Transcript
Page 1: Regional Differences in Innovation and Economic Performance

ASB 2011 Ryan MacNeil

Charlottetown, Prince Edward Island Department of Business & Tourism

Mount Saint Vincent University

REGIONAL DIFFERENCES IN INNOVATION AND ECONOMIC PERFORMANCE

IN CANADA’S INFORMATION TECHNOLOGY INDUSTRIES1

Innovation is a key mechanism for improving economic productivity. The literature suggests

approaches to innovation are socially embedded,

and protean industrial cultures outperform

autarkic ones. This study reports on differences in innovation culture across Canada‟s provincial

ICT industries, and the impact of those

differences on employment growth and decline.

Innovation and Economic Performance

Neoclassical Economic Theory

Government policy in Canada is often informed by neoclassical economic theory. As the theory

goes, regional output of a commodity (Q) is a function of the capital (k) and labour (L) employed

in its production (see Equation 1). By modifying this function, it can be shown that an increase in productivity (defined as output per unit of labour) is the result of an increase in the ratio of capital

to labour (see Equation 2). Therefore, increases in productivity can only be achieved two ways:

labour must remain constant while capital increases, or capital must increase faster than labour. Unfortunately, this simplistic version of the theory suggests that technological progress has no

qualitative effect on productivity. Technology can only manifest as additional capital inputs and

reduced labour inputs.

Q = f (k, L) (1)

Q / L = f (k / L) (2)

1 The author wishes to acknowledge Peter V. Hall, Simon Fraser University, for valuable feedback on an

earlier approach to this topic.

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Endogenous Growth Theory

Acs and Varga (2002, p. 137) compare neo-classical and endogenous growth theories and explain

that the latter allows for “the modeling of technological change as a result of profit-motivated investments in knowledge creation by private economic agents.” They argue that neo-classical

theory is limited by its assumption of perfect competition and constant returns to scale. In fact,

technology is not a purely „public good‟ since knowledge can be “sticky” (Bourgeois and LeBlanc, 2002) in time and space. Patents and tacit knowledge can create disparity in

technological diffusion. Firms and regions that can develop “sticky” innovations gain market

power and fixed-term monopoly profits (Bourgeois and LeBlanc, 2002).

Endogenous growth theory attributes productivity growth beyond a change in the capital-labour

ratio to “innovations”. These take the form of product or service innovations, process innovations,

and/or organizational innovations (Morgan, 1997; Bourgeois and LeBlanc, 2002; and Betts,

1998). Product or service innovations can be incremental changes to existing products or services, or entirely new ones. Process innovations can either reduce the costs or improve the quality of

production (for example, just-in-time inventory systems). Organizational innovations involve

some form of structural advantage, such as the way Walmart coordinates its distribution chain through computerized inventory systems. Morgan (1997) credits Marx and Schumpeter for

introducing the idea that innovation is the root of regional development in capitalist economies.

Schumpeter‟s seminal work (1943) on innovation and capitalism argues that economic growth requires innovation. Even when experiencing equal capital and labour growth, the theory suggests

that „innovating firms‟ will see growth in output over those which do not innovate. This

revelation has encouraged governments to divert some resources from expensive capital-

mobilization strategies to innovation-catalyzing ones. However, encouraging innovation defies simple government intervention.

Not Simply Research and Development

A typical government initiative might involve encouraging research and development. When discussing the downfalls of typical job-creation strategies for declining regions, Hall (1984)

suggests using an existing or “deliberately implanted” research and development tradition to

create an entrepreneurial tradition. He is cautious, and notes, “such bold strategies may succeed,

but they are likely to take a long time to produce substantial results…no single strategy, but rather a combination of different approaches, will be appropriate” (p. 35). Despite this hesitation, and

the tradition of peer-juried awarding of university research grants, Hall concludes with a call for

“the establishment of regional quotas to the Research Councils” (in the UK, USA and Canada). Indeed, there is evidence that the Canadian government‟s university research grants neglect

disadvantaged regions. Over its first five years, the Canada Foundation for Innovation invested

only 3.2% of its total contributions in Atlantic Canada (Beaudin and Breau, 2001, p. 133). But only measuring innovation in terms of gross expenditures on research and development (GERD)

is inappropriate. GERD is “meant to reflect the degree of innovative effort and intent, not

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necessarily innovative potential and success” (Bourgeois and LeBlanc, 2002, p. 170). Despite a

low level of government R&D funding grants, Bourgeois and LeBlanc found that Atlantic Canadian firms in knowledge intensive industries (computer services, engineering consultant

services, and other scientific and computer services) have innovation rates near the national

average (2002, p. 71). However, this innovation is much less likely to involve the introduction of

new capital-intensive technologies than elsewhere in Canada because financial capital is lacking. They say that, “studies in the last ten years are increasingly rejecting R&D as a master key that

unlocks a linear innovation process, seeing it instead as one of several pieces to the innovation

puzzle” (p. 170).

There is a myth that innovation is unique to technology industries and only happens in R&D

laboratories. Bourgeois and LeBlanc, as well as Beaudin and Breau, note the importance of

innovation to firms in the primary and service sectors. For example, in the Atlantic fish processing sector between 1988 and 1996, the number of labour-hours declined 40% but the

value-added per hour rose 35% (Beaudin and Breau, 2001, p. 89). These industries “acquire ideas

not from in-house R&D but by tapping into the knowledge and ingenuity of their workers, suppliers and customers – by networking with research institutions, universities, competitors,

governments, and other stakeholders” (Bourgeois and LeBlanc, 2002, p. 18). Maskell and

Malmberg (1999, p. 21) argue that knowledge-based competition is forcing firms to place “a new

premium on establishing cooperative relations with firms and institutions with complementary competencies.”

There is a burgeoning volume of research on the social-embeddedness of innovation. Noted academics argue that community networks encourage the free-flow of ideas and therefore foster

continuous innovation. Morgan (1997, p. 493) says that, “innovation is shaped by a variety of

institutional routines and social conventions.” The Danish Aalborg group of economists goes so

far as to say that “knowledge is the most strategic resource and learning the most important process” (Ibid.) for regional development. This connects with research on Japanese organizational

innovations that recognizes tacit knowledge as highly personal and difficult to measure. Nelson

(1993) is recognized as the pioneer of research on national innovation systems.2 He attributes the

rise of Japanese leadership in automotive and consumer electronics production in part to interfirm

linkages (Nelson, 1999, p. 5). Japan is renowned for unique supplier-customer partnership chains

at the interfirm level. At the national level, Japan also has strong interfirm institutions (like trade and professional associations). Meanwhile, at the intrafirm level, the Japanese kaizen

3 approach

results in horizontal information flows and decentralized learning. Storper (1992, 1994, 1995) is

credited with relating these issues of learning, innovation and institutions to the study of

economic geography. His work outlines the importance of untraded interdependencies in organizational learning.

Feldman and Florida (1994, p. 211) conclude that a broad case study literature, “encourages

scholars to shift focus from the firm-level to a consideration of innovation as a social process.” They argue that innovation stems from an agglomeration of social and economic institutions

2 Note that Nelson does not consider geography to be as important to innovation as the other authors

referenced here. Nelson (1999, p. 8) says, “it is the connections, not geographic proximity at all…”. 3 “…continuous improvement through interactive learning and problem-solving…” (Morgan, 1997, p. 494)

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which form part of a broader social structure (Ibid., p. 220). Saxenian‟s work contrasting

Massachusetts‟ „Route 128‟ and California‟s „Silicon Valley‟ supports a similar view. She describes the innovation in these two regions as „ecosystems‟,

Silicon Valley is like the rainforest. It‟s a

decentralized system with a complex and continually diversifying mix of species, flora

and fauna that spontaneously and repeatedly

cross-polinate. Route 128, by contrast, using this metaphor is like a plantation. It‟s a more

centralized system dominated by large

corporations that crowd out local opportunities

for new growth (Saxenian, 1998, p. 3).

Saxenian is critical of science parks and other strategies that aim to create replica Silicon Valleys.

She concludes that, “ultimately regions are best served by policies that help companies to learn

and respond quickly to changing conditions – rather than policies that either protect or isolate them from competition or external change” (1994, p. 166).

In her work, Saxenian contends that the mechanism of Silicon Valley‟s success was its collaborative industrial structure. In contrast, she says that Route 128, “came to be dominated by

a small number of large, vertically integrated minicomputer firms…that had minimal

relationships with each other or with local or regional institutions” (Saxenian, 1998, p. 2). If

Saxenian is correct, regions with protean industrial structures (like the versatile, horizontally networked system in Silicon Valley) will see greater economic growth and resilience than regions

with autarkic structures (like the closed, vertically integrated industrial system of Route 128). The

key difference between these regions would be their approach to innovation. The most successful regions would be home to firms that collaborate with suppliers, customers, universities and

competitors. The least successful regions would be home to highly secretive firms that make full

use of the law to protect their intellectual property, and of „vertical integration‟ (mergers and

acquisitions) to acquire (rather than create) protected intellectual property.

Method

Approach

This paper presents empirical evidence to support these theories in the Canadian context. It examines inter-provincial variations in the approach to innovation taken by the information and

communication technology (ICT) service industry. The research question is whether these

variations in innovation culture explain variations in regional economic performance. Maskell

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and Malmberg (1999, p. 21) proposed this line of inquiry when they asked, “Do firms from

different regions exhibit different patterns of interaction and cooperation?”

Data Sources

The two data sources used in this study were supplied by Statistics Canada and accessed through

the CANSIM database. Provincial employment trends were extracted from the Survey of

Employment, Earnings and Hours (Statistics Canada, 2011). This survey‟s population includes all business in Canada found on either Statistics Canada‟s Business Register or in Revenue Canada‟s

Business Number Database. From this dataset, provincial employment levels in January 2001 and

January 2011 were extracted for all NAICS 2002 (North American Industrial Classification System) codes relating to the international standard information and communication technology

(ICT) service industries. Table 1 provides the list of NAICS categories making up the ICT service

industry. Total industry employment and total overall employment were calculated for each

province.

Table 1: Information and Communication Technology Industries by NAICS 2002

NAICS Description

4173 Computer and Communications Equipment and Supplier Wholesaler-Distributors 41791

a Office and Store Machinery and Equipment Wholesaler-Distributors

5112 Software Publishers

5171 Wired Telecommunications Carriers 5172 Wireless Telecommunications Carriers (except Satellite)

5173 Telecommunications Resellers

5174 Satellite Telecommunications

5175 Cable and Other Program Distribution 5179 Other Telecommunications

518111b Internet Service Providers

518112b Web Search Portals

5182 Data Processing, Hosting, and Related Services

53242c Office Machinery and Equipment Rental and Leasing

5415 Computer Systems Design and Related Services 8112 Electronic and Precision Equipment Repair and Maintenance

Table Source: Statistics Canada, Survey of Innovation 2003, Methodology Note (p. 3). a This classification is unavailable in CANSIM Table 281-0023. The higher level of

classification, “4179 - Other machinery, equipment and supplies wholesaler-distributors” is used.

b CANSIM Table 281-0023 combines these two classifications into “5181 - Internet service

providers, web search portals”. c This classification is unavailable in CANSIM Table 281-0023. The higher level of

classification, “5324 - Commercial and industrial machinery and equipment rental and leasing”

is used.

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Data describing provincial approaches to innovation were drawn from the Survey of Innovation,

2003 (Statistics Canada, 2003). The survey “is based on the Oslo Manual (OECD/Eurostat, 1997) which outlines proposed guidelines for collecting and interpreting innovation data at the level of

the firm” (Ibid.). Its population includes those establishments with more than 15 employees and

over $250,000 per year in revenues. Four broad industry classifications were sampled, including

the ICT service industry defined in Table 1. The results are at the provincial aggregation.

Procedure

The effect of an innovative culture on regional economic performance is not direct. The literature

suggests a causal relationship similar to that outlined in Figure 1Error! Reference source not

found.. A high level of innovation is predicted for regions where industry approaches innovation

in a collaborative manner. Conversely, a secretive approach that relies on strict intellectual

property protection, and is generates large vertically integrated companies, should result in a

lower level of regional innovation. In turn, endogenous growth theory predicts that the level of innovation will influence a region‟s economic growth.

Figure 1: Predicted Pattern of Causation for Innovation and Economic Performance

A number of variables represent the culture/attitudes toward innovation among Canada‟s provinces. Each variable represents the proportion of firms which recognize the importance of, or

are actively engaged in, a given innovation strategy. Summary statistics for these variables are

included in Table 2.

Culture/Attitudes Toward Innovation

Autarkic (Strict IP Protection

and Acquisition)

Protean

(Collaborative Learning and Relationships)

Product and Process

Innovations

Economic Performance

Predicted Pattern of Causation for Innovation and Economic Performance

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Table 2: Variables defining a province’s culture/attitudes toward innovation

Variable Mean SD

Proximity to knowledge institutions is highly or moderately highly

important to success (ProxKnow). 14.24 6.40

Proximity to knowledge institutions is moderately highly important to

success (ProxKnowMod). 11.11 4.14

Proximity to knowledge institutions is highly important to success

(ProxKnowHigh). 3.13 2.72

Involvement in industry associations is highly or moderately highly

important to success (IndAssoc). 25.00 9.62

Involvement in industry associations is moderately highly important to success (IndAssocMod).

18.60 9.76

Involvement in industry associations is highly important to success

(IndAssoc High). 6.40 3.24

The use of partnerships, strategic alliances or joint ventures to acquire

knowledge is highly or moderately highly important to success (Partner). 42.61 18.81

The use of partnerships, strategic alliances or joint ventures to acquire

knowledge is moderately highly important to success (PartnerMod). 29.65 6.36

The use of partnerships, strategic alliances or joint ventures to acquire

knowledge is highly important to success (Partner High). 18.29 8.26

Collaborated and cooperated to develop new innovations (CollabTOT). 59.40 10.20

Collaborated with competitors to innovate (CollabCOMP). 29.66 8.54

Collaborated with universities or other higher education institutes to

innovate (CollabUNIV). 22.64 10.15

Used patents to protect intellectual property (Patents). 15.28 3.60 Used secrecy to protect intellectual property (Secrecy). 50.74 8.91

Used a lead-time strategy to protect intellectual property (LeadTime). 53.09 10.80

An additional variable representing the average firm size for each province was created by

dividing the total ICT employment in each province by the population of ICT firms identified in

the documentation for the Survey of Innovation (Statistics Canada, 2003). The mean firm size is 52 full-time equivalents (FTEs) with a standard deviation of 15 FTEs.

Simple correlation was used to test the relationships in the model. For the first set of relationships

(where the approach to innovation is said to influence the level of innovation), the variables identified above were tested against the proportion of innovative ICT firms in each province

4.

Pearson‟s product moment correlation coefficient (r) was calculated. Each r-value was interpreted

using a standard rubric (see Table 3).

4 The variable for “Percentage of innovative business units in Canada during the period 2001 to 2003”

(Innovators) has a mean of 74.67 and a standard deviation of 7.83.

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Table 3: Pearson’s Product Moment Correlation Coefficient Interpretation

Association Absolute r-value

Perfect (P) 1.00 Strong (S) 0.75 – 0.99

Moderately Strong (M) 0.50 – 0.74

Weak (W) 0.01 – 0.49 None (N) 0.00

A measure of relative regional economic performance was calculated to test the second half of the model. The three elements of „shift and share‟ (see Newkirk, 2002) were calculated for the ICT

industry in each province for the period January 2001 – January 2011. This is a statisitical

accounting framework widely used for regional economic analysis. It yields a „differential shift

coefficient‟, which is a standardized comparable measure of regional performance. This the context of this study, it represents the quality of regional economic performance in the ICT

industry separate from the influences of national economic growth and national industry growth

(decline). The full results of the shift and share analysis can be found in Appendix A. Differential shift coefficients for each province were tested for correlation with the proportion of innovative

ICT firms in each province.

Limitations

Two key limitations to this method are acknowledged. First, there is broad recognition of the inherent time lag in the innovation model. Feldman and Florida (1994, p. 217) note that it is

difficult to measure the length of this time lag. However, Mansfield (1991) suggests the lag is in

the order of 7 years (with a standard deviation of 2 years) between an academic research finding and commercial introduction of a new product. The method presented above attempts to

compensate by comparing innovation data at the beginning of a time period (2001-2003) with

economic data for the subsequent decade (2001-2011).

The second limitation is in using a provincial level of analysis. As Feldman and Florida (1994, p.

216) explain, in the American context, “using the state as the unit of analysis inevitably obscures

spatial processes that occur within a state or across state boundaries.” Unfortunately, results from the Survey of Innovation (or any similar data) are not available at a sub-provincial level.

An additional two limitations were addressed in the data analysis. First, most of the Survey of

Innovation results from Prince Edward Island have been suppressed under Statistics Canada‟s privacy policies. Unfortunately this meant that PEI could not be included in this study. In other

provinces, data for certain sub-industries were suppressed for one of the two time periods. In

these cases, the sub-industries were not included in provincial industry employment totals.

Furthermore, the ICT industry classification identified above included wired telecommunication

companies. In many Canadian provinces, only one firm (the current or former crown telephone

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corporation) fits this category. In those cases where more than one firm is found in the category,

the majority of the labour force is still employed by the one dominant firm. This means that for many provinces employment data in the 5171 NAICS category has been suppressed. This NAICS

category has therefore been completely excluded from this study‟s ICT industry definition.

Results

Innovation Across Canada

The results indicate a high level of innovation among ICT firms across the country. New Brunswick had the greatest proportion of innovators (83.1%), followed by British Columbia

(81.1%). Saskatchewan had the lowest proportion of innovators (60.6%), followed by

Newfoundland and Labrador (63.5%). The other provinces had innovation rates ranging from 72-79% (see Figure 2). These findings support Bourgeois and LeBlanc‟s (2002) conclusion that

firms in Atlantic Canada innovate at, or above, the national level. Innovation in Canada‟s ICT

industry does not seem to follow typical lines of regional disparity. However, regional differences in innovativeness are still evident and deserve closer examination.

Figure 2: Proportion of Innovative ICT Firms by Province

63.5

83.1 79.2

77.5 79.5

72.7 60.6 74.8 81.1

50% 100%

Proportion of Innovative ICT Firms

Proportion of Innovative ICT Firms by Province (2001-2003)

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Approach to Innovation vs. Innovativeness

Canada‟s highest levels of collaboration were found in the east (see Figure 3). Although

Newfoundland and Labrador had the second lowest level of innovation, it had by far the highest

level of collaboration. If these findings held tightly to the literature, Newfoundland and Labrador‟s collaborative environment would have led to a high level of innovation. There may

however be additional obstacles in that province. Further research should be conducted to identify

barriers to innovation in the poorer provinces. The literature suggests that these barriers might include a lack of venture capital. Additional research can also explore any functional differences

in collaboration across the country.

Figure 3: Proportion of Collaborative ICT Firms by Province (2001-2003)

Some evidence did emerge to support the link between approaches to innovation and regional innovativeness. Unfortunately many of the innovation variables were only weakly associated with

the level of innovation (see Table 4). Six variables did yield a moderately strong association.

Surprisingly, a negative relationship was found for both the importance placed on industry

associations (IndAssoc) and proximity to knowledge institutions (ProxKnow). This suggests that innovation is lower where firms identified these success factors as highly and moderately

important. Perhaps these firms are not actually engaged in these collaborations but simply see

them as important. This logic is supported by additional findings. First, innovation was greater where firms noted the importance of partnerships, strategic alliances and joint ventures (Partner).

Also, a moderately strong positive relationship was found between two measures of collaborative

action and the level of innovativeness. The most innovative provinces saw higher levels of collaboration with competitors (CollabCOMP) and with universities (CollabUNIV). These

findings all point to the relationship between collaboration and innovation. No strong evidence

emerged to support or refute the proposition that secrecy strategies undermine regional levels of

innovation.

83.3

58.0 66.2

60.6 53.1

52.2 57.6 51.0 52.6

50% 100%

Proportion of Collaborative ICT Firms

Proportion of Collaborative ICT Firms by Province (2001-2003)

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Table 4: Correlation of Innovation Strategies with Innovators

Variable r-value Variable r-value

ProxKnow -0.55 Partner High +0.05

ProxKnow Mod -0.43 CollabTOT -0.44

ProxKnow High -0.65 CollabCOMP +0.56

IndAssoc -0.40 CollabUNIV +0.65

IndAssoc Mod -0.53 Patents -0.44

IndAssoc High +0.39 Secrecy +0.22

Partner +0.58 LeadTime +0.45

Partner Mod -0.03 AvgFirmSize +0.71

Another surprising finding was that firm size has a moderately strong positive association with innovativeness. The literature predicts that autarky will be present in regions where average firm

size is large. This may not be the case for the Canadian ICT industry since the provincial average

firm sizes are all below 75 FTEs. The mean firm size is only 52 FTEs and there is little interprovincial variation (a standard deviation of only 15 FTEs). There simply is not the same

contrast in average firm size among Canadian provinces as the contrast Saxenian (1998) saw

between Route 128 and Silicon Valley. There appears to be a „small business bias‟ in the

Canadian ICT sector (when the large telephone companies are excluded). The positive correlation may also indicate the relative strength or maturity of larger SMEs.

Innovativeness vs. Economic Performance

Between 2001 and 2011, employment in the ICT service industry declined in every province except New Brunswick, Quebec, Alberta and British Columbia. The „shift and share‟ results

indicate that each province should have seen 13% employment growth thanks to the national

employment trend. However, employment in the ICT industry underperformed with respect to the

national economy. Nationally the change in ICT sector employment was a net increase of only 6% (or 21,307 FTEs). As a result, the industry mix coefficient is set to -7% to indicate that the

ICT industry‟s performance offset the overall performance of the national economy. In addition

to poor national performance, the industry performed poorly regionally. New Brunswick, Quebec, Alberta and British Columbia saw positive differential shifts. But all other provinces saw negative

differential shifts (see Figure 4). The provinces with the lowest differential shifts are located in

the east (Nova Scotia and Newfoundland and Labrador). But there were also low shifts in Ontario and Manitoba. Again, this pattern does not follow the predicted lines of regional disparity.

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Figure 4: Differential Shift for ICT Industries by Province (2001-2011)

-0.30

+0.08

-0.33

+0.08

-0.07

-0.26-0.20+0.09+0.05

-0.35 +0.35

Differential Shift Coefficient

Differential Shift for ICT Industriesby Province (2001-2011)

The evidence linking innovation to regional economic performance is moderately strong. The relationship between the proportion of innovators (Innovators) and differential shift (DiffShift) is

positive, and moderately strong (r = 0.54). It is possible that the relationship could be stronger, if

not for other barriers preventing the translation of innovations into commercially viable products and services.

It is useful to note the results from a direct test of association between the innovation approach

variables and the differential shift. Although there is clearly an intermediary step in the innovation process, some interesting findings emerged. First, the relationship of firm-university

collaboration to the differential shift is stronger (r = 0.93) than its relationship to the level of

innovation (r = 0.65). The former relationship was the strongest identified in this study. It suggests that firms may not be only collaborating with universities to develop innovations. They

may also be commercializing innovations already developed by university researchers.

A second interesting finding, is that perhaps not all collaborations are created equally. Provinces with high levels of total collaboration (CollabTOT) generally had lower differential shift

coefficients (r = -0.54). It is possible that some types of formalized collaboration are more likely

to result in the kind of vertically integrated systems Saxenian described along Route 128. Closer examination is required.

Finally, some evidence emerged to support the theory that wide-spread patent protection

strategies could hinder economic performance. The relationship of patent-use to regional differential shifts was negative and moderately strong (r = -0.54). The literature suggested that

patent-use can be indicative of an autarkic industrial culture, and that such autarky can stifle

economic performance.

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Conclusions

The correlation results support the structure of the causal model being tested (see Figure 5).

Provinces with higher levels of open collaboration with universities saw a correspondingly high

proportion of their ICT firms innovating, and correspondingly stronger economic performance. Provinces with higher levels of patent use saw lower levels of innovation and poorer regional

economic performance. Furthermore, the evidence connecting levels of innovation with economic

performance was moderately strong. Clearly, innovation was connected to economic performance in the ICT industry between 2001 and 2011. However, the approach to innovation (protean versus

autarkic) was critical.

Figure 5: Observed Pattern of Causation for Innovation and Economic Performance

The findings presented here support the idea that regional approaches to innovation can affect

regional economic growth. Variation was found among Canada‟s provinces in terms of their

innovation cultures, their level of innovation activity, and their relative employment growth/decline. The most successful provinces were home to a greater proportion of firms that

collaborate with universities. However, not all other forms of collaboration seem to yield positive

results (more research is needed). The least successful provinces were home to a greater

proportion of highly secretive firms that used patents to protect their intellectual property.

These findings support the conclusion that provinces with more protean industrial cultures

outperform provinces with more autarkic industrial cultures. A culture of open innovation can boost innovativeness, creating a regional economic advantage. Business schools can therefore

contribute to regional advantage by furthering research on inter-firm collaboration, and by

working with industry to create product, process, and organizational innovations.

Culture/Attitudes Toward Innovation

Innovators (Innovators)

Regional Advantage

(DiffShift)

r = 0.65

r = -0.44

r = 0.54

(Patents) r = -0.54

r = 0.93 (CollabUNIV)

Observed Pattern of Causation for

Innovation and Economic Performance

(CollabUNIV)

(Patents) Autarkic

(Strict IP Protection and Acquisition)

Protean

(Collaborative Learning and Relationships)

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APPENDIX A: Shift and Share Coefficients

Employment in 2001

Canada NL PE NS NB PQ ON MB SK AB BC

ICT 387,916 1,465 288 6,069 3,300 82,765 185,822 6,248 1,679 32,276 37,315

Total 12,482,719 159,254 52,577 350,108 278,587 2,939,945 4,919,896 493,259 364,316 1,315,062 1,567,213

Employment in 2011

Canada NL PE NS NB PQ ON MB SK AB BC

ICT 374,723 1,114 480 4,379 3,772 88,963 177,954 5,366 3,182 36,125 39,630

Total 14,524,398 190,620 59,592 396,748 307,520 3,306,709 5,603,240 550,760 441,651 1,739,056 1,872,590

Change 2001-2011

Canada NL PE NS NB PQ ON MB SK AB BC

ICT -3% -24% 67% -28% 14% 7% -4% -14% 90% 12% 6%

Total 13% 9% 6% 8% 3% 8% 12% 11% 19% 29% 17%

Shift and Share Coefficients

NL PE NS NB PQ ON MB SK AB BC

Regional Share 0.13 0.13 0.13 0.13 0.13 0.13 0.13 0.13 0.13 0.13

Industry Mix -0.17 -0.17 -0.17 -0.17 -0.17 -0.17 -0.17 -0.17 -0.17 -0.17

Differential Shift -0.21 0.70 -0.24 0.18 0.11 -0.01 -0.11 0.93 0.15 0.10

Shift and Share Components - Analysis of Change 2001-2011

NL PE NS NB PQ ON MB SK AB BC

2001 Employment 1,465 288 6,069 3,300 82,765 185,822 6,248 1,679 32,276 37,315

Regional Share 193 38 800 435 10,916 24,508 824 221 4,257 4,922

Industry Mix (243) (48) (1,007) (547) (13,731) (30,828) (1,037) (279) (5,355) (6,191)

Differential Shift (301) 202 (1,484) 584 9,013 (1,548) (670) 1,560 4,947 3,584

2011 Employment 1,114 480 4,379 3,772 88,963 177,954 5,366 3,182 36,125 39,630

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APPENDIX B: Correlation Tables

Effect of Innovation Variables on the Differential Shift for ICT Industry in each Province

Mean StDev r

Differential Shift (0.09) 0.18

ProxKnow 14.24 6.40 -0.48

ProxKnow Mod 11.11 4.14 -0.45

ProxKnow High 3.13 2.72 -0.46

IndAssoc

25.00 9.62 -0.45

IndAssoc Mod 18.60 9.76 -0.38

IndAssoc High 6.40 3.24 -0.21

Partner

42.61 18.81 -0.10

Partner Mod 29.65 6.36 -0.06

Partner High 18.29 8.26 -0.65

Innovators

74.67 7.83 0.54

CollabTOT 59.40 10.20 -0.54

CollabCOMP 29.66 8.54 0.23

CollabUNIV 22.64 10.15 0.93

Patents

15.28 3.60 -0.54

Secrecy

50.74 8.91 0.22

LeadTime

53.09 10.80 0.43

AvgFirmSize 52.48 15.28 0.62

Effect of Approaches to Innovation on the Level of Innovation in Each Province

Mean StDev r

Innovators 74.67 7.83

ProxKnow 14.24 6.40 -0.55

ProxKnow Mod 11.11 4.14 -0.43

ProxKnow High 3.13 2.72 -0.65

IndAssoc

25.00 9.62 -0.40

IndAssoc Mod 18.60 9.76 -0.53

IndAssoc High 6.40 3.24 0.39

Partner

42.61 18.81 0.58

Partner Mod 29.65 6.36 -0.03

Partner High 18.29 8.26 0.05

CollabTOT 59.40 10.20 -0.44

CollabCOMP 29.66 8.54 0.56

CollabUNIV 22.64 10.15 0.65

Patents

15.28 3.60 -0.44

Secrecy

50.74 8.91 0.22

LeadTime

53.09 10.80 0.45

AvgFirmSize 52.48 15.28 0.71

Page 16: Regional Differences in Innovation and Economic Performance

References

Acs, Z. and Varga, A., “Geography, Endogenous Growth and Innovation,” International Regional

Science Review, 25 (1), (2002), 132-148.

Beaudin, M. and S. Breau, Employment, Skills, and the Knowledge Economy in Atlantic Canada,

Maritime Series, Monographs, Moncton, NB: The Canadian Institute for Research on Regional

Development, 2001.

Betts, Y., “II. Resources and Technology: The Implications of Technological Change for Human

Resource Policy,” Canada in the 21st Century. Ottawa, ON: Industry Canada Research

Publications Program, 1998.

Bourgeois, Y. and S. LeBlanc, Innovation in Atlantic Canada, Maritime Series, Monographs.

Moncton, NB, The Canadian Institute for Research on Regional Development, 2002.

Feldman, M.P. and R. Florida, “The Geographic Sources of Innovation: Technological

Infrastructure and Product Innovation in the United States,” Annals of the Association of

American Geographers, 84 (2), (1994), 210 – 229.

Hall, P., “The New Geography of Innovation,” in C. Bryant (ed.) Waterloo Lectures in

Geography, Waterloo: Department of Geography, University of Waterloo, 1, (1984), 29 – 38.

Mansfield, E.J., “Academic Research and Industrial Innovation,” Research Policy, 20, (1991), 1 – 12.

Maskell, P. and A. Malmberg, “The Competitiveness of Firms and Regions: „Ubiquitification‟ and Localized Learning,” European Urban and Regional Studies, 6 (1), (1999), 9 – 25.

Morgan, K., “The Learning Region: Institutions, Innovation and Regional Renewal,” Regional

Studies, 31 (5), (1997), 491 – 503.

Nelson, R.,“The Sources of Industrial Leadership: A Perspective on Industrial Policy,” De

Economist, 147, (1999), 1 – 18.

Nelson, R. (Ed.), National Innovation Systems, Oxford, UK: Oxford University Press, 1993.

Newkirk, R., Techniques for Regional Planning. Waterloo, ON: University of Waterloo under

license from ingenious solutions inc., 2002.

OECD/Eurostat, Proposed Guidelines for Collecting and Interpreting Innovation Data (Oslo

Manual), Paris: Author, 1997.

Saxenian, A., Regional Advantage: Culture and Competition in Silicon Valley and Route 128.

Cambridge, MA: Harvard University Press, 1994.

Page 17: Regional Differences in Innovation and Economic Performance

Saxenian, A., “A Climate for Entrepreneurship. Presentation at Creating an Environment for

Growth,” Proceedings of the XII International Conference of Private Business Associations, Stockholm, Sweden, (June 1998).

Schumpeter, J., Capitalist, Socialism and Democracy. London: Allen & Unwin, 1943.

Statistics Canada, Survey of Innovation 2003 [machine readable data file and documentation],

Ottawa: Statistics Canada, Catalogue no. 88-524-XCB2005001, (2003).

Statistics Canada, Survey of Employment, Earnings and Hours [machine readable data file and documentation], Ottawa: Statistics Canada, Catalogue no. 72-002-XIB (CANSIM Table 281-

0023), (2004).

Storper, M., “The Limits to Globalization: Technology Districts and International Trade,” Economic Geography, 68, (1992), 60 – 93.

Storper, M., “Institutions of the learning economy.” Proceedings of the Conference on

Employment and Growth in the Knowledge-based Economy, Copenhagen, Denmark, (November, 1994).

Storper, M., “The resurgence of regional economic ten years later: the region as a nexus of

untraded interdependencies,” European Urban and Regional Studies, 2, (1995), 191 – 221.


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