, P, Benbasat, I & Dexter, A S. "EDI Adoption: An Empirical Test of an Integrative Model," working paper, University of British Columbia, 1997. 8. Chisholm, Jeffrey S., President of Mbanx, "Can a Bank Change," European Financial Management and Marketing Association Newsletter, May 1998. 9. Daniel, Elizabeth & Storey, Chris, "On-line Banking: Strategic and Management Challenges," Long Range Planning, December 1997, p.890-898. 10. Dillon, W R & Goldstein M , "Multivariate Analysis, Methods and Applications," Chapter 10 and 11, 1984. 11. Dintz, Eduardo, "Web banking in USA," Journal of Internet Banking and Commerce, June 1998. 12. 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