UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

High technology locational factors : an analysis of major cities in Canada Short, Joel Nelson 1988

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
831-UBC_1989_A8_2 S46.pdf [ 7.3MB ]
Metadata
JSON: 831-1.0097986.json
JSON-LD: 831-1.0097986-ld.json
RDF/XML (Pretty): 831-1.0097986-rdf.xml
RDF/JSON: 831-1.0097986-rdf.json
Turtle: 831-1.0097986-turtle.txt
N-Triples: 831-1.0097986-rdf-ntriples.txt
Original Record: 831-1.0097986-source.json
Full Text
831-1.0097986-fulltext.txt
Citation
831-1.0097986.ris

Full Text

HIGH TECHNOLOGY LOCATIONAL FACTORS: An Analysis of Major Cities in Canada by - JOEL NELSON SHORT B .A . , The University of Vic tor ia , 1983 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS in THE FACULTY OF GRADUATE STUDIES School of Community and Regional Planning We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA September 1988 © J o e l Nelson Short, 1988 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. Department of The University of British Columbia Vancouver, Canada DE-6 (2/88) ABSTRACT High technology i n d u s t r i e s have caught the a t t e n t i o n of many l o c a l economic development agencies, and many of these agencies have attempted to a t t r a c t high technology i n d u s t r i e s to t h e i r areas. There i s a lack of in f o r m a t i o n , however, on the f a c t o r s that i n f l u e n c e the l o c a t i o n of high technology. This study attempts to determine the l o c a t i o n f a c t o r s that are important f o r high technology i n d u s t r i e s i n Canada. Because no u n i v e r s a l l y accepted d e f i n i t i o n of high technology e x i s t s , previous d e f i n i t i o n s of high technology are examined, and a s u i t a b l e d e f i n i t i o n i s developed f o r Canada. A review of e x i s t i n g l i t e r a t u r e on the l o c a t i o n a l f a c t o r s f o r high technology i n d u s t r y i s conducted, and based on t h i s review, a set of l o c a t i o n a l f a c t o r s to be examined f o r Canada i s e s t a b l i s h e d . Data on the l o c a t i o n of high technology i n Canadian Census M e t r o p o l i t a n Areas (CMAs) are examined, as w e l l as the s p a t i a l i ncidence of the p o t e n t i a l l o c a t i o n a l f a c t o r s across the 24 Canadian CMAs. Regression a n a l y s i s i s used to determine the strengths of r e l a t i o n s h i p s between high technology i n d u s t r y and l o c a t i o n a l f a c t o r s . The r e s u l t s of t h i s study are compared to the r e s u l t s of s i m i l a r s t u d i e s conducted i n the U.S. and A u s t r a l i a . This study f i n d s that few of the p o t e n t i a l l o c a t i o n a l f a c t o r s examined have a high c o r r e l a t i o n with the l o c a t i o n of high technology i n d u s t r i e s . Percentage of labour forc e i n s c i e n t i f i c , engineering and mathematical occupations; telephones per c a p i t a ; income l e v e l s ; d w e l l i n g p r i c e s ; a i r p o r t s i z e ; u n i v e r s i t y enrolment; and percentage of labour forc e w i t h u n i v e r s i t y i i degrees are s i g n i f i c a n t f a c t o r s ; however i t i s not c l e a r i f d i f f e r e n c e s i n these v a r i a b l e s i n f l u e n c e the l o c a t i o n of high technology, or i f the presence of high technology i n d u s t r i e s generate d i f f e r e n c e s i n these v a r i a b l e s . A comparison of the r e s u l t s of t h i s study with the r e s u l t s of s i m i l a r s t u d i e s conducted i n the U.S. and A u s t r a l i a reveals several s i m i l a r i t i e s and a few d i f f e r e n c e s . TABLE OF CONTENTS Abstract i i L i s t of Tables v i CHAPTER I - INTRODUCTION 1 1.1 Purpose 1 1.2 Context 3 1.3 S i g n i f i c a n c e 6 1.4 Methodology 7 1.5 L i m i t a t i o n s 9 1.6 Orga n i z a t i o n 10 CHAPTER I I - DEFINING HIGH TECHNOLOGY 11 2.1 D i f f i c u l t i e s i n D e f i n i n g High Technology 11 2.1.1 Uncertainty over the term 'High Technology'(11); 2.1.2 Competing D e f i n i t i o n s (12); 2.1.3 Goals Behind High Tech (13); 2.1.4 Obstacles to D e f i n i t i o n (14) 2.2. High Technology D e f i n i t i o n s E x i s t i n g i n the L i t e r a t u r e . . . . 15 2.2.1 Research and Development D e f i n i t i o n s (15); 2.2.2 Employee Occupation D e f i n i t i o n s (17); 2.2.3 Growth D e f i n i t i o n s (23); 2.2.4 Technological S o p h i s t i c a t i o n D e f i n i t i o n s (26); 2.2.5 Other D e f i n i t i o n s (27) 2.3 D e f i n i t i o n of High Technology 28 CHAPTER I I I - LOCATION FACTORS IN THE LITERATURE 37 3.1 Location Factors i n General 37 3.1.1 What are 'Location Factors'? (37); 3.1.2 The Value of Knowing Location Factors (37); 3.1.3 Determining Location Factors (38) 3.2 L o c a t i o n a l Factors I d e n t i f i e d i n Three Major Studies 39 3.2.1 The Glasmeier, H a l l and Markusen Study (40); 3.2.2 The Premus Study (43); 3.2.3 The Newton and O'Connor Study (47) 3.3 Seven Groups of Location Factors I d e n t i f i e d i n the L i t e r a t u r e . . 49 3.3.1 U n i v e r s i t y Presence and S k i l l e d Labour (50); 3.3.2 Defense Spending (52); 3.3.3 Agglomeration Economies and I n e r t i a (53); 3.3.4 Business Climate (54); 3.3.5 Tra n s p o r t a t i o n and Communication (56); 3.3.6 Local Costs and A v a i l a b i l i t y Factors (57); 3.3.7 Q u a l i t y of L i f e (58); 3.3.8 Non- q u a n t i f i a b l e Power and Influence Factors (60); 3.3.9 R e l a t i v e Importance of Location Factors (62) 3.4 Lo c a t i o n Factors Examined f o r Canada 63 CHAPTER IV - DATA DESCRIPTION 68 4.1 I n t r o d u c t i o n 68 i v 4.2 Data on the Location of High Technology 68 4.2.1 Data Gathering and O p e r a t i o n a l i z a t i o n (68); 4.2.2 D i s t r i b u t i o n of High Tech i n Canada (69); 4.3 D i s t r i b u t i o n of Location f a c t o r s i n Canada 69 CHAPTER V - DATA ANALYSIS 82 5.1 D e s c r i p t i o n of A n a l y s i s 82 5.2 B i v a r i a t e Regression A n a l y s i s 83 5.2.1 I n t r o d u c t i o n (83); 5.2.2 U n i v e r s i t y Enrolment (83); 5.2.3 Education Level (87); 5.2.4 S c i e n t i f i c , Engineering and Mathematical Occupations (88); 5.2.5 Natural Science Expenditures (89); 5.2.6 Union Membership (91); 5.2.7 I n d u s t r i a l Research and Development Employees (92); 5.2.8 Federal Government Employment (93); 5.2.9 A i r l i n e F l i g h t s (94); 5.2.10 Number of Telephones (94); 5.2.11 Average Family Income (95); 5.2.12 Consumer P r i c e Index (96); 5.2.13 E l e c t r i c i t y Rates (97); 5.2.14 Average Dwelling P r i c e (97); 5.2.15 Sunshine and Warm Weather (98); 5.2.16 A i r Q u a l i t y Index (99) 5.3 M u l t i p l e Regression A n a l y s i s 99 5.4 Comparison of Results w i t h Other Studies 102 5.4.1 Comparison with United States Study (102); 5.4.2 Comparison with A u s t r a l i a n Study (105) 5.5 Relevance of Results to Planners 108 5.5.1 No Prime L o c a t i o n a l Determinant (108); 5.5.2 Economic Development (108); 5.5.3 Housing (109); 5.5.4 Education and Labour Force (111); 5.5.5 A i r T r a n s p o r t a t i o n (111); 5.5.6 N o n - l i m i t i n g Factors (112); 5.5.7 P o l i c y A n a l y s i s (112); CHAPTER VI - CONCLUSION 114 6.1 Study Conclusions 114 6.2 S i m i l a r i t i e s w i t h Other Studies 116 6.3 L i m i t a t i o n s of Methodology 117 6.4 A l t e r n a t i v e Approaches to t h i s Study 118 6.5 Suggestions f o r Further Study 120 APPENDIX I - CHARACTERIZATION OF HIGH TECH IN EACH CMA 122 APPENDIX I I - DATA SOURCES AND THE INCIDENCE OF LOCATION FACTORS IN EACH CMA 130 BIBLIOGRAPHY 141 v LIST OF TABLES Table 1 High Technology I n d u s t r i e s as Defined by Glasmeier, H a l l and Markusen 19 Table 2 Standard I n d u s t r i a l C l a s s i f i c a t i o n (SIC) Codes of Recent High Technology Industry D e f i n i t i o n s 29 Table 3 High Tech I n d u s t r i e s i n Canada 36 Table 4 Factors Associated w i t h M e t r o p o l i t a n Dependence on High technology 41 Table 5 Factors Associated with High Technology Job S h i f t s 41 Table 6 Factors Associated w i t h High Tech Plant S h i f t s 42 Table 7 V a r i a b l e s I n s i g n i f i c a n t i n E x p l a i n i n g High Tech Industry Locations 43 Table 8 Most Commonly Occurring and Consistency Ranking of V a r i a b l e s E x p l a i n i n g Net Plant Change 44 Table 9 Factors that Influence the Regional Location Choices of High Technology Companies 45 Table 10 Factors that Influence the Choice of a High Technology Company's Loc a t i o n W i t h i n a Region 46 Table 11 C o r r e l a t i o n of L o c a t i o n a l Factors w i t h the Location of High Tech i n Melbourne 48 Table 12 Regression A n a l y s i s R e s u l t s , Location Factors — High Tech Location 49 Table 13 L o c a t i o n Factors to be Examined and Expected R e l a t i o n s h i p . . . . 64 Table 14 Employment by High Tech Sector by Census M e t r o p o l i t a n Area . . . . 70 Table 15 Location Factor D i s t r i b u t i o n i n Canada by Census M e t r o p o l i t a n Area 79 Table 16 Results of B i v a r i a t e Regression Analyses Between High Tech and L o c a t i o n Factors 84 Table 17 A l t e r n a t i v e High Tech D e f i n i t i o n s , L i s t of I n d u s t r i e s Included 86 Table 18 Comparison of C o r r e l a t i o n Values f o r A u s t r a l i a and Canada . . . . 106 Table 19 M u l t i p l e Regression R e s u l t s , A u s t r a l i a Canada Comparison 107 v i Table 20 Results of B i v a r i a t e Regression A n a l y s i s Between High Tech and Location Factors 115 v i i CHAPTER I INTRODUCTION  1.1 Purpose "High Tech i n d u s t r i e s have a l o t going f o r them. Investors are w i l l i n g to provide c a p i t a l . Their products are i n demand. Economic developers are s t r i v i n g to l u r e them to t h e i r areas" (Bergeron, 1983). Advanced technology a c t i v i t i e s have a t t r a c t e d the a t t e n t i o n of many economic development or g a n i z a t i o n s because these a c t i v i t i e s maintained strong growth i n the e a r l y 1980s while other s e c t o r s of the economy were experiencing s i g n i f i c a n t r e c e s s i o n and d e c l i n e . Faced with d e c l i n i n g employment i n t r a d i t i o n a l i n d u s t r i a l s e c t o r s , many communities looked to high technology as a panacea f o r t h e i r economic woes. Thousands of economic development agencies s t r a i n e d amidst the importuning clamour attempting to a t t r a c t high technology i n d u s t r i e s that would make t h e i r regions new and prosperous " S i l i c o n V a l l e y s " . Numerous communities asked: what was necessary? What d i d the high technology i n d u s t r i e s want i n order f o r them to l o c a t e i n a s p e c i f i c community and allow that community to become an advanced technology centre? The economic developers were w i l l i n g to s a c r i f i c e t a x a t i o n , land, anything to a t t r a c t high technology. Many of these communities d i d not r e a l i z e that i t took time to b u i l d a r o s t e r of high technology i n d u s t r i e s w i t h i n t h e i r communities. S i l i c o n V a l l e y d i d not grow up overnight. I t s t a r t e d almost f i f t y years ago i n 1938 when Hewlett - Packard Co. began operations i n as small garage i n Palo A l t o (Saxenian, 1983). Many communities d i d not r e a l i z e the 1 length of time i t took to develop high tech and consequently have become d i s i l l u s i o n e d i n t h e i r search f o r high tech. Recently economic development commissions have come to r e a l i z e that i t takes time to b u i l d a high technology centre and that high tech i s not the panacea i t was e a r l i e r seen to be. High technology i s now seen more as part of an o v e r a l l economic development s t r a t e g y . I t remains an important sector of the economy and promises long-term development p o t e n t i a l through continuous growth and i n n o v a t i o n . The e f f o r t s of such i n d u s t r i e s help maintain continued v i t a l i t y i n a l o c a l economy. What, then, i s necessary to develop or a t t r a c t high technology i n d u s t r i e s ? Part of the answer might be found by examining where high technology i s p r e s e n t l y l o c a t i n g and the a t t r i b u t e s a s s o c i a t e d w i t h the p a r t i c u l a r l o c a t i o n . This type of examination has yet to be done f o r Canada. The purpose of t h i s t h e s i s i s to determine the f a c t o r s that are s i g n i f i c a n t l y c o r r e l a t e d w i t h the l o c a t i o n of high technology i n d u s t r i e s i n Canada. The n u l l hypothesis, which t h i s t h e s i s w i l l attempt to disprove, i s that no l o c a t i o n a l f a c t o r s examined w i l l have a s t a t i s t i c a l l y s i g n i f i c a n t r e l a t i o n s h i p w i t h the l o c a t i o n of high technology a c t i v i t i e s . In order to examine Canadian high technology i n d u s t r i e s an o p e r a t i o n a l d e f i n i t i o n of high technology i s necessary. As a r e s u l t , a secondary purpose of t h i s t h e s i s i s to i d e n t i f y a d e f i n i t i o n of high technology that w i l l be both l o g i c a l l y sound and r e a d i l y a p p l i c a b l e to the a v a i l a b l e data base. Once a s u i t a b l e d e f i n i t i o n has been i d e n t i f i e d , i t w i l l then be used to determine which i n d u s t r i e s are high tech i n Canada. Another purpose of t h i s study i s to compare any s i g n i f i c a n t l o c a t i o n a l f a c t o r s found f o r Canada with the l o c a t i o n a l f a c t o r s i d e n t i f i e d i n the United 2 States and A u s t r a l i a . By uncovering s i m i l a r i t i e s and d i f f e r e n c e s between Canada and other c o u n t r i e s , the study can add to the knowledge of where Canada stands i n r e l a t i o n to other c o u n t r i e s regarding high technology l o c a t i o n a l f a c t o r s . I f s i m i l a r i t i e s are found, then perhaps p o l i c i e s regarding s i m i l a r l o c a t i o n a l f a c t o r s i n other c o u n t r i e s would be examined f o r t h e i r p o t e n t i a l a p p l i c a b i l i t y to Canada. D i f f e r e n c e s that are found may lead to i n v e s t i g a t i o n s of the cause of those d i f f e r e n c e s and how Canada may r e q u i r e unique p o l i c i e s f o r s p e c i f i c l o c a t i o n a l f a c t o r s . In summary, the purposes of t h i s t h e s i s i s to i d e n t i f y a d e f i n i t i o n of high technology, to determine the important l o c a t i o n a l f a c t o r s f o r high technology i n Canada, and to compare the important l o c a t i o n a l f a c t o r s i n Canada with those found i n other c o u n t r i e s . 1.2 Context This t h e s i s f i t s w i t h i n the context of previous work done on high technology l o c a t i o n a l f a c t o r s and d e f i n i t i o n s of high technology. I t a l s o f o l l o w s some of the same a n a l y t i c a l patterns taken by other s t u d i e s examining the l o c a t i o n of high technology. The work that most c l o s e l y p a r a l l e l s t h i s t h e s i s i s part of a l a r g e r study conducted by Glasmeier, H a l l and Markusen (1983) at the I n s t i t u t e of Urban and Regional Development at the U n i v e r s i t y of C a l i f o r n i a Berkeley. Part of t h i s study i s comprised of a r e g r e s s i o n a n a l y s i s used to determine the r e l a t i o n s h i p between the incidence of high technology i n d u s t r i e s and the incidence of various l o c a t i o n a l f a c t o r s across 218 s t a t i s t i c a l m e t r o p o l i t a n areas i n the United States. 3 Several other authors have examined l o c a t i o n a l f a c t o r s f o r high technology using other methodologies. C a s t e l l s (1985) proposed a model of high tech l o c a t i o n based on an assessment of recent work by seven other authors. The f i v e c h a r a c t e r i s t i c s that he noted as important to make a place a t t r a c t i v e to high tech are major u n i v e r s i t i e s , space and m i l i t a r y spending, venture c a p i t a l , lack of a union presence, and a good l o c a t i o n i n a t r a n s p o r t a t i o n and communication network. In an a r t i c l e on high technology Peter H a l l and Ann Markusen (1985) pointed to sev e r a l important l o c a t i o n a l f a c t o r s , i n c l u d i n g government R & D l a b o r a t o r i e s , m i l i t a r y spending, a h i g h l y s k i l l e d labour f o r c e , a good p h y s i c a l and s o c i a l environment, good communications i n t e r n a l l y and g l o b a l l y , and agglomeration f o r c e s . Robert Premus (1982) conducted a U.S. nation-wide survey of high tech firms and found that s e v e r a l f a c t o r s were s i g n i f i c a n t to t h e i r d e c i s i o n s on where to loc a t e new plant f a c i l i t i e s . He ranked the f a c t o r s , and the top f i v e , s t a r t i n g w i t h the most important, are labour s k i l l s and a v a i l a b i l i t y , labour c o s t s , tax cl i m a t e w i t h i n a re g i o n , academic i n s t i t u t i o n s , and the cost of l i v i n g . Past attempts to define high technology a l s o form part of the context of t h i s t h e s i s . Several attempts have been made to deal w i t h the problem of d e f i n i n g high tech a c t i v i t i e s . D i f f i c u l t i e s a r i s e from the t r a d e - o f f s that must be made between a sound conceptual d e f i n i t i o n of high tech and p r a c t i c a l i t i e s i n the measurement of high tech (Newton and O'Connor, 1985). E x i s t i n g d e f i n i t i o n s that t r y to overcome the d i f f i c u l t i e s u s u a l l y deal w i t h the type of labour f o r c e employed and the type of product produced. Newton and O'Connor (1985 p.3) i n d i c a t e s that a widely accepted d e f i n i t i o n i s that advanced by Glasmeier H a l l and Markusen (1983) based on "the degree of 4 s o p h i s t i c a t i o n and competence embodied i n the t e c h n i c a l occupations w i t h i n the i n d u s t r y " . The d e f i n i t i o n can make use of a v a i l a b l e data on the percentages of s c i e n t i f i c , engineering, and t e c h n i c a l occupations i n an i n d u s t r y , making i t easy to o p e r a t i o n a l i z e . Malecki (1984) points to other d e f i n i t i o n s that r e l y on the inputs of research and development (R & D). I n d u s t r i e s w i t h s i g n i f i c a n t l y above-average expenditures on R & D are considered as high tech. Measures i n c l u d e r a t i o s of R & D expenditure to s a l e s , t o t a l investments, or value added. D e f i n i t i o n s that r e l y on employment p r o f i l e s or R & D expenditures are l i m i t e d , however, i n that they emphasize the development stages of high tech, and de-emphasize the manufacturing and use aspects of high tech. Premus (1982) employs a broader three part d e f i n i t i o n , i n d i c a t i n g that high tech firms are l a b o u r - i n t e n s i v e rather than c a p i t a l - i n t e n s i v e i n t h e i r production processes; they are science based, applying new advances to the marketplace i n the form of new products and processes; and R & D i s more important to high tech than to other f i r m s . However, he does not o p e r a t i o n a l l y d e fine the three parts and goes on to simply choose f i v e t w o - d i g i t S.I.C. categories that he f e e l s f i t the d e f i n i t i o n . The Economic Council of Canada i s developing a d e f i n i t i o n based more on the t e c h n o l o g i c a l s o p h i s t i c a t i o n of the products produced and/or used by an i n d u s t r y (Economic Council of Canada, 1985). Hopefully t h i s w i l l prove to be a broader and more widely a p p l i c a b l e d e f i n i t i o n . A drawback i n d e a l i n g w i t h the products produced or used i s that data r e l a t i n g to these d e f i n i t i o n s are d e f i c i e n t (Wiewel et a l . , 1984). 5 1.3 S i g n i f i c a n c e This t h e s i s i s s i g n i f i c a n t to the planning p r o f e s s i o n i n f i v e areas of endeavour: economic development, p o l i c y development, land use management, f o r e c a s t i n g and suggestions f o r f u r t h e r research. Planners i n v o l v e d i n economic development may consider the development of high technology i n d u s t r i e s i n t h e i r community as part of a broader economic development s t r a t e g y . In order to encourage high technology i n d u s t r i e s , planners need i n f o r m a t i o n on various aspects of the i n d u s t r y . Knowing how high technology i n d u s t r i e s l o c a t e w i l l be an important part of that l a r g e r set of infor m a t i o n . Awareness of l o c a t i o n a l f a c t o r s that are important to high technology w i l l allow planners to b e t t e r d i r e c t e f f o r t s to develop the i n d u s t r y i n t h e i r community. The management and d i r e c t i o n of land use forms an i n t e g r a l part of the planning p r o f e s s i o n . Planners can e s t a b l i s h uses allowed i n s p e c i f i c areas and they can i n d i c a t e where c e r t a i n uses should be e s t a b l i s h e d . By knowing s p e c i f i c land uses that r e l a t e to the l o c a t i o n of high technology a c t i v i t i e s , planners w i l l be b e t t e r able to manage and d i r e c t the l o c a t i o n and content of high technology a c t i v i t i e s i n a community. The r e s u l t s of t h i s t h e s i s may be important to planners i n v o l v e d i n f o r e c a s t i n g . I f strong r e l a t i o n s h i p s are found between the l o c a t i o n of high technology and various l o c a t i o n a l f a c t o r s , the p r o b a b i l i t y of high technology l o c a t i n g i n an area could be determined based on c e r t a i n a t t r i b u t e s found i n a community. The a b i l i t y to f o r e c a s t the development of high technology i n an area may increase the a b i l i t y to fo r e c a s t employment, income, and population growth i n an area. 6 This t h e s i s w i l l a l s o be s i g n i f i c a n t to planners i n that i t w i l l provide d i r e c t i o n f o r f u r t h e r research. I t w i l l i d e n t i f y c e r t a i n l o c a t i o n a l f a c t o r s that should be examined more c l o s e l y . I t w i l l a l s o point to research that i s a l o g i c a l extension of t h i s t h e s i s such as an examination of the change i n the l o c a t i o n of high tech over time i n Canada, and the p o t e n t i a l i n f l u e n c e s that p o l i c i e s may have had i n generating that change. While t h i s t h e s i s may point to some f r u i t f u l new avenues of research, i t s primary s i g n i f i c a n c e r e s t s i n the knowledge i t w i l l give planners on how high technology i n d u s t r i e s l o c a t e . 1.4 Methodology The methodology followed i n the execution of t h i s t h e s i s i s comprised of an i n i t i a l review of l i t e r a t u r e on d e f i n i t i o n s and l o c a t i o n a l f a c t o r s f o r high technology, followed by c o m p i l a t i o n of data on the l o c a t i o n of high technology and i t s p o t e n t i a l l o c a t i o n a l f a c t o r s , and concluding w i t h a s t a t i s t i c a l a n a l y s i s of the r e l a t i o n s h i p s between the l o c a t i o n of high technology and i t s various l o c a t i o n a l f a c t o r s . The l i t e r a t u r e review w i l l examine d e f i n i t i o n s of high technology used i n research conducted on high technology a c t i v i t i e s i n the United States, the United Kingdom and A u s t r a l i a . From t h i s examination a d e f i n i t i o n of high technology w i l l be chosen that i s most appropriate f o r the purposes of t h i s study. The l i t e r a t u r e review w i l l a l s o o u t l i n e past research done i n the same three nations on l o c a t i o n a l f a c t o r s f o r high technology. From those f a c t o r s uncovered i n past research, a number of f a c t o r s w i l l be chosen which have a v a i l a b l e data and which show promise f o r having a s i g n i f i c a n t r e l a t i o n s h i p w i t h the l o c a t i o n of high technology. 7 The chosen d e f i n i t i o n of high technology w i l l be a p p l i e d to the Canadian s i t u a t i o n to determine which i n d u s t r i e s i n Canada are defined as high technology i n d u s t r i e s . Data on the labour f o r c e employed i n the defined high technology i n d u s t r i e s across the various Census M e t r o p o l i t a n Areas w i l l then be compiled. This w i l l show the d i s t r i b u t i o n of high technology i n d u s t r i e s across Canada. Operational d e f i n i t i o n s w i l l be e s t a b l i s h e d f o r each l o c a t i o n a l f a c t o r and data w i l l be compiled on the i n t e n s i t y of the l o c a t i o n a l f a c t o r s i n each of the Census M e t r o p o l i t a n Areas. This w i l l show how the l o c a t i o n a l f a c t o r s are d i s t r i b u t e d across the various metropolitan areas of Canada. Once the data have been compiled i t w i l l be entered i n t o a Lotus 123 spreadsheet w i t h each row corresponding to a s p e c i f i c CMA and the columns corresponding to the labour f o r c e i n high technology and the values i d e n t i f i e d f o r various l o c a t i o n a l f a c t o r s . Using Lotus 123, b i v a r i a t e r e g r e s s i o n analyses w i l l be conducted to analyze the r e l a t i o n s h i p between the labour force employed i n high technology and the value f o r l o c a t i o n a l f a c t o r s . A s c a t t e r p l o t of the r e l a t i o n s h i p f o r each l o c a t i o n a l f a c t o r s w i l l be produced and analyzed, w i t h the i n t e n s i t y of the l o c a t i o n a l f a c t o r s on the x - a x i s , and the employment i n high technology on the y - a x i s , and w i t h each CMA represented by a point on the s c a t t e r p l o t . The R2 value f o r each r e g r e s s i o n a n a l y s i s w i l l be produced and analyzed to determine the variance i n the dependent v a r i a b l e (employment i n high technology) that i s explained by the independent v a r i a b l e s (values f o r l o c a t i o n a l f a c t o r s ) . Those l o c a t i o n a l f a c t o r s w i t h a high R2 w i l l be i d e n t i f i e d as those f a c t o r s being p o t e n t i a l l y important l o c a t i o n a l f a c t o r s f o r high technology. A stepwise m u l t i p l e r e g r e s s i o n a n a l y s i s w i l l a l s o be conducted using the SPSS:X 8 s t a t i s t i c a l a n a l y s i s program. This w i l l allow general l o c a t i o n a l f a c t o r s to be entered i n t o an explanatory equation. The m u l t i p l e r e g r e s s i o n a n a l y s i s w i l l a l s o i d e n t i f y those v a r i a b l e s that e x p l a i n the greatest amount of v a r i a t i o n i n the l o c a t i o n of high tech. The l o c a t i o n a l f a c t o r s w i t h a high R2 i n Canada w i l l be compared w i t h those l o c a t i o n a l f a c t o r s i d e n t i f i e d as being s t r o n g l y r e l a t e d to high technology i n other c o u n t r i e s . 1.5 L i m i t a t i o n s The l i m i t a t i o n s of t h i s t h e s i s a r i s e p r i m a r i l y from l i m i t a t i o n s i n data a v a i l a b i l i t y ; however, some l i m i t a t i o n s are inherent i n the a n a l y t i c a l techniques used. Data e x i s t only f o r a l i m i t e d number of l o c a t i o n a l f a c t o r s . Even though some s p e c i f i c l o c a t i o n a l f a c t o r s are found to be important, i n v e s t i g a t i o n of the f a c t o r s might be l i m i t e d due to d i f f i c u l t i e s i n q u a n t i f y i n g the f a c t o r s , a complete lack of data on a f a c t o r , or missing data f o r some of the Census M e t r o p o l i t a n Areas. Discrepancies and l i m i t a t i o n s i n the accuracy of the a n a l y s i s may a l s o a r i s e due to d i f f e r e n c e s i n the boundaries of urban regions f o r d i f f e r e n t data types. A l i m i t a t i o n inherent i n the re g r e s s i o n a n a l y s i s that w i l l be performed i s that a r e g r e s s i o n a n a l y s i s only shows a c o r r e l a t i o n a l r e l a t i o n s h i p and not a cause and e f f e c t r e l a t i o n s h i p . A strong R2 r e l a t i o n s h i p between a l o c a t i o n a l f a c t o r and high tech w i l l only show that a s p e c i f i c l o c a t i o n a l f a c t o r s h i f t s i n i n t e n s i t y over space i n a manner that i s some c l o s e f u n c t i o n of the way the i n t e n s i t y of high technology a c t i v i t y s h i f t s over space. I t does not prove that a s p e c i f i c f a c t o r caused a high technology a c t i v i t y to 9 l o c a t e i n a p a r t i c u l a r CMA, or even that high technology a c t i v i t i e s caused a p a r t i c u l a r l o c a t i o n a l f a c t o r to develop i n the area. A strong R2 can only lead one to say that where a s p e c i f i c l o c a t i o n a l f a c t o r can be found there i s a high p r o b a b i l i t y that high technology a c t i v i t y w i l l be found i n accordance with the f u n c t i o n a l r e l a t i o n s h i p i d e n t i f i e d as e x i s t i n g between high tech and a s p e c i f i c f a c t o r . 1.6 Organization This t h e s i s i s organized i n t o s i x chapters. Subsequent to t h i s f i r s t chapter, the a d d i t i o n a l f i v e chapters are organized as f o l l o w s : Chapter 2 - defines high technology, f i r s t examining the d i f f i c u l t i e s i n d e f i n i n g high technology, then reviewing e x i s t i n g d e f i n i t i o n s and f i n a l l y choosing an appropriate d e f i n i t i o n . Chapter 3 - i d e n t i f i e s l o c a t i o n a l f a c t o r s f o r high technology by f i r s t reviewing l o c a t i o n a l f a c t o r s f o r high technology noted i n the l i t e r a t u r e and s t i p u l a t i n g the l o c a t i o n a l f a c t o r s that w i l l be examined i n t h i s study. Chapter 4 - presents a d e s c r i p t i o n and overview of the data by f i r s t d e s c r i b i n g how the data was c o l l e c t e d , then d i s c u s s i n g the d i s t r i b u t i o n of high technology a c t i v i t i e s i n Canada and f i n a l l y d i s c u s s i n g the d i s t r i b u t i o n of l o c a t i o n a l f a c t o r s i n Canada. Chapter 5 - w i l l present the r e s u l t s of the data a n a l y s i s , a comparison of the r e s u l t s to f i n d i n g s i n the United States and A u s t r a l i a , and a d i s c u s s i o n of the relevance of the r e s u l t s to planners. Chapter 6 - w i l l d iscuss the conclusions of the study and suggest f u r t h e r avenues of study that might be pursued. 10 CHAPTER I I DEFINING HIGH TECHNOLOGY 2.1 D i f f i c u l t i e s i n D e f i n i n g High Technology Before a s t r u c t u r e d i n v e s t i g a t i o n i n t o the l o c a t i o n a l c h a r a c t e r i s t i c s of high technology a c t i v i t i e s can occur, an acceptable d e f i n i t i o n of high technology must f i r s t be e s t a b l i s h e d . D e f i n i n g high technology, however, i s not simply a matter of c o n s u l t i n g the l i t e r a t u r e f o r the c u r r e n t l y accepted d e f i n i t i o n , because a wide v a r i e t y of competing d e f i n i t i o n s e x i s t . 2.1.1. Uncertainty over the term 'High Technology' In the l i t e r a t u r e and the media there has been considerable u n c e r t a i n t y as to what e x a c t l y the term 'high technology' i s meant to in c l u d e . The term 'high tech' i s often used l o o s e l y , r e f e r r i n g to some vague set of i n d u s t r i e s c h a r a c t e r i z e d by high growth and the use of advancing technologies. Breheny, Cheshire and Langridge (1985, pp. 119 -120) note that "Not only does the a v a i l a b l e l i t e r a t u r e show an ignorance of the nature of reasons f o r the high tech growth..., but i t a l s o shows great confusion as to ju s t what c o n s t i t u t e s high-technology i n d u s t r y . . . . Too oft e n the term 'high tech' i s no more than p o l i t i c a l glibspeak or property developer's a d v e r t i s i n g copy." Malecki (1984, p. 263) i n d i c a t e d that " The d e f i n i t i o n of 'high technology' i s one of the fundamental stumbling blocks i n the study of current economic change and the design of l o c a l economic development p o l i c y . A common i n t e r p r e t a t i o n simply i n c l u d e s an i n d u s t r y that has been growing or i s l i k e l y to grow i n employment, but that s o r t of c l a s s i f i c a t i o n i s not very meaningful". "To some," the O f f i c e of Technology Assessment (1985, p.17) 11 a s s e r t s , "the term 'high technology* r e f e r s to a vague notio n of i n d u s t r i e s i n v o l v e d w i t h computers, telecommunications, e l e c t r o n i c s , biotechnology and other emerging and r a p i d l y e v o l v i n g technologies". The Economic Council of Canada (1985, p. 2) found that "While most people have a hazy idea of what c o n s t i t u t e s a high tech i n d u s t r y , Council researchers found i t hard to p i n down one unanimously accepted d e f i n i t i o n " . 2.1.2. Competing D e f i n i t i o n s "As yet, as many d e f i n i t i o n s have emerged as there are research p r o j e c t s . " (Breheny and McQuaid 1985, p. 5). Because of the wide v a r i e t y of d e f i n i t i o n s that has been developed, there i s some disagreement over which d e f i n i t i o n best a p p l i e s . " There i s considerable debate about what c o n s t i t u t e s a high technology i n d u s t r y . Although the computer and m i c r o e l e c t r o n i c s i n d u s t r i e s are g e n e r a l l y considered to be 'high tech', the i n c l u s i o n of other t e c h n o l o g y - i n t e n s i v e i n d u s t r i e s , such as chemicals and machinery, i s c o n t r o v e r s i a l . A number of measures have been used to define high tech, a l l of which lack p r e c i s i o n and c o m p a r a b i l i t y .... S p e c i f i c a l l y the measures e i t h e r are too aggregate or f a i l to t r e a t a l l i n d u s t r i e s i n the same manner." (Glasmeier 1985, p. 56). Glasmeier, H a l l and Markusen (1983, p . l ) a l s o note that the term 'high technology' has d i f f e r e n t meanings w i t h i n d i f f e r e n t contexts such as economic development contexts, i n d u s t r i a l contexts, p o l i t i c a l contexts, and academic contexts. Weiss (1985, p. 80) i n d i c a t e s there i s "a modest amount of disagreement" over the i n d u s t r i e s that should be i n c l u d e d as high tech. He goes on to question how 'high' tech d i f f e r s from 'low' or 'medium' technology; whether high tech i s part of the 12 process or the product; and i f i t i s n e c e s s a r i l y connected with manufacturing or d i s t r i b u t i o n , goods or s e r v i c e s , new or o l d innovations. 2.1.3 Goals Behind High Tech A f u r t h e r complicating f a c t o r behind the d e f i n i t i o n of high tech i s that the type of d e f i n i t i o n used may depend on the reasons f o r examining high tech i n the f i r s t place. If a community i s examining high tech from the point of view of attempting to generate a h i g h l y s k i l l e d work f o r c e , then i t may want to define high tech as those i n d u s t r i e s that have a high p r o p o r t i o n of s k i l l e d and educated employees. I f a community i s i n t e r e s t e d p r i m a r i l y i n jobs of any s k i l l l e v e l , then i t might t r y to define high tech based on the type of product produced. That way the d e f i n i t i o n would i n c l u d e high tech product assembly and manufacturing f a c i l i t i e s that might employ r e l a t i v e l y u n s k i l l e d workers, as w e l l as research and development f a c i l i t i e s which employ h i g h l y s k i l l e d and educated employees. A community might be i n t e r e s t e d i n i n d u s t r i e s w i t h high growth p o t e n t i a l , and might define high tech as those i n d u s t r i e s which produce t e c h n o l o g i c a l l y advanced products and are experiencing high rates of growth. The primary a t t r a c t i o n i n high tech f o r other m u n i c i p a l i t i e s might be the c l e a n l i n e s s of these i n d u s t r i e s . Communities i n t e r e s t e d i n examining non-p o l l u t i n g i n d u s t r i e s might define high tech as those i n d u s t r i e s that produce a r e l a t i v e l y advanced product and e x h i b i t such p h y s i c a l a t t r i b u t e s as v i s u a l l y appealing b u i l d i n g s , few p o l l u t a n t s and low noise l e v e l s . 13 2.1.4 Obstacles to D e f i n i t i o n The primary problem i n d e f i n i n g high technology i s the compromise that u s u a l l y needs to be made between the sound c o n c e p t u a l i z a t i o n of high tech and the p r a c t i c a l i t i e s of measurement (Breheny and McQuaid 1985; Newton and O'Connor 1985). I t would be d e s i r a b l e to develop a d e f i n i t i o n that attempts to recognize the i n t e n s i t y of various high technology i n d i c a t o r s , such as the t e c h n o l o g i c a l s o p h i s t i c a t i o n of an i n d u s t r y ' s products, or the amount of Research and Development time spent i n developing products. I t i s d i f f i c u l t , however, to obt a i n q u a n t i f i a b l e data f o r many s p e c i f i c c h a r a c t e r i s t i c s . Another problem a r i s e s due to the co n s t a n t l y changing nature of the in d u s t r y ( O f f i c e of Technology Assessment 1984; Glasmeier 1985). An i n d u s t r y that may have been considered to be on the leading edge of inn o v a t i o n at one time may no longer be considered a part of the advanced technology universe. Further problems a r i s e when c o n s i d e r a t i o n i s given to the observation that not a l l of a high tech corporation's resources are devoted to a c t i v i t i e s that might be considered 'high tech'. Some parts of a f i r m may be in v o l v e d i n high tech, while others might not be. The f i n a l production of some advanced technology products - computer component assembly, f o r example - might i n v o l v e u n s k i l l e d manual labour performing r e p e t i t i o u s tasks. Perhaps production processes based l a r g e l y on manual labour should not be considered as high technology. The presence of problems i n d e f i n i n g high tech has le d not to a paucity but rather a p r o l i f e r a t i o n of d e f i n i t i o n s . The numerous e x i s t i n g d e f i n i t i o n s w i l l be discussed i n the next s e c t i o n . 14 2.2 High Technology D e f i n i t i o n s E x i s t i n g  i n the L i t e r a t u r e The high tech d e f i n i t i o n s discussed i n the l i t e r a t u r e are l a r g e l y confined to four major types based on the f o l l o w i n g i n d u s t r y c h a r a c t e r i s t i c s : research and development expenditures; p r o p o r t i o n of s c i e n t i f i c , engineering and t e c h n i c a l employees; recent rates of growth; and the t e c h n o l o g i c a l s o p h i s t i c a t i o n of products. Of course there are s e v e r a l d e f i n i t i o n s that do not f a l l w i t h i n these four c a t e g o r i e s , and there are d e f i n i t i o n s that use a combination of these and other c h a r a c t e r i s t i c s , but the vast m a j o r i t y f a l l i n t o the four categories mentioned above. 2.2.1 Research and Development D e f i n i t i o n s D e f i n i t i o n s that use research and development f i g u r e s are found i n several forms. Several authors have noted that high tech can be defined as those i n d u s t r i e s that have high research and development (R&D) expenditures i n r e l a t i o n to t o t a l s a l e s (Newton 1985; Glasmeier, Markusen and H a l l 1983; Rogers and Larsen 1984; O f f i c e of Technology Assessment 1984). This type of d e f i n i t i o n i s p a r t i c u l a r l y good f o r i d e n t i f y i n g firms that may be spending a great deal of time and e f f o r t on developing a new product that i s not yet i n f u l l production. I t a l s o i d e n t i f i e s firms t h a t , while experiencing s i g n i f i c a n t s a l e s volumes, continue to i n v e s t considerable funds i n R&D. This d e f i n i t i o n , however, tends to ignore those i n d u s t r i e s that are engaged i n high volume s a l e s of advanced technology products but spend a p r o p o r t i o n a t e l y smaller amount of funds on R&D. A c q u i r i n g accurate data f o r t h i s d e f i n i t i o n can a l s o be a problem. While f i g u r e s regarding s a l e s revenues are r e l a t i v e l y easy to o b t a i n , a c c u r a t e l y determining the expenditures on R&D can prove to 15 be d i f f i c u l t . Not a l l firms i d e n t i f y t h e i r expenditures on R&D, and those that do have t h e i r own d i s t i n c t d e f i n i t i o n s of what e x a c t l y R&D e n t a i l s . Another v e r s i o n of a high tech d e f i n i t i o n that uses R&D f i g u r e s i s a d e f i n i t i o n i d e n t i f i e d by Newton (1985) and the Economic Council of Canada (1985). This d e f i n i t i o n i s based on R&D expenditures i n r e l a t i o n to t o t a l investments. Once again t h i s d e f i n i t i o n w i l l h i g h l i g h t small firms that have r e l a t i v e l y few investments and spend a r e l a t i v e l y l a rge p o r t i o n of t h e i r budgets on R&D. This d e f i n i t i o n may overlook firms which have large investments yet s t i l l a l l o c a t e s i g n i f i c a n t resources f o r R&D. This d e f i n i t i o n a l s o s u f f e r s from the problem of R&D meaning d i f f e r e n t things to d i f f e r e n t companies, as w e l l as the problem of a c q u i r i n g accurate data. Other d e f i n i t i o n s u t i l i z i n g R&D f i g u r e s consider high tech i n d u s t r i e s to be those that have e i t h e r higher than average, s i g n i f i c a n t l y above average, or double the average proportionate expenditures on R&D (Malecki 1984; S h a k l i n and Ryans 1984; O f f i c e of Technology Assessment 1984). C e r t a i n l y t h i s d e f i n i t i o n would e l i m i n a t e many small firms that have r e l a t i v e l y low expenditures on R&D i n comparison to l a r g e r f i r m s , yet s t i l l spend a large p r o p o r t i o n of t h e i r budget on R&D. References have a l s o been made to R&D expenditures i n d e f i n i t i o n s that were not p r e c i s e l y o p e r a t i o n a l i z e d . For example, Markusen and Bloch (1985, p. 107) i n d i c a t e d that one of the components of a high tech company was "a large research and development e f f o r t a s s o c i a t e d with production". Premus (1982, p.4) i n d i c a t e d that one of the a t t r i b u t e s of high technology i n d u s t r i e s was that "R&D inputs are much more important to the continued s u c c e s s f u l operation of high technology firms than i s the case f o r other manufacturing i n d u s t r i e s . " Oakey (1984, p. 149) w r i t e s that "The common feature of a l l high 16 technology i n d u s t r i e s i s t h e i r uniformly high commitment to research and development, which i s a good broad d e f i n i t i o n of high technology i n d u s t r y . " . These d e f i n i t i o n s of high technology serve to show the importance that i s a t t r i b u t e d to the r o l e of research and development i n high technology i n d u s t r i e s . 2.2.2 Employee Occupation D e f i n i t i o n s A commonly used and widely accepted basis upon which to i d e n t i f y a high technology i n d u s t r y i s the p r o p o r t i o n of s c i e n t i f i c , engineering and t e c h n i c a l (SET) personnel w i t h i n the i n d u s t r y . A high technology i n d u s t r y would have a high p r o p o r t i o n of these types of employees. There are s e v e r a l v a r i a t i o n s on t h i s theme, and these are discussed below. D e f i n i t i o n s based on t h i s human c a p i t a l component of advanced technology i n d u s t r i e s d i f f e r p r i m a r i l y i n the occupations that are considered to be important to the d e f i n i t i o n ; and i n the p r o p o r t i o n of s p e c i f i c s c i e n t i f i c , engineering and t e c h n o l o g i c a l employees chosen as the c u t - o f f point f o r i n c l u s i o n i n the high technology group of i n d u s t r i e s . In a d e f i n i t i o n used by Newton and O'Connor (1985, pp. 6-7), seventeen s p e c i f i c occupations were chosen as f o l l o w s : " c i v i l engineers, e l e c t r i c a l and communications engineers, mechanical engineers, chemical engineers, m e t a l l u r g i s t s , p r o f e s s i o n a l engineers n . e . c , chemists, p h y s i c i s t s , g e o l o g i s t s and g e o p h y s i c i s t s , p h y s i c a l s c i e n t i s t s n . e . c , medical s c i e n t i s t s , b i o l o g i c a l and animal s c i e n t i s t s , s e n i o r u n i v e r s i t y academics, s t a t i s t i c i a n s and mathematicians, computer programmers and computer systems a n a l y s t s " . Newton and O'Connor then determined the percentage of the n a t i o n a l work forc e that comprised these types of employees. They found that only 1.4% of the 17 n a t i o n a l work forc e was made up of the above mentioned occupations and decided, based on work done i n the U.S. by Glasmeier, H a l l and Markusen (1983) to set the high tech cut o f f value at 6%. I n d u s t r i e s w i t h greater than 6% of t h e i r work forc e employed i n the chosen occupations would be considered as high tech. This d e f i n i t i o n was chosen to "... i d e n t i f y i n d u s t r i e s i n A u s t r a l i a w i t h many times the n a t i o n a l c o n t r i b u t i o n to s c i e n t i f i c work and provide a sharp measure of the p o t e n t i a l f o r new product development." (Newton and O'Connor 1985, p. 8). A f t e r r e j e c t i n g d e f i n i t i o n s based on t e c h n i c a l s o p h i s t i c a t i o n of products, growth r a t e s , and R&D expenditures due to a lack of o p e r a t i o n a l p r e c i s i o n , Glasmeier, H a l l and Markusen (1983, p.10) e s t a b l i s h e d a d e f i n i t i o n based on "the percent of engineers, engineering t e c h n i c i a n s , computer s c i e n t i s t s , l i f e s c i e n t i s t s , and mathematicians exceeding the manufacturing average f o r these occupational c a t e g o r i e s . " They found 29 i n d u s t r i e s that exceeded the manufacturing average of 5.82% of employees engaged i n the s p e c i f i e d occupations. The 29 i n d u s t r i e s i d e n t i f i e d are o u t l i n e d on Table 1 i n rank order. This d e f i n i t i o n has been widely recognized and u t i l i z e d i n research on high tech i n d u s t r i e s . 18 TABLE 1 HIGH TECHNOLOGY INDUSTRIES AS DEFINED BY GLASMEIER HALL AND MARKUSEN Percent Engineers, Eng.Tech./Comp.Sci. Rank SIC T i t l e Science and Math 1 376 M i s s i l e s 41. ,19 2 357 O f f i c e Computing Machines 26. ,70 3 381 Engineering, Laboratory and S c i e n t i f i c Instruments 26. ,45 4 366 Communication Equipment 21. ,86 5 383 O p t i c a l Instruments and Lenses 19. ,80 6 286 I n d u s t r i a l Organic Chemicals 19. ,60 7 372 A i r c r a f t and Parts 18. ,53 8 283 Drugs 17. ,67 9 291 Petroleum R e f i n i n g 14, ,62 10 382 Measuring and C o n t r o l l i n g Instruments 14. ,14 11 367 E l e c t r o n i c Components and Assembly 12. ,84 12 281 I n d u s t r i a l Inorganic Chemicals 12. ,65 13 282 P l a s t i c s and Syn t h e t i c Resins 11. ,36 14 351 Engines and Turbines 10. ,65 15 348 Ordnance 10, .42 16 289 Misc. Chemicals 10, ,10 17 386 Photographic Equipment 9, .48 18 362 E l e c t r i c a l I n d u s t r i a l Apparatus 9, ,30 19 361 E l e c t r i c a l Transmission Equipment 8, .59 20 353 Construction Equipment 8, .43 21 285 P a i n t s 8, .20 22 303 Reclaimed Rubber 7, .53 23 356 General Industry Machinery 7, .27 24 374 Ra i l r o a d s 6, .75 25 365 Radio and TV Receiving Equipment 6, .72 26 287 A g r i c u l t u r a l Chemicals 6 .48 27 354 Metal Working Machinery 6 .28 28 384 Medical and Dental Supply 6.03 29 284 Soap 5, .91 Source: Glasmeier, H a l l and Markusen 1983, pp. 16-17 Glasmeier, H a l l and Markusen a l s o reviewed a study conducted by the Massachusetts Manpower Development Department which defined high tech based on the percentage of employees i n t e c h n i c a l occupations. The Massachusetts s t a t e manufacturing average was 8.7%, and the durable goods manufacturing average was 13.7%. To be considered as high tech, the i n d u s t r y needed a higher than average percentage of i t s work forc e engaged i n t e c h n i c a l occupations. These f i g u r e s were s u b s t a n t i a l l y higher than the ones Glasmeier, H a l l and Markusen found f o r the U.S. as a whole. They explained the d i f f e r e n c e as being due to the high p r o p o r t i o n of high tech i n d u s t r i e s i n Massachusetts. One of the d e f i n i t i o n s used by the O f f i c e of Technology Assessment (1984, p.18) i d e n t i f i e d a group of i n d u s t r i e s that employ a p r o p o r t i o n of s c i e n t i f i c , engineering and t e c h n i c a l workers greater than 1.5 times the average f o r a l l i n d u s t r i e s , or 5.1% of t h e i r t o t a l employment. The O f f i c e of Technology Assessment (1984) a l s o examined a d e f i n i t i o n developed by the Brookings I n s t i t u t i o n . In t h i s d e f i n i t i o n , i n d u s t r i e s i n cluded as being high tech had to have more than 8% of i t s employees engaged i n s c i e n t i f i c , engineering and t e c h n i c a l occupations, with at l e a s t 5% engaged i n a more narrowly defined c l a s s of s c i e n t i f i c and engineering occupations. The cut o f f percentages used were based on the average p r o p o r t i o n of SET occupations i n durable goods manufacturing i n the U.S. Other authors i n d i c a t e l e s s q u a n t i f i a b l e d e f i n i t i o n s that i d e n t i f y the human s k i l l s component of high technology a c t i v i t i e s as being important. Weiss (1984, p. 81) i d e n t i f i e s one d e f i n i t i o n as having " l o g i c a l consistency i n measurement and a p p l i c a t i o n " i n which a high tech i n d u s t r y i s defined as having "an above average percentage of i t s labour f o r c e engaged i n engineering, s c i e n t i f i c , p r o f e s s i o n a l and t e c h n i c a l work" . As part of a 20 m u l t i v a r i a t e d e f i n i t i o n Rogers and Larson (1984, p. 29) i n d i c a t e d the high tech i n d u s t r i e s are those that have " h i g h l y s k i l l e d employees, many of whom are s c i e n t i s t s and engineers". Markusen and Bloch (1985 p. 108) define high tech i n d u s t r i e s as "those i n d u s t r i e s w i t h a higher than average p r o p o r t i o n of t h e i r work f o r c e i n s c i e n t i f i c and t e c h n i c a l occupations (engineers, engineering t e c h n i c i a n s , computer s c i e n t i s t s , l i f e s c i e n t i s t s , mathematicians)". One of the c r i t e r i a i d e n t i f i e d by Premus (1982 p. 4) was that the firms had to be " l a b o u r - i n t e n s i v e rather than c a p i t a l - i n t e n s i v e i n t h e i r production processes, employing a higher percentage of t e c h n i c i a n s , engineers and s c i e n t i s t s than other manufacturing companies". High tech d e f i n i t i o n s based on the p r o p o r t i o n of s c i e n t i f i c , engineering and t e c h n i c a l (SET) employees, and v a r i a t i o n s of t h i s d e f i n i t i o n , are widely u t i l i z e d because of the advantages t h i s type of d e f i n i t i o n o f f e r s . Being based on occupational i n f o r m a t i o n , the SET d e f i n i t i o n s have the advantage of using Standard Occupational Categories (SOCs). E s t a b l i s h e d d e f i n i t i o n s e x i s t f o r each occupation, and data regarding the number of employees engaged i n various occupations w i t h i n each i n d u s t r y are r e a d i l y a v a i l a b l e . Once the core group of occupations has been i d e n t i f i e d and the c u t - o f f percentage e s t a b l i s h e d , the SET d e f i n i t i o n s can be uniformly a p p l i e d across a l l Standard I n d u s t r i a l C l a s s i f i c a t i o n s (SICs). The SIC codes are based on standard d e f i n i t i o n s of i n d u s t r i a l s e c t o r s . The r e s u l t of applying the d e f i n i t i o n i s a l i s t of i n d u s t r i e s that meet the c r i t e r i o n e s t a b l i s h e d . For research purposes, a l i s t of SIC categories i s very convenient, because often other data of relevance to research e f f o r t s has been i n t e r r e l a t e d w i t h the SIC data. For example, the number of employees working i n each SIC category has been tabulated by Census M e t r o p o l i t a n Area, a l l o w i n g an 21 examination of the s p a t i a l tendencies of various i n d u s t r i e s . The use of Standard I n d u s t r i a l C l a s s i f i c a t i o n s and Standard Occupational Categories gives the SET d e f i n i t i o n s p r e c i s i o n , because the in f o r m a t i o n can be disaggregated to a s i g n i f i c a n t l e v e l of d e t a i l . They a l s o give the SET d e f i n i t i o n s c o m p a r a b i l i t y , because the inform a t i o n i s uniformly a p p l i e d to a l l occupations and i n d u s t r i e s . This d e f i n i t i o n i s a l s o l o g i c a l l y sound i n that the genesis of t e c h n o l o g i c a l i n n o v a t i o n i s based on the education and e x p e r t i s e of employees. Those employees with a s c i e n t i f i c , engineering and t e c h n i c a l background have the t o o l s and knowledge to b r i n g new t e c h n o l o g i c a l ideas i n t o r e a l i t y and production. I t l o g i c a l l y f o l l o w s that the i n d u s t r i e s w i t h a higher p r o p o r t i o n of SET employees w i l l have a higher p r o b a b i l i t y of generating advanced technologies. However, the SET d e f i n i t i o n s have some disadvantages. While the use of SIC codes allow a good l e v e l of dis a g g r e g a t i o n , there i s s t i l l p o t e n t i a l f o r i n c l u s i o n of firms that f i t w i t h i n the SIC category, but do not meet the d e f i n i t i o n a l c r i t e r i a . For example, an i n d i v i d u a l f i r m may have very few SET employees, but because of i t s product i t might be i n c l u d e d i n an SIC that i s defined as high tech. The SET d e f i n i t i o n s a l s o under represent those i n d u s t r i e s that use high tech processes. This i s because the use of high tech processes and equipment does not n e c e s s a r i l y r e q u i r e workers engaged i n SET occupations. Advanced technology may a c t u a l l y reduce the s k i l l s needed to perform various f u n c t i o n s . This under r e p r e s e n t a t i o n may be seen as an advantage, though, i n research that wishes to i n c l u d e only those i n d u s t r i e s that produce high technology products, and not those that use high tech processes. In g e n e r a l , the SET d e f i n i t i o n s seem to be c h a r a c t e r i z e d by 22 f a r more advantages than disadvantages.The b e n e f i t s of accuracy, consistency, c o m p a r a b i l i t y and data a v a i l a b i l i t y arguably out-weigh the disadvantages of some data aggregation and the e x c l u s i o n of i n d u s t r i e s that may use high tech products rather than produce them. 2.2.3 Growth D e f i n i t i o n s Several d e f i n i t i o n s of high tech are based on the c r i t e r i o n of high employment growth. U s u a l l y d e f i n i t i o n s that r e l y on high growth rates as being the key i n d i c a t o r a l s o r e l y on another secondary i n d i c a t o r , such as R&D expenditures, p r o d u c t i v i t y (Glasmeier H a l l and Markusen 1983) or SET employment. The r a t i o n a l e behind using growth rates as an i n d i c a t o r of high tech i s that high tech i n d u s t r i e s are perceived to have grown at a higher r a t e than more t r a d i t i o n a l s e c t o r s . For example, i n d u s t r i e s such as Petroleum, Chemicals, E l e c t r i c a l Equipment, S c i e n t i f i c Instruments and Machinery increased an average of 16.6% from 1965 to 1977, while employment i n t r a d i t i o n a l i n d u s t r i e s such as T e x t i l e s ; Foods and Kindred Products; and Stone Clay and Glass grew only 4.2% from 1965 to 1977 (Glasmeier, H a l l and Markusen 1983 pp. 4-5). Maleki (1984, p. 63) noted that "a common i n t e r p r e t a t i o n [of high tech] simply i n c l u d e s any i n d u s t r y that has been growing or i s l i k e l y to grow i n employment, but that s o r t of c l a s s i f i c a t i o n i s not very meaningful". Weiss (1984, p. 82), i n d i s c u s s i n g p o l i t i c a l d e f i n i t i o n s of high tech, i n d i c a t e d that "At the f e d e r a l l e v e l , the key c r i t e r i a seems to be that the high tech i n d u s t r i e s are now manufacturing i n d u s t r i e s which have grown r a p i d l y i n economic power and importance i n the l a s t decade, but have not as yet (with 23 the exception of IBM) organized s u f f i c i e n t l y to lobby f o r t h e i r s p e c i a l needs with Congress and f e d e r a l agencies." Weiss (1984) a l s o notes that high tech i n d u s t r i e s are those new technology goods-producing i n d u s t r i e s that have not yet s a t u r a t e d the market, those f l e d g l i n g i n d u s t r i e s that have room to expand to meet growing demand. These i n d u s t r i e s are e i t h e r experiencing high rates of growth on a percentage b a s i s , or w i l l experience high rates of growth i n the near f u t u r e . Markusen and Bloch (1985) i n d i c a t e that one of the features g e n e r a l l y a s s o c i a t e d w i t h high tech i s a r a p i d r a t e of employment growth a s s o c i a t e d with an i n n o v a t i v e product. Rogers and Larson (1984) a l s o note a f a s t r a t e of growth as being a s i g n i f i c a n t t r a i t of high technology i n d u s t r i e s . Using high growth rates as a means of d e f i n i n g high technology i n d u s t r i e s has several advantages and disadvantages.In conjunction w i t h other measures of high tech, such as R&D expenditures and SET employment the c r i t e r i o n of high growth provides a u s e f u l screen to i d e n t i f y p a r t i c u l a r types of high tech. The high growth c r i t e r i o n acts to f u r t h e r narrow the range of i n d u s t r i e s considered as high tech, and may help to i d e n t i f y i n d u s t r i e s that might be more d e s i r a b l e from an economic development point of view. A d e f i n i t i o n based on growth rates might i d e n t i f y those i n d u s t r i e s w i t h i n c r e a s i n g demands f o r employment, thereby focussing on i n d u s t r i e s which might help toward a p o s s i b l e goal of economic development through employment i n an area. Another advantage of using a growth-based d e f i n i t i o n i s that i t h i g h l i g h t s small new i n d u s t r i e s which, because of t h e i r i n i t i a l low numbers of employees, experience high growth i n percentage terms as new workers j o i n t h e i r small work f o r c e . These i n d u s t r i e s are often i n the embryonic stages 24 w i t h p o t e n t i a l f o r expansion i n the f u t u r e , and they may be the type of a c t i v i t y that some communities wish to i d e n t i f y f o r development or a t t r a c t i o n . While a growth-based d e f i n i t i o n may have some advantages, i t a l s o s u f f e r s from se v e r a l s e r i o u s disadvantages. I f the d e f i n i t i o n i s based on employment growth alone, the d e f i n i t i o n may i d e n t i f y i n d u s t r i e s that are growing r a p i d l y , but have nothing to do with advancing technology at a l l . Growth d e f i n i t i o n s might a l s o serve to exaggerate the importance of smaller i n d u s t r i e s , p a r t i c u l a r l y i f growth i s determined on a percentage b a s i s . Growth d e f i n i t i o n s a l s o work to reduce the perceived importance of e s t a b l i s h e d i n d u s t r i e s that may produce advanced technology products, or are i d e n t i f i e d as high technology by other d e f i n i t i o n s , but are not growing r a p i d l y . This e f f e c t would be evident i n i n d u s t r i e s that employ l a r g e numbers of people, where large absolute increases i n employment would have to occur before a s i g n i f i c a n t percentage increase i s noted. The growth d e f i n i t i o n may ignore some small i n d u s t r i e s on the advancing edge of technology that are s t i l l i n the research stages. These smaller i n d u s t r i e s may be making large investments i n t e c h n o l o g i c a l development, but are not yet experiencing s i g n i f i c a n t employment growth. C a p i t a l - i n t e n s i v e i n d u s t r i e s that might otherwise be defined as high tech may a l s o be ignored i f only growth i n employment i s considered. Growth i n c a p i t a l investments may be oc c u r r i n g rather than growth i n employment, but the in d u s t r y might s t i l l be i n v o l v e d i n advancing technology. A f i n a l disadvantage of the growth d e f i n i t i o n i s that growth could be t i e d to sev e r a l i n d i c a t o r s : revenue growth, expenditure growth, investment growth, s p a t i a l growth, and employment growth. Depending on the type of growth chosen as the 25 i n d i c a t o r , d i f f e r e n t i n d u s t r i e s might be seen as belonging to the high tech group. 2.2.4 Technological S o p h i s t i c a t i o n D e f i n i t i o n s Several authors have examined or developed d e f i n i t i o n s of high technology i n d u s t r i e s based on the t e c h n o l o g i c a l s o p h i s t i c a t i o n (TS) of goods produced or used by an i n d u s t r y . Newton and O'Connor (1985, p. 2) noted that some high tech d e f i n i t i o n s are based on output f a c t o r s , w i t h the emphasis being on the "Technological s o p h i s t i c a t i o n of products produced by an i n d u s t r y " . Glasmeier, H a l l and Markusen (1983) note that the Massachusetts D i v i s i o n of Employment S e c u r i t y (MDES) developed a l i s t of 20 high tech i n d u s t r i e s based on a s u b j e c t i v e review of i n d u s t r i e s c l a s s i f i e d i n the SIC manual. Those in c l u d e d i n the l i s t had a high perceived degree of t e c h n o l o g i c a l s o p h i s t i c a t i o n i n the products generated by the i n d u s t r y . Markusen and Bloch (1985) i n d i c a t e d that one of the features of a high tech i n d u s t r y was an extensive degree of t e c h n o l o g i c a l s o p h i s t i c a t i o n embodied i n a product. Malecki (1984) i d e n t i f i e s a d e f i n i t i o n of high tech that i s t i e d to science-based, emerging products and processes that r e l y on s t a t e - o f - t h e - a r t knowledge. The Economic Council of Canada (1985) researchers are developing a d e f i n i t i o n based on the t e c h n o l o g i c a l s o p h i s t i c a t i o n of the products produced and/or used by an i n d u s t r y . D e f i n i t i o n s based on the t e c h n o l o g i c a l s o p h i s t i c a t i o n of products are advantageous i n that the popular perception of high tech u s u a l l y r e l a t e s to the products generated by an i n d u s t r y . High tech i s oft e n a s s o c i a t e d w i t h computers, s c i e n t i f i c equipment, s o p h i s t i c a t e d m i l i t a r y equipment and the l i k e . I f t h i s popular perception can be o p e r a t i o n a l i z e d and used i n a s t r u c t u r e d d e f i n i t i o n , the group of i n d u s t r i e s that would r e s u l t may i n c l u d e those that many people would agree should be considered as high tech. The problems of d e f i n i n g high tech based on product s o p h i s t i c a t i o n stem from the d i f f i c u l t i e s i n o p e r a t i o n a l i z i n g the d e f i n i t i o n . I t i s very d i f f i c u l t to place a value or r a t i n g on the t e c h n o l o g i c a l s o p h i s t i c a t i o n of a product. Even i f an adequate t e c h n o l o g i c a l s o p h i s t i c a t i o n r a t i n g system was devised, i t would s t i l l be an enormous task to r a t e a l l the products produced by each i n d u s t r y . Another problem with TS d e f i n i t i o n s i s that i n d u s t r i e s produce a wide range of goods. That range may span from products of very low s o p h i s t i c a t i o n to those of very high s o p h i s t i c a t i o n . A minimum i n d u s t r y content of h i g h l y s o p h i s t i c a t e d products could be e s t a b l i s h e d , but then another measurement problem would a r i s e . Would content be measured as revenues generated by a product, value added by a product, number of persons i n v o l v e d i n production, or some other measure? P r i m a r i l y because of problems i n o p e r a t i o n a l i z a t i o n and measurement, t e c h n o l o g i c a l s o p h i s t i c a t i o n type d e f i n i t i o n s have not been used e x t e n s i v e l y i n the e x i s t i n g l i t e r a t u r e . This type of d e f i n i t i o n i s u s u a l l y considered, but q u i c k l y r e j e c t e d i n favour of d e f i n i t i o n s that are more a c c u r a t e l y and e a s i l y implemented. 2.2.5 Other D e f i n i t i o n s Several d e f i n i t i o n s e x i s t that combine the types of d e f i n i t i o n s discussed above. To be considered as part of high tech, i n d u s t r i e s must meet several c r i t e r i a . Wiewel et al.(1984) notes that Thompson and Thompson (1983) used a complex index combining the p r o p o r t i o n of s c i e n t i f i c personnel, the 27 r a t i o of R&D to value added and the r a t i o of patents i s s u e d to a l l employees. Rogers and Larsen (1984) i n d i c a t e that high tech i n d u s t r i e s should have h i g h l y s k i l l e d employees, a f a s t r a t e of growth, a high r a t i o of R&D expenditures to s a l e s , and a world wide market f o r t h e i r products. Peter Haug (1986) generated a d e f i n i t i o n based on 14 previous s t u d i e s that attempted to define high technology i n d u s t r i e s . He i d e n t i f i e d high technology i n d u s t r i e s as those SIC code groups defined as high technology i n d u s t r i e s by ten or more research s t u d i e s . Table 2 shows the SIC codes that were considered as high tech i n 14 r e l a t i v e l y recent s t u d i e s . While Haug's d e f i n i t i o n of high tech i s somewhat s u b j e c t i v e , he does i d e n t i f y those i n d u s t r i e s on which there i s some consensus on whether or not they should be considered as high tech i n d u s t r i e s . 2.3 D e f i n i t i o n of High Technology In t h i s t h e s i s high technology i n d u s t r i e s are defined as those i n d u s t r i e s w i t h percentages of t h e i r labour f o r c e engaged i n Natural Sciences, Engineering and Mathematics occupations that are more than double the n a t i o n a l mean f o r a l l i n d u s t r i e s . This d e f i n i t i o n i s analogous to the SET d e f i n i t i o n s discussed i n s e c t i o n 2.2. I t was used because the in f o r m a t i o n needed to o p e r a t i o n a l i z e the d e f i n i t i o n was r e a d i l y a v a i l a b l e from S t a t i s t i c s Canada. This type of d e f i n i t i o n i s a l s o l o g i c a l l y sound and has been widely used and accepted i n other s t u d i e s of high technology. Although other d e f i n i t i o n s noted i n s e c t i o n 2.2 were considered, they were r e j e c t e d f o r s e v e r a l reasons. D e f i n i t i o n s based on R&D f i g u r e s were r e j e c t e d because accurate data were d i f f i c u l t to o b t a i n on R&D expenditures. 28 TABLE 2 STANDARD INDUSTRIAL CLASSIFICATION (SIC) CODES OF RECENT HIGH TECHNOLOGY INDUSTRY DEFINITIONS Vinson and Aho and SIC Industry K e l l y , Harrington, Rosen, 1977 1979 1980 281 I n d u s t r i a l i n o r g a n i c chemicals X X X 282 P l a s t i c m a t e r i a l s and s y n t h e t i c s X X X 283 Drugs and medicine X X X 284 Soaps and cleaners - - -285 Paints and a l l i e d products - - -286 I n d u s t r i a l organic chemicals - - -285 A g r i c u l t u r a l chemicals X - X 289 Miscellaneous chemical products - - -291 Petroleum r e f i n i n g - - -301 Tyres and inner tubes - - -324 Cement, h y d r a u l i c - - -348 Ordnance and accessories - - X 351 Engines and t u r b i n e s X X X 352 Farm and garden machinery - - -353 C o n s t r u c t i o n , mining equipment - - -354 Metalworking machinery - - -355 S p e c i a l i n d u s t r i a l machinery - - -356 General i n d u s t r i a l machinery - - -357 O f f i c e , computing and acct. machines X X X 358 R e f r i g e r a t i o n and s e r v i c e machinery - - -361 E l e c t r i c t r a n s , and d i s t . equipment X X X 362 E l e c t r i c a l i n d u s t r i a l apparatus X X X 363 Household appliances - - -364 E l e c t r i c l i g h t i n g and w i r i n g - - X 365 Radio and TV r e c e i v i n g equipment X - X 366 Communication equipment X X X 367 E l e c t r o n i c components X X X 369 Misc. e l e c t r i c a l machinery - - -371 Motor v e h i c l e s and equipment - - X 372 A i r c r a f t and P a r t s X X X 376 Guided m i s s i l e s and space v e h i c l e s - X -381 S c i e n t i f i c instruments X X X 382 Measuring and c o n t r o l instruments X X X 383 O p t i c a l instruments and lenses X X X 384 Medical and dental instruments X - X 385 Ophthamalic goods X - X 386 Photographic Equipment X X X 387 Watches and Clocks X - X 483 Radio and TV Broadcasting - - X 737 Computer and data process s e r v i c e s - X -7391 Research and development labs - X -891 Engineering and surveying s e r v i c e s - X -892 Noncomm. research o r g a n i z a t i o n s X 29 TABLE 2 (CONTINUED) STANDARD INDUSTRIAL CLASSIFICATION (SIC) CODES OF RECENT HIGH TECHNOLOGY INDUSTRY DEFINITIONS SIC Industry Davis, Boretsky, Lawson, 1982 1982 1982 281 I n d u s t r i a l i n o r g a n i c chemicals X - -282 P l a s t i c m a t e r i a l s and s y n t h e t i c s X - -283 Drugs and medicine X X X 284 Soaps and cleaners - - -285 P a i n t s and a l l i e d products - - -286 I n d u s t r i a l organic chemicals - - -285 A g r i c u l t u r a l chemicals - - -289 Miscellaneous chemical products - - -291 Petroleum r e f i n i n g - - -301 Tyres and inner tubes - - -324 Cement, h y d r a u l i c - - -348 Ordnance and accessories X - -351 Engines and t u r b i n e s X - -352 Farm and garden machinery - - -353 C o n s t r u c t i o n , mining equipment - -354 Metalworking machinery - - -355 S p e c i a l i n d u s t r i a l machinery - - -356 General i n d u s t r i a l machinery - - -357 O f f i c e , computing and acct. machines X X X 358 R e f r i g e r a t i o n and s e r v i c e machinery - - -361 E l e c t r i c t r a n s , and d i s t . equipment - X X 362 E l e c t r i c a l i n d u s t r i a l apparatus - X X 363 Household appliances - - X 364 E l e c t r i c l i g h t i n g and w i r i n g - - X 365 Radio and TV r e c e i v i n g equipment X X -366 Communication equipment X X X 367 E l e c t r o n i c components X X X 369 Misc. e l e c t r i c a l machinery - - X 371 Motor v e h i c l e s and equipment - - -372 A i r c r a f t and Parts X X X 376 Guided m i s s i l e s and space v e h i c l e s X X X 381 S c i e n t i f i c instruments X X X 382 Measuring and c o n t r o l instruments X X X 383 O p t i c a l instruments and lenses X X X 384 Medical and dental instruments X X X 385 Ophthamalic goods - - X 386 Photographic Equipment - - X 387 Watches and Clocks - - X 483 Radio and TV Broadcasting - - -737 Computer and data process s e r v i c e s - - -7391 Research and development labs - - -891 Engineering and surveying s e r v i c e s - - -892 Noncomm. research o r g a n i z a t i o n s 30 TABLE 2 (CONTINUED) STANDARD INDUSTRIAL CLASSIFICATION (SIC) CODES OF RECENT HIGH TECHNOLOGY INDUSTRY DEFINITIONS SIC Industry MDES,i M i n s h a l l , WICHE,2 1982 1982 1983 281 I n d u s t r i a l i n o r g a n i c chemicals - - -282 P l a s t i c m a t e r i a l s and s y n t h e t i c s - - -283 Drugs and medicine X X X 284 Soaps and cleaners - - -285 P a i n t s and a l l i e d products - - -286 I n d u s t r i a l organic chemicals - X -285 A g r i c u l t u r a l chemicals - X -289 Miscellaneous chemical products - - -291 Petroleum r e f i n i n g - - -301 Tyres and inner tubes - - -324 Cement, h y d r a u l i c - - -348 Ordnance and accessories X - X 351 Engines and t u r b i n e s - - -352 Farm and garden machinery - - -353 C o n s t r u c t i o n , mining equipment - - -354 Metalworking machinery - - -355 S p e c i a l i n d u s t r i a l machinery - - -356 General i n d u s t r i a l machinery - X -357 O f f i c e , computing and a c c t . machines X X X 358 R e f r i g e r a t i o n and s e r v i c e machinery X - -361 E l e c t r i c t r a n s , and d i s t . equipment X - X 362 E l e c t r i c a l i n d u s t r i a l apparatus X - X 363 Household appliances X X X 364 E l e c t r i c l i g h t i n g and w i r i n g X - X 365 Radio and TV r e c e i v i n g equipment X X X 366 Communication equipment X X X 367 E l e c t r o n i c components X X X 369 Misc. e l e c t r i c a l machinery X X X 371 Motor v e h i c l e s and equipment - - -372 A i r c r a f t and Parts - - X 376 Guided m i s s i l e s and space v e h i c l e s X X X 381 S c i e n t i f i c instruments X - X 382 Measuring and c o n t r o l instruments X X X 383 O p t i c a l instruments and lenses X X X 384 Medical and dental instruments X X X 385 Ophthamalic goods X - X 386 Photographic Equipment X X X 387 Watches and Clocks X - X 483 Radio and TV Broadcasting - - -737 Computer and data process s e r v i c e s - X X 7391 Research and development labs - -891 Engineering and surveying s e r v i c e s - - -892 Noncomm. research o r g a n i z a t i o n s - - -1. Massachusetts D i v i s i o n of Employment S e c u r i t y 2. Western I n t e r s t a t e Commission f o r Higher Education 31 TABLE 2 (CONTINUED) STANDARD INDUSTRIAL CLASSIFICATION (SIC) CODES OF RECENT HIGH TECHNOLOGY INDUSTRY DEFINITIONS SIC Industry R i t c h i e , Hecker and Burgan a 1983 D 1983 c 1983 281 I n d u s t r i a l i n o r g a n i c chemicals X - X 282 P l a s t i c m a t e r i a l s and s y n t h e t i c s X - X 283 Drugs and medicine X X X 284 Soaps and cleaners X - X 285 P a i n t s and a l l i e d products X - X 286 I n d u s t r i a l organic chemicals X - X 285 A g r i c u l t u r a l chemicals X - X 289 Miscellaneous chemical products X - X 291 Petroleum r e f i n i n g X - X 301 Tyres and inner tubes X - -324 Cement, h y d r a u l i c X - -348 Ordnance and accessories X - X 351 Engines and t u r b i n e s X - X 352 Farm and garden machinery X - -353 C o n s t r u c t i o n , mining equipment X - -354 Metalworking machinery X - -355 S p e c i a l i n d u s t r i a l machinery X - X 356 General i n d u s t r i a l machinery X - -357 O f f i c e , computing and a c c t . machines X X X 358 R e f r i g e r a t i o n and s e r v i c e machinery X - -361 E l e c t r i c t r a n s , and d i s t . equipment X - X 362 E l e c t r i c a l i n d u s t r i a l apparatus X - X 363 Household appliances X - -364 E l e c t r i c l i g h t i n g and w i r i n g X - -365 Radio and TV r e c e i v i n g equipment X - X 366 Communication equipment X X X 367 E l e c t r o n i c components X X X 369 Misc. e l e c t r i c a l machinery X - X 371 Motor v e h i c l e s and equipment X - -372 A i r c r a f t and Parts X X X 376 Guided m i s s i l e s and space v e h i c l e s X X X 381 S c i e n t i f i c instruments X - X 382 Measuring and c o n t r o l instruments X - X 383 O p t i c a l instruments and lenses X - X 384 Medical and dental instruments X - X 385 Ophthamalic goods X - -386 Photographic Equipment X - X 387 Watches and Clocks X - -483 Radio and TV Broadcasting X - -737 Computer and data process s e r v i c e s X - X 7391 Research and development labs X - X 891 Engineering and surveying s e r v i c e s X - -892 Noncomm. research o r g a n i z a t i o n s X 32 TABLE 2 (CONTINUED) STANDARD INDUSTRIAL CLASSIFICATION (SIC) CODES OF RECENT HIGH TECHNOLOGY INDUSTRY DEFINITIONS  Cole Total SIC Industry Gandia et. a l . number 1983 1984 s e l e c t e d 281 I n d u s t r i a l i n o r g a n i c chemicals X X 8 282 P l a s t i c m a t e r i a l s and s y n t h e t i c s X X 8 283 Drugs and medicine X X 14 284 Soaps and cleaners - - 2 285 P a i n t s and a l l i e d products - X 3 286 I n d u s t r i a l organic chemicals - X 4 285 A g r i c u l t u r a l chemicals - - 5 289 Miscellaneous chemical products - - 2 291 Petroleum r e f i n i n g - - 3 301 Tyres and inner tubes - - 1 324 Cement, h y d r a u l i c - - 1 348 Ordnance and accessories X - 7 351 Engines and t u r b i n e s X X 8 352 Farm and garden machinery - - 1 353 C o n s t r u c t i o n , mining equipment - - 1 354 Metalworking machinery - - 1 355 S p e c i a l i n d u s t r i a l machinery - - 2 356 General i n d u s t r i a l machinery - • - 2 357 O f f i c e , computing and acct. machines X X 14 358 R e f r i g e r a t i o n and s e r v i c e machinery - - 1 361 E l e c t r i c t r a n s , and d i s t . equipment - X 10 362 E l e c t r i c a l i n d u s t r i a l apparatus - X 10 363 Household appliances - - 5 364 E l e c t r i c l i g h t i n g and w i r i n g - - 5 365 Radio and TV r e c e i v i n g equipment - X 10 366 Communication equipment X X 14 367 E l e c t r o n i c components X X 14 369 Misc. e l e c t r i c a l machinery - X 7 371 Motor v e h i c l e s and equipment - - 2 372 A i r c r a f t and Parts X X 12 376 Guided m i s s i l e s and space v e h i c l e s X X 12 381 S c i e n t i f i c instruments X X 12 382 Measuring and c o n t r o l instruments X X 13 383 O p t i c a l instruments and lenses X X 13 384 Medical and dental instruments X X 12 385 Ophthamalic goods X - 7 386 Photographic Equipment X X 11 387 Watches and Clocks X - 7 483 Radio and TV Broadcasting - - 2 737 Computer and data process s e r v i c e s X X 7 7391 Research and development labs X X 5 891 Engineering and surveying s e r v i c e s - - 2 892 Noncomm. research o r g a n i z a t i o n s X 3 33 R&D-based d e f i n i t i o n s a l s o tend to exaggerate or d i m i n i s h various i n d u s t r i e s depending on whether the d e f i n i t i o n i s based on the r e l a t i o n s h i p between R&D expenditures and s a l e s , or the r e l a t i o n s h i p between R&D expenditures and investments, or a comparison of an i n d u s t r y ' s R&D expenditures with average R&D expenditures. Growth-based d e f i n i t i o n s were r e j e c t e d because they often i n c l u d e i n d u s t r i e s that are growing but do not r e l y on advancing technology i n any way at a l l . Growth based d e f i n i t i o n s a l s o tend to exaggerate the importance of smaller i n d u s t r i e s i f considered on a percentage growth b a s i s . D e f i n i t i o n s based on the t e c h n o l o g i c a l s o p h i s t i c a t i o n of products used or produced were r e j e c t e d p r i m a r i l y because of d i f f i c u l t i e s i n o p e r a t i o n a l i z a t i o n and severe data l i m i t a t i o n s . The d e f i n i t i o n used i n t h i s t h e s i s was o p e r a t i o n a l i z e d by examining S t a t i s t i c s Canada t a b l e s which show the number of workers employed i n each Standard I n d u s t r i a l C l a s s i f i c a t i o n disaggregated by Standard Occupational C l a s s i f i c a t i o n . From t h i s t a b l e , the percentage of labour for c e i n each i n d u s t r y that was engaged i n Natural Sciences, Engineering and Mathematics occupations was c a l c u l a t e d . The mean of t h i s percentage f o r a l l i n d u s t r i e s i n Canada was found to be 5.39%. I n d u s t r i e s w i t h double the average, that i s , i n d u s t r i e s w i t h greater than 10.8% of i t s work force engaged i n Natural Sciences, Engineering and Mathematics occupations are defined as high technology i n d u s t r i e s . Table 3 o u t l i n e s the high technology i n d u s t r i e s that f i t w i t h i n the d e f i n i t i o n used i n t h i s t h e s i s . SIC # 863, O f f i c e s of A r c h i t e c t s , was included i n the o r i g i n a l l i s t of i n d u s t r i e s developed through a p p l i c a t i o n of the d e f i n i t i o n a l c r i t e r i a . I t was decided, however, that A r c h i t e c t s were not i n v o l v e d as s t r o n g l y i n the development of advanced technology as were S c i e n t i s t s , Engineers and 34 Mathematicians ( u n f o r t u n a t e l y , S t a t i s t i c s Canada included a r c h i t e c t s w i t h i n i t s Natural Sciences, Engineering and Mathematics occupational category). Therefore, SIC # 863, O f f i c e s of A r c h i t e c t s , was removed from the l i s t of high tech i n d u s t r i e s . 35 TABLE 3 HIGH TECH INDUSTRIES IN CANADA % Natural Sc. Engineering and SIC # D e s c r i p t i o n of Industry Mathematics 864 Engineering and S c i e n t i f i c Services 61. .37 853 Computer Services 37. ,89 064 Crude Petroleum and Natural Gas i n d u s t r y 24. ,33 318 O f f i c e and Store Machinery Manufacturers 19. .91 572 E l e c t r i c Power 18, .86 039 Fo r e s t r y Services 18. .3 335 Communications Equipment Manufacturers 17. .28 378 I n d u s t r i a l Chemicals Manufacturers 15, ,82 867 Management and Business Consultants 15, .76 365 Petroleum R e f i n e r i e s 15, .74 099 Mining Services 14, .82 321 A i r c r a f t and A i r c r a f t Parts Manufacturers 11, .94 336 E l e c t r i c a l I n d u s t r i a l Equipment Manufacturers 11, .37 36 CHAPTER I I I LOCATION FACTORS IN THE LITERATURE  3.1 Loc a t i o n Factors i n General 3.1.1 What are 'Location Factors'? Location f a c t o r s can be seen as c h a r a c t e r i s t i c s of a place that i n f l u e n c e the l o c a t i o n of i n d u s t r y . They are s p e c i f i c i n g r e d i e n t s needed at a l o c a t i o n i n order f o r an a c t i v i t y to take place. For example, an i n d u s t r y might need raw m a t e r i a l s , labour and a power supply a l l i n one l o c a t i o n to manufacture a product, as w e l l as a nearby market f o r s a l e s of the product. If one of these l o c a t i o n f a c t o r s i s missing, the i n d u s t r y may go elsewhere. A s i n g l e l o c a t i o n f a c t o r i s r a r e l y an absolute determinant of i n d u s t r i a l l o c a t i o n . The lack of an important f a c t o r , s p e c i a l i z e d labour f o r example, does not n e c e s s a r i l y preclude an i n d u s t r y from l o c a t i n g i n a s p e c i f i c place. Labour could be transported to a l o c a l i t y , or e x i s t i n g labour i n the area could be t r a i n e d . While they do not provide a p e r f e c t i n d i c a t i o n of where i n d u s t r y w i l l l o c a t e , l o c a t i o n f a c t o r s do provide some c r i t e r i a by which to judge the l i k e l i h o o d of an i n d u s t r y l o c a t i n g i n a c e r t a i n area. 3.1.2 The Value of Knowing Location Factors Location f a c t o r s provide i n f o r m a t i o n on the s p a t i a l needs of an in d u s t r y . This inform a t i o n can be u s e f u l i n seve r a l ways. F i r s t , from the perspe c t i v e of a growing i n d u s t r y , l o c a t i o n f a c t o r s are obviously u s e f u l i n l o c a t i o n a l decision-making. A new venture lo o k i n g f o r a place to e s t a b l i s h a business would b e n e f i t from a c l e a r knowledge of 37 l o c a t i o n a l f a c t o r s . This knowledge would allow a new business venture to look f o r a s i t e which o f f e r s c h a r a c t e r i s t i c s that could play a major r o l e i n the success of the venture. Second, l o c a t i o n a l f a c t o r s can help a n a l y s t s f o r e c a s t where i n d u s t r y might l o c a t e . This would be p a r t i c u l a r l y u s e f u l f o r i n f r a s t r u c t u r e planners. Knowing the p o t e n t i a l l o c a t i o n and type of an i n d u s t r y can help determine the c a p a c i t y and l o c a t i o n of f u t u r e u t i l i t i e s . Knowing the p o t e n t i a l l o c a t i o n of i n d u s t r i e s would a l s o be b e n e f i c i a l to developers making investment d e c i s i o n s . T h i r d , l o c a t i o n f a c t o r s can be u s e f u l i n determining the types of i n d u s t r i e s that might l o c a t e i n an area, based on the area's l o c a t i o n a l c h a r a c t e r i s t i c s . I f a community wanted to get a b e t t e r idea of what types of i n d u s t r i e s might be a t t r a c t e d to i t s region, i t could analyze i t s c h a r a c t e r i s t i c s , compare them w i t h the l o c a t i o n a l f a c t o r s required by various i n d u s t r i e s , and focus on any p o t e n t i a l match that could be made. A community could a l s o target a s p e c i f i c i n d u s t r y to a t t r a c t and then work at developing the l o c a t i o n a l f a c t o r s that the i n d u s t r y needs. 3.1.3 Determining Location Factors There are two prevalent methods used to uncover the l o c a t i o n a l f a c t o r s of an i n d u s t r y . One method, perhaps y i e l d i n g the most accurate r e s u l t s , i s to ask those experienced i n making l o c a t i o n a l d e c i s i o n s w i t h i n an i n d u s t r y . They could o u t l i n e the f a c t o r s they consider i n making a l o c a t i o n a l d e c i s i o n , and i n d i c a t e the r e l a t i v e importance of each f a c t o r . However, conducting a survey of an i n d u s t r y can be expensive and time consuming. 38 An e a s i e r method i s to r e l a t e e x i s t i n g data on the l o c a t i o n of an i n d u s t r y to data on the l o c a t i o n of various f a c t o r s . The s t r e n g t h of c o r r e l a t i o n between the l o c a t i o n of i n d u s t r y and the various f a c t o r s can be determined through re g r e s s i o n a n a l y s i s . A major problem with t h i s methodology i s that only a c o r r e l a t i o n a l and not a c a u s a t i o n a l r e l a t i o n s h i p can be determined. C e r t a i n f a c t o r s may be h i g h l y c o r r e l a t e d w i t h the l o c a t i o n of an i n d u s t r y . These could be f a c t o r s that play l i t t l e or no r o l e i n the l o c a t i o n a l decision-making process of components w i t h i n the i n d u s t r y . On the other hand, t h i s method b e n e f i t s from the s i g n i f i c a n t advantage of being r e l a t i v e l y inexpensive and quick to apply. This t h e s i s i s designed to i d e n t i f y the l o c a t i o n a l f a c t o r s a s s o c i a t e d with high technology i n d u s t r i e s by a three-step process. F i r s t , i t w i l l review the l o c a t i o n a l f a c t o r s f o r high technology i n d u s t r i e s i d e n t i f i e d as being important i n the l i t e r a t u r e ; second, i t w i l l examine a set of l o c a t i o n a l f a c t o r s chosen from those i d e n t i f i e d i n the l i t e r a t u r e , f o r which adequate data e x i s t ; t h i r d , i t w i l l perform a r e g r e s s i o n a n a l y s i s r e l a t i n g the l o c a t i o n a l f a c t o r s to the a c t u a l l o c a t i o n of high technology i n d u s t r i e s . 3.2 L o c a t i o n a l Factors I d e n t i f i e d  i n Three Major Studies This s e c t i o n w i l l review the f i n d i n g s of three important s t u d i e s conducted on the l o c a t i o n of high technology. These three s t u d i e s are reviewed i n d e t a i l because of t h e i r immediate relevance to t h i s t h e s i s , both i n t h e i r methodology and t h e i r f i n d i n g s . The s e c t i o n f o l l o w i n g t h i s one w i l l d i s c u s s seven groups of l o c a t i o n a l f a c t o r s which have been i d e n t i f i e d as important by many researchers, i n c l u d i n g those i n v o l v e d i n the three s t u d i e s discussed i n t h i s s e c t i o n . 39 3.2.1 The Glasmeier, H a l l and Markusen Study Glasmeier, H a l l and Markusen (1983) examined a wide range of p o t e n t i a l l o c a t i o n a l f a c t o r s across 218 metropolitan areas i n the United States. They examined the r e l a t i o n s h i p between the l o c a t i o n a l f a c t o r s and three measures of the s p a t i a l tendency of high technology: the dependence of a metropolitan area on high technology, expressed as the p r o p o r t i o n of the area labour f o r c e engaged i n high tech jobs; s h i f t s i n the l o c a t i o n of high tech jobs, expressed as the absolute change i n the number of high technology jobs w i t h i n an area; and s h i f t s i n the l o c a t i o n of high technology p l a n t s , expressed as an absolute change i n an area's number of high technology p l a n t s . In examining the f a c t o r s a s s o c i a t e d with the dependence of a metro-p o l i t a n area on high technology jobs, the authors found only f i v e f a c t o r s s i g n i f i c a n t l y r e l a t e d . The f i v e v a r i a b l e s explained only 18% of the v a r i a t i o n i n high technology dependence, and two of those f a c t o r s had unexpected r e l a t i o n s h i p s w i t h high tech dependence, as shown i n Table 4. The strongest f a c t o r i d e n t i f i e d was defense spending, e x p l a i n i n g o n e - t h i r d of the v a r i a t i o n . The other f a c t o r s shown i n Table 4 explained l e s s , w i t h u t i l i t y rates and low unemployment rates e x p l a i n i n g l e s s than 2% of the v a r i a t i o n each. Nine v a r i a b l e s were i d e n t i f i e d by the authors as being s i g n i f i c a n t l y r e l a t e d to high technology job s h i f t s . Twenty-eight percent of the absolute change i n the number of high technology jobs from 1972 to 1977 i n the 218 metropolitan areas was explained by the nine v a r i a b l e s shown i n Table 5. Defense spending, housing p r i c e s and freeway d e n s i t y accounted f o r h a l f of 40 TABLE 4 FACTORS ASSOCIATED WITH METROPOLITAN DEPENDENCE ON HIGH TECHNOLOGY Factor C o r r e l a t i o n Defense Spending P o s i t i v e (expected) % L a t i n o Negative (expected) % Black Negative (expected) U t i l i t y Rates P o s i t i v e (unexpected) Low unemployment rates P o s i t i v e (unexpected) Source: Glasmeier H a l l and Markusen 1983, pp. 40-41 the explained v a r i a t i o n . While defense spending was p o s i t i v e l y c o r r e l a t e d as expected, housing p r i c e s and freeway d e n s i t y had c o r r e l a t i o n s which were unexpected by the authors. TABLE 5 FACTORS ASSOCIATED WITH HIGH TECHNOLOGY JOB SHIFTS Factor Defense Spending Housing P r i c e s Freeway Density U n i o n i z a t i o n Rates % Blacks Educational Options 1977 Labour Force S i z e A r t s Index P o l l u t i o n Index C o r r e l a t i o n P o s i t i v e P o s i t i v e Negative Negative Negative P o s i t i v e P o s i t i v e Negative P o s i t i v e (expected) (unexpected) (unexpected) (expected) (expected) (expected) (expected) (unexpected) (unexpected) Source: Glasmeier H a l l and Markusen 1983, pp. 41-43 In a n a l y z i n g aggregate plant s h i f t s across the 218 metropolitan areas, Glasmeier H a l l and Markusen found that 68% of the v a r i a t i o n was explained by 41 9 f a c t o r s shown on Table 6. Labour f o r c e s i z e i n 1977 explained 26% of a l l net pl a n t change. This was expected because i t simply means that gains i n p l a n t s were grea t e s t i n places where the labour forc e was l a r g e s t . The second most important f a c t o r was the presence of fortune 500 headquarters which had a negative c o r r e l a t i o n and explained 24% of the variance. The remaining s i g n i f i c a n t v a r i a b l e s c o n t r i b u t e d l e s s than 3% each toward e x p l a i n i n g t o t a l TABLE 6 FACTORS ASSOCIATED WITH HIGH TECH PLANT SHIFTS Factor Labour Force S i z e Fortune 500 Headquarters A r t s Index Housing P r i c e s Freeway Density Defense Spending % Black U n i o n i z a t i o n Rates Educational Spending C o r r e l a t i o n P o s i t i v e Negative Negative P o s i t i v e Negative P o s i t i v e Negative Negative Negative (expected) (unexpected) (unexpected) (unexpected) (unexpected) (expected) (expected) (expected) (unexpected) Source: Glasmeier H a l l and Markusen 1983, pp. 43 - 44. v a r i a t i o n . The authors wrote that "great caut i o n should be used i n r e f e r r i n g to those c h a r a c t e r i s t i c s which d i d t u r n out to be s i g n i f i c a n t as 'determinants' of high tech l o c a t i o n . While per c a p i t a defense spending d i d turn out to be p o s i t i v e , s i g n i f i c a n t and present i n a l l three r e g r e s s i o n s , i t i s important to remember that i t accounts f o r only 6%, 4% and 2% of t o t a l v a r i a t i o n r e s p e c t i v e l y " (Glasmeier, H a l l and Markusen 1983, pp. 45-46). Glasmeier, H a l l and Markusen (1983, p. 52) a l s o conducted regressions f o r i n d i v i d u a l high tech i n d u s t r i e s and i d e n t i f i e d ten v a r i a b l e s that were i n s i g n i f i c a n t i n e x p l a i n i n g high tech i n d u s t r y l o c a t i o n s . These 42 v a r i a b l e s c o n t r i b u t e d more than 2% to the explanation i n only 5% or l e s s of the cases when a n a l y s i s was conducted i n an i n d u s t r y by i n d u s t r y b a s i s . The ten v a r i a b l e s are shown on Table 7. TABLE 7 VARIABLES INSIGNIFICANT IN EXPLAINING HIGH TECH INDUSTRY LOCATIONS - Educational Spending - Unemployment Rate - I n d u s t r i a l U t i l i t y Rates - % Republican - Manufacturing Wage - % L a t i n o - U n i o n i z a t i o n Rate - Educational Options - Climate Index - Percent Black Source: Glasmeier H a l l and Markusen 1983, p. 52 The authors found nine independent v a r i a b l e s that turned up f r e q u e n t l y and explained more than 2% of t o t a l v a r i a t i o n . The v a r i a b l e s i d e n t i f i e d are l i s t e d i n Table 8. The r e s u l t s of the Glasmeier H a l l and Markusen study h i g h l i g h t that there are few l o c a t i o n a l f a c t o r s that act as strong determinants f o r high technology, and that the l o c a t i o n a l tendencies of high technology i n d u s t r i e s are very d i s p a r a t e across the i n d i v i d u a l components that make up high technology. 3.2.2 The Premus Study In 1982 Robert Premus conducted a survey of high technology firms f o r the J o i n t Economic Committee of Congress of the United States. The high technology fi r m s surveyed c o n s i s t e d of s e l e c t e d members of the American E l e c t r o n i c s A s s o c i a t i o n and approximately 400 companies i n the highway 128 43 TABLE 8 MOST COMMONLY OCCURRING AND CONSISTENCY RANKING OF VARIABLES EXPLAINING NET PLANT CHANGE Most Common Rank* Frequency (# of Cases) Consistency Ranking** % Cases Sign Expected Labour Force 1977 Fortune 500 A r t s Index Major U n i v e r s i t i e s P o l l u t i o n Index Housing P r i c e s Freeway Density A i r p o r t s Ranked Defense Spending 48 36 22 14 13 13 11 10 8 A i r p o r t s (+) 90% Defense Spending (+) 88 Labour Force ( + ) 79 Major U n i v e r s i t i e s (+) 57 P o l l u t i o n (-) 38 Fortune 500 ( + ) 28 Ar t s (+) 27 Freeway Density (+) 0 House P r i c e s (-) 0 * The frequency r a t i n g shows the number of s u c c e s s f u l i n d i v i d u a l i n d u s t r y regressions (N=61) i n which t h i s v a r i a b l e was s i g n i f i c a n t c o n t r i b u t o r to t o t a l e x p l a nation. V a r i a b l e s which are s i g n i f i c a n t at the .10 l e v e l . ** The percentages here show the percentages of cases i n which the v a r i a b l e d i s p l a y e d the expected s i g n i n the r e g r e s s i o n . Source: Glasmeier H a l l and Markusen 1983, p. 54. area of Boston. Responses were recei v e d from 691 of the 1750 high tech companies surveyed. The high tech companies were asked about f a c t o r s that i n f l u e n c e t h e i r l o c a t i o n a l d e c i s i o n s . They were asked to d i s t i n g u i s h between those f a c t o r s that i n f l u e n c e t h e i r choice between regions and f a c t o r s that i n f l u e n c e t h e i r d e c i s i o n of where to lo c a t e w i t h i n a region. Table 3.6 shows that labour s k i l l s and a v a i l a b i l i t y are the most important c o n s i d e r a t i o n s . This f i n d i n g emphasizes the importance of s k i l l e d personnel i n the development and production of advanced technology products. High tech companies need people with an advanced education i n order to stay competitive i n t h e i r r a p i d l y changing and competitive business. 44 Labour costs and tax cl i m a t e followed as important f a c t o r s i n f l u e n c i n g l o c a t i o n choices. This points to a concern over the cost of doing business i n an area. The f o u r t h concern, academic i n s t i t u t i o n s , i s r e l a t e d to the f i r s t concern over labour s k i l l s and a v a i l a b i l i t y . The presence of good academic i n s t i t u t i o n s can help ensure a supply of s k i l l e d labour. Several other f a c t o r s and t h e i r r e l a t i v e importance are shown i n Table 9. I t i s i n t e r e s t i n g to note that f a c t o r s such as C u l t u r a l Amenities and Climate were rated r e l a t i v e l y low i n importance. This goes against the popular n o t i o n that a good climate and c u l t u r a l amenities are a necessary component of an area i n order to a t t r a c t and r e t a i n top employees. Other i n f l u e n c e s mentioned by the respondents i n c l u d e d the f a c t that the founder of the company was from the area or that an area had a good p u b l i c a t t i t u d e toward business. TABLE 9 FACTORS THAT INFLUENCE THE REGIONAL LOCATION CHOICES OF HIGH TECHNOLOGY COMPANIES Rank Factor % S i g n i f i c a n t or Very S i g n i f i c a n t 1 Labour S k i l l s / A v a i l a b i l i t y 89.3 2 Labour Costs 72.2 3 Tax Climate w i t h i n the Region 67.2 4 Academic I n s t i t u t i o n s 58.7 5 Cost of L i v i n g 58.5 6 Tr a n s p o r t a t i o n 58.4 7 Access to Markets 58.1 8 Regional Regulatory P r a c t i c e s 49.0 9 Energy C o s t s / A v a i l a b i l i t y 41.4 10 C u l t u r a l Amenities 36.8 11 Climate 35.8 12 Access to Raw M a t e r i a l s 27.6 Source: Premus 1982, p. 23 45 The survey went on to ask about f a c t o r s that i n f l u e n c e a high technology company's l o c a t i o n a l choice w i t h i n a region. The r e s u l t s are shown i n Table 10 and r e i n f o r c e the importance of s k i l l e d , t e c h n i c a l and p r o f e s s i o n a l workers to high technology i n d u s t r i e s . Local tax s t r u c t u r e and community a t t i t u d e s toward business were noted as important f a c t o r s . These two f a c t o r s are often i n t e r r e l a t e d i n that communities w i t h a favorable a t t i t u d e toward business may provide a favorable tax s t r u c t u r e . Several other f a c t o r s are shown to be important i n Table 10. TABLE 10 FACTORS THAT INFLUENCE THE CHOICE OF A HIGH TECHNOLOGY COMPANY'S LOCATION WITHIN A REGION % s i g n i f i c a n t or Rank Factor Very S i g n i f i c a n t 1 A v a i l a b i l i t y of workers 96.1 S k i l l e d 88.1 U n s k i l l e d 52.4 Technical 96.1 P r o f e s s i o n a l 87.3 2 State and/or l o c a l government tax s t r u c t u r e 85.5 3 Community a t t i t u d e s toward business 81.9 4 Cost of property and c o n s t r u c t i o n 78.8 5 Good t r a n s p o r t a t i o n f o r people 76.1 6 Ample area f o r expansion 75.4 7 Pro x i m i t y to good schools 70.8 8 Proximity to r e c r e a t i o n a l and c u l t u r a l o p p o r t u n i t i e s 61.1 9 Good t r a n s p o r t a t i o n f a c i l i t i e s f o r m a t e r i a l s and products 56.9 10 Pr o x i m i t y to customers 56.8 11 A v a i l a b i l i t y of energy s u p p l i e s 45.6 12 Proximity to raw m a t e r i a l s and component s u p p l i e s 35.7 13 Water supply 35.3 14 Adequate waste treatment f a c i l i t i e s 26.4 Source: Premus 1982, p. 25 46 I t i s i n t e r e s t i n g to note that t r a d i t i o n a l l o c a t i o n a l f a c t o r s such as pro x i m i t y to customers, a v a i l a b i l i t y of energy s u p p l i e s and proximity to raw m a t e r i a l s were not rated as being very important by high technology i n d u s t r i e s . The Premus study was important i n that i t showed the importance of a s k i l l e d labour force and academic i n s t i t u t i o n s i n the l o c a t i o n a l choice of a high technology i n d u s t r y . Premus noted that the importance placed on l o c a l tax s t r u c t u r e s may a l s o be r e l a t e d to the emphasis on s k i l l e d labour, because high taxes may dissuade some s k i l l e d , t e c h n i c a l and p r o f e s s i o n a l employees from l o c a t i n g i n an area. Lower l o c a l taxes would a l s o allow companies to pay t h e i r workers more. So s e v e r a l f a c t o r s i d e n t i f i e d i n the Premus Study were r e l a t e d to developing, a t t r a c t i n g and r e t a i n i n g a q u a l i f i e d labour f o r c e . 3.2.3 The Newton and O'Connor Study Newton and O'Connor (1985) conducted a study using c o r r e l a t i o n and re g r e s s i o n a n a l y s i s to determine how 12 l o c a t i o n a l f a c t o r s c o r r e l a t e d w i t h the l o c a t i o n of high technology establishments across 55 Local Government Areas i n Melbourne, A u s t r a l i a . Table 11 shows how s e v e r a l l o c a t i o n a l f a c t o r s c o r r e l a t e w i t h the t o t a l number of high tech establishments i n an area. The highest c o r r e l a t i o n was w i t h the number of research establishments, which included the number of u n i v e r s i t i e s . This emphasizes the importance of academic i n s t i t u t i o n s and other sources of research and development to high technology i n d u s t r i e s . The presence of o f f i c e and f a c t o r y space constructed s i n c e 1981 was a l s o important. The importance of an area's general s o c i a l s t a tus was shown 47 by the importance of 3 f a c t o r s : area socio-economic s t a t u s ; d w e l l i n g p r i c e s ; and academic q u a l i f i c a t i o n s of area r e s i d e n t s . s t a t u s i s f u r t h e r underscored by the r e s u l t s of a m u l t i p l e r e g r e s s i o n a n a l y s i s that Newton and O'Connor performed. The r e s u l t s of t h e i r m u l t i p l e r e g r e s s i o n a n a l y s i s are shown i n Table 12, with research establishments and housing p r i c e s showing as the f i r s t two e n t r i e s i n t o the re g r e s s i o n equation. The authors note that "the 'model' f o r t o t a l high tech establishments suggests the importance of a l o c a l research environment, high r e s i d e n t i a l amenities and a w e l l e s t a b l i s h e d , high q u a l i t y i n f r a - s t r u c t u r e f o r o f f i c e and factory-based a c t i v i t y ; i n many ways embracing the standard p r e s c r i p t i o n f o r high tech i n d u s t r y " (Newton and O'Connor 1985 p 23). The authors a l s o noted, however, that a large number of f a c t o r s were found to be r e l a t i v e l y unimportant. The s i g n i f i c a n c e of research establishments and an area's s o c i a l TABLE 11 CORRELATION OF LOCATIONAL FACTORS WITH THE LOCATION OF HIGH TECH IN MELBOURNE Factor C o r r e l a t i o n Research establishments New (post 1981) O f f i c e Space Area Socio-Economic Status Dwelling P r i c e s Academic Q u a l i f i c a t i o n s of Area Residents Manufacturing D i v e r s i t y Index Value of Area's O f f i c e and Factory .58 .56 .55 .55 .52 .48 I n f r a s t r u c t u r e R e l a t i v e A c c e s s i b i l i t y .29 - .40 Source: Newton and O'Connor 1985, Appendix: Table 6 48 TABLE 12 REGRESSION ANALYSIS RESULTS LOCATION FACTORS — HIGH TECH LOCATION Factor Step of entry i n t o equation R e s u l t i n g M u l t i p l e R Number of Research Establishments P r i c e of Housing Value of O f f i c e and Factory I n f r a s t r u c t u r e 1 2 3 .58 .67 .71 Source: Newton and O'Connor 1985, Appendix: Table 7 In t h e i r c o n c l u s i o n the authors w r i t e that " I t i s a l s o p o s s i b l e that high tech a c t i v i t y i s not perhaps as l o c a t i o n a l l y v o l a t i l e as was f i r s t thought, and i s anchored to some c u r r e n t l y e s t a b l i s h e d and f o r the time being e f f i c i e n t i n s t i t u t i o n s that were b u i l t i n the c e n t r a l part of the metr o p o l i t a n area say 50 or so years ago" (Newton and O'Connor 1983, p. 26). This s e c t i o n reviews d i v e r s e l i t e r a t u r e on high tech l o c a t i o n f a c t o r s . I t concentrates on seven groups of high technology l o c a t i o n a l f a c t o r s : u n i v e r s i t y presence and s k i l l e d labour supply f a c t o r s ; defense spending f a c t o r s ; agglomeration economy and i n e r t i a f a c t o r s ; business c l i m a t e f a c t o r s ; t r a n s p o r t a t i o n and communication f a c t o r s ; l o c a l costs and a v a i l a b i l i t y f a c t o r s ; and q u a l i t y of l i f e f a c t o r s . 3.3 Seven Groups of Location Factors  I d e n t i f i e d i n the L i t e r a t u r e 49 3.3.1 U n i v e r s i t y Presence and S k i l l e d Labour U n i v e r s i t y presence and s k i l l e d labour are considered together because of t h e i r strong i n t e r r e l a t i o n s h i p s . Good u n i v e r s i t i e s can provide the h i g h l y s k i l l e d and s p e c i a l i z e d workers needed i n high technology i n d u s t r i e s . Malecki (1984) wrote that u n i v e r s i t i e s are an important l o c a t i o n a l f a c t o r i n a t t r a c t i n g h i g h tech growth because they can supply t r a i n e d personnel, f a c i l i t a t e improvement of e x i s t i n g employees, and conduct research and development. Major u n i v e r s i t i e s and research establishments have been i d e n t i f i e d as important f a c t o r s i n the l o c a t i o n of high technology by many authors (Glasmeier H a l l and Markusen 1985; Premus 1982; Newton and O'Connor 1985; Saxenian 1985; Malecki 1984; C a s t e l l s 1985; Feldman 1985). Most s t u d i e s found the presence of academic and research establishments to be among the most important high tech l o c a t i o n a l f a c t o r s . U n i v e r s i t i e s are important because they provide two major b u i l d i n g blocks f o r high technology: the new technology necessary f o r high tech; and the h i g h l y s p e c i a l i z e d employees needed to apply and develop the new technologies. " U n i v e r s i t i e s provide b e n e f i t s to high technology companies through t h e i r b a s i c research a c t i v i t i e s and through the i n t e l l e c t u a l and c u l t u r a l c l i m a t e that they provide. More important, perhaps, u n i v e r s i t i e s provide s k i l l e d labour i n the form of f a c u l t y c o n s u l t a n t s , research a s s i s t a n t s , and graduating students." (Premus 1982, p. 34). Annalee Saxenian, (1985, p. 83) i n her study of the Genesis of S i l i c o n V a l l e y , wrote that "Stanford U n i v e r s i t y provided the f o c a l point f o r the i n n o v a t i v e a c t i v i t i e s and new f i r m s t a r t - u p s i n the Santa C l a r a County during the 1950's and 1960*s." 50 The a v a i l a b i l i t y of a s k i l l e d labour f o r c e has a l s o been i d e n t i f i e d as an important, i f not the most important, f a c t o r i n high technology l o c a t i o n (Premus 1982; Newton and O'Connor 1985; Rogers and Larsen 1985; Malecki 1984; Breheny and McQuaid 1985; C a s t e l l s 1985; H a l l , Markusen, Osborn and Wachsman 1985). Malecki (1984, p. 264) emphasized that "The s k i l l e d t e c h n i c a l and p r o f e s s i o n a l workers needed i n the non-routine a c t i v i t i e s are the greatest s i n g l e l o c a t i o n f a c t o r f o r new products and high technology." In the study by Premus (1982) which was reviewed i n the previous s e c t i o n , labour s k i l l s and a v a i l a b i l i t y were the primary c o n s i d e r a t i o n s f o r making i n t e r - r e g i o n a l l o c a t i o n choices. Labour s k i l l s and a v a i l a b i l i t y were c i t e d as being s i g n i f i c a n t or very s i g n i f i c a n t f a c t o r s by 89.3% of the 691 high tech firms surveyed. Breheny and McQuaid (1985) conclude that s k i l l e d labour a v a i l a b i l i t y was one of the key f a c t o r s i n generating the high technology i n d u s t r i e s along the M4 c o r r i d o r i n B r i t a i n . Saxenian (1985) noted that the unusually large supply of s c i e n t i f i c and engineering manpower helped produce S i l i c o n V a l l e y . Related to labour supply are labour c o s t s . Premus (1982) found that labour costs were the second most important f a c t o r , rated as s i g n i f i c a n t or very s i g n i f i c a n t by 72.2% of high tech firms surveyed. On the other hand, Glasmeier H a l l and Markusen (1985) found manufacturing wage to be i n s i g n i f i c a n t i n e x p l a i n i n g high tech i n d u s t r y l o c a t i o n s . The importance of labour cost may depend on the type of high tech a c t i v i t y . Research and development a c t i v i t i e s may have to expend high labour costs to a t t r a c t h i g h l y s p e c i a l i z e d labour. Competition f o r t h i s h i g h l y s p e c i a l i z e d labour i s on a n a t i o n a l s c a l e , so r e g i o n a l d i f f e r e n c e s i n average wages probably play a 51 small r o l e i n the l o c a t i o n of research and development. Conversely, wages might be an important l o c a t i o n a l f a c t o r f o r high tech production a c t i v i t i e s such as component assembly, where r e l a t i v e l y u n s k i l l e d l o c a l labour i s required. U n i o n i z a t i o n i s another f a c t o r r e l a t e d to labour supply. Markusen and Bloch (1985), i n d i s c u s s i n g the l o c a t i o n a l requirements of high technology m i l i t a r y - o r i e n t e d producers, w r i t e that these types of i n d u s t r i e s do not l i k e unions. The d i s l i k e of unions i s not because of the wages as s o c i a t e d w i t h union workers, but because of the time delays a s s o c i a t e d w i t h unions. C a s t e l l s (1985) w r i t e s that areas with strong union t r a d i t i o n s discourage high tech. He notes that management of high tech firms are not concerned so much with wages and b e n e f i t s , but fear b u r e a u c r a t i z a t i o n and slowness where the i n d u s t r y r e q u i r e s f l e x i b i l i t y and i n n o v a t i o n . On the other hand Glasmeier H a l l and Markusen (1983) found a low c o r r e l a t i o n between u n i o n i z a t i o n rates and the l o c a t i o n of high technology. Although u n i o n i z a t i o n rates were found to be r e l a t i v e l y unimportant, the r e l a t i o n s h i p was negative: where u n i o n i z a t i o n rates were higher, the incidence of high technology was lower. 3.3.2 Defense Spending The s p a t i a l incidence of defense spending has a strong i n f l u e n c e on the l o c a t i o n of high technology i n d u s t r i e s (Glasmeier H a l l and Markusen 1983; Saxenian 1985a, 1985b; Markusen and Block 1985; Breheny and McQuaid 1985; Steed and DeGenova 1983; C a s t e l l s 1985). Defense spending often c o n t r i b u t e s to advanced technology through the need f o r performance, regardless of cost, 52 by the m i l i t a r y . The m i l i t a r y i s w i l l i n g to spend l a r g e amounts of money f o r research and development of high performance products. Glasmeier H a l l and Markusen (1983) found that defense spending was the strongest f a c t o r i n e x p l a i n i n g the dependence of a metropolitan area on high tech and i n e x p l a i n i n g high technology job s h i f t s from area to area. Saxenian (1985b) found that the huge l o c a l market f o r semiconductors from defense and aerospace c o n t r a c t s and sub-contracts was one of the c h a r a c t e r i s t i c s that helped the S i l i c o n V a l l e y become a high tech centre. S i m i l a r l y Breheny and McQuaid (1985) found that the l o c a t i o n of major government defense research establishments i n the south east or eastern south west areas of B r i t a i n were important l o c a t i o n a l f a c t o r s i n developing the M4 c o r r i d o r . In Canada, Steed and DeGenova (1983) found,that compared with other government agencies, the Department of National Defense contract linkage was deemed important by the greatest number of firms (31%) surveyed i n Ottawa's 'technology o r i e n t e d complex'. 3.3.3 Agglomeration Economies and I n e r t i a Agglomeration economies are moderately important f a c t o r s f o r the l o c a t i o n of high technology i n d u s t r y (Saxenian 1985a; Malecki 1984; Markusen and Bloch 1985; Steed and DeGenova 1983; H a l l 1985). Although some authors have found that various f a c t o r s a s s o c i a t e d w i t h agglomeration economies, such as p r o x i m i t y to customers and major s u p p l i e r s , are r e l a t i v e l y unimportant (Premus 1982; Feldman 1985). Malecki (1984) w r i t e s that high technology i n d u s t r i e s need to l o c a t e i n e x i s t i n g high tech areas. This need r e i n f o r c e s high tech agglomeration 53 economies. He a l s o notes that an area needs to have a r e p u t a t i o n as 'the r i g h t place to be' i n order to a t t r a c t s k i l l e d personnel. Saxenian (1985a, p. 30) r e i n f o r c e s t h i s concept, w r i t i n g that "once [Santa C l a r a County] had a t t a i n e d the s t a t u s as the seat of a l l knowledge and the hotbed of technology f o r the semi-conductor i n d u s t r y , ambitious young s c i e n t i s t s i n the f i e l d i n v a r i a b l y wanted to land jobs or s t a r t t h e i r own firms i n the county". H a l l (1985b, p. 14) goes even f u r t h e r , i n d i c a t i n g that i n places l i k e S i l i c o n V a l l e y e x t e r n a l economies of agglomeration are created. "For computer s c i e n t i s t s , l e a v i n g S i l i c o n V a l l e y would be l i k e g e t t i n g o f f the world.... l i k e a f i s h out of water, t h e i r c r e a t i v e energies may j u s t d i e " . Three agglomeration r e l a t e d f a c t o r s were found important i n the l o c a t i o n a l choices of high tech firms i n the Ottawa area, these included the presence of the f e d e r a l government, the f a c t that the founders were r e s i d e n t i n the area, and the existence of a high technology agglomeration. A l l three of these f a c t o r s t i e together forming a strong high technology i n e r t i a e f f e c t f o r the Ottawa area. While the existence of s p e c i a l i z e d l o c a l markets f o r high technology products may play a r o l e i n producing agglomeration economies (Saxenian 1985; Breheny and McQuaid 1985), i t seems that the more powerful f o r c e i n generating high tech agglomeration economies i s the need f o r constant i n t e r a c t i o n between the minds that generate the advanced technology. 3.3.4 Business Climate The business climate of an area i n c l u d e s community a t t i t u d e s toward business as w e l l as the l o c a l l e v e l of taxes, red tape and venture c a p i t a l . 54 These f a c t o r s are important f o r every type of i n d u s t r y , i n c l u d i n g high technology. Premus (1982) found that the f a c t o r of community a t t i t u d e toward business was l i s t e d as s i g n i f i c a n t or very s i g n i f i c a n t by 81.9% of firms surveyed. He a l s o found that the l o c a l tax s t r u c t u r e was a s i g n i f i c a n t or very s i g n i f i c a n t f a c t o r i n making i n t r a - r e g i o n a l l o c a t i o n a l d e c i s i o n s by 85.5% of firms surveyed. Taxes were a l s o found to be of moderate importance by Feldman (1985) f o r the biotechnology i n d u s t r y . The presence of adequate venture c a p i t a l can be a key f a c t o r i n generating high technology growth (Rogers and Larson 1984; C a s t e l l s 1985; Saxenian 1985b). Venture c a p i t a l i s necessary f o r small companies s t a r t i n g on t h e i r own or spinning o f f from l a r g e r , more e s t a b l i s h e d high technology f i r m s . C a s t e l l s (1985, p. 13) notes that the a v a i l a b i l i t y of venture c a p i t a l f o r investment i n high technology depends on both a high l e v e l of wealth i n an area and "an e n t r e p r e n e u r i a l c u l t u r e o r i e n t e d toward n o n - t r a d i t i o n a l f i n a n c i a l markets". Rogers and Larson (1984, p. 68) c i t e the existence of 'Cronyism', informal friendship-based networks of venture c a p i t a l sources, as being an important f a c t o r i n f i n a n c i n g new high technology e n t e r p r i s e s . Too much red tape can repel high technology i n d u s t r i e s . Both Feldman (1985) and Premus (1982) c i t e red tape and regional r e g u l a t o r y p r a c t i c e s as l o c a t i o n a l c o n s i d e r a t i o n s f o r high technology. The i n d u s t r y needs f l e x i b i l i t y and speed i n developing p o t e n t i a l new p l a n t s or research centres. Areas w i t h a slow-moving, b u r e a u c r a t i c , o v e r l y r e g u l a t o r y development process may see high tech firms l o o k i n g elsewhere. 55 3.3.5 Tra n s p o r t a t i o n and Communication Tra n s p o r t a t i o n and communication r e l a t e d f a c t o r s were found to have a bearing on the l o c a t i o n of high tech by some authors. The presence of an a i r p o r t was u n i v e r s a l l y seen as a p o s i t i v e f a c t o r (Glasmeier H a l l and Markusen 1983; Malecki 1984; Breheny and McQuaid 1985; H a l l 1985; Feldman 1985), while the presence of a freeway network was found to be a p o s i t i v e f a c t o r by some (Breheny and McQuaid 1985; H a l l 1985; Feldman 1985) and a negative f a c t o r by others (Glasmeier H a l l and Markusen 1983; Newton and O'Connor 1985). A good p o s i t i o n w i t h i n a communications network was a l s o seen as an important f a c t o r by some researchers ( C a s t e l l s 1985; H a l l , Markusen, Osborne and Wachsman 1985). Breheny and McQuaid (1985) conducted a study i n the B e r s h i r e area east of London, England, asking firms what they considered to be advantages of the eastern part of the M4 c o r r i d o r compared to other p a r t s of B r i t a i n . P r o x i m ity to Heathrow A i r p o r t was l i s t e d as an advantage by the highest number of fir m s (75%) followed by the M4 Motorway (63%) and other motorways and major roads (40%). The importance of a i r p o r t s as l o c a t i o n a l f a c t o r s i s b o l s t e r e d by the Glasmeier H a l l and Markusen (1983) f i n d i n g t h a t , i n examining net plant change f o r i n d i v i d u a l high tech i n d u s t r i e s , a i r p o r t s had the most c o n s i s t e n t r e g r e s s i o n s i g n , w i t h 90% of the re g r e s s i o n analyses showing a p o s i t i v e r e l a t i o n s h i p between a i r p o r t s and net high tech p l a n t change. On the other hand, they found that freeway d e n s i t y had a c o n s i s t e n t l y negative r e l a t i o n s h i p w i t h high tech job s h i f t s and plant s h i f t s . R e l a t i v e freeway a c c e s s i b i l i t y was a l s o found to be n e g a t i v e l y c o r r e l a t e d (-.40) with the l o c a t i o n of high tech i n a study conducted by Newton and O'Connor (1985). 56 Freeway d e n s i t y may be seen as a negative f a c t o r because of some of the environmental disadvantages a s s o c i a t e d with freeways such as noise congestion and p o l l u t i o n . A i r p o r t s , on the other hand, are v i t a l l y necessary f o r the shipping and r e c e i v i n g of high tech components and the t r a n s p o r t a t i o n of high tech personnel. C a s t e l l s (1985) argues that high tech needs to be l o c a t e d i n a good p o s i t i o n i n a communications network because the production process i n high tech can e a s i l y be separated i n time and space. Research and development, f a b r i c a t i o n , assembly and t e s t i n g f u n c t i o n s can a l l be i n separate l o c a t i o n s . In order f o r s p a t i a l l y d i s c r e t e production components to i n t e r a c t , however, they need to be located where they can communicate e f f e c t i v e l y . 3.3.6 Local Costs and A v a i l a b i l i t y Factors Local costs and a v a i l a b i l i t y f a c t o r s i n c l u d e f a c t o r s such as housing c o s t s , u t i l i t y r a t e s , energy c o s t s , cost of l i v i n g i n d i c e s , land costs and a v a i l a b i l i t y , and o f f i c e and f a c t o r y space q u a l i t y and a v a i l a b i l i t y . Most of these f a c t o r s were found to be only moderately important, and some, such as energy c o s t s , were found to be almost completely unimportant. Housing costs were p o s i t i v e l y c o r r e l a t e d w i t h the l o c a t i o n of high tech i n s t u d i e s by Glasmeier H a l l and Markusen (1983) and Newton and O'Connor (1985). Malecki (1984) noted that r e l a t i v e l y high housing p r i c e s might be an a t t r a c t i o n s i n c e they are a s s o c i a t e d w i t h growing, dynamic c i t i e s . Higher housing p r i c e s may be the r e s u l t of increased demand f o r housing brought on by e x i s t i n g high tech a c t i v i t y , r ather than being a f a c t o r which a t t r a c t s high tech. 57 The a v a i l a b i l i t y of s u i t a b l e land, o f f i c e and f a c t o r y space were f a c t o r s i n d i c a t e d by some authors (Newton and O'Connor 1985; Markusen and Bloch, 1985; Breheny and McQuaid 1985; Feldman 1985; Saxenian 1985b), w i t h the primary c o n s i d e r a t i o n being the a v a i l a b i l i t y of space f o r p o t e n t i a l expansion. Various high tech i n d u s t r i e s have experienced r a p i d growth i n the past, and high tech firms need to l o c a t e where r a p i d expansion i s p o s s i b l e . Premus (1982) found that the cost of property and c o n s t r u c t i o n was a s i g n i f i c a n t or very s i g n i f i c a n t i n t r a - r e g i o n a l l o c a t i o n c o n s i d e r a t i o n f o r 78.8% of firms surveyed. I n d u s t r i a l u t i l i t y r ates were found to be i n s i g n i f i c a n t i n e x p l a i n i n g high tech i n d u s t r y l o c a t i o n s by Glasmeier H a l l and Markusen (1983). S i m i l a r l y both Premus (1982) and Feldman (1985) wrote that the a v a i l a b i l i t y of r e l i a b l e energy was not important f o r the l o c a t i o n of high tech. This i s l i k e l y because high tech i n d u s t r i e s are not large consumers of energy and the r e l a t i v e d i f f e r e n c e s i n a firm's energy costs from area to area would be minor. 3.3.7 Q u a l i t y of L i f e Several authors have i n d i c a t e d that an area needs a high perceived ' q u a l i t y of l i f e ' i n order to a t t r a c t and r e t a i n s k i l l e d p r o f e s s i o n a l and s c i e n t i f i c personnel. Q u a l i t y of l i f e f a c t o r s i n c l u d e amenities such as a pleasant c l i m a t e , good c u l t u r a l and r e c r e a t i o n a l f a c i l i t i e s , low p o l l u t i o n l e v e l s and e x c e l l e n t s o c i a l o p p o r t u n i t i e s (Saxenian 1985; Malecki 1984; H a l l 1985a, 1985b; Markusen 1985; Feldman 1985). Malecki (1984, p. 266) w r i t e s that "Generally an urban m i l i e u w i t h e x c e l l e n t u n i v e r s i t i e s , abundant urban s o c i a l a c t i v i t i e s and a job market that allows i n d i v i d u a l s (and spouses) to 58 s w i t c h jobs without r e l o c a t i n g i s the type of place where high tech a c t i v i t i e s are found." S i m i l a r l y Saxenian (1985, p. 30), i n d e s c r i b i n g S i l i c o n V a l l e y i n C a l i f o r n i a , w r i t e s thaf'through s o c i a l i n t e r a c t i o n , these young p r o f e s s i o n a l s a l s o created a s o c i a l and c u l t u r a l m i l i e u i n the v a l l e y which provided a h i g h l y d e s i r a b l e l i f e s t y l e f o r these s c i e n t i s t s . " In the same v e i n : The new captains of i n d u s t r y are a t t r a c t e d to places untouched by the o l d t r a d i t i o n s : places p r e v i o u s l y a g r a r i a n and small town i n chara c t e r , w i t h a good ( i f l a r g e l y man-made) p h y s i c a l and s o c i a l environment, and with good communications both i n t e r n a l l y and wi t h the wider world. This i s the q u a l i t y both of S i l i c o n V a l l e y and the M4 c o r r i d o r ( H a l l and Markusen 1985, p. 147). While some l i t e r a t u r e i n d i c a t e s the general importance of q u a l i t y of l i f e f a c t o r s to the l o c a t i o n of high tech, e m p i r i c a l data do not t o t a l l y support t h i s premise. Glasmeier H a l l and Markusen (1983) found unexpected negative c o r r e l a t i o n s between t h e i r a r t s index and high tech jobs s h i f t s and plant s h i f t s . They a l s o found negative c o r r e l a t i o n s f o r the a r t s index i n 73% of t h e i r cases when i n d i v i d u a l high tech i n d u s t r i e s were examined. Furthermore they found an unexpected p o s i t i v e r e l a t i o n s h i p between high tech and t h e i r p o l l u t i o n index i n 62% of t h e i r cases when examining i n d i v i d u a l high tech i n d u s t r i e s . Their c l i m a t e index was a l s o found to be an i n s i g n i f i c a n t f a c t o r i n e x p l a i n i n g the l o c a t i o n of high tech. Premus (1982) a l s o found that q u a l i t y of l i f e f a c t o r s were given a r e l a t i v e l y low importance r a t i n g by the high tech i n d u s t r i e s he surveyed. When asked about f a c t o r s important f o r making i n t e r - r e g i o n a l l o c a t i o n a l d e c i s i o n s , firms rated ' C u l t u r a l Amenities' 10th and 'Climate' 11th out of 12 f a c t o r s . When asked about i n t r a - r e g i o n a l l o c a t i o n f a c t o r s 'Proximity to Good 59 Schools' was rated 7th and 'Proximity to Recreation and Cultural Opportunities' was rated 8th out of 14 factors for consideration. The l i t e r a t u r e seems to show that quality of l i f e i s important i n a general sense, but th i s factor i s less c r i t i c a l than other factors. Quality of l i f e perhaps should not be seen as a strong attracting factor, but as a basic requirement that i s needed i n order not to repel high tech. 3.3.8 Non-Quantifiable, Power and Influence Factors The power and influence of a community's residents can have a si g n i f i c a n t bearing on whether or not high technology industries locate or develop i n an area. The connections local p o l i t i c i a n s and businessmen have with sources of funding and members of the high technology business community can often have an influence on where high tech locates. This type of influence can often be far greater than the influence of in f r a s t r u c t u r a l factors such as excellent u n i v e r s i t i e s and large airports. The main problem with studying power and influence factors i s that they are very d i f f i c u l t to quantify. It i s close to impossible to say that an area has one more unit of power and influence than another area. For that reason, power and influence factors have not been subject to rigorous s t a t i s t i c a l analysis. Observations of cases where high technology industries have grown can provide some insight to the role of power and influence factors i n the location of high tech. Saxenian (1985b) writes that S i l i c o n Valley grew largely because of the efforts of Frederic Terman, an e l e c t r i c a l engineering professor at Stanford. Terman returned to Stanford from administering a 60 major m i l i t a r y p r o j e c t at Harvard during World War I I a f t e r having e s t a b l i s h e d numerous i n f l u e n t i a l contacts i n the eastern United S t a t e s . "Terman r e p o r t e d l y used government and academic contacts he made during the war to a t t r a c t a large p r o p o r t i o n of the Pentagon's research and procurement d o l l a r s to the Stanford area" (Saxenian 1985b, p. 24). Terman a l s o convinced Stanford's engineering graduates to e s t a b l i s h science-based businesses near the campus, r e s u l t i n g i n a c l o s e r e l a t i o n s h i p between Stanford U n i v e r s i t y and the advanced technology business world. Steed and DeGenova (1983) found that p r o x i m i t y to the f e d e r a l government was an important f a c t o r i n developing Ottawa's high technology i n d u s t r y base. Being c l o s e to sources of decision-making power on f e d e r a l c o n t r a c t s and grants was seen to be a s i g n i f i c a n t advantage. P o l i t i c a l f a c t o r s , such as the power of an area's e l e c t e d r e p r e s e n t a t i v e s , can i n f l u e n c e where advanced technology research and development funds are d i r e c t e d . I f an area's member of parliament i s a l s o a member of the f e d e r a l c abinet, he or she could have a strong i n f l u e n c e on where money i s spent. The p o l i t i c a l s e n s i t i v i t y of some areas might a l s o i n f l u e n c e how money i s a l l o c a t e d . Areas where the v o t i n g preferences can change e a s i l y depending on the amount of money d i r e c t e d to the area may see more funding f o r advanced technology i n d u s t r i e s f u n n e l l e d i n t h e i r d i r e c t i o n . In a d d i t i o n to the power and i n f l u e n c e presence i n an area, the de d i c a t i o n of p o l i t i c a l forces i n a m u n i c i p a l i t y i s a l s o important. I f a l o c a l i t y ' s p o l i t i c i a n s make the development of advanced technology i n d u s t r y i n the area a high p r i o r i t y , then the p o l i t i c a l f o r c e behind the idea may lead to f r u i t i o n . 61 3 . 3 . 9 Re la t ive Importance of Locat ion Factors The r e l a t i v e importance of various l o c a t i o n fac tors can be summarized i n a very general sense. The l i t e r a t u r e ind ica te s that the presence of a q u a l i t y u n i v e r s i t y and the subsequent generation of h ighly s k i l l e d work force are perhaps the most important f a c t o r s . The s p a t i a l incidence of defense spending i s next i n importance, although i n nations where defense spending i s less prevalent t h i s fac tor would not be as dominant as i t i s i n the United States . T h i r d i n importance are agglomeration economies and i n e r t i a e f f e c t s . The r o l e of agglomeration and i n e r t i a are to generate stronger high tech growth where i t a lready e x i s t s . Fourth i n importance, and re la t ed to agglomeration and i n e r t i a , i s the business c l imate of an area . The 'welcome mat' that a l o c a t i o n sets out for a p o t e n t i a l new high tech f i rm i s qu i te important. Transporta t ion and Communication fac tors are f i f t h i n importance because of the need for high tech to be i n t e r l i n k e d with i t s often s p a t i a l l y separated product ion process and market. S ix th i n importance are l o c a l costs and a v a i l a b i l i t y . In p a r t i c u l a r an area needs land for po tent ia l expansion. Qua l i ty of l i f e i s seventh i n importance. C u l t u r a l , s o c i a l , environmental and r e c r e a t i o n a l amenities are important, but not c r i t i c a l fac tors i n the l o c a t i o n of high tech. The importance of power and inf luence factors i s d i f f i c u l t to gauge; however, i t i s conceivable that i n some cases these fac tors could be of greater importance than a l l the other factors d i scussed . The above r a t i n g i s very general and would probably change s u b s t a n t i a l l y for s p e c i f i c subsectors of the high tech industry . For example, l o c a l land costs might be the most important fac tor for land-extensive high tech t e s t i n g f a c i l i t i e s , with the presence of an exce l l ent u n i v e r s i t y being a r e l a t i v e l y i n s i g n i f i c a n t f a c t o r . 62 3.4 Location Factors Examined f o r Canada Based on the l i t e r a t u r e review i n the previous two s e c t i o n s , t h i s t h e s i s w i l l attempt to examine f a c t o r s from each of the seven groups of l o c a t i o n f a c t o r s i d e n t i f i e d . In some cases, l i m i t a t i o n s i n data a v a i l a b i l i t y w i l l prevent a wholly s a t i s f a c t o r y and accurate i n d i c a t i o n of a f a c t o r ' s s p a t i a l i n c i d e n c e . The need to use the data i n a r e g r e s s i o n a n a l y s i s a l s o l i m i t s the type of l o c a t i o n f a c t o r that can be analyzed. Table 13 o u t l i n e s the l o c a t i o n f a c t o r s to be examined under each group heading, and the expected r e l a t i o n s h i p w i t h the l o c a t i o n of high technology i n d u s t r y . U n i v e r s i t y presence and labour c o n s i d e r a t i o n s w i l l be represented by f i v e f a c t o r s . F i r s t , u n i v e r s i t y enrollment i n absolute numbers should give some i n d i c a t i o n of the r e l a t i v e s i z e and importance of u n i v e r s i t i e s w i t h i n a CMA. This i m p l i e s that a l a r g e r u n i v e r s i t y presence w i l l c o r r e l a t e w i t h a l a r g e r high technology presence. The case may a c t u a l l y be that a high q u a l i t y u n i v e r s i t y presence, or one that i s more dedicated to high tech, rather than a l a r g e r u n i v e r s i t y , may form a c l o s e r r e l a t i o n s h i p w i t h the presence of high tech; however, data l i m i t a t i o n s allow only the examination of the absolute s i z e of U n i v e r s i t i e s . Second, the percentage of a CMA's work force that has s c i e n t i f i c and p r o f e s s i o n a l s k i l l s should be a r e l a t i v e l y accurate r e f l e c t i o n of the presence of a s k i l l e d labour f o r c e f o r high tech i n d u s t r i e s . T h i r d , the percentage of a CMA's work forc e that has a u n i v e r s i t y degree should be a r e f l e c t i o n of the p r o p o r t i o n of workers w i t h the advanced education needed i n some forms of high tech. Fourth, the number 63 TABLE 13 LOCATION FACTORS TO BE EXAMINED AND EXPECTED RELATIONSHIP Factor Expected Relationship University Presence and Labour University enrolment % Work Force S c i e n t i f i c Engineering and Mathematical % Work Force with University Degree Number of R and D f a c i l i t i e s Union membership Defense Spending Data not available Agglomeration Economies and Inertia Federal government employees Number of R and D employees Natural Science Expenditures + + + + + + + Business Climate Data Not Available Transportation and Communication Network A i r l i n e f l i g h t s + Telephone connections + Local Costs and A v a i l a b i l i t y Average wages Consumer Price Index E l e c t r i c i t y rates Housing costs Quality of L i f e A i r quality index + Climate index + 64 of research and development f a c i l i t i e s should a l s o be an i n d i c a t i o n of the number of h i g h l y s k i l l e d workers e x i s t i n g i n an area. I t should a l s o point to the p r ogenitors of advanced technology. F i f t h union membership should a c c u r a t e l y r e f l e c t the tendency of a CMA's labour force to be union-oriented, a negative f a c t o r f o r the l o c a t i o n of high tech. Defense spending f a c t o r s w i l l not be represented i n t h i s t h e s i s . They w i l l not be examined p r i m a r i l y because defense spending f i g u r e s are d i f f i c u l t to o b t a i n on a s p a t i a l b a s i s f o r Canada, and, u n l i k e the United States and Great B r i t a i n , Canada spends r e l a t i v e l y l i t t l e on defense research. Agglomeration economies and i n e r t i a f a c t o r s w i l l be represented by the number of f e d e r a l government employees and the number of R and D f a c i l i t i e s i n each CMA. The number of f e d e r a l government employees should be an i n d i c a t i o n of the f e d e r a l presence i n a CMA. The f e d e r a l government provides a large market f o r high technology products i n Canada. A high f e d e r a l presence should provide o p p o r t u n i t i e s f o r linkages between firms and f e d e r a l c l i e n t s , thereby c r e a t i n g p o t e n t i a l f o r f u r t h e r development of high tech agglomeration economies. A higher number of R and D f a c i l i t i e s should a l s o provide the p o t e n t i a l f o r high tech agglomeration economies. Business c l i m a t e i s d i f f i c u l t to determine without an i n t i m a t e knowledge of the p o l i t i c s i n a l l of the CMAs, and the r e l a t i v e acceptance of new business and growth to an area. I n d u s t r i a l tax rates would provide some measure of the l o c a l t a x a t i o n c l i m a t e f o r high tech i n d u s t r i e s , however these data are not r e a d i l y and c o n s i s t e n t l y a v a i l a b l e across Canada. Tr a n s p o r t a t i o n and communication network f a c t o r s w i l l be represented by numbers of annual a i r l i n e f l i g h t s and t o t a l telephone connections. The geographical d i s p e r s i o n of various stages of the high tech production process 65 r e q u i r e s easy t r a n s f e r of personnel and in f o r m a t i o n as w e l l as quick a v a i l a b i l i t y of components. A i r l i n e f l i g h t s w i l l show how well-connected a CMA i s to other areas. They w i l l a l s o i l l u s t r a t e the r e l a t i v e s i z e and importance of a CMA's a i r p o r t s . T o tal telephone connections w i l l once again show how w e l l connected a CMA i s to other areas, but through e l e c t r o n i c rather than p h y s i c a l means. The number of telephone connections may a l s o r e f l e c t how important telephone communication i s to a p a r t i c u l a r CMA. Local costs and a v a i l a b i l i t y w i l l be represented by four f a c t o r s . F i r s t , average wages w i l l i n d i c a t e l o c a l labour c o s t s . Production o r i e n t e d high tech may be c o r r e l a t e d w i t h lower labour c o s t s ; however, the opposite may be tr u e f o r research and development components of high technology. This t h e s i s w i l l expect a negative r e l a t i o n s h i p between wage rates and high tech, bearing i n mind that the reverse may be t r u e . Second, the cost of l i v i n g index w i l l r e f l e c t l o c a l costs f o r high tech employees. I t i s expected that the l o c a t i o n of high tech should have a negative r e l a t i o n s h i p w i t h the cost of l i v i n g . T h i r d , e l e c t r i c i t y r ates should be n e g a t i v e l y r e l a t e d with the l o c a t i o n of high tech. While high tech a c t i v i t i e s are u s u a l l y not large users of e l e c t r i c i t y they w i l l probably not be found where e l e c t r i c i t y r ates are high. Fourth, housing costs are expected to be n e g a t i v e l y c o r r e l a t e d with the l o c a t i o n of high tech. High tech firms would probably not wish to impose high housing costs on t h e i r employees as a consequence of l o c a t i o n . High housing c o s t s , however, are often a s s o c i a t e d w i t h areas of high amenities which may be seen as a p o s i t i v e l o c a t i o n a l f a c t o r by some high tech f i r m s , so a p o s i t i v e r e l a t i o n s h i p may r e s u l t . Q u a l i t y of l i f e f a c t o r s w i l l be i n d i c a t e d by the a i r q u a l i t y index and clim a t e index. While many more f a c t o r s c o n t r i b u t e to the r e l a t i v e q u a l i t y of 66 l i f e i n an area, data are o f t e n d i f f i c u l t to o b t a i n . A i r q u a l i t y and c l i m a t e should give a general i n d i c a t i o n of the environmental l i v e a b i l i t y of an area. I t i s expected that higher a i r q u a l i t y and b e t t e r c l i m a t e w i l l be p o s i t i v e l y r e l a t e d w i t h the l o c a t i o n of high technology i n d u s t r i e s . 67 CHAPTER IV DATA DESCRIPTION  4.1 I n t r o d u c t i o n Chapter IV discusses and describes data that have been gathered f o r the a n a l y s i s of high technology l o c a t i o n f a c t o r s , t h i s chapter f i r s t examines data on the l o c a t i o n of high tech i n d u s t r i e s i n Canada. I t reviews how data were gathered and o p e r a t i o n a l i z e d , describes where high tech i s concentrated i n Canada, i d e n t i f i e s CMAs with a heavy r e l i a n c e on high tech and notes the various types of high tech prevalent i n each area. This chapter goes on to di s c u s s the data on each high technology l o c a t i o n a l f a c t o r i d e n t i f i e d i n Chapter I I I . I t i d e n t i f i e s the source of the data, shows how the data were o p e r a t i o n a l i z e d , o u t l i n e s the l i m i t a t i o n s of the data i n t h e i r a p p l i c a t i o n i n t h i s t h e s i s , and describes the s p a t i a l i n cidence of the l o c a t i o n f a c t o r s across Canada. 4.2 Data on the Location of High Technology  4.2.1 Data Gathering and O p e r a t i o n a l i z a t i o n Chapter I I defined high tech f o r Canada and i d e n t i f i e d a l i s t of high tech i n d u s t r i e s . To determine the amount of high tech employment i n each CMA, the number of employees i n each high tech i n d u s t r y f o r each area were summed. Data on employment by i n d u s t r y f o r the 24 Canadian CMAs were r e a d i l y a v a i l a b l e from S t a t i s t i c s Canada. Table 14 shows the number of people employed i n each high tech s e c t o r f o r a l l 24 Census M e t r o p o l i t a n Areas i n Canada. To show the r e l a t i v e dependence of each CMA on high tech the number of high tech employees was 68 d i v i d e d by the t o t a l labour f o r c e to give the percentage of the t o t a l labour for c e engaged i n high tech. The r e l a t i v e importance of each high tech i n d u s t r y i n each CMA i s a l s o shown by the percentage d i s t r i b u t i o n of the high tech labour f o r c e amongst the 13 high tech i n d u s t r i e s . 4.2.2 D i s t r i b u t i o n of High Tech i n Canada In terms of absolute numbers, Table 14 shows that Toronto has the highest number of high tech employees with 102,754, followed by Montreal wit h 75,150 and Vancouver with 56,640. Data on the percentage of labour f o r c e devoted to high tech p a i n t s a s l i g h t l y d i f f e r e n t p i c t u r e , however. Calgary has the highest dependence on high tech w i t h 13.6% of i t s labour f o r c e engaged i n high tech, Vancouver i s second with 8.3% i n high tech and Toronto t h i r d w i t h 6.1%. The lowest number of high tech workers are C h i c o u t i m i -Jonquiere wi t h 1340, Sudbury w i t h 1380 and T r o i s R i v i e r e s with 1850. These three CMAs a l l have small work f o r c e s , but there are other CMAs w i t h s m a l l e r work f o r c e s , so work forc e s i z e alone cannot e x p l a i n the low numbers of high tech workers. Places w i t h the lowest percentage of t h e i r labour f o r c e i n high tech are Windsor with only 1.6%, V i c t o r i a w i t h 1.7% and Sudbury w i t h 2.0%. A d e t a i l e d d i s c u s s i o n of the c h a r a c t e r i s t i c s of high tech i n each CMA i s presented i n Appendix I, which describes the i n d u s t r i e s i n which the high tech workers i n each CMA are concentrated. 4.3 D i s t r i b u t i o n of Location f a c t o r s i n Canada F i f t e e n l o c a t i o n f a c t o r s are be reviewed as f o l l o w s : u n i v e r s i t y enrolment; employees i n n a t u r a l s c i e n c e s , engineering and mathematical 69 TABLE 14 EMPLOYMENT BY HIGH TECH SECTOR BY CENSUS METROPOLITAN AREA St. John's H a l i f a x Saint John High Tech Employment High Tech Employment High Tech Employment D e s c r i p t i o n of Industry Number Percent Number Percent Number Percent Engineering & S c i e n t i f i c Services 905 33.15% 1185 23.42% 195 10.08% Computer Services 185 6.78% 380 7.51% 35 1.81% Crude Petroleum & Natural Gas Industry 210 7.69% 110 2.17% 10 0.52% O f f i c e & Store Machinery Manufacturers 20 0.73% 130 2.57% 10 0.52% E l e c t r i c Power 855 31.32% 1025 20.26% 880 45.48% F o r s e s t r y Services 95 3.48% 80 1.58% 40 2.07% Communication Equipment Manufacturers 45 1.65% 685 13.54% 110 5.68% Manuf. of I n d u s t r i a l Chemicals 70 2.56% 95 1.88% 30 1.55% O f f i c e s of Management & Bus. Consultants 115 4.21% 280 5.53% 35 1.81% Petroleum R e f i n e r i e s 105 3.85% 780 15.42% 590 30.49% Misc. Services I n c i d e n t a l to Mining 105 3.85% 65 1.28% 0 0.00% A i r c r a f t & A i r c r a f t Parts Manuf. 10 0.37% 200 3.95% 0 0.00% E l e c t r i c a l I n d u s t r i a l Equip. Manuf. 10 0.37% 45 0.89% 0 0.00% Total High Tech Employees 2730 100.00% 5060 100.00% 1935 100.00% Total CMA Employment 71370 143995 52195 % High Tech 3.83% 3.51% 3.71% 70 TABLE 14 (Continued) EMPLOYMENT BY HIGH TECH SECTOR BY CENSUS METROPOLITAN AREA Chicoutimi -Jonquiere Montreal Ottawa--Hull High Tech Employment High Tech Employment High Tech Employment D e s c r i p t i o n of Industry Number Percent Number Percent Number Percent Engineering & S c i e n t i f i c Services 515 39.77% 14825 19.73% 4565 27.53% Computer Services 50 3.86% 3855 5.13% 1890 11.40% Crude Petroleum & Natural Gas Industry 5 0.39% 185 0.25% 85 0.51% O f f i c e & Store Machinery Manufacturers 20 1.54% 3260 4.34% 1330 8.02% E l e c t r i c Power 410 31.66% 10675 14.20% 1235 7.45% Fo r s e s t r y S e r vices 50 3.86% 95 0.13% 135 0.81% Communication Equipment Manufacturers 35 2.70% 11500 15.30% 5050 30.46% Manuf. of I n d u s t r i a l Chemicals 25 1.93% 2585 3.44% 280 1.69% O f f i c e s of Management & Bus. Consultants 55 4.25% 4110 5.47% 1530 9.23% Petroleum R e f i n e r i e s 20 1.54% 4800 6.39% 65 0.39% Misc. Services I n c i d e n t a l to Mining 100 7.72% 115 0.15% 95 0.57% A i r c r a f t & A i r c r a f t Parts Manuf. 5 0.39% 16460 21.90% 180 1.09% E l e c t r i c a l I n d u s t r i a l Equip. Manuf. 5 0.39% 2685 3.57% 140 0.84% To t a l High Tech Employees 1295 100.00% 75150 100.00% 16580 100.00% Total CMA Employment 57680 1428705 386170 % High Tech 2.25% 5.26% 4.29% 71 TABLE 14 (Continued) EMPLOYMENT BY HIGH TECH SECTOR BY CENSUS METROPOLITAN AREA Quebec T r o i s - R i v i e r e s Hamilton High Tech Employment High Tech Employment High Tech Employment D e s c r i p t i o n of Industry Number Percent Number Percent Number Percent Engineering & S c i e n t i f i c Services 2190 35.24% 210 11.54% 1890 18.97% Computer Services 575 9.25% 25 1.37% 530 5.32% Crude Petroleum & Natural Gas Industry 85 1.37% 5 0.27% 45 0.45% O f f i c e & Store Machinery Manufacturers 250 4.02% 45 2.47% 365 3.66% E l e c t r i c Power 1550 24.94% 1085 59.62% 1380 13.85% F o r s e s t r y Services 115 1.85% 35 1.92% 25 0.25% Communication Equipment Manufacturers 220 3.54% 55 3.02% 1520 15.25% Manuf. of I n d u s t r i a l Chemicals 85 1.37% 145 7.97% 460 4.62% O f f i c e s of Management & Bus. Consultants 375 6.03% 40 2.20% 600 6.02% Petroleum R e f i n e r i e s 395 6.36% 20 1.10% 860 8.63% Misc. Services I n c i d e n t a l to Mining 110 1.77% 0 0.00% 30 0.30% A i r c r a f t & A i r c r a f t Parts Manuf. 25 0.40% 0 0.00% 90 0.90% E l e c t r i c a l I n d u s t r i a l Equip. Manuf. 240 3.86% 155 8.52% 2170 21.78% Total High Tech Employees 6215 100.00% 1820 100.00% 9965 100.00% Total CMA Employment 280960 60845 278745 % High Tech 2.21% 2.99% 3.58% 72 TABLE 14 (Continued) EMPLOYMENT BY HIGH TECH SECTOR BY CENSUS METROPOLITAN AREA Kitchener London Oshawa High Tech Employment High Tech Employment High Tech Employment D e s c r i p t i o n of Industry Number Percent Number Percent Number Percent Engineering & S c i e n t i f i c Services 755 10.70% 695 12.80% 430 12.20% Computer Services 235 3.33% 425 7.83% 250 7.09% Crude Petroleum & Natural Gas Industry 25 0.35% 60 1.10% 45 1.28% O f f i c e & Store Machinery Manufacturers 1290 18.28% 220 4.05% 120 3.40% E l e c t r i c Power 650 9.21% 565 10.41% 1275 36.17% F o r s e s t r y Services 0 0.00% 10 0.18% 10 0.28% Communication Equipment Manufacturers 1405 19.91% 2085 38.40% 840 23.83% Manuf. of I n d u s t r i a l Chemicals 365 5.17% 180 3.31% 100 2.84% O f f i c e s of Management & Bus. Consultants 350 4.96% 265 4.88% 120 3.40% Petroleum R e f i n e r i e s 55 0.78% 75 1.38% 75 2.13% Misc. Services I n c i d e n t a l to Mining 10 0.14% 0 0.00% 0 0.00% A i r c r a f t & A i r c r a f t Parts Manuf. 555 7.87% 0 0.00% 140 3.97% E l e c t r i c a l I n d u s t r i a l Equip. Manuf. 1360 19.28% 850 15.65% 120 3.40% Total High Tech Employees 7055 100.00% 5430 100.00% 3525 100.00% Total CMA Employment 153610 152475 78645 % High Tech 4.59% 3.56% 4.48% 73 TABLE 14 (Continued) EMPLOYMENT BY HIGH TECH SECTOR BY CENSUS METROPOLITAN AREA St. Catherines-Niagara Sudbury Thunder Bay High Tech Employment High Tech Employment High Tech Employment D e s c r i p t i o n of Industry Number Percent Number Percent Number Percent Engineering & S c i e n t i f i c Services 1755 32 .23% 270 19.85% 435 22.48% Computer Services 85 1 .56% 40 2.94% 15 0.78% Crude Petroleum & Natural Gas Industry 30 0 .55% 20 1.47% 35 1.81% O f f i c e & Store Machinery Manufacturers 255 4 .68% 40 2.94% 15 0.78% E l e c t r i c Power 840 15 .43% 350 25.74% 785 40.57% F o r s e s t r y Services 15 0 .28% 120 8.82% 270 13.95% Communication Equipment Manufacturers 95 1 .74% 45 3.31% 25 1.29% Manuf. of I n d u s t r i a l Chemicals 1125 20 .66% 60 4.41% 120 6.20% O f f i c e s of Management & Bus. Consultants 200 3 .67% 15 1.10% 110 5.68% Petroleum R e f i n e r i e s 60 1 .10% 30 2.21% 20 1.03% Misc. Services I n c i d e n t a l to Mining 25 0 .46% 320 23.53% 65 3.36% A i r c r a f t & A i r c r a f t Parts Manuf. 425 7 .81% 15 1.10% 40 2.07% E l e c t r i c a l I n d u s t r i a l Equip. Manuf. 535 9 .83% 35 2.57% 0 0.00% Total High Tech Employees 5445 100 .00% 1360 100.00% 1935 100.00% Total CMA Employment 148850 68810 62205 % High Tech 3.66% 1.98% 3.11% 74 TABLE 14 (Continued) EMPLOYMENT BY HIGH TECH SECTOR BY CENSUS METROPOLITAN AREA Toronto Windsor Winnipeg High Tech Employment High Tech Employment High Tech Employment D e s c r i p t i o n of Industry Number Percent Number Percent Number Percent Engineering & S c i e n t i f i c Services 17170 16.71% 635 33, .25% 1505 13.79% Computer Services 11685 11.37% 60 3, .14% 595 5.45% Crude Petroleum & Natural Gas Industry 1065 1.04% 10 0, .52% 105 0.96% O f f i c e & Store Machinery Manufacturers 7315 7.12% 80 4, .19% 715 6.55% E l e c t r i c Power 14760 14.37% 435 22, .77% 2735 25.07% Fo r s e s t r y Services 300 0.29% 10 0, .52% 165 1.51% Communication Equipment Manufacturers 13155 12.80% 35 1, .83% 505 4.63% Manuf. of I n d u s t r i a l Chemicals 4850 4.72% 205 10, .73% 255 2.34% O f f i c e s of Management & Bus. Consultants 7030 6.84% 155 8, .12% 720 6.60% Petroleum R e f i n e r i e s 4930 4.80% 35 1, .83% 230 2.11% Misc. Services I n c i d e n t a l to Mining 900 0.88% 10 0. .52% 80 0.73% A i r c r a f t & A i r c r a f t Parts Manuf. 12095 11.77% 75 3, .93% 2725 24.98% E l e c t r i c a l I n d u s t r i a l Equip. Manuf. 7490 7.29% 165 8 .64% 575 5.27% Total High Tech Employees 102745 100.00% 1910 100, .00% 10910 100.00% Total CMA Employment 1678560 116285 309360 % High Tech 6.12% 1.64% 3.53% 75 TABLE 14 (Continued) EMPLOYMENT BY HIGH TECH SECTOR BY CENSUS METROPOLITAN AREA Regina Saskatoon Calgary High Tech Employment High Tech Employment High Tech Employment D e s c r i p t i o n of Industry Number Percent Number Percent Number Percent Engineering S S c i e n t i f i c Services 620 20.23% 1105 43.56% 11225 23.74% Computer Services 265 8.65% 110 4.34% 2075 4.39% Crude Petroleum & Natural Gas Industry 165 5.38% 80 3.15% 24715 52.28% O f f i c e & Store Machinery Manufacturers 50 1.63% 55 2.17% 340 0.72% E l e c t r i c Power 970 31.65% 375 14.78% 1395 2.95% F o r s e s t r y Services 10 0.33% 15 0.59% 85 0.18% Communication Equipment Manufacturers 125 4.08% 350 13.80% 510 1.08% Manuf. of I n d u s t r i a l Chemicals 135 4.40% 190 7.49% 1045 2.21% O f f i c e s of Management & Bus. Consultants 160 5.22% 175 6.90% 1545 3.27% Petroleum R e f i n e r i e s 360 11.75% 45 1.77% 1090 2.31% Misc. Services I n c i d e n t a l to Mining 25 0.82% 22 0.87% 2855 6.04% A i r c r a f t & A i r c r a f t Parts Manuf. 25 0.82% 5 0.20% 295 0.62% E l e c t r i c a l I n d u s t r i a l Equip. Manuf. 155 5.06% 10 0.39% 100 0.21% Total High Tech Employees 3065 100.00% 2537 100.00% 47275 100.00% Total CMA Employment 86875 81655 348400 % High Tech 3.53% 3.11% 13.57% 76 TABLE 14 (Continued) EMPLOYMENT BY HIGH TECH SECTOR BY CENSUS METROPOLITAN AREA Edmonton Vancouver V i c t o r i a High Tech Employment High Tech Employment High Tech Employment D e s c r i p t i o n of Industry Number Percent Number Percent Number Percent Engineering & S c i e n t i f i c Services 5990 27.53% 20505 36.20% 930 24 .70% Computer Services 1220 5.61% 5025 8.87% 455 12 .08% Crude Petroleum & Natural Gas Industry 3415 15.70% 270 0.48% 20 0 .53% O f f i c e & Store Machinery Manufacturers 265 1.22% 1825 3.22% 60 1 .59% E l e c t r i c Power 1690 7.77% 10255 18.11% 305 8 .10% F o r s e s t r y Services 395 1.82% 1170 2.07% 1495 39 .71% Communication Equipment Manufacturers 285 1.31% 4355 7.69% 85 2 .26% Manuf. of I n d u s t r i a l Chemicals 2555 11.74% 1325 2.34% 10 0 .27% O f f i c e s of Management & Bus. Consultants 1270 5.84% 5850 10.33% 270 7 .17% Petroleum R e f i n e r i e s 1480 6.80% 2780 4.91% 35 0 .93% Misc. Services I n c i d e n t a l to Mining 2545 11.70% 1250 2.21% 30 0 .80% A i r c r a f t & A i r c r a f t Parts Manuf. 480 2.21% 1025 1.81% 70 1 .86% E l e c t r i c a l I n d u s t r i a l Equip. Manuf. 165 0.76% 1005 1.77% 0 0 .00% T o t a l High Tech Employees 21755 100.00% 56640 100.00% 3765 100 .00% Total CMA Employment 373530 681385 224275 % High Tech 5.82% 8.31% 1.68% 77 occupations; percentage labour f o r c e w i t h a u n i v e r s i t y degree; n a t u r a l science expenditures; union membership; i n d u s t r i a l research and development employment; f e d e r a l government employment; a i r l i n e f l i g h t s ; telephones connections; f a m i l y income; cl i m a t e index; and a i r q u a l i t y index. Table 15 d e t a i l s the values f o r l o c a t i o n f a c t o r s f o r each CMA. These f i f t e e n l o c a t i o n a l f a c t o r s were chosen f o r examination i n chapter I I I , based on the l i t e r a t u r e review and the a v a i l a b i l i t y of data. A d e t a i l e d d i s c u s s i o n of each of these f a c t o r s , i n c l u d i n g a d i s c u s s i o n of t h e i r source, and how the f a c t o r s vary across the 24 Census M e t r o p o l i t a n Areas can be found i n Appendix I I . 78 TABLE 15 LOCATION FACTOR DISTRIBUTION IN CANADA BY CENSUS METROPOLITAN AREA Percent Percent Percent S c i e n t i f i c Labour Percent Total Labour Engineering Force Federal Labour Force U n i v e r s i t y & Mathematics w i t h Union Gov't Census M e t r o p o l i t a n Area Force i n High Tech Enrolment Employees Membership Employees St. John's 71370 3.83% 7631 3.63% 35.68% 5.48% H a l i f a x 143995 3.51% 12729 3.94% 29.61% 8.84% Saint John 52195 3.71% • • • 2.65% 34.63% 2.96% Chicoutimi-Jonquiere 57680 2.25% 2244 3.68% 42.57% 0.82% Montreal 1428705 5.26% 57742 3.51% 31.45% 2.22% Ottawa-Hull 386170 4.29% 21667 6.15% 31.67% 24.26% Quebec 280960 2.21% 18115 4.47% 39.13% 3.16% T r o i s - R i v i e r e s 60845 2.99% 4217 2.22% • • « • • • Hamilton 278745 3.58% 10529 3.54% 26.12% 1.26% Kitchener 153610 4.59% 19942 3.43% 24.74% 1.01% London 152475 3.56% 18680 2.84% 31.66% 1.91% Oshawa 78645 4.48% • • * 3.17% 34.41% 0.56% St. Catherines-Niagara 148850 3.66% 2642 3.26% 28.35% 0.97% Sudbury 68810 1.98% 2975 3.00% 37.85% 1.46% Thunder Bay 62205 3.11% 2991 2.74% 51.38% 1.97% Toronto 1678560 6.12% 57142 4.23% 26.61% 1.90% Windsor 116285 1.64% 7444 2.28% 33.41% 1.49% Winnipeg 309360 3.53% 16284 3.32% 31.12% 3.45% Regina 86875 3.53% 4033 3.86% 38.47% 3.92% Saskatoon 81655 3.11% 11274 3.91% 32.39% 2.89% Calgary 348400 13.57% 12106 7.52% 22.83% 1.45% Edmonton 373530 5.82% 19612 4.76% 29.51% 2.15% Vancouver 681385 8.31% 26017 3.70% 41.04% 2.43% V i c t o r i a 224275 1.68% 6519 2.16% 16.55% 2.84% 79 TABLE 15 (Continued) LOCATION FACTOR DISTRIBUTION IN CANADA BY CENSUS METROPOLITAN AREA Telephone Average Consumer Average A i r l i n e Connections Family P r i c e E l e c t r i c i t y Dwelling Census M e t r o p o l i t a n Area F l i g h t s per 100 pop. Income Index Rates P r i c e St. John's 8966 66.3 $25,653 254.1 $1,189 $64,805 H a l i f a x 29816 77.6 $25,887 232.0 $1,588 $60,542 Saint John 5523 70.3 $24,896 238.6 $1,390 $46,945 Chicoutimi-Jonquiere • • • 57.9 $23,860 i • • • « * $45,372 Montreal 97446 84.1 $27,191 234.2 $1,024 $66,338 Ottawa-Hull 30735 79.9 $30,575 231.4 $850 $70,138 Quebec 13609 71.1 $27,305 233.5 • • • $52,861 T r o i s - R i v i e r e s • • • 52.7 $23,135 • • • $43,038 Hamilton 3217 73.2 $28,199 $990 $66,965 Kitchener • • • 69.2 $27,022 $908 $62,963 London • • • 75.5 $27,080 $806 $65,784 Oshawa • • • 65.3 $28,290 $864 $70,027 St. Catherines-Niagara • • * 75.5 $25,727 $833 $55,551 Sudbury 4005 70.2 $26,015 $1,027 $54,532 Thunder Bay 9314 77.7 $29,355 234.0 $796 $66,682 Toronto 142517 87.2 $31,238 235.1 $1,138 $114,284 Windsor 4903 68.5 $26,643 • • • $876 $66,212 Winnipeg 39126 83.0 $26,715 235.5 $815 $58,866 Regina 12051 87.9 $29,423 234.3 $935 $60,637 Saskatoon 12723 90.8 $28,093 230.6 $973 $69,628 Calgary 60386 112.0 $33,462 236.1 $1,077 $114,666 Edmonton 49590 95.5 $31,998 238.5 $1,000 $102,982 Vancouver 79055 79.2 $31,634 238.9 $915 $171,726 V i c t o r i a 9050 59.2 $28,580 . . . . . . $132,529 80 TABLE 15 (Continued) LOCATION FACTOR DISTRIBUTION IN CANADA BY CENSUS METROPOLITAN AREA Natural Percent Percent Sciences I n d u s t r i a l A i r Labour Expenditures R&D Q u a l i t y Climate Force Census M e t r o p o l i t a n Area $ M i l l i o n Employees Index Index with Degree St. John's 69 0.17% 0.302 13.27% H a l i f a x 130 0.10% 27 0.457 17.98% Saint John 0.20% 34 0.393 10.94% Chicoutimi-Jonquiere 0.35% . , • • • 10.97% Montreal 230 0.23% 37 0.464 14.24% Ottawa-Hull 740 0.36% 22 0.427 21.91% Quebec 38 0.05% 37 0.360 15.74% T r o i s - R i v i e r e s » . 0.00% , . • • • 10.09% Hamilton 62 0.10% 43 « • • 11.95% Kitchener 0.02% 43 • • • 12.02% London 0.10% 41 0.475 15.95% Oshawa 0.57% . , • » • 8.04% St. Catherines-Niagara 0.23% 40 i • • 9.54% Sudbury • 0.00% • • • 10.28% Thunder Bay 0.02% • * • 10.26% Toronto 248 0.31% 39 0.560 16.32% Windsor 0.03% 42 • • » 12.37% Winnipeg 75 0.14% 37 0.379 14.13% Regina . , 0.10% 52 0.385 13.64% Saskatoon 37 0.14% • • 0.395 16.31% Calgary 36 0.19% 33 0.413 17.41% Edmonton 49 0.20% 41 0.400 15.56% Vancouver 121 0.24% 34 0.643 15.38% V i c t o r i a 70 0.01% 22 0.710 8.95% 81 CHAPTER V DATA ANALYSIS 5.1 D e s c r i p t i o n of A n a l y s i s Regression analyses were conducted using the data described i n chapter IV. Two types of regressions were undertaken. F i r s t , b i v a r i a t e regressions were run w i t h the percentage of t o t a l labour f o r c e employed i n high tech i n d u s t r y as the dependent v a r i a b l e and the values f o r the l o c a t i o n f a c t o r s as the independent v a r i a b l e s . The b i v a r i a t e r e g r e s s i o n a n a l y s i s provided data showing the s i g n i f i c a n c e of each f a c t o r , the amount of variance i n the dependent v a r i a b l e explained by each f a c t o r , and the mathematical r e l a t i o n s h i p between each of the l o c a t i o n f a c t o r s and high tech. A m u l t i p l e r e g r e s s i o n a n a l y s i s was a l s o conducted with a stepwise entry of the independent v a r i a b l e s i n t o the explanatory equation. This showed which of the f a c t o r s explained the greatest amount of variance i n the l o c a t i o n of high tech i n l i g h t of i n t e r r e l a t i o n s h i p s between a l l the other independent v a r i a b l e s The m u l t i p l e r e g r e s s i o n a n a l y s i s a l s o provided an equation modeling the r e l a t i o n s h i p between l o c a t i o n f a c t o r s and the l o c a t i o n of high tech. A b i v a r i a t e r e g r e s s i o n a n a l y s i s can i l l u s t r a t e the amount of variance i n a dependent v a r i a b l e that can be explained by a s i n g l e independent v a r i a b l e ; however, a m u l t i p l e r e g r e s s i o n a n a l y s i s must be run to determine the amount of variance i n a dependent v a r i a b l e that can be explained by a seve r a l independent v a r i a b l e s , i n l i g h t of the i n t e r c o r r e l a t i o n between independent v a r i a b l e s . A m u l t i p l e r e g r e s s i o n a n a l y s i s w i l l show the amount of new in f o r m a t i o n an independent v a r i a b l e can b r i n g i n t o the explanatory 82 equation. I f there i s a high degree of i n t e r c o r r e l a t i o n between two independent v a r i a b l e s , and one of them enters the explanatory equation, then the second one w i l l not add much to the amount of variance explained because a great deal of variance w i l l have already been explained by the f i r s t independent v a r i a b l e . This i n f o r m a t i o n was not provided i n a b i v a r i a t e r e g r e s s i o n a n a l y s i s , t h e r e f o r e a m u l t i p l e r e g r e s s i o n a n a l y s i s had to be performed. 5.2 B i v a r i a t e Regression A n a l y s i s 5.2.1 I n t r o d u c t i o n This s e c t i o n w i l l d i s c u s s the r e s u l t s of the b i v a r i a t e r e g r e s s i o n analyses performed with each l o c a t i o n f a c t o r using Lotus 123. I t w i l l review the s i g n i f i c a n c e of the r e l a t i o n s h i p between the l o c a t i o n f a c t o r and the l o c a t i o n of high tech, and i t w i l l d i s c u s s the amount of variance i n the Location of high tech explained by the l o c a t i o n f a c t o r . This s e c t i o n w i l l a l s o suggest p o s s i b l e explanations f o r the r e s u l t s found. The r e s u l t s are summarized i n t a b l e 16. 5.2.2 U n i v e r s i t y Enrolment The r e l a t i o n s h i p between u n i v e r s i t y enrolment and the l o c a t i o n of high tech i s examined i n a number of ways. F i r s t , the number of f u l l time u n i v e r s i t y students e n r o l l e d i s regressed against high tech emphasis (the percentage of t o t a l labour f o r c e engaged i n high tech i n d u s t r y i n each CMA). This r e s u l t s i n an R2 of 0.11 and a r e l a t i o n s h i p that i s not s i g n i f i c a n t at the 95% confidence i n t e r v a l . Some improvement i n the r e l a t i o n s h i p i s achieved when four o u t l i e r s are removed. These are Saint John and Oshawa, 83 which have no u n i v e r s i t y enrolment, and Montreal and Toronto, which have very high u n i v e r s i t y enrolment. With the removal of these 4 o u t l i e r s the R2 increases to 0.24 and the r e l a t i o n s h i p s are s i g n i f i c a n t . TABLE 16 RESULTS OF BIVARIATE REGRESSION ANALYSES BETWEEN HIGH TECH AND LOCATION FACTORS Factor R e s u l t i n g Sign of Slope ( B i ) of R2 Explanatory Equation % Natural Science engineering 0.51 + and Mathematics occupation Telephones per 100 persons 0.51 + Average Family Income 0.48 + Average Dwelling P r i c e 0.33 + A i r l i n e F l i g h t s 0.33 + U n i v e r s i t y Enrollment against modified high tech 0.32 + U n i v e r s i t y Enrolment without o u t l i e r s 0.24 + % Labour Force w i t h Degree 0.16 + % Labour Force i n Industry R&D 0.08 + Labour Force w i t h Union Membership 0.06 -Consumer P r i c e Index 0.008 + E l e c t r i c i t y r ates 0.007 + Hours Sunshine/heating Degree Days 0.005 + A i r q u a l i t y Index 0.004 -Natural Sciences Expenditures 0.002 -% Federal Gov't Employment 0.002 An even higher R2 value i s achieved when a d i f f e r e n t d e f i n i t i o n of high tech i s used. The d e f i n i t i o n i n c l u d e s those i n d u s t r i e s which have a higher than average percentage of Natural Sciences, Engineering and Mathematical occupation employees which were chosen, based on judgement by the author, as high tech i n d u s t r i e s . The l i s t of i n d u s t r i e s i s shown i n t a b l e 17. With 84 t h i s d e f i n i t i o n of high tech an R2 of 0.32 i s achieved and the r e l a t i o n s h i p i s s i g n i f i c a n t and p o s i t i v e at the 95% confidence i n t e r v a l . This means that 32% of the variance i n high tech emphasis i s explained by u n i v e r s i t y enrolment. The u n i v e r s i t y enrolment R2 of 0.32 i s not p a r t i c u l a r l y impressive i n the l i g h t of the supposed importance of u n i v e r s i t i e s to the development of high tech as suggested i n the l i t e r a t u r e reviewed i n chapter I I I . There are sever a l p o s s i b l e reasons f o r t h i s low R 2. The low R2 might be due to problems with the data that was analyzed. Gross u n i v e r s i t y enrolment f i g u r e s were used, and b e t t e r r e s u l t s might have been achieved i f enrolment i n engineering, computing sciences and the l i k e were examined. In a d d i t i o n , the d e f i n i t i o n of high tech that was used included not only research and development components of an i n d u s t r y , but a l s o the manufacturing component of high tech. I t i s p o s s i b l e that a large u n i v e r s i t y presence i s not that important to the l o c a t i o n of manufacturing f a c i l i t i e s . A d e f i n i t i o n that focused more on the research and development component of high tech may have y i e l d e d a higher R2 when regressed against u n i v e r s i t y enrolment. Reasons other than data c h a r a c t e r i s t i c s might e x p l a i n the low R 2. I f i t i s assumed that the r e s u l t i n g R2 i s an i n d i c a t i o n of the actu a l r e l a t i o n s h i p between the l o c a t i o n of high tech and u n i v e r s i t y enrolment, then perhaps there i s a weak r e l a t i o n s h i p between the u n i v e r s i t y research community and the p r i v a t e high tech research and production e n t i t i e s i n Canada. There might not be a strong enough dialogue between u n i v e r s i t i e s and 85 p r i v a t e i n t e r e s t s i n order f o r u n i v e r s i t i e s to play a major r o l e i n the l o c a t i o n of high tech. TABLE 17 ALTERNATIVE HIGH TECH DEFINITIONS LIST OF INDUSTRIES INCLUDED SIC # D e s c r i p t i o n 864 Engineering and S c i e n t i f i c Services 853 Computer Services 318 O f f i c e and Store Machinery Manufacturers 572 E l e c t r i c Power 335 Communication Equipment Manufacturers 378 I n d u s t r i a l Chemical Manufacturers 867 O f f i c e s of Management and Business Consultants 099 Misc. Services i n c i d e n t a l to Mining 321 A i r c r a f t and A i r c r a f t Parts Manufacturers 336 E l e c t r i c a l I n d u s t r i a l Equipment Manufacturers 374 Pharmaceuticals and Medicines Manufacturers 544 Telephone Systems 379 Miscellaneous Chemical I n d u s t r i e s 806 U n i v e r s i t i e s and Colleges 391 S c i e n t i f i c and P r o f e s s i o n a l Equipment I n d u s t r i e s 315 E l e c t r i c a l machinery Equipment and Supplies 621 Misc. Non-Metallic Mineral Products I n d u s t r i e s 359 Services I n c i d e n t a l to A i r Transport 502 A g r i c u l t u r a l Implement Industry M o b i l i t y might a l s o play a r o l e i n the weak r e l a t i o n s h i p between u n i v e r s i t i e s and high tech. Engineers and s c i e n t i s t s might re c e i v e t h e i r education i n one place and then leave to e s t a b l i s h a business or work i n a high tech i n d u s t r y elsewhere. Perhaps graduates i n f i e l d s that generate advanced technology should be encouraged to s t a r t high tech firms i n the communities where they r e c e i v e t h e i r education. This could be done p o s s i b l y by p r o v i d i n g i n c e n t i v e s such as reasonably p r i c e d i n d u s t r i a l space, venture c a p i t a l , and a s s i s t a n c e during the s t a r t - u p phases. 86 Another p o s s i b l e reason f o r the weak r e l a t i o n s h i p i s that Canadian high tech workers might be employed p r i m a r i l y i n manufacturing branch p l a n t s which conduct very l i t t l e research. I f research and development i s done outside of Canada, then a l o c a t i o n near a Canadian u n i v e r s i t y may not be important. While the s t r e n g t h of the r e l a t i o n s h i p between high tech and u n i v e r s i t y presence seems low, the R2 i s s t i l l high enough to suggest that some r e l a t i o n s h i p e x i s t s between the two. U n i v e r s i t i e s are a prime source of the h i g h l y educated workers necessary f o r the generation of high tech products. Being c l o s e to t h i s e s s e n t i a l supply of labour must be an important c o n s i d e r a t i o n f o r some types of high tech, and could go toward a p a r t i a l e x planation of the r e l a t i o n s h i p . 5.2.3 Education Level The education l e v e l i n a CMA i s c a l c u l a t e d as the number of persons with u n i v e r s i t y degrees, as a percentage of the labour f o r c e . The r e l a t i o n s h i p between education l e v e l and high tech emphasis i s p o s i t i v e but j u s t b a r e l y s i g n i f i c a n t w i t h an R2 of only 0.16. One of the primary reasons f o r the low R2 might be that persons w i t h a l l types of u n i v e r s i t y degrees were in c l u d e d i n the a n a l y s i s . A stronger r e l a t i o n s h i p might have been found i f only those people w i t h degrees e s s e n t i a l f o r the development of advanced technology were included. Another reason f o r the small R2 might l i e i n the d e f i n i t i o n of high technology. I t i n c l u d e s the manufacturing component of high tech, which might not r e q u i r e as many persons with u n i v e r s i t y degrees as would research and development f a c i l i t i e s . 87 I f the r e s u l t s of the a n a l y s i s are taken to mean that there a c t u a l l y i s r e l a t i v e l y l i t t l e r e l a t i o n s h i p between education l e v e l and high tech employment, then i t i s p o s s i b l e that persons with degrees are not using t h e i r knowledge of advance technology, but perhaps to apply current or past technology. The case might a l s o be that i n Canada, w i t h i t s heavy emphasis on resource e x t r a c t i o n and development, people w i t h u n i v e r s i t y degrees apply t h e i r knowledge to primary i n d u s t r i e s rather than to high tech i n d u s t r i e s . 5.2.4 S c i e n t i f i c , Engineering and Mathematical Occupations The percentage of t o t a l labour f o r c e engaged i n n a t u r a l s c i e n c e s , engineering and mathematical occupations i n each CMA has a moderately sound r e l a t i o n s h i p w i t h the high tech emphasis of each CMA. The r e s u l t s of the r e g r e s s i o n a n a l y s i s show a s i g n i f i c a n t p o s i t i v e r e l a t i o n s h i p and an R2 of 0.51, the highest R2 found f o r a l l f a c t o r s t e s t e d . The high R2 i s due, i n p a r t , to the d e f i n i t i o n of high tech that was used. The d e f i n i t i o n i d e n t i f i e s as high tech those i n d u s t r i e s w i t h a high p r o p o r t i o n of n a t u r a l s c i e n c e s , engineering and mathematical occupation employees. This r e s u l t s i n a c i r c u l a r r e l a t i o n s h i p between the l o c a t i o n of high tech and the l o c a t i o n of people w i t h the s k i l l s used i n high tech. However, not a l l n a t u r a l s c i e n c e s , engineering and mathematics employees work i n high tech i n d u s t r i e s . In f a c t only 37% are employed i n high tech, the res t are employed i n other i n d u s t r y s e c t o r s . Another more subs t a n t i v e reason f o r the high R2 i s that labour i s one of the most important components of advanced technology. Highly s k i l l e d and educated people are needed to conduct research, to apply technologies and to b r i n g advanced goods i n t o production. The presence of a labour f o r c e w i t h 88 s k i l l s needed by high tech should be a strong drawing for c e f o r high tech i n d u s t r i e s . This l o g i c , however, can work i n the opposite d i r e c t i o n . The presence of high tech i n d u s t r y may be a f o r c e that a t t r a c t s s k i l l e d labour to the area. In a l l l i k e l i h o o d both forces are at work. A f t e r some time agglomeration economies develop, w i t h an area r e c e i v i n g a r e p u t a t i o n f o r t e c h n o l o g i c a l development. This leads to a stronger draw f o r persons with education and experience needed by high tech and subsequent f u r t h e r development of high tech i n d u s t r y . As w i t h u n i v e r s i t y presence and education l e v e l , one of the reasons that the r e l a t i o n s h i p i s not stronger i s probably because the d e f i n i t i o n i n c l u d e s employment i n manufacturing f a c i l i t i e s and branch p l a n t s . These types of a c t i v i t i e s have l e s s emphasis on the need f o r h i g h l y educated employees. 5.2.5 Natural Science Expenditures There i s v i r t u a l l y no r e l a t i o n s h i p between n a t u r a l science expenditures by the f e d e r a l government and high tech employment i n the 24 CMAs across Canada. The r e g r e s s i o n proved not to be s i g n i f i c a n t at the 95% confidence i n t e r n a l and the r e s u l t i n g R2 was approximately 0.002, which means that the dependent and independent v a r i a b l e s are almost as unr e l a t e d as p o s s i b l e . This lack of any r e l a t i o n s h i p i s p u z z l i n g , because i t would seem l o g i c a l that f e d e r a l expenditure on bas i c research should l a y the groundwork fo r the development of advanced technology and subsequent high tech employment. 89 Some explanation might be found i n problems w i t h the data. 'Natural science expenditures' w i t h i n the context of the data examined covers a wide range of a c t i v i t i e s from the National Research C o u n c i l , to Energy Mines and Resources, to Regional I n d u s t r i a l Expansion, to F i s h e r i e s and Oceans. The scope i s broader than that covered by the d e f i n i t i o n of high tech used i n t h i s t h e s i s , t h e r e f o r e the r e l a t i o n s h i p between n a t u r a l sciences expenditures and high tech employment might be weak. Another data problem i s that t h i s data are f o r only one year, 1983-84, and that year i s not the same as the a n a l y s i s year, 1981. A c l o s e r r e l a t i o n s h i p might have been found i f average annual n a t u r a l sciences expenditures over the 10 years before 1981 were used. Another f a c t o r i s that data were missing f o r s e v e r a l CMAs. Only 13 CMAs were considered i n the a n a l y s i s of the r e l a t i o n s h i p between n a t u r a l science expenditures and high tech emphasis, and that number of data p o i n t s may have been too low to give an accurate r e f l e c t i o n of n a t u r a l sciences expenditures across Canada. The lack of a s i g n i f i c a n t r e l a t i o n s h i p might a l s o be due to the r e g i o n a l spending p o l i c i e s of the f e d e r a l government. Perhaps more money i s a l l o c a t e d to disadvantaged areas, which might a l s o be areas of low high tech employment. D i s p r o p o r t i o n a t e l y large amounts of n a t u r a l sciences funding are d i r e c t e d to St. John's and H a l i f a x , both of which are o f t e n perceived as areas of low economic growth. However, Ottawa receives almost three times the expenditures that any other Canadian c i t y , and Montreal and Toronto both re c e i v e a major p o r t i o n of the n a t u r a l sciences expenditures. I t would be d i f f i c u l t to argue that Ottawa, Montreal and Toronto are disadvantaged areas. 90 A f i n a l c o n s i d e r a t i o n i s that the a n a l y s i s i s an accurate r e f l e c t i o n of the s i t u a t i o n i n Canada, and that there i s v i r t u a l l y no r e l a t i o n s h i p between employment i n high technology i n d u s t r i e s and the s p a t i a l a l l o c a t i o n of money spent by the f e d e r a l government on n a t u r a l sciences research. 5.2.6 Union Membership The r e l a t i o n s h i p between union membership, expressed as a percentage of the t o t a l labour f o r c e , and high tech emphasis i s not s i g n i f i c a n t at the 95% confidence i n t e r v a l and the R2 i s very low at 0.06. Although the re g r e s s i o n i s not s i g n i f i c a n t , i t i s i n t e r e s t i n g to note that the r e l a t i o n s h i p i s negative, as was hypothesized i n Chapter I I I . I f the a n a l y s i s had been s i g n i f i c a n t , a negative r e l a t i o n s h i p would mean that high tech emphasis decreases as union emphasis in c r e a s e s . A stronger negative r e l a t i o n s h i p may have been found i f only the manufacturing component of high tech was examined. The manufacturing component i s probably more vul n e r a b l e to union a c t i v i t i e s than research and development a c t i v i t i e s , and might avoid l o c a t i o n s w i t h a strong union t r a d i t i o n . The low R2 i s probably a r e s u l t of high tech d e f i n i t i o n i n c l u d i n g a combination of R & D, s e r v i c e and manufacturing components, a l l w i t h d i f f e r i n g s e n s i t i v i t i e s to union a c t i v i t y . I t i s a l s o p o s s i b l e that the l o c a t i o n of high tech i s not i n f l u e n c e d by the union a c t i v i t y i n a p a r t i c u l a r CMA, and that the r e s u l t s are an accurate r e f l e c t i o n of the r e l a t i o n s h i p that e x i s t s . 91 5.2.7 I n d u s t r i a l Research and Development Employees Very l i t t l e v a r i a t i o n i n high tech emphasis i s explained by the percentage of the labour f o r c e engaged i n i n d u s t r i a l research and development a c t i v i t i e s . The re g r e s s i o n i s not s i g n i f i c a n t at the 95% confidence i n t e r v a l and the r e s u l t i n g R2 was only 0.08. There should probably be a stronger r e l a t i o n s h i p between i n d u s t r i a l R & D and high tech, because R & D should be part of high tech, and i n d u s t r i a l R & D should lead to the development of some high tech products and subsequent high tech employment. The poor r e l a t i o n s h i p might stem from c h a r a c t e r i s t i c s of the data. Information on i n d u s t r i a l R & D was taken from a d i r e c t o r y of i n d u s t r i a l R & D f a c i l i t i e s i n Canada. The d i r e c t o r y was based on a voluntary survey, and many R & D f a c i l i t i e s might not have answered the survey or might have been omitted from the m a i l i n g l i s t . In a d d i t i o n , the survey was conducted during 1984, and the a n a l y s i s year f o r t h i s study i s 1981. Furthermore, a great deal of i n d u s t r i a l R & D i s conducted outside the scope of i n d u s t r i e s defined as high tech i n t h i s t h e s i s . I n d u s t r i a l research and development often deals w i t h products such as soap, t i r e s , s t e e l , concrete or i n s u l a t i o n . I n d u s t r i a l R & D f a c i l i t i e s a l s o have more of an emphasis on research, while the l i s t of high tech i n d u s t r i e s used i n t h i s t h e s i s i n c l u d e s manufacturing f a c i l i t i e s . To a large degree the poor r e l a t i o n s h i p can be explained by the data c h a r a c t e r i s t i c s ; however, the low c o r r e l a t i o n might s t i l l be presenting some informati o n on the r e l a t i o n s h i p between the l o c a t i o n of i n d u s t r i a l R & D and the l o c a t i o n of high tech. Perhaps the a n a l y s i s i s showing that R & D work done i n Canada i s not d i r e c t e d toward high tech. I t might a l s o be i n d i c a t i n g that R & D work i s not leading to the s p i n o f f of new f i r m s , not leading to 92 agglomeration economics with symbiotic r e l a t i o n s h i p s between a wide range of high tech f i r m s . Perhaps i n d u s t r i a l R & D firms e x i s t more as separate enclaves and not so much as key play e r s w i t h i n a community network of high tech a c t i v i t i e s . I t i s d i f f i c u l t to say with any c e r t a i n t y without f u r t h e r research. 5.2.8 Federal Government Employment The r e l a t i o n s h i p between the percentage of the labour force employed by the f e d e r a l government and the percentage of the labour f o r c e employed i n high tech i s not s i g n i f i c a n t at the 95% confidence i n t e r n a l , and the r e s u l t i n g R2 i s a low 0.002. Although the r e l a t i o n s h i p i s not s i g n i f i c a n t , i t i s negative, the opposite of the hypothesized d i r e c t i o n of the r e l a t i o n s h i p . Federal government employment was meant to be an i n d i c a t o r of f e d e r a l government presence, which could i n turn be an i n d i c a t i o n of the p o t e n t i a l f o r the procurement of f e d e r a l government grants and c o n t r a c t s , and use of f e d e r a l research r e s u l t s . The a c t u a l number of employees, however, might not be r e p r e s e n t a t i v e of the p o t e n t i a l a v a i l a b i l i t y of grants, c o n t r a c t s or research r e s u l t s . I t i s q u i t e probable, though, that there i s l i t t l e r e l a t i o n s h i p between f e d e r a l government presence and high tech emphasis across the 24 Canadian CMAs. Perhaps the only CMA where f e d e r a l presence i s a f a c t o r i s i n Ottawa, where the f e d e r a l government employs over 24% of the work f o r c e . In other CMAs the d i f f e r e n c e s i n f e d e r a l government presence are probably not great enough to i n f l u e n c e the l o c a t i o n of high tech. 93 5.2.9 A i r l i n e F l i g h t s High tech emphasis has a moderately good r e l a t i o n s h i p w i t h a i r p o r t s i z e , measured as the number of a i r l i n e f l i g h t s per year. The r e l a t i o n s h i p i s s i g n i f i c a n t , p o s i t i v e and has an R2 of 0.33. This means that 33% of the v a r i a t i o n i n high tech emphasis can be explained by the v a r i a t i o n i n the number of a i r l i n e f l i g h t s f o r Canadian CMAs. This p o s i t i v e r e l a t i o n s h i p was expected and might have been even stronger i f 6 data points were not missing. The moderate c o r r e l a t i o n between high tech and a i r p o r t s i z e makes sense. Because the various production components of high tech (research and development, manufacturing, d i s t r i b u t i o n ) are o f t e n separated across space ( C a s t e l l s , 1985), i t i s necessary f o r the i n d u s t r y to l o c a t e near a good a i r p o r t . Frequent and convenient f l i g h t s are necessary f o r t i m e l y t r a n s p o r t a t i o n of parts and personnel. 5.2.10 Number of Telephones Compared w i t h other l o c a t i o n f a c t o r s examined, the number of telephones per 100 persons has one of the strongest r e l a t i o n s h i p s w i t h high tech emphasis. The r e g r e s s i o n r e l a t i o n s h i p i s p o s i t i v e , s i g n i f i c a n t , and has an R2 of 0.51. The number of telephones per 100 persons was o r i g i n a l l y intended to be an i n d i c a t i o n of how e l e c t r o n i c a l l y well-connected a CMA was w i t h the r e s t of the world. High tech i n d u s t r i e s were expected to l o c a t e i n areas that were b e t t e r l i n k e d to other parts of the globe. The number of telephones, however, seems to be more an i n d i c a t o r of the r e l a t i v e a f f l u e n c e of a CMA, than of how w e l l - l i n k e d a CMA i s to other areas. When telephones per 100 persons are regressed against average f a m i l y incomes, and an R2 of .56 94 r e s u l t s , so there i s a s i g n i f i c a n t r e l a t i o n s h i p between average income and telephones per 100 persons. If the number of telephones i s an i n d i c a t o r of economic p r o s p e r i t y , then perhaps i t i s not the number of telephones that i n f l u e n c e s the l o c a t i o n of high tech, but the l o c a t i o n of high tech that i n f l u e n c e s the number of telephones. High tech might be generating economic growth which creates jobs and allows people and businesses to a f f o r d more goods and s e r v i c e s , telephones being one of them. On the other hand, high tech might be a t t r a c t e d to areas of economic growth to take advantage of growing l o c a l markets and economic optimism. E i t h e r way, high tech seems to be a s s o c i a t e d w i t h economic p r o s p e r i t y . 55.2.11 Average Family Income V a r i a t i o n s i n average f a m i l y income e x p l a i n 48% of the v a r i a t i o n i n percentage of the labour f o r c e engaged i n high technology i n d u s t r i e s . The r e l a t i o n s h i p i s p o s i t i v e and s i g n i f i c a n t at the 95% confidence i n t e r v a l . Average f a m i l y income was intended to be an i n d i c a t i o n of average wages i n each CMA, and i t was hypothesized that areas w i t h higher labour costs would have lower amounts of high tech i n d u s t r y . T h i s , however, might be true only f o r manufacturing high tech a c t i v i t i e s and not f o r research and development a c t i v i t i e s . A negative r e l a t i o n s h i p might have been found i f j u s t manufacturing a c t i v i t i e s were examined, but the strong p o s i t i v e r e l a t i o n s h i p leads one to t h i n k that such a r e s u l t would be u n l i k e l y . The r e l a t i v e l y strong p o s i t i v e r e l a t i o n s h i p i n d i c a t e s that perhaps the l o c a t i o n of high tech i s i n f l u e n c i n g income rather than income i n f l u e n c i n g the l o c a t i o n of high tech. As discussed i n the previous s e c t i o n on telephones, 95 high tech might generate economic growth and higher l e v e l s of employment, leading to higher income l e v e l s . Another p o s s i b i l i t y i s that high tech i s a t t r a c t e d to areas of economic p r o s p e r i t y and growth. Income l e v e l s are an i n d i c a t i o n of the economic w e l l - b e i n g of a CMA, and those areas w i t h higher average incomes might be places which are perceived to have b r i g h t economic f u t u r e s . High tech i n d u s t r i e s might f i n d the prospect of expanding l o c a l markets and i n c r e a s i n g incomes a t t r a c t i v e f o r n u r t u r i n g f u t u r e growth. Another explanation might be that the n a t u r a l s c i e n t i s t s , engineers and mathematicians employed by high tech have higher than average incomes. CMAs with greater proportions of high tech workers would have higher average incomes than those CMAs with low proportions of high tech workers. High tech, however, only employs a small p r o p o r t i o n of the t o t a l labour f o r c e , and n a t u r a l s c i e n c e s , engineering and mathematics workers make up only part of the high tech labour f o r c e , so the impact of these r e l a t i v e l y low numbers of w e l l paid workers on the average income of the t o t a l labour f o r c e i s l i k e l y to be smal1. 5.2.12 Consumer P r i c e Index The r e l a t i o n s h i p between consumer p r i c e index and the l o c a t i o n of high tech i s not s i g n i f i c a n t at the 95% confidence i n t e r v a l and the R2 r e s u l t i n g from the r e g r e s s i o n a n a l y s i s was a very low 0.008. The poor r e l a t i o n s h i p may have been due i n part to missing data. Data were not a v a i l a b l e f o r 10 CMAs. The low R2 a l s o makes sense i n some resp e c t s , because there i s l i t t l e v a r i a t i o n i n consumer p r i c e index from CMA to CMA across Canada. This lack of v a r i a t i o n means that consumer p r i c e s could be ignored by those people making l o c a t i o n a l d e c i s i o n s , without major 96 consequences. The cost of l i v i n g would probably only act as a deterrent to high tech i n d u s t r y i f i t was n o t i c e a b l y high. 5.2.13 E l e c t r i c i t y Rates There i s v i r t u a l l y no r e l a t i o n s h i p between e l e c t r i c i t y r ates and the l o c a t i o n of high tech i n d u s t r y . The r e g r e s s i o n a n a l y s i s between these two f a c t o r s r e s u l t s i n an R2 of 0.007 and a r e l a t i o n s h i p which i s not s i g n i f i c a n t at the 95% confidence i n t e r v a l . The most probable explanation of the low R2 i s that high technology i n d u s t r i e s are not p a r t i c u l a r l y l a r ge users of e l e c t r i c i t y and t h e r e f o r e would not be o v e r l y concerned about e l e c t r i c i t y c o s t s . 5.2.14 Average Dwelling P r i c e There i s a moderate p o s i t i v e c o r r e l a t i o n between v a r i a t i o n s i n average d w e l l i n g p r i c e s and v a r i a t i o n s i n the percentage of the labour force employed i n high tech i n d u s t r i e s . The r e g r e s s i o n a n a l y s i s r e s u l t s i n an R2 of 0.33 and a r e l a t i o n s h i p that i s s i g n i f i c a n t at the 95% confidence i n t e r v a l . The r e l a t i o n s h i p between d w e l l i n g p r i c e s and high tech was p r o j e c t e d to be negative i n Chapter I I I . The l o g i c was that because high tech employs some hi g h l y s k i l l e d workers who can choose t h e i r place of work, a high tech company would not want to l o c a t e where high housing p r i c e s might repel good p o t e n t i a l employees. The moderate p o s i t i v e c o r r e l a t i o n suggests that higher housing p r i c e s might be an i n d i c a t i o n of an a t t r a c t i v e l o c a t i o n w i t h a high q u a l i t y of l i f e and numerous amenities. A place w i t h high housing p r i c e s might have c h a r a c t e r i s t i c s that are a t t r a c t i v e to high tech workers. 97 The p o s i t i v e r e l a t i o n s h i p might a l s o be the r e s u l t of high tech i n d u s t r i e s generating economic growth, c r e a t i n g jobs, i n c r e a s i n g demand f o r housing and bid d i n g up housing p r i c e s . High housing p r i c e s might a l s o be an i n d i c a t i o n of economic growth and p r o s p e r i t y , which might act to a t t r a c t high tech. Some high tech a c t i v i t i e s might be drawn to areas and w i t h l a r g e r amounts of money to spend on advanced technology products. 5.2.15 Sunshine and Warm Weather There i s almost no r e l a t i o n s h i p between the v a r i a t i o n i n the amount of sunshine and warm weather and v a r i a t i o n i n high tech emphasis. The cli m a t e index used i s based on the r a t i o of annual hours of b r i g h t sunshine to annual heating degree days (days with temperatures below 18° C). A higher number means more hours of b r i g h t sunshine and fewer days below 18° C. This r a t i o would not be appropriate i n c o u n t r i e s where temperatures can become unbearably hot f o r extended periods of time. In hot co u n t r i e s a higher number would not be i n d i c a t i v e of a more pleasant c l i m a t e . The r e s u l t i n g R2 i s 0.005 and the r e l a t i o n s h i p i s not s i g n i f i c a n t at the 95% confidence i n t e r v a l . The poor r e l a t i o n s h i p may be due to problems with the cli m a t e index used. Other f a c t o r s such as wind, r a i n and snow may play important r o l e s i n determining the l i v e a b i l i t y of CMA's cli m a t e . Obviously, though, i f i t i s sunny and warm, as the index used accounts f o r , i t i s not l i k e l y snowing or r a i n i n g . Of course, the a n a l y s i s may be i n d i c a t i n g that sunshine and warm weather are not important l o c a t i o n a l f a c t o r s f o r high tech i n Canada. I f i t 98 was important there would probably be more high tech establishments i n V i c t o r i a and fewer i n Winnipeg. 5.2.16 A i r Q u a l i t y Index There i s e s s e n t i a l l y no r e l a t i o n s h i p between a i r q u a l i t y index l e v e l s and the l e v e l of high tech employment across Canadian census metropolitan areas. The R2 r e s u l t i n g from the r e g r e s s i o n a n a l y s i s i s only 0.004, and the r e l a t i o n s h i p i s not s i g n i f i c a n t at the 95% confidence i n t e r v a l . The lack of a r e l a t i o n s h i p i s probably because the a i r q u a l i t y i n Canadian c i t i e s i s e i t h e r good or f a i r i n most cases. I t i s u n l i k e l y that poor a i r q u a l i t y would impinge upon the q u a l i t y of l i f e enjoyed i n a Canadian c i t y . A i r q u a l i t y would probably only become an important negative f a c t o r i f i t was very poor. 5.3 M u l t i p l e Regression A n a l y s i s A m u l t i p l e r e g r e s s i o n a n a l y s i s was conducted to explore f u r t h e r the r e l a t i o n s h i p between the l o c a t i o n of high tech, and the s p a t i a l incidence of the l o c a t i o n f a c t o r s . The m u l t i p l e r e g r e s s i o n a n a l y s i s was conducted using SPSS:X, a s t a t i s t i c a l package f o r s o c i a l sciences. SPSS:X allows the user to e s t a b l i s h c r i t e r i a which v a r i a b l e s must meet f o r entry i n t o the explanatory equation. The user can s p e c i f y the p r o b a b i l i t y a s s o c i a t e d w i t h the F s t a t i s t i c , c a l l e d the p r o b a b i l i t y of F-to-enter, that a v a r i a b l e must meet before i t i s entered i n t o the equation. The F s t a t i s t i c r e s u l t s from a F t e s t f o r the hypothesis that the c o e f f i c i e n t of the entered v a r i a b l e i s zero. 99 The p r o b a b i l i t y of F to enter i s set a 0.10, which means that a v a r i a b l e enters the equations only i f the p r o b a b i l i t y a s s o c i a t e d with the F t e s t i s l e s s than or equal to 0.10. SPSS:X sets a d e f a u l t value of 0.05, however the value of 0.10 was chosen to allow more v a r i a b l e s to enter the equation. The t o l e r a n c e l e v e l was l e f t at the d e f a u l t value set by SPSS:X, which i s 0.01. The t o l e r a n c e i s the p r o p o r t i o n of v a r i a b i l i t y i n an independent v a r i a b l e not explained by the other independent v a r i a b l e s . By s e t t i n g the t o l e r a n c e l e v e l at 0.01, i f 1% of the v a r i a b i l i t y i n an independent v a r i a b l e i s not explained by the other independent v a r i a b l e s , then the v a r i a b l e i s a candidate f o r entry i n t o the explanatory equation, provided i t meets the other c r i t e r i a e s t a b l i s h e d . A Stepwise s e l e c t i o n of independent v a r i a b l e s was used. In a stepwise s e l e c t i o n the f i r s t entry i n t o the equation i s the one with the l a r g e s t p o s i t i v e or negative c o r r e l a t i o n w i t h the dependent v a r i a b l e , provided that i t meets the p r o b a b i l i t y of F-to-enter and other c r i t e r i a . The second v a r i a b l e i s s e l e c t e d based on the highest p a r t i a l c o r r e l a t i o n . I f i t passes entry c r i t e r i a , i t a l s o enters the equation. In the subsequent steps, a new v a r i a b l e i s entered and each v a r i a b l e i n the equation i s examined to see i f i t should be removed from the equation based on a set maximum p r o b a b i l i t y of F that a v a r i a b l e can have. This i s c a l l e d the p r o b a b i l i t y of F-to-remove. I f a v a r i a b l e i n the equation exceeds the maximum p r o b a b i l i t y of F-to-remove, i t i s removed. The p r o b a b i l i t y of F-to-remove was set at 0.15. Forward or Backward s e l e c t i o n a l t e r n a t i v e s are a l s o o f f e r e d by SPSS:X, however, the Stepwise s e l e c t i o n was chosen because i t o f f e r s advantages provided i n both Forward and Backward s e c t i o n s . 100 M i s s i n g cases were deleted on a pa i r w i s e b a s i s . Another a l t e r n a t i v e o f f e r e d by SPSS:X i s s u b s t i t u t i o n of average values f o r missing cases. I t was not f e l t that t h i s would be appropriate f o r t h i s t h e s i s . Some f a c t o r s have a wide range of v a r i a b l e s from CMA to CMA, and s u b s t i t u t i o n of average values might give misleading r e s u l t s . The percentage of labour f o r c e engaged i n n a t u r a l s c i e n c e s , engineering and mathematics occupations was the f i r s t independent v a r i a b l e to enter the m u l t i p l e r e g r e s s i o n equation r e s u l t i n g i n an R2 of 0.51. In the second step average d w e l l i n g p r i c e entered i n t o the equation, b r i n g i n g the R2 to 0.67. The r e s u l t i n g m u l t i p l e r e g r e s s i o n equation suggests that the presence of s p e c i f i c s k i l l s w i t h i n a CMA's labour f o r c e i s an important l o c a t i o n f a c t o r . I t a l s o suggests that the economic p r o s p e r i t y and general d e s i r a b i l i t y as a place to l i v e , represented by housing p r i c e s , should be high i n order f o r high tech to l o c a t e there. The r e s u l t s might a l s o suggest that the presence of high tech leads to the a t t r a c t i o n of a work forc e w i t h i n n a t u r a l s c i e n c e s , engineering and mathematics s k i l l s , and a l s o leads to increased demand f o r housing and subsequent increases i n housing p r i c e s . Because of the c i r c u l a r r e l a t i o n s h i p between the percentage of the t o t a l labour f o r c e employed i n Natural Sciences, Engineering, and Mathematics (SEM) occupations and the d e f i n i t i o n of high tech as those establishments w i t h a high percentage of n a t u r a l s c i e n c e s , engineering and mathematics employees, a r e g r e s s i o n a n a l y s i s was run without the SEM v a r i a b l e to see what other v a r i a b l e s might enter the equation. When t h i s was done, the number of telephones per 100 persons became the f i r s t and only entry i n t o the regr e s s i o n equation r e s u l t i n g i n an R2 of 0.51. 101 I f i t i s assumed that higher numbers of telephones per 100 persons i s an i n d i c a t i o n of higher incomes, more jobs and g e n e r a l l y b e t t e r economic w e l l -being, then t h i s second r e g r e s s i o n supports the previous suggestion that high tech i n d u s t r y l o c a t e s i n areas with a b e t t e r than average economic c l i m a t e . The reverse may a l s o be t r u e , however, with the presence of high tech i n d u s t r i e s c r e a t i n g a b e t t e r than average economic c l i m a t e . 5.4 Comparison of Results w i t h Other Studies  5.4.1 Comparison with United States Study There are strong p a r a l l e l s between the methodology used i n t h i s t h e s i s and the methodology used i n a U.S. study by Glasmeier, H a l l and Markusen (1983). Both use a d e f i n i t i o n of high tech based on p r o p o r t i o n of s c i e n t i f i c , engineering, and mathematical workers; both examine v a r i a t i o n s across census metropolitan areas; both examine s i m i l a r independent v a r i a b l e s ; and both perform r e g r e s s i o n analyses to determine the st r e n g t h of the r e l a t i o n s h i p between dependent and independent v a r i a b l e s . There are a l s o major d i f f e r e n c e s between the two methodologies. The U.S. study examines three measures of the s p a t i a l tendency of high tech, as discussed i n Chapter I I I , while t h i s t h e s i s uses only one measure. There are a l s o several independent v a r i a b l e s which are not common to both s t u d i e s . Another disadvantage f o r comparison i s that the U.S. study does not c o n s i s t e n t l y present the R2 r e s u l t i n g from t h e i r r e g r e s s i o n analyses. Although some d i f f e r e n c e s e x i s t , general comparisons can s t i l l be made. The f i r s t measure of high tech l o c a t i o n used by Glasmeier, H a l l and Markusen (1983) i s expressed as the pro p o r t i o n of the area labour f o r c e engaged i n high tech jobs. S i g n i f i c a n t r e l a t i o n s h i p s are found between t h i s 102 measure of high tech and defense spending, percent L a t i n o , percent Black, u t i l i t y rates and low employment r a t e s . This t h e s i s does not examine comparable l o c a t i o n f a c t o r s except perhaps e l e c t r i c i t y r a t e s , which could be seen as roughly the same as u t i l i t y r a t e s . The U.S. study f i n d s that u t i l i t y r a tes are p o s i t i v e l y c o r r e l a t e d w i t h high tech, but e x p l a i n s l i t t l e of the variance. This t h e s i s s i m i l a r l y f i n d s e l e c t r i c i t y r ates p o s i t i v e l y c o r r e l a t e d w i t h high tech, but i n s i g n i f i c a n t and e x p l a i n i n g l e s s the 1% of the variance. Glasmeier, H a l l and Markusen's (1983) second measure of high tech i s expressed as the absolute change i n the number of high tech jobs w i t h i n an area from 1972 to 1977. Their a n a l y s i s using t h i s second measure has some r e s u l t s which are s i m i l a r to the r e s u l t s i n t h i s t h e s i s . The U.S. study and t h i s t h e s i s both f i n d housing p r i c e s to be r e l a t i v e l y s t r o n g l y r e l a t e d and p o s i t i v e . U n i o n i z a t i o n rates are n e g a t i v e l y r e l a t e d to high tech and e x p l a i n a low amount of high tech variance i n both s t u d i e s . U n i o n i z a t i o n rates e x p l a i n l e s s than 3% of high tech variance i n the U.S. study and does not enter the explanatory equation determined using m u l t i p l e r e g r e s s i o n a n a l y s i s i n t h i s t h e s i s . A p o l l u t i o n index that the U.S. study uses has a p o s i t i v e r e l a t i o n s h i p w i t h high tech, but e x p l a i n s l e s s than 3% of the variance. A s i m i l a r measure that t h i s t h e s i s uses, the a i r q u a l i t y index, has a negative r e l a t i o n s h i p w i t h high tech, although the r e l a t i o n s h i p i s not s i g n i f i c a n t . P o l l u t i o n l e v e l s might perform l a r g e r r o l e s i n U.S. c i t i e s than i n Canadian c i t i e s . The t h i r d measure of high tech i n the Glasmeier, H a l l and Markusen (1983) study i s the absolute change i n an area's number of high technology p l a n t s from 1972 to 1977. Once again the U.S. study f i n d s housing p r i c e s to be s i g n i f i c a n t and p o s i t i v e l y r e l a t e d , which i s s i m i l a r to the r e s u l t s found 103 i n t h i s t h e s i s . A l s o , u n i o n i z a t i o n rates are found to have a negative r e l a t i o n s h i p w i t h high tech l o c a t i o n , and to e x p l a i n l i t t l e high tech variance i n both the U.S. study and i n t h i s t h e s i s . The Glasmeier, H a l l and Markusen (1983) study a l s o conducts r e g r e s s i o n analyses f o r high tech on an i n d u s t r y by i n d u s t r y b a s i s . They f i n d that several f a c t o r s are i n s i g n i f i c a n t . S i m i l a r f a c t o r s are found to be i n s i g n i f i c a n t i n t h i s t h e s i s . These f a c t o r s are u t i l i t y r a t e s , u n i o n i z a t i o n rates and c l i m a t e . While the U.S. study f i n d s manufacturing wage to be i n s i g n i f i c a n t , t h i s t h e s i s f i n d s a roughly s i m i l a r factor,average f a m i l y income, to be s i g n i f i c a n t . The d i f f e r e n c e may stem mainly from the data. Manufacturing wage considers only a small s e c t o r of the work f o r c e , while average f a m i l y income deals w i t h the e n t i r e income-earning population. In the i n d u s t r y by i n d u s t r y a n a l y s i s the U.S. study a l s o f i n d s some s i g n i f i c a n t l o c a t i o n f a c t o r s which are l i k e w i s e found to be s i g n i f i c a n t i n t h i s t h e s i s . In both s t u d i e s u n i v e r s i t y presence i s s i g n i f i c a n t and p o s i t i v e l y r e l a t e d , housing p r i c e s are s i g n i f i c a n t and p o s i t i v e l y r e l a t e d , and a i r p o r t s are s i g n i f i c a n t and p o s i t i v e l y r e l a t e d . On the other hand, the p o l l u t i o n index i s s i g n i f i c a n t and n e g a t i v e l y r e l a t e d i n the U.S. study, but i n s i g n i f i c a n t and n e g a t i v e l y r e l a t e d i n t h i s t h e s i s . Again, p o l l u t i o n l e v e l s are probably a greater concern f o r U.S. c i t i e s than f o r Canadian c i t i e s . In general the two s t u d i e s are s i m i l a r i n that they both f i n d s i g n i f i c a n t p o s i t i v e r e l a t i o n s h i p s between high tech and three f a c t o r s : housing p r i c e s , u n i v e r s i t y presence and a i r p o r t s . Both s t u d i e s s i m i l a r l y f i n d negative r e l a t i o n s h i p s of low s i g n i f i c a n c e between high tech and u n i o n i z a t i o n . Both s t u d i e s a l s o f i n d u t i l i t y r a t e s , and clim a t e to be i n s i g n i f i c a n t . The major d i f f e r e n c e between the two st u d i e s i s that the U.S. study f i n d s 104 p o l l u t i o n l e v e l s to be a s i g n i f i c a n t f a c t o r , but t h i s t h e s i s , which examines the Canadian s i t u a t i o n , f i n d s p o l l u t i o n l e v e l s to be an i n s i g n i f i c a n t f a c t o r . 5.4.2 Comparison with A u s t r a l i a n Study Strong s i m i l a r i t i e s e x i s t between the methodology used i n an A u s t r a l i a n study by Newton and O'Connor (1985) and the methodology used i n t h i s t h e s i s . Both use a s i m i l a r d e f i n i t i o n of high tech based on p r o p o r t i o n of workers i n s p e c i f i c occupations; both examine s i m i l a r independent v a r i a b l e s ; and both perform r e g r e s s i o n analyses to determine the st r e n g t h of the r e l a t i o n s h i p between dependent and independent v a r i a b l e s . However, some major d i f f e r e n c e s e x i s t between the two methodologies. One d i f f e r e n c e , which i s p a r t i c u l a r l y detrimental to the comparison of these two s t u d i e s , i s that the Newton and O'Connor (1985) study examines the l o c a t i o n of high tech across subregions w i t h i n a metropolitan area, and not across separate metropolitan areas. Another d i f f e r e n c e i s that the A u s t r a l i a n study examines as i t s dependent v a r i a b l e the number of high tech establishments i n each subregion, and not the percentage of labour f o r c e engaged i n high tech. While the d i f f e r e n c e s are of concern, some cautious comparisons can s t i l l be made. Newton and O'Connor (1985) present a c o r r e l a t i o n matrix showing the c o r r e l a t i o n of various f a c t o r s w i t h the l o c a t i o n of high tech i n Melbourne. The c o r r e l a t i o n values f o r both the A u s t r a l i a n study and t h i s t h e s i s are shown i n t a b l e 18. Only those f a c t o r s which are examined i n both s t u d i e s are shown. The r e s u l t s of the A u s t r a l i a n study are g e n e r a l l y s i m i l a r to the r e s u l t s of t h i s t h e s i s f o r the four f a c t o r s shown. A l l are p o s i t i v e r e l a t i o n s h i p s , although average f a m i l y incomes have a higher c o r r e l a t i o n with high tech i n Canada than does area socioeconomic s t a t u s , the A u s t r a l i a n 105 equivalent. The Canadian r e s u l t s a l s o show lower c o r r e l a t i o n s f o r the percentage of labour f o r c e w i t h a u n i v e r s i t y degree and f o r I n d u s t r i a l R & D employees. The d i f f e r e n c e s can probably be accounted f o r more by d i f f e r e n c e s i n the data and methodology than by d i f f e r e n c e s between the two c o u n t r i e s . Newton and O'Connor a l s o performed a stepwise m u l t i p l e r e g r e s s i o n a n a l y s i s and found r e s u l t s that were i n some ways comparable to the r e s u l t s of t h i s t h e s i s . The f a c t o r s , step of entry i n t o the m u l t i p l e r e g r e s s i o n equation, and r e s u l t i n g m u l t i p l e R f o r both s t u d i e s are shown i n t a b l e 19. The number of research establishments (shown i n the A u s t r a l i a n r e s u l t s ) might be m i l d l y p a r a l l e l to the percentage of labour f o r c e engaged i n n a t u r a l s c i e n c e s , engineering and mathematical occupations (shown i n the Canadian r e s u l t s ) , s i n c e the A u s t r a l i a n research establishments probably employ a high p r o p o r t i o n of n a t u r a l s c i e n c e s , engineering and mathematics employees. Both show the importance of h i g h l y educated and experienced labour f o r the l o c a t i o n of high tech. TABLE 18 COMPARISON OF CORRELATION VALUES FOR AUSTRALIA AND CANADA Factor C o r r e l a t i o n A u s t r a l i a Research Establishments Area Socioeconomic Status Dwelling P r i c e s Academic Q u a l i f i c a t i o n s .58 .55 .55 .52 Canada I n d u s t r i a l R&D Employees Average Family Incomes Average Dwelling P r i c e s Percent with U n i v e r s i t y Degree .34 .69 .57 .40 106 TABLE 19 MULTIPLE REGRESSION RESULTS AUSTRALIA CANADA COMPARISON Factor Step of entry i n t o equation R e s u l t i n g M u l t i p l e R A u s t r a l i a Number of Research Establishments Dwelling P r i c e s Value of O f f i c e and Factory 1 2 3 .58 .67 .71 I n f r a s t r u c t u r e Canada Percentage S c i . Eng. and Math employees Average Dwelling P r i c e s 1 2 .71 .82 I t i s very i n t e r e s t i n g to note that d w e l l i n g p r i c e s entered i n t o the r e g r e s s i o n on the second step i n both the A u s t r a l i a n and the Canadian a n a l y s i s . In both equations d w e l l i n g p r i c e s c o n t r i b u t e to approximately the same increase i n m u l t i p l e R, a 0.09 increase i n the A u s t r a l i a n r e s u l t s and a 0.11 increase i n the Canadian r e s u l t s . As s t a t e d e a r l i e r , the importance of d w e l l i n g p r i c e s i n both Canada and A u s t r a l i a suggest that high tech l o c a t e s i n areas that are i n high demand, e i t h e r due to economic p r o s p e r i t y or r e s i d e n t i a l amenity or both. The casual r e l a t i o n s h i p may, however, be the reverse of that i m p l i e d by the r e g r e s s i o n equation. The r e s u l t s suggest that the presence of high tech i n d u s t r i e s and employment might b i d up the p r i c e of housing i n an area. 107 5.5 Relevance of Results to Planners 5.5.1 Ho Prime Locat iona l Determinant The r e s u l t s of the regress ion ana lys i s show that there i s no s i n g l e secret formula or l o c a t i o n a l a t t r i b u t e that w i l l a t t r a c t or develop high tech i n an area. There seems to be nothing that w i l l work q u i c k l y to br ing high tech to an area . The r e s u l t s of the regress ion ana lys i s combined with the l i t e r a t u r e review r e i n f o r c e the idea that i t takes time to develop high tech i n d u s t r i e s i n an area . Perhaps planners involved i n economic development and a t t r a c t i n g high tech should adopt a long range approach. This type of approach would work toward developing the various i n f r a s t r u c t u r e components that , over the long term might increase the p o s s i b i l i t y of generating and a t t r a c t i n g high tech i n d u s t r y . The i n f r a s t r u c t u r e components might inc lude high q u a l i t y u n i v e r s i t y f a c i l i t i e s , exce l l ent r e s i d e n t i a l areas, and large well-connected a i r p o r t f a c i l i t i e s . Planners might fos ter the development of a community environment which re ta ins and a t t r a c t s h ighly s k i l l e d and educated members of the work force . 5.5.2 Economic Development The importance of general economic v i t a l i t y to the l o c a t i o n of high tech seems h i g h l i g h t e d by the r e l a t i v e l y strong r e l a t i o n s h i p between high tech and fac tors that can be seen as i n d i c a t o r s of economic p r o s p e r i t y . These fac tors are a l l i n t e r r e l a t e d and inc lude dwel l ing p r i c e s , average income, number of telephones per c a p i t a , and a i r l i n e f l i g h t s . As these i n d i c a t o r s increase the percentage of labour force engaged i n high tech has a tendency to increase . 108 I f i t i s a community's d e s i r e to a t t r a c t and develop high tech then perhaps i t i s appropriate to pursue a s t r a t e g y of o v e r a l l economic development. Planners have a r o l e to play i n the fo r m u l a t i o n of community economic development s t r a t e g i e s , both i n preparing s t r a t e g i e s and i n shaping the economic components of o f f i c i a l community plans. They can a l s o i n f l u e n c e zoning r e g u l a t i o n s and the a v a i l a b i l i t y of developable land, which may have an impact on economic development. The development and a t t r a c t i o n of high technology i n d u s t r i e s could form part of comprehensive economic development s t r a t e g i e s . The r e s u l t s of t h i s t h e s i s a l s o suggest that high technology i n d u s t r y helps generate economic v i t a l i t y . I f t h i s i s the case, perhaps an i t e r a t i v e approach to economic development might be suggested. In such an approach an i n i t i a l s t r a t e g y would be formulated to s t a r t economic development based on the area's e x i s t i n g s t r e n g t h s , i n other words, to p i c k the low-hanging f r u i t . Once an i n i t i a l l e v e l of development i s a t t a i n e d another i t e r a t i o n of the s t r a t e g y would s t r i v e toward some more d i f f i c u l t to reach i n d u s t r i e s , perhaps some high tech i n d u s t r i e s . Further i t e r a t i o n s might f u r t h e r extend the scope of the s t r a t e g y , p o t e n t i a l l y drawing i n more high tech i n d u s t r i e s and generating increased economic v i t a l i t y u n t i l a l e v e l of economic development de s i r e d i n the community i s reached. 5.5.3 Housing This t h e s i s , as w e l l as the A u s t r a l i a n study by Newton and O'Connor (1985) and the U.S. study by Glasmeier, H a l l and Markusen (1983), found that d w e l l i n g p r i c e s have a r e l a t i v e l y strong r e l a t i o n s h i p w i t h the l o c a t i o n of high tech. I t may be that high tech i s a t t r a c t e d to areas of economic growth 109 and r e s i d e n t i a l amenity where housing p r i c e s are higher, or that the presence of high tech bids up the p r i c e of housing. I t i s h i g h l y probable that both of the above i n f l u e n c e s are at work. I f high tech i s a t t r a c t e d to areas of economic growth, a community can pursue an economic development s t r a t e g y as mentioned i n the previous s e c t i o n . If r e s i d e n t i a l amenity i s important to high tech, then planners can work to improve the q u a l i t y of r e s i d e n t i a l areas. Numerous t o o l s are a v a i l a b l e to planners to i n f l u e n c e the l i v e a b i l i t y of a r e s i d e n t i a l area, i n c l u d i n g zoning r e g u l a t i o n s , o f f i c i a l community plans, development permit g u i d e l i n e s , park land a c q u i s i t i o n requirements, and s u b d i v i s i o n and development c o n t r o l r e g u l a t i o n s . Planners might consider the r e s u l t s of t h i s t h e s i s and i n c l u d e the enhancement of r e s i d e n t i a l l i v e a b i l i t y as part of t h e i r s t r a t e g y to develop high tech i n d u s t r y i n t h e i r community. I f i t i s true that high tech i n d u s t r i e s lead to an increase i n housing p r i c e s due to increased demand, then planners might work to avoid t h i s consequence by p r o v i d i n g developable r e s i d e n t i a l areas, or by encouraging the development of new housing. An increase i n supply should help prevent i n c r e a s i n g housing c o s t s . On the other hand, high d w e l l i n g values might a l s o be seen as d e s i r a b l e and could be used as an argument by planners f o r the development and a t t r a c t i o n of high tech i n d u s t r i e s . High d w e l l i n g values r e s u l t i n an increased municipal tax base and greater p o t e n t i a l f o r municipal revenue generation. E x i s t i n g property owners might a l s o enjoy seeing the r e a l value of t h e i r property i n c r e a s e . 110 5.5.4 Education and Labour Force The r e s u l t s of t h i s t h e s i s suggest that an educated and s k i l l e d labour f o r c e , and a source of that labour force such as a u n i v e r s i t y , are important f o r the development of high technology a c t i v i t i e s . I f i t i s the d e s i r e of a community to pursue high technology i n d u s t r i e s , then planners can work at ensuring that s k i l l e d members of the work f o r c e , p a r t i c u l a r l y those i n sci e n c e s , engineering and mathematics occupation, move to and stay i n the area. This could be done by encouraging u n i v e r s i t y and c o l l e g e graduates to stay and s t a r t businesses w i t h i n the area, perhaps by p r o v i d i n g lower cost i n d u s t r i a l and business land, p r o v i d i n g f o r developments i n c l o s e a s s o c i a t i o n w i t h research and education f a c i l i t i e s , or j u s t by making the development process l e s s b u r e a u c r a t i c . Planners could a l s o encourage i n d u s t r i e s to l o c a t e i n t h e i r community which have a higher p r o p o r t i o n of educated and s k i l l e d workers. This could be done by e s t a b l i s h i n g c r i t e r i a f o r development, or by a l l o w i n g s p e c i f i c land uses w i t h i n a high tech zone. 5.5.5 A i r T r a n s p o r t a t i o n The importance of a i r p o r t s to high tech i s suggested i n t h i s t h e s i s and i n the U.S. Study by Glasmeier H a l l and Markusen (1983). I f a i r p o r t s are an important l o c a t i o n a l c o n s i d e r a t i o n , communities that wish to pursue high tech should perhaps f a c i l i t a t e l inkages between the a i r p o r t and high tech a c t i v i t i e s . Planners i n conjunction w i t h m u n i c i p a l i t i e s could do t h i s by e s t a b l i s h i n g i n d u s t r i a l parks near a i r p o r t s . They could a l s o designate land i n the O f f i c i a l Community Plan f o r fu t u r e high tech and a i r p o r t - r e l a t e d uses i n areas with good linkages to the a i r p o r t . This could be f u r t h e r supported 111 by establishing a zone for high tech and airport-related commercial and light industrial uses. Guidelines could also be set out to ensure that a specific standard of development is achieved within the high tech zone. Emphasis could also be placed on expansion and development of airports, planners working within airport administration could point to the potential benefits for high tech industry in support of an argument for airport expansion. High tech f a c i l i t i e s such as aircraft testing, research f a c i l i t i e s , and manufacturers of products which need to be shipped quickly by air could become integral parts of the airport f a c i l i t y . 5.5.6 Non-limiting Factors This thesis provides important information to planners by showing that certain factors are not that important to the location of high tech. If a community is lacking with respect to an insignificant factor, planners might be able to disregard the factor and concentrate on other more important variables. For Canada the non-limiting or insignificant factors are climate, cost of living index, electricity rates, union membership, and air quality. Unless a community has extremely adverse conditions with respect to these non-limiting factors, then planners, limited though they may be in controlling the factors, need not attempt to alter these factors in order to develop or attract high tech. 5.5.7 Policy Analysis A comparison of the results of this thesis with the results of the work done by other researchers in Australia and the United States finds some similarities. This suggests that successful policies in the U.S. and 112 A u s t r a l i a might be t r a n s f e r a b l e to Canada, and s u c c e s s f u l Canadian p o l i c i e s could be t r a n s p l a n t e d to the U.S. and A u s t r a l i a . A program f o r i d e n t i f y i n g , monitoring, and e v a l u a t i n g p o l i c i e s and s t r a t e g i e s that attempt to i n f l u e n c e the development and l o c a t i o n of high tech could be e s t a b l i s h e d by planners i n a l l three c o u n t r i e s . S t r a t e g i e s that work wel l i n one area could be adapted and implemented i n another area. The i d e n t i f i c a t i o n of s u c c e s s f u l s t r a t e g i e s could allow communities to focus t h e i r energy i n d i r e c t i o n s which are more l i k e l y to produce p o s i t i v e r e s u l t s . 113 CHAPTER VI CONCLUSION 6.1. Study Conclusions This t h e s i s f i n d s that there are few important f a c t o r s that i n f l u e n c e the l o c a t i o n of high tech. Table 20 o u t l i n e s the r e s u l t s of the r e g r e s s i o n a n a l y s i s conducted between the percentage of t o t a l labour force employed i n high tech i n d u s t r i e s and various l o c a t i o n f a c t o r s across 24 Canadian Census M e t r o p o l i t a n Areas (CMAs). G e n e r a l l y , the important f a c t o r s are as f o l l o w s : a s k i l l e d labour f o r c e w i t h a high p r o p o r t i o n of n a t u r a l sciences, engineering and mathematics employees; a high degree of economic v i t a l i t y as i n d i c a t e d by income, telephones per c a p i t a and d w e l l i n g p r i c e s ; a high l e v e l of r e s i d e n t i a l amenity and demand as i n d i c a t e d by housing p r i c e s ; an a i r p o r t w i t h a high annual t r a f f i c volume; and a large u n i v e r s i t y presence. Those f a c t o r s were s t a t i s t i c a l l y s i g n i f i c a n t and disprove the n u l l hypothesis that no l o c a t i o n a l f a c t o r s examined w i l l have a s t a t i s t i c a l l y s i g n i f i c a n t r e l a t i o n s h i p w i t h the l o c a t i o n of high technology a c t i v i t i e s . Several of the s i g n i f i c a n t r e l a t i o n s h i p s had the expected slope s i g n . The most notable d i f f e r e n c e s were average family incomes and average d w e l l i n g p r i c e which were expected to have negative r e l a t i o n s h i p s because they represented high labour costs and housing c o s t s , which were thought to be a deterrent to high tech. I t seems, however, that higher incomes and housing p r i c e s are a s s o c i a t e d w i t h places that have r e l a t i v e l y high economic p r o s p e r i t y , which might be a t t r a c t i v e to high tech, or might be the r e s u l t of high tech l o c a t i n g w i t h i n an area. 114 TABLE 20 RESULTS OF BIVARIATE REGRESSION ANALYSIS BETWEEN HIGH TECH AND LOCATION FACTORS Sign of Expected Sign R e s u l t i n g Slope ( B i ) of of Slope ( B i ) Factor R2 Explanatory Explanatory Equation Equation % Natural Science engineering 0.51 + + and Mathematics occupation Telephones per 100 persons 0.51 + + Average Family Income 0.48 + -Average Dwelling P r i c e 0.33 + -A i r l i n e F l i g h t s 0.33 + + U n i v e r s i t y Enrollment against modified high tech 0.32 + + U n i v e r s i t y Enrolment without o u t l i e r s 0.24 + + % Labour Force w i t h Degree 0.16 + % Labour Force i n Industry R&D 0.08 + + % Labour Force w i t h Union Membership 0.06 - -Consumer P r i c e Index 0.008 + -E l e c t r i c i t y r a t e s 0.007 + -Hours Sunshine/heating Degree Days 0.005 + + A i r q u a l i t y Index 0.004 - + Natural Sciences Expenditures 0.002 - + % Federal Gov't Employment 0.002 — + Other f a c t o r s w i t h slope signs opposite to the expected s i g n each had a very low R2 and were i n s i g n i f i c a n t . The s i g n of the slope i s : not a s i g n i f i c a n t i n d i c a t o r and t h e r e f o r e any p o s s i b l e reasons f o r the c o n f l i c t i n g signs are not discussed. While some f a c t o r s showed as being s i g n i f i c a n t , none seem to be of s u b s t a n t i a l importance. One s i g n i f i c a n t f i n d i n g of t h i s t h e s i s , then, may be that no f a c t o r s can be s a i d to be t r u l y important f o r the l o c a t i o n of high tech. I t may be that high technology i n d u s t r i e s , when viewed as a whole, are 115 rather f o o t l o o s e and can l o c a t e i n a broad range of places w i t h varying c h a r a c t e r i s t i c s . 6.2 S i m i l a r i t i e s w i t h Other Studies I t i s a l s o s i g n i f i c a n t that there were numerous s i m i l a r i t i e s and only a few d i f f e r e n c e s found between the r e s u l t s of t h i s t h e s i s and the r e s u l t s of other s t u d i e s . The f i n d i n g s of t h i s t h e s i s were g e n e r a l l y s i m i l a r to the f i n d i n g s of an A u s t r a l i a n study by Newton and O'Connor (1985). Both s t u d i e s had s i m i l a r l e v e l s of p o s i t i v e c o r r e l a t i o n between high tech l o c a t i o n and i n d i c a t o r s of income, d w e l l i n g p r i c e , education l e v e l , and research and development employment. In a m u l t i p l e r e g r e s s i o n a n a l y s i s , however, t h i s t h e s i s showed 'percentage of n a t u r a l s c i e n c e s , engineering and mathematics employees' to be the f i r s t entry i n t o the equation, while the A u s t r a l i a n a n a l y s i s showed 'number of research establishments' as the f i r s t entry. The a n a l y s i s i n t h i s t h e s i s had a v a r i a b l e s i m i l a r to Newton's 'number of research establishments' v a r i a b l e , but i t had a f a r weaker r e l a t i o n s h i p w i t h high tech. This i s probably due to the large amounts of non-high tech employment i n Canadian Research and Development (R & D) establishments. Many Canadian R & D establishments work to generate products f o r i n d u s t r i e s that were not in c l u d e d i n the l i s t of high tech i n d u s t r i e s i d e n t i f i e d i n t h i s t h e s i s . On the other hand, the m u l t i p l e r e g r e s s i o n a n a l y s i s f o r both s t u d i e s were very s i m i l a r i n that both had d w e l l i n g p r i c e s enter the reg r e s s i o n i n the second step and d w e l l i n g p r i c e s explained s i m i l a r amounts of v a r i a t i o n i n the l o c a t i o n of high tech. 116 This t h e s i s found that housing p r i c e s , u n i v e r s i t y presence, and a i r p o r t s were r e l a t i v e l y s t r o n g l y r e l a t e d to the presence of high tech employment, as was s i m i l a r l y found i n a U.S. study by Glasmeier, H a l l and Markusen (1983). Both the U.S. study and t h i s t h e s i s a l s o found that u t i l i t y r a tes and c l i m a t e were unimportant f a c t o r s . D i f f e r e n c e s were found i n that p o l l u t i o n was a s i g n i f i c a n t v a r i a b l e i n the U.S., but not i n Canada. With Canadian c i t i e s having r e l a t i v e l y low l e v e l s of p o l l u t i o n , t h i s f a c t o r i s probably l e s s important i n Canada than i t i s i n the U.S. Perhaps the most important s i m i l a r i t y between t h i s t h e s i s and the U.S. study was that both found no f a c t o r s to be of compelling importance. Even the most s i g n i f i c a n t f a c t o r s have, at best, only a moderately good r e l a t i o n s h i p with the l o c a t i o n of high tech. This i n d i c a t e s that considerable evidence e x i s t s to support the suggestion that high tech i s r e l a t i v e l y f o o t l o o s e . 6.3 L i m i t a t i o n s of Methodology Furthermore, one should be s u s p i c i o u s of the f a c t o r s f o r which s i g n i f i c a n t r e s u l t s were found. The percentage of labour force employed i n n a t u r a l s c i e n c e s , engineering and mathematics bears a c i r c u l a r r e l a t i o n s h i p w i t h the d e f i n i t i o n of high tech. Several other f a c t o r s - d w e l l i n g p r i c e s , average f a m i l y income, telephones per 100 persons, and a i r l i n e f l i g h t s - may have a causal r e l a t i o n s h i p w i t h high tech l o c a t i o n that i s the reverse from the one i m p l i e d i n the re g r e s s i o n a n a l y s i s . In e f f e c t i t may be that the presence of high tech i n f l u e n c e s these f a c t o r s and not that the presence of these f a c t o r s i n f l u e n c e the l o c a t i o n of high tech. The mutual interdependence between the dependent and independent v a r i a b l e s l i m i t s the usefulness of re g r e s s i o n a n a l y s i s i n determining which 117 f a c t o r s i n f l u e n c e the l o c a t i o n of high tech i n d u s t r i e s . This could be seen as a s i g n i f i c a n t f i n d i n g of t h i s t h e s i s : that r e g r e s s i o n a n a l y s i s i s perhaps not the best way to analyze l o c a t i o n a l determinants. Regression a n a l y s i s should be used only a f t e r the dependent and independent v a r i a b l e s have been c a r e f u l l y examined f o r interdependence. The very nature of l o c a t i o n a l f a c t o r s increases the p o t e n t i a l f o r interdependence and decreases the a p p l i c a b i l i t y of r e g r e s s i o n a n a l y s i s . Another l i m i t a t i o n to the methodology i s the importance of the d e f i n i t i o n of high tech to the r e s u l t s . I t i s probable that the r e s u l t s of t h i s t h e s i s would vary s u b s t a n t i a l l y i f d i f f e r e n t d e f i n i t i o n s of high technology were used. Problems e x i s t e d with the d e f i n i t i o n used, p r i m a r i l y because of the aggregation of data. Employment i n s p e c i f i c i n d u s t r i e s was grouped by product, and i t was not p o s s i b l e to disaggregate employment to research and development, manufacturing, marketing and d i s t r i b u t i o n components when co n s i d e r i n g one i n d u s t r y . Disaggregated data would have been u s e f u l i n a n a l y z i n g the l o c a t i o n a l c h a r a c t e r i s t i c s of, f o r example, the research and development component of high tech. 6 . 4 A l t e r n a t i v e Approaches to t h i s Study In view of the l i m i t a t i o n s of the methodology used i n t h i s study, a l t e r n a t i v e methods can be suggested f o r determining the l o c a t i o n a l f a c t o r s that are important to high technology i n d u s t r i e s . In chapter three b r i e f c o n s i d e r a t i o n i s given to conducting a survey of high tech i n d u s t r i e s , but t h i s method i s dismissed as being too expensive and time-consuming. In r e t r o s p e c t , the expense and amount of time needed to conduct a survey may be j u s t i f i e d i f meaningful r e s u l t s could be obtained. 118 Rather than having to i n f e r the importance of various l o c a t i o n a l f a c t o r s through r e g r e s s i o n a n a l y s i s , l o c a t i o n a l decision-makers could be asked d i r e c t l y what a t t r i b u t e s they consider important i n an area. This method does meet problems when respondents can not what f a c t o r s were important, or they give answers that they perceive to be the ones the researchers are l o o k i n g f o r . Surveys a l s o s u f f e r from the s t r u c t u r e d approach they must f o l l o w i n order to f a c i l i t a t e s t a t i s t i c a l a n a l y s i s of the r e s u l t s . Often surveys do not allow the time or space f o r respondents to elaborate on the d e t a i l of circumstances surrounding l o c a t i o n a l d e c i s i o n s . A d d i t i o n a l d e t a i l and understanding could be obtained by conducting personal i n t e r v i e w s w i t h a l i m i t e d number of high tech f i r m s , i n conjunction with a wider ranging survey. The i n t e r v i e w could probe respondents to go i n t o more d e t a i l , and i f s p e c i f i c circumstances surround a p a r t i c u l a r l o c a t i o n a l d e c i s i o n , a f u l l d e s c r i p t i o n of the process could be obtained. Further improvement i n method could be achieved i f the study concentrated on a s p e c i f i c subsector or s e l e c t e d a c t i v i t y w i t h i n high tech. D i f f e r e n t types of high tech probably have d i f f e r e n t l o c a t i o n a l requirements. A study of an aggregation of every high tech i n d u s t r y leads to g e n e r a l i z e d r e s u l t s that would not address l o c a t i o n a l requirements that may be e x c l u s i v e to a s p e c i f i c high tech i n d u s t r y . By concentrating on one a c t i v i t y w i t h i n high tech, the s p e c i a l l o c a t i o n a l f a c t o r s f o r that a c t i v i t y might be uncovered. This could provide i n f o r m a t i o n very u s e f u l to those i n t e r e s t e d or i n v o l v e d i n the subject a c t i v i t y . A survey r e i n f o r c e d w i t h i n t e r v i e w s and concentrating on one high tech sub-sector would l i k e l y provide more concrete and u s e f u l r e s u l t s than the g e n e r a l i z e d r e s u l t s found i n t h i s t h e s i s . 119 6.5 Suggestions f o r Further Study Several avenues of f u r t h e r study can be taken from the point where t h i s t h e s i s concludes. Using the data c o l l e c t e d f o r t h i s t h e s i s , r e g r e s s i o n analyses could be conducted on an i n d u s t r y by i n d u s t r y b a s i s , separately using a l l the i n d i v i d u a l i n d u s t r i a l components that make up high tech. The re g r e s s i o n could be conducted against the same l o c a t i o n a l f a c t o r s examined i n t h i s t h e s i s . A f a c t o r a n a l y s i s could a l s o be conducted using the data c o l l e c t e d f o r t h i s t h e s i s to f u r t h e r explore the r e l a t i o n s h i p between the l o c a t i o n of high tech and the various l o c a t i o n f a c t o r s . One suggestion f o r f u r t h e r study could use some of the data presented i n t h i s t h e s i s i n combination w i t h new data. The study could examine the changes i n high tech l o c a t i o n and l o c a t i o n a l f a c t o r i n t e n s i t y from 1981 to 1986. A r e g r e s s i o n a n a l y s i s could be run to see i f changes i n c e r t a i n l o c a t i o n f a c t o r s from 1981 to 1986 are r e l a t e d to changes i n the l o c a t i o n of high tech from 1981 to 1986. The data used i n t h i s type of study would a l s o h i g h l i g h t which c i t i e s are gai n i n g i n t h e i r p r o p o r t i o n of labour f o r c e engaged i n high tech and which c i t i e s are l o o s i n g high tech. A n a t u r a l progression of t h i s a n a l y s i s would be to conduct a s h i f t - s h a r e a n a l y s i s of high tech i n the 24 Canadian CMAs. Perhaps one of the more f r u i t f u l avenues of research i n t o high tech l o c a t i o n a l decision-making would be to conduct case s t u d i e s of sev e r a l expanding high technology f i r m s . I t may be p o s s i b l e to d i r e c t l y observe the d e c i s i o n making process as i t happens and to i d e n t i f y the key f a c t o r s which are considered i n making l o c a t i o n a l d e c i s i o n s . Further research could a l s o be conducted to examine the p o l i c i e s that s p e c i f i c a l l y attempt to generate or a t t r a c t high tech i n d u s t r i e s . The success 120 of each p o l i c y could be analyzed and the more s u c c e s s f u l p o l i c i e s and s t r a t e g i e s could be i d e n t i f i e d as p o t e n t i a l models to be followed elsewhere. The research p o s s i b i l i t i e s of high tech seem boundless, and indeed research w i l l probably need to be done on a continuous basis because the very nature of high t e c h continuously changes as new d i s c o v e r i e s and advanced technologies come to l i g h t . 121 APPENDIX I CHARACTERIZATION OF HIGH TECH IN EACH CMA St. John's St. John's Newfoundland has most of i t s high tech work forc e concentrated i n engineering and s c i e n t i f i c s e r v i c e s , and e l e c t r i c power. Together these two SIC cate g o r i e s comprise 64.4% of St. John's high tech work for c e . St. John's i s ranked 9th out of 24 CMAs i n terms of high tech emphasis, w i t h high tech emphasis being based on the percentage of t o t a l labour f o r c e employed i n high tech i n d u s t r i e s . H a l i f a x The l a r g e s t number of high tech workers i n H a l i f a x are employed i n engineering and s c i e n t i f i c s e r v i c e s w i t h 23.4%, and e l e c t r i c power with 20.2%. H a l i f a x ranks 13th i n high tech dependence when compared with other CMAs i n Canada. Saint John Saint John, New Brunswick has i t s high tech emphasis i n e l e c t r i c power and petroleum r e f i n e r i e s . High tech workers are q u i t e concentrated with f u l l y 76.0% i n these two s e c t o r s , g i v i n g Saint John a 10th place ranking i n high tech emphasis amongst other Canadian CMAs. Chicoutimi-Jonquiere With a low emphasis on high tech, Chicoutimi-Jonquiere ranks 21st i n terms of the percentage of work forc e employed i n high tech. 71.3% of t h i s 122 high tech work f o r c e i s concentrated i n engineering and s c i e n t i f i c s e r v i c e s , and e l e c t r i c power. Montreal Montreal has s i g n i f i c a n t employed i n a wide range of high tech i n d u s t r i e s and ranks 5th i n Canada with respect to high tech emphasis. The l a r g e s t p r o p o r t i o n of high tech workers i s employed i n a i r c r a f t and a i r c r a f t parts manufacturers, w i t h 21.9% of the high tech work f o r c e . Engineering and s c i e n t i f i c s e r v i c e s comprise 19.7% of the high tech work f o r c e , w i t h communications equipment manufacturers and e l e c t r i c power a l s o p l a y i n g large r o l e s . Ottawa-Hull The Ottawa-Hull Census M e t r o p o l i t a n Area ranks 8th i n high tech emphasis with 4.3% of i t s work forc e engaged i n high tech. Communications equipment manufacturers employ 30.5% of the Ottawa-Hull area's high tech work f o r c e , and engineering and s c i e n t i f i c s e r v i c e s employ 27.5%. While 58.0% of high tech employees are concentrated i n two SICs, s i g n i f i c a n t numbers of workers are employed i n other high tech i n d u s t r i e s such as computer s e r v i c e s , management and business c o n s u l t i n g , and o f f i c e and s t o r e machinery manufacturing. Quebec Quebec C i t y has a r e l a t i v e l y low emphasis on high tech employment, w i t h only 2.4% of i t s labour f o r c e i n high tech i n d u s t r i e s , g i v i n g i t a rank of 123 20th i n comparison with other Canadian CMAs. Most of Quebec C i t y ' s high tech workers are concentrated i n engineering and s c i e n t i f i c s e r v i c e s (35.2%) and e l e c t r i c power (24.9%). T r o i s - R i v i e r e s T r o i s - R i v i e r e s ' s i n g l e major high tech i n d u s t r y i s e l e c t r i c power, employing 59.6% of the high tech work f o r c e . A l l other high tech i n d u s t r i e s i n T r o i s R i v i e r e s employ r e l a t i v e l y low numbers of workers. Because of t h i s low employment i n other high tech s e c t o r s , T r o i s R i v i e r e s ranks 19th i n high tech emphasis when compared w i t h other Canadian CMAs. Hamilton Hamilton ranks 15th i n Canada i n terms of high tech emphasis. The l a r g e s t high tech i n d u s t r y i s e l e c t r i c a l i n d u s t r i a l equipment manufacturers employing 2,170 workers or 21.8% of the high tech work f o r c e . Engineering and s c i e n t i f i c s e r v i c e s are a l s o important, employing 19.0 percent. Other important high tech i n d u s t r i e s are communication equipment manufacturers and e l e c t r i c power. Kitchener Kitchener ranks q u i t e h i g h l y i n high tech emphasis, p l a c i n g 6th amongst other Canadian CMAs. A large p o r t i o n of Kitchener's high tech workers are concentrated i n three i n d u s t r i e s , communication equipment manufacturers w i t h 19.9%, e l e c t r i c a l i n d u s t r i a l equipment manufacturers w i t h 19.3%, and o f f i c e and s t o r e machinery manufacturers w i t h 18.3% of t o t a l high tech employment. 124 London London, Ontario ranks 16th i n high tech emphasis. Communication equipment manufacturing i s by f a r the l a r g e s t i n d u s t r y , employing 38.4% of high tech workers, w i t h e l e c t r i c a l i n d u s t r i a l equipment manufacturing as the second l a r g e s t , employing 15.7 percent. Oshawa With 4.5% of i t s work f o r c e employed i n high tech i n d u s t r i e s , Oshawa ranks 7th i n terms of high tech emphasis. Most of Oshawa's high tech employment i s concentrated i n e l e c t r i c power (36.2%) and communication equipment manufacturers (23.8%), w i t h r e l a t i v e l y l i t t l e employment i n other high tech s e c t o r s . St. Catherines-Niagara The St. Catherines-Niagara area ranks 11th i n percentage of labour force employed i n high tech i n d u s t r i e s when compared with the r e s t of Canada. 32.2% of t h i s area's t o t a l high tech labour force are employed i n engineering and s c i e n t i f i c s e r v i c e s and 20.6% are employed i n i n d u s t r i a l chemical manufacturing. Sudbury Sudbury receives a low ranking i n terms of high tech emphasis, w i t h a rank of 22nd out of 24 CMAs. Of i t s 1380 high tech employees 350 (25.7%) are engaged e l e c t r i c power and 23.5% are engaged i n miscellaneous s e r v i c e s i n c i d e n t a l to mining. The concentration i n the l a t t e r i n d u s t r y i s probably due to extensive mining a c t i v i t i e s that occur i n Sudbury. 125 Thunder Bay Thunder Bay ranks 18th i n high tech emphasis i n Canada. I t s high tech employees are concentrated i n engineering and s c i e n t i f i c s e r v i c e s , w i t h 22.4%, and e l e c t r i c power, with 40.6%. A l l other high tech s e c t o r s have r e l a t i v e l y low employment. Toronto Toronto has a broad base of high tech employment, with s i g n i f i c a n t numbers of workers i n every high tech i n d u s t r y . Because of the large numbers of workers i n v o l v e d i n a wide cross s e c t i o n of high tech a c t i v i t i e s , Toronto i s ranked t h i r d i n terms of high tech emphasis, with 6.1% of i t s t o t a l labour for c e engaged i n high tech i n d u s t r i e s . Toronto's l a r g e s t high tech s e c t o r i s engineering and s c i e n t i f i c s e r v i c e s w i t h 16.7% of high tech employment. This i s f o l l owed by e l e c t r i c power w i t h 14.4% and communication equipment manufacturers with 12.8%. Two other important s e c t o r s are computer s e r v i c e s , and a i r c r a f t and a i r c r a f t p a r t s manufacturing. Windsor Windsor has the lowest ranking of a l l CMAs i n Canada w i t h regard to emphasis of employment i n high tech i n d u s t r i e s . Only 1.6% of the labour f o r c e i s employed i n high tech i n d u s t r i e s . The l a r g e s t p o r t i o n of that high tech employment i s i n engineering and s c i e n t i f i c s e r v i c e s (33.3%) and e l e c t r i c power (22.8%). 126 Winnipeg Winnipeg i s rated 14th i n Canada with regards to high tech emphasis. Winnipeg has employment i n a wide range of high tech i n d u s t r i e s , w i t h primary emphasis i n two areas, e l e c t r i c power with 25.1%, and a i r c r a f t and a i r c r a f t p a r t s manufacturing wit h 25.0% of t o t a l employment i n high tech i n d u s t r i e s . Regina With 3.5% of i t s work f o r c e employed i n high tech i n d u s t r i e s , Regina i s ranked 14th i n high tech emphasis out of 24 CMAs. The primary emphasis of high tech employment i s i n e l e c t r i c power (31.6%) and engineering and s c i e n t i f i c s e r v i c e s (20.2%). Saskatoon Saskatoon i s ranked 17th i n high tech emphasis. The l a r g e s t p o r t i o n of high tech employment i s concentrated i n engineering and s c i e n t i f i c s e r v i c e s w i t h 43.6 percent of high tech employment. The r e s t of Saskatoon's high tech employees are s p a r s e l y d i s t r i b u t e d amongst a wide range of high tech i n d u s t r i e s . Calgary Calgary i s the Canadian CMA that has the greatest emphasis on high tech employment, with 13.6% of i t s t o t a l labour force working i n high tech i n d u s t r i e s . This i s l a r g e l y due to the e x t r a o r d i n a r i l y l a rge number of people working i n the crude petroleum and n a t u r a l gas i n d u s t r y . This i n d u s t r y employs 24,715 people which i s 52.3% of the t o t a l high tech labour f o r c e i n Calgary. Another large high tech i n d u s t r y i s engineering and s c i e n t i f i c 127 s e r v i c e s , which employs 23.7% of the high tech labour f o r c e . Calgary a l s o has high l e v e l s of employment i n s e v e r a l other high tech i n d u s t r i e s such as computer s e r v i c e s and miscellaneous s e r v i c e s i n c i d e n t a l to mining. Edmonton Edmonton has the f o u r t h highest emphasis on high tech employment i n Canada, i n comparison with the 23 other CMAs. The l a r g e s t p o r t i o n i s employed i n engineering and s c i e n t i f i c s e r v i c e s with 27.5% of a l l high tech employment. As with Calgary, Edmonton has a high p r o p o r t i o n of workers i n v o l v e d i n the crude petroleum of workers i n v o l v e d i n the crude petroleum and n a t u r a l gas i n d u s t r y . This i n d u s t r y comprises 15.7% of Edmonton's t o t a l high tech work for c e . Edmonton a l s o has a l a r g e number of workers i n i n d u s t r i a l chemical manufacturing and miscellaneous s e r v i c e s i n c i d e n t a l to mining. Vancouver Vancouver has the second highest emphasis on employment i n high technology i n d u s t r i e s i n Canada. Vancouver has strong l e v e l s of employment i n almost a l l high tech i n d u s t r i e s . The primary c o n t r i b u t i o n to high tech employment i s engineering and s c i e n t i f i c s e r v i c e s w i t h 20,505 employees or 36.2% of Vancouver's high tech work f o r c e . The number of people employed i n Vancouver's engineering and s c i e n t i f i c s e r v i c e s i n d u s t r y i s higher than the number employed i n Montreal or Toronto, even though both have more than double the t o t a l labour f o r c e that Vancouver has. Vancouver a l s o has a strong emphasis on e l e c t r i c power (18.1%), w i t h o f f i c e s of management and business c o n s u l t a n t s , and computer s e r v i c e s a l s o showing high l e v e l s of employment. 128 V i c t o r i a V i c t o r i a has the second lowest emphasis on high tech i n d u s t r y i n Canada, with only 1.7% of i t s labour f o r c e employed i n high tech i n d u s t r i e s . The l a r g e s t p o r t i o n of V i c t o r i a ' s high tech employment, 39.7 percent, are engaged i n the f o r e s t r y s e r v i c e i n d u s t r y . The second l a r g e s t p o r t i o n , 24.7 percent, are engaged i n engineering and s c i e n t i f i c s e r v i c e s . 129 APPENDIX I I DATA SOURCES AND THE INCIDENCE OF LOCATION FACTORS IN EACH CMA In t r o d u c t i o n The purpose of t h i s s e c t i o n i s to d e t a i l the data source f o r each l o c a t i o n a l f a c t o r and to show how the data f o r each l o c a t i o n a l f a c t o r was o p e r a t i o n a l i z e d f o r use i n a r e g r e s s i o n a n a l y s i s . This s e c t i o n a l s o discusses how the values f o r each l o c a t i o n f a c t o r vary across the 24 Census M e t r o p o l i t a n Areas i n Canada. This d i s c u s s i o n w i l l provide an understanding of the d i s t r i b u t i o n of various l o c a t i o n f a c t o r s and should allow f o r an informed i n t e r p r e t a t i o n of the r e g r e s s i o n a n a l y s i s r e s u l t s . U n i v e r s i t y Enrolment S t a t i s t i c s Canada (1983c) provides i n f o r m a t i o n on u n i v e r s i t y enrolment by province and i n s t i t u t i o n , but not by Census M e t r o p o l i t a n Area (CMA). In order to determine the u n i v e r s i t y presence, or s i z e of u n i v e r s i t y enrolment i n each CMA, the address of each u n i v e r s i t y had to be determined and i t s t o t a l enrolment a l l o c a t e d to the host CMA. The absolute s i z e of u n i v e r s i t y enrolment i s intended to provide a measure of the u n i v e r s i t y presence i n the CMA. I t i s assumed that a l a r g e r u n i v e r s i t y w i l l provide impetus f o r high technology development. This assumption may, however, not be t r u e . A u n i v e r s i t y ' s emphasis on f i e l d s such as engineering and science may have more bearing on i t s p o t e n t i a l as a progenitor of high tech than the gross s i z e of i t s enrolment. Data on 130 enrolment by degree by i n s t i t u t i o n were not r e a d i l y a v a i l a b l e though, so t o t a l enrolment s i z e was used. U n i v e r s i t y enrolment i s highest i n Montreal, w i t h 57,742 f u l l time students e n r o l l e d . Toronto i s a c l o s e second w i t h 57,142 students. The number of u n i v e r s i t y students i n both Montreal and Toronto i s s i g n i f i c a n t l y higher than any other CMA i n Canada. Vancouver places a f a r t h i r d w i t h only 26,017 students. Numerous CMAs f a l l i n t o the 15,000 to 22,000 student range i n c l u d i n g Ottawa-Hull, Quebec, Kitche n e r , London, Winnipeg and Edmonton. Oshawa and Saint John, New Brunswick, had no u n i v e r s i t y enrolment. This i s probably because F r e d e r i c t o n has a large p o r t i o n of the u n i v e r s i t y enrolment i n New Brunswick, and Oshawa i s very c l o s e to the large u n i v e r s i t i e s i n Toronto. Natural Sciences, Engineering and Mathematical Occupations Information on the number of persons employed i n n a t u r a l s c i e n c e s , engineering and mathematical occupations i n each CMA i s r e a d i l y a v a i l a b l e from S t a t i s t i c s Canada (1983b). The data are disaggregated by sex, so the male and female components were summed and d i v i d e d by the t o t a l labour f o r c e to gi v e the percentage of t o t a l labour f o r c e engaged i n n a t u r a l s c i e n c e s , engineering and mathematics occupations. The data were a v a i l a b l e f o r a l l Census M e t r o p o l i t a n areas. The i n t e n t of t h i s measure i s to represent a CMA's l e v e l of s k i l l e d employees i n d i s c i p l i n e s u s e f u l f o r high tech development. Calgary, Ottawa and Edmonton have the highest percentages of employees engaged i n n a t u r a l s c i e n c e s , engineering and mathematics occupations w i t h 7.5%, 6.1% and 4.7% r e s p e c t i v e l y . 131 V i c t o r i a , w i t h only 2.15%, T r o i s R i v i e r e s w i t h 2.22% and Windsor w i t h 2.28% have the lowest percentages employed i n the target occupations. On the whole there i s r e l a t i v e l y l i t t l e v a r i a t i o n i n the percentage of labour f o r c e employed i n n a t u r a l sciences engineering and mathematics occupations, w i t h most f a l l i n g w i t h i n 2% to 4% range. Labour Force w i t h U n i v e r s i t y Degree S t a t i s t i c s Canada (1983d) provides i n f o r m a t i o n on the number of persons with a u n i v e r s i t y degree i n each CMA. This f i g u r e was d i v i d e d by the t o t a l CMA labour f o r c e to give the percentage of t o t a l labour f o r c e w i t h a u n i v e r s i t y degree. The r e s u l t i n g f i g u r e gives an i n d i c a t i o n of the percentage of the labour f o r c e w i t h s k i l l s that may be u s e f u l i n high tech i n d u s t r i e s . These data s u f f e r from the l i m i t a t i o n of i n c l u d i n g persons with any type of u n i v e r s i t y degree, however, and could not be disaggregated to provide i n f o r m a t i o n on the number of persons with s p e c i f i c degrees necessary f o r a c t i v i t i e s w i t h i n high tech i n d u s t r i e s . The CMAs having the l a r g e s t percentage of t h e i r labour f o r c e with u n i v e r s i t y degrees are Ottawa-Hull w i t h 21.9%, H a l i f a x w i t h 18.0%, and Calgary with 17.4%. The lowest percentages i n Canada were found f o r Oshawa with 8.0%, V i c t o r i a w i t h 9.0%, and St. Catherines-Niagara w i t h 9.5%. Natural Science Expenditures Data on expenditures on n a t u r a l sciences a c t i v i t i e s by the f e d e r a l government, Canadian i n d u s t r y , Canadian u n i v e r s i t i e s and other Canadian 132 performers are o c c a s i o n a l l y a v a i l a b l e through S t a t i s t i c s Canada's Science S t a t i s t i c s S e r v i c e B u l l e t i n (1985a). The informa t i o n used i s f o r 1983-84, although 1981 data are p r e f e r a b l e f o r consistency w i t h the other data being analyzed. Another drawback i s that data are only a v a i l a b l e f o r 13 CMA, l e a v i n g out 11 CMAs. Natural science expenditures are highest i n Ottawa with $740 m i l l i o n , most of which comes from the f e d e r a l government. Toronto and Montreal f o l l o w f a r behind w i t h $248 m i l l i o n and $230 m i l l i o n r e s p e c t i v e l y . H a l i f a x and Vancouver are the only other two CMAs w i t h annual n a t u r a l sciences expenditures above $100 m i l l i o n . Union Membership Union membership data were obtained from S t a t i s t i c s Canada (1983a) p u b l i c a t i o n s . The t o t a l membership i n r e p o r t i n g labour o r g a n i z a t i o n s i n each CMA was d i v i d e d by the t o t a l labour f o r c e i n each CMA to determine the percentage of the labour f o r c e that has union membership w i t h i n each CMA. Data were a v a i l a b l e f o r 1981 f o r a l l CMAs except T r o i s - R i v i e r e s . The percentage of the labour f o r c e i n v o l v e d i n unions v a r i e s widely across the 23 CMAs. Thunder Bay has the highest membership with 51.4%, followed by Chicoutimi-Jonquiere w i t h 42.6% and Vancouver with 41.0%. The lowest labour union membership r a t e was found i n V i c t o r i a w i t h only 16.6% followed by Calgary w i t h 22.8% and Kitchener with 24.7%. 133 I n d u s t r i a l Research and Development Employment The names of i n d u s t r i a l research and development f i r m s , t h e i r addresses, numbers of employees and d i s c i p l i n e s of concentration are a v a i l a b l e through S t a t i s t i c s Canada (1985b). The i n f o r m a t i o n was based on a voluntary survey conducted i n 1984, so many employers might not have been i n c l u d e d , and the year of the data i s not c o n s i s t e n t w i t h the 1981 data used i n the r e s t of the a n a l y s i s . For these two reasons, any r e s u l t s based on t h i s data should be i n t e r p r e t e d w i t h c a u t i o n . To o p e r a t i o n a l i z e the data, the number of employees i n each f i r m was added to the appropriate CMA, based on the address given. This r e s u l t e d i n the t o t a l number of i n d u s t r i a l research and development employees i n each CMA. Toronto has the highest number of i n d u s t r i a l R & D workers, with 5,190, followed by Montreal w i t h 3,240 and Vancouver with 1,660. Two CMAs had no i n d u s t r i a l R & D workers r e g i s t e r e d at a l l , these were T r o i s - R i v i e r e s and Sudbury. Thunder Bay and Saint John a l s o had only approximately 10 persons engaged i n i n d u s t r i a l R & D each. Federal Government Employees Information on the numbers of f e d e r a l government employees i n census met r o p o l i t a n areas i s a v a i l a b l e from S t a t i s t i c s Canada (1982b). The t o t a l number of f e d e r a l government employees i n each CMA was d i v i d e d by the t o t a l CMA labour f o r c e to give the percentage i n each CMA employed with the f e d e r a l government. Data were a v a i l a b l e f o r 1981 f o r a l l CMAs except T r o i s R i v i e r e s . Federal government employment f i g u r e s are used to model f e d e r a l government presence i n each CMA. I t i s assumed that a higher f e d e r a l government presence w i l l lead to a higher p o t e n t i a l f o r firms to make contacts 134 w i t h f e d e r a l government and subsequently work f o r the f e d e r a l government i n high tech development. The l i t e r a t u r e i n d i c a t e s that a f e d e r a l government presence may lead to generation of high tech a c t i v i t i e s (Steed and DeGenova 1985). As would be expected, Ottawa has by f a r the highest f e d e r a l government presence, wit h 24.3% of i t s work forc e employed with the f e d e r a l government. This i s followed by H a l i f a x , w i t h 8.8% and St. John's with 5.5%. The lowest percentages f o r f e d e r a l workers were found f o r Oshawa with only 0.6% and Chicoutimi-Jonquiere w i t h 0.8%. A i r l i n e F l i g h t s S t a t i s t i c s Canada (1983d) has data on the number of a i r l i n e f l i g h t s f o r the top 50 a i r p o r t s i n Canada. The absolute number of f l i g h t s f o r each a i r p o r t was a l l o c a t e d to the appropriate CMA. Unf o r t u n a t e l y , the a i r p o r t s of several CMAs were not inc l u d e d i n the top 50 a i r p o r t s . These CMAs were T r o i s -R i v i e r e s , K i t c h e n e r , London, Oshawa and St. Catherines-Niagara. Toronto has the l a r g e s t number of annual f l i g h t s with 142,517, followed by Montreal w i t h 97,446 and Vancouver with 79,055. This ranking i s c o n s i s t e n t with the r e l a t i v e p opulation s i z e of the three centres. The use of r e l a t i v e a i r p o r t s i z e , f l i g h t s per c a p i t a perhaps, was considered and r e j e c t e d because high tech i n d u s t r i e s seem to need a large number of f l i g h t s w i t h convenient departure and a r r i v a l times as w e l l as numerous d e s t i n a t i o n s . A small a i r p o r t i n an even smaller community would not o f f e r an advantage to high tech even though a high number of f l i g h t s per c a p i t a might be c a l c u l a t e d . 135 Telephones Data on the number of telephones i n each CMA are a v a i l a b l e from S t a t i s t i c s Canada (1982c) i n the form of absolute numbers of telephones and telephones per 100 p o p u l a t i o n . The data used are the number of telephones per 100 p o p u l a t i o n f o r 1981 f o r a l l 24 CMAs. The number of telephones per 100 people i s intended to provide a measure of how well-connected a CMA i s i n t o a communication network. C a s t e l l s (1985) notes that high tech a c t i v i t i e s have a tendency to l o c a t e i n a good p o s i t i o n w i t h i n or communications network. The number of telephones per 100 persons, however, might a l s o be an i n d i c a t i o n of r e l a t i v e a f f l u e n c e w i t h more telephones per c a p i t a being a s s o c i a t e d w i t h a higher income per c a p i t a . Calgary has the highest number of telephones per 100 people at 112.0, Edmonton i s next w i t h 95.5 and Saskatoon i s t h i r d w i t h 90.8. The lowest number of telephones per 100 people was found f o r T r o i s - R i v i e r e s at 52.7 and Chicoutimi-Jonquiere at 57.9. Average Family Income Average f a m i l y income data f o r 1981 i s a v a i l a b l e from S t a t i s t i c s Canada (1983b) and i s based on the 1981 Census of Canada. The average f a m i l y income data i s intended to represent average s a l a r y l e v e l s across the 24 CMAs. Because average s a l a r y data was not a v a i l a b l e , average f a m i l y income was used. The highest average f a m i l y income f o r 1981 was found i n Calgary, at $33,462; the second highest was found i n Edmonton, at $31,998 and the t h i r d highest was found i n Vancouver at $31,634. The lowest incomes i n Canada were 136 found i n T r o i s - R i v i e r e s and Chicoutimi-Jonquiere, the same two CMAs f o r which the lowest number of telephones per c a p i t a were found. Consumer P r i c e Index S t a t i s t i c s Canada (1982a) r e g u l a r l y compiles Consumer P r i c e Index data f o r major me t r o p o l i t a n areas i n Canada. Several of the 24 CMA are omitted, however, and these are Chicoutimi-Jonquiere, T r o i s - R i v i e r e s , Hamilton, K i t c h e n e r , London, Oshawa, St. Catherines-Niagara, Sudbury and Windsor. There i s very l i t t l e v a r i a t i o n i n consumer p r i c e index f i g u r e s across Canada. St. John's, Newfoundland has the highest consumer p r i c e index at 254.1, followed by Vancouver w i t h 238.9. The two lowest consumer p r i c e index f i g u r e s were f o r Saskatoon with 230.6 and Ottawa-Hull w i t h 231.4. E l e c t r i c i t y Rates Information on e l e c t r i c i t y r ates across Canadian Census M e t r o p o l i t a n Areas can be found i n S t a t i s t i c s Canada (1981) p u b l i c a t i o n s . The i n f o r m a t i o n i s presented as monthly commercial e l e c t r i c i t y charges based on b i l l i n g demand and on k i l o w a t t - h o u r s consumption. The f i g u r e s presented here are based on a 100 kw b i l l i n g demand and 25,000 kwh monthly consumption. This b i l l i n g demand and monthly consumption, however, might not be r e p r e s e n t a t i v e of the requirements of a high tech i n d u s t r y . E l e c t r i c i t y r a t e i n f o r m a t i o n i s not a v a i l a b l e f o r Chicoutimi-Jonquiere, Quebec, T r o i s - R i v i e r e s , Hamilton or V i c t o r i a . E l e c t r i c i t y rates are highest i n H a l i f a x and Saint John, New Brunswick with a monthly charge of $1,588 and $1,390 r e s p e c t i v e l y . The lowest 137 e l e c t r i c i t y r a t e s i n Canada can be found i n Thunder Bay w i t h monthly charges of $796 and Winnipeg with $815. Average Dwelling Value Based on the 1981 Census of Canada, S t a t i s t i c s Canada (1983b) has published documents which c o n t a i n i n f o r m a t i o n on average d w e l l i n g values across a l l 24 CMAs i n Canada. The d o l l a r value presented i n the S t a t i s t i c s Canada document i s the value used i n t h i s a n a l y s i s . The highest d w e l l i n g p r i c e s i n 1981 were found i n Vancouver, w i t h an average value of $171,726. This i s followed by V i c t o r i a with $132,519 and Calgary w i t h $114,666. The lowest d w e l l i n g values i n Canada were found i n T r o i s - R i v i e r e s at $43,038 and Chicoutimi Jonquiere with an average value of $45,372. Climate Index Various types of c l i m a t i c data are a v a i l a b l e i n Climate Canada w r i t t e n by Hare and Thomas (1979). Heating degree day data (heating degree days are days w i t h temperatures below 18° C) are a v a i l a b l e f o r 15 of the 24 CMAs stu d i e d . The f i g u r e s are based on the mean of the annual values from 1941 to 1970. The mean of the annual hours of b r i g h t sunshine from 1946 to 1970 was a l s o a v a i l a b l e f o r the same 15 CMAs. A cl i m a t e index was formulated to i n d i c a t e the general c l i m a t i c comfort of a CMA. This was based on the r a t i o of hours of b r i g h t sunshine to heating degree days. A high number r e s u l t s when a CMA has more hors of b r i g h t sunshine and fewer heating degree days. Although t h i s c l i m a t e index does not s p e c i f i c a l l y address other c l i m a t i c f a c t o r s such as r a i n , cloud, snow, and 138 wind, i t does address some by d e f a u l t . A place w i t h more hours of b r i g h t sunshine and fewer days with temperatures below 18° C w i l l be l e s s l i k e l y to experience r a i n , snow, or clouds. V i c t o r i a and Vancouver have by f a r the highest climate i n d i c e s . V i c t o r i a has a f i g u r e of 0.71 and Vancouver has 0.64. Toronto t r a i l s t h i r d with 0.56. The lowest climate index f i g u r e i s found f o r St. John's, Newfoundland, at 0.30. Quebec and Winnipeg were a l s o low w i t h 0.36 and 0.38 r e s p e c t i v e l y . A i r Q u a l i t y Index Environment Canada (1984) publishes i n f o r m a t i o n on n a t i o n a l urban a i r q u a l i t y trends. An a i r q u a l i t y index has been devised by the F e d e r a l -P r o v i n c i a l Committee on A i r P o l l u t i o n based on the average of three d i f f e r e n t p o l l u t a n t s that have the most s i g n i f i c a n t e f f e c t on the environment during a given year. P o l l u t a n t s i n c l u d e sulphur d i o x i d e , n i t r o g e n d i o x i d e , suspended p a r t i c u l a t e matter, carbon d i o x i d e and ozone. A i r q u a l i t y index data, however, are not a v a i l a b l e f o r some CMAs. These i n c l u d e St. John's, Chicoutimi-Jonquiere, T r o i s - R i v i e r e s , Oshawa, Sudbury, Thunder Bay and Saskatoon. A lower a i r q u a l i t y index score means a higher a i r q u a l i t y . In 1981, both V i c t o r i a and Ottawa-Hull had the highest a i r q u a l i t y , w i t h a score of 22 each. The worst a i r q u a l i t y i n 1981 was found i n Regina with a score of 52 and i n Hamilton and K i t c h e n e r , both with scores of 43. I t should be noted that a r a t i n g of greater than 50 i s r e q u i r e d before a i r q u a l i t y i s defined as 'poor'. A 'poor' r a t i n g was only given to one CMA i n Canada, with the r e s t 139 being rated as ' f a i r ' or 'good'. This i n d i c a t e s that a i r p o l l u t i o n i s not a s i g n i f i c a n t f a c t o r i n most Canadian CMAs. 140 BIBLIOGRAPHY Aho, CM. and Rosen, H.F. (1980) "Trends i n Technology-Intensive Trade: w i t h S p e c i a l Reference to US Competitiveness", Bureau of I n t e r n a t i o n a l Labor A f f a i r s , US Department of Labor. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies, V o l . 20.2, pp. 103-116. Begeron, T. (1983) "High Hopes f o r High Tech", Area Development, S i t e s and  F a c i l i t i e s Planning. V o l . 18, No. 4, p. 4. Boretsky, M. (1982) "The Threat to US High Technology I n d u s t r i e s : Economic and S e c u r i t y I m p l i c a t i o n s ( D r a f t ) " , I n t e r n a t i o n a l Trade A d m i n i s t r a t i o n , US Department of Commerce. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies. V o l . 20.2, pp. 103-116. Breheny, M.; Cheshire, P.; and Langridge, R. (1985) "The Anatomy of Job Creation? I n d u s t r i a l Change i n B r i t a n ' s M4 C o r r i d o r " , i n S i l i c o n  Landscapes, E d i t e d by P. H a l l and A. Markusen, A l l e n and Unwin, New York. Breheny, M. and McQuaid, R. (1985) "The M4 C o r r i d o r : Patterns and Causes of Growth i n High Technology I n d u s t r i e s " , Reading Geographical Papers, No. 87. C a s t e l l s , M. (1985) "High Technology, Economic R e s t r u c t u r i n g , and the Urban Regional Process i n the United S t a t e s " , i n High Technology, Space and  S o c i e t y , E d i t e d by M. C a s t e l l s , Urban A f f a i r s Annual Reviews, V o l . 28, Sage P u b l i c a t i o n s , Beverly H i l l s . Cole, R.; D i v e l y , D.; M o r r i s , F.A.; S c h i l l i n g , H.A.; and Shen, E.T. (1984) High Technology Employment, Education and T r a i n i n g i n Washington S t a t e , B a t t e l l e Research Center, S e a t t l e . Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies, V o l . 20.2, pp. 103-116. Davis, L.A. (1982) "Technology I n t e n s i t y of US Output and Trade, S t a f f Report", I n t e r n a t i o n a l Trade A d m i n i s t r a t i o n , US Department of Commerce. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional S t u d i e s , V o l . 20.2, pp. 103-116. Economic Council of Canada. (1985) "Tech Change i n the Job Market", Au  Courant. V o l . 6, No. 1, pp. 2-3. Feldman, M. (1985) "Biotechnology and Local Economic Growth: The American P a t t e r n " , i n S i l i c o n Landscapes, E d i t e d by P. H a l l and A. Markusen, A l l e n and Unwin, New York. 141 Gandia, D.M. (1983) "Defi n i n g High Tech ( D r a f t ) " , D i v i s i o n of Research, Maryland Department of Economic and Community Development. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies. V o l . 20.2, pp. 103-116. Glasmeier, A.; Markusen, A.; and H a l l , P. (1983) D e f i n i n g High Technology  I n d u s t r i e s , Working Paper No. 407, I n s t i t u t e of Urban and Regional Development, U n i v e r s i t y of C a l i f o r n i a , Berkeley. Glasmeier, A.; H a l l , P.; and Markusen, A. (1983) Recent Evidence on High- Technology Industry's S p a t i a l Tendencies: A P r e l i m i n a r y I n v e s t i g a t i o n , Working Paper No. 417, I n s t i t u t e of Urban and Regional Development, U n i v e r s i t y of C a l i f o r n i a , Berkeley. Glasmeier, A. (1985) "Innovative Manufacturing I n d u s t r i e s : S p a t i a l Incidence i n the United S t a t e s " , i n High Technology, Space and S o c i e t y , E d i t e d by M. C a s t e l l s , Urban A f f a i r s Annual Reviews, V o l . 28, Sage P u b l i c a t i o n s , Beverly H i l l s . H a l l , P. (1985a) "Technology, Space, and So c i e t y i n Contemporary B r i t a i n " , i n High Technology. Space and S o c i e t y , E d i t e d by M. C a s t e l l s , Urban A f f a i r s Annual Reviews, V o l . 28, Sage P u b l i c a t i o n s , Beverly H i l l s . H a l l , P. (1985b) "The Geography of the F i f t h K o n d r a t i e f f " , i n S i l i c o n Landscapes. Edi t e d by P. H a l l and A. Markusen, A l l e n and Unwin, New York. H a l l , P. and Markusen, A. (1985) "High Technology and Regional-Urban P o l i c y " , i n S i l i c o n Landscapes. E i d t e d by P. H a l l and A. Markusen, A l l e n and Unwin, New York. H a l l , P.; Markusen, A.; Osbourne, R.; and Wachsman, B (1985) "The American Computer Software Industry: Economic Development Prospects", i n S i l i c o n  Landscapes, E d i t e d by P. H a l l and A. Markusen, A l l e n and Unwin, New York. Haug, P. (1986) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies, V o l . 20.2, pp. 103-116. K e l l y , R.K. (1977) "The Impact of Technological Innovation on I n t e r n a t i o n a l Trade P a t t e r n s " , S t a f f Economic Report, O f f i c e of I n t e r n a t i o n a l Research, US Department of Commerce. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies, V o l . 20.2, pp. 103-116. Lawson, A.M. (1982) "Technological Growth and High Technology i n US I n d u s t r i e s " , I n d u s t r i a l Economic Review, V o l . 1. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional  Studies. V o l . 20.2, pp. 103-116. M a l e c k i , E. (1984) "High Technology and Local Economic Development", Journal  of the American Planning A s s o c i a t i o n . V o l . 50, No. 3, pp. 262-269. 142 Markusen, A. (1985) "High Tech Jobs, Markets and Economic Development Prospects: Evidence From C a l i f o r n i a " , i n S i l i c o n Landscapes, E d i t e d by P. H a l l and A. Markusen, A l l e n and Unwin, New York. Markusen, A. and Bloch, R. (1985) "Defensive C i t i e s : M i l i t a r y Spending, High Technology, and Human Settlements", i n High Technology. Space and  S o c i e t y . E d i t e d by M. C a s t e l l s , Urban A f f a i r s Annual Reviews, V o l . 28, Sage P u b l i c a t i o n s , Beverly H i l l s . Massachusetts D i v i s i o n of Employment S e c u r i t y . (1982) "High Technology Employment: Massachusetts and Selected States 1975-1981" Massachusetts D i v i s i o n of Employment S e c u r i t y , Boston, Ma. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional  Studies . V o l . 20.2, pp 103-116. M i n s h a l l , C.W. (1982) Development of High Technology i n New York. B a t t e l l e Research Center, Columbus. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies, V o l . 20.2, pp 103-116. Newton, P. and O'Connor, K. (1985) The Location of High Tecnology Industry: An A u s t r a l i a n Pespective, CSIRO and Monash U n i v e r s i t y , Melbourne, Paper prepared f o r CIB W72 - World U n i v e r s i t y Workshop: 'Innovation, Technological Change, and S p a t i a l Impacts'. Oakey, R. (1984) High Technology Small Firms: Regional Development i n B r i t a i n  and the United Sta t e s. Frances P i n t e r , London. O f f i c e of Technology Assessment. (1984) Technology, Innovation and Regional  Economic Development, U.S. Congress, Washington D.C. Premus, R. (1982) Location of High Technology Firms and Regional Economic  Development, J o i n t Economic Committee, U.S. Congress, Washington D.C. Riche, R.W.; Heckler, D.E.; and Burgan, J.V. (1983) "High Technology Today and Tomorrow: a Small S l i c e of the Employment P i e " , Monthly Lab.  Review, V o l . 106. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies, V o l . 20.2, pp. 103-116. Rogers, E. and Larsen, J. (1984) S i l i c o n V a l l e y Fever: Growth of High  Technology C u l t u r e , Basic Books Inc. P u b l i s h e r s , New York. Saxenian, A. (1983) "The Urban C o n t r a d i c t i o n s of S i l i c o n V a l l e y : Regional Growth and R e s t r u c t u r i n g of the Semiconductor Industry", I n t e r n a t i o n a l  Journal of Urban and Regional Research, V o l . 7, No. 2, pp. 237-262. Saxenian, A. (1985) "The Genesis of S i l i c o n V a l l e y " , i n S i l i c o n Landscapes, E d i t e d by P. H a l l and A. Markusen, A l l e n and Unwin, New York. 143 S h a k l i n , W. and Ryans, J. J r . (1984) Marketing High Technology, Lexington Books, D.C. Heath and Company, Toronto. S t a t i s t i c s Canada, Business Finance D i v i s i o n , Labour Unions Sec t i o n . (1983a) Corporations and Labour Unions Returns Act: Report f o r 1981. Part I I - Labour Unions, Catalogue No. 71-202, Ottawa. S t a t i s t i c s Canada, Education C u l t u r e and Tourism D i v i s i o n , Post Secondary Education S e c t i o n . (1983c) U n i v e r s i t i e s : Enrolment and Degrees 1981, Catalogue No. 81-204, Ottawa. S t a t i s t i c s Canada, Manufacturing and Primary I n d u s t r i e s D i v i s i o n . (1981) E l e c t r i c i t y B i l l s f o r Domestic Commercial and Small Power Se r v i c e 1981, Catalogue No. 57-203, Ottawa. S t a t i s t i c s Canada, P r i c e s D i v i s i o n . (1982a) The Consumaer P r i c e Index,  December 1981. Catalogue No. 62-001, V o l . 60, No. 12, Ottawa. S t a t i s t i c s Canada, P u b l i c Finance D i v i s i o n , Consolidated and Federal Government Sec t i o n . (1982b) Federal Government Employment i n  M e t r o p o l i t a n Areas: September 1981, Catalogue No. 75-205, Ottawa. S t a t i s t i c s Canada, Science and Technology S t a t i s t i c s D i v i s i o n . (1985a) Science S t a t i s t i c s S e r v i c e B u l l e t i n , Catalogue No. 88-001, V o l . 9, No. 5, Ottawa. S t a t i s t i c s Canada, Science Technology and C a p i t a l Stock D i v i s i o n . (1985b) D i r e c t o r y of I n d u s t r i a l Research and Development F a c i l i t i e s i n Canada,  1985, Catalogue No. 88-205E, Ottawa. S t a t i s t i c s Canada, T r a n s p o r t a t i o n and Communications D i v i s i o n , A v i a t i o n S t a t i s t i c s Centre. (1983d) A i r C a r r i e r T r a f f i c at Canadian A i r p o r t s .  1981, Catalogue No. 51-203, Ottawa. S t a t i s t i c s Canada, T r a n s p o r t a t i o n and Communications D i v i s i o n , Communications Sect i o n . (1982c) Telephone S t a t i s t i c s 1981, Catalogue No. 56-203, Ottawa. S t a t i s t i c s Canada, 1981 Census of Canada. (1983b) Census M e t r o p o l i t a n Areas  with Components. Popu l a t i o n , Occupied P r i v a t e Dwellings, P r i v a t e  Households and Census and Economic F a m i l i e s i n P r i v a t e Households,  Selected S o c i a l and Economic C h a r a c t e r i s t i c s , Catalogue No. 95-943, Ottawa. Steed, G.P. and DeGenova, D. (1983) "Ottawa's Technology Oriented Complex", Canadian Geographer, V o l . 27, No. 3, pp. 267-278. Vinson, R. and Harrin g t o n , P. (1979) " D e f i n i n g "High Technology' I n d u s t r i e s i n Massachusetts", Department of Manpower Development, Boston. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies, V o l . 20.2, pp. 103-116. 144 Weiss, M.A. (1985) "High Technology I n d u s t r i e s and the Future of Employment", i n S i l i c o n Landscapes. E d i t e d by P. H a l l and A. Markusen, A l l e n and Unwin, New York. Western I n t e r s t a t e Commission f o r Higher Education. (1983) P r o f i l e s : High  Technology Education and Manpower i n the West, Boulder, Co. Quoted i n Haug, Peter (1985) "US High Technology M u l t i n a t i o n a l s and S i l i c o n Glen", Regional Studies. V o l . 20.2, pp. 103-116. Wiewel, W.; deBettencourt, J.S.; and Mier, R. "Planners Technology and Economic Growth", Journal of the American Planning A s s o c i a t i o n , V o l . 50, No. 3, pp. 290-297. 145 

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
http://iiif.library.ubc.ca/presentation/dsp.831.1-0097986/manifest

Comment

Related Items