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Note: The asterisk(s) before the slash denote(s) if the coefficient is significantly different from zero; the asterisk(s) after the slash indicate(s) if the coefficient is signifi cantly different from the values for Baden (x° test). Asymptotic ¢-values of the coefficient appear in parentheses. ns = no statistically significant estimate of the mode could be attained. *p= .05. **p = 01. TABLE 1. Estimates of the Constant Term and of Output Elasticity of Research and Development (R&D) Input in the Different Regions

Table 1 Note: The asterisk(s) before the slash denote(s) if the coefficient is significantly different from zero; the asterisk(s) after the slash indicate(s) if the coefficient is signifi cantly different from the values for Baden (x° test). Asymptotic ¢-values of the coefficient appear in parentheses. ns = no statistically significant estimate of the mode could be attained. *p= .05. **p = 01. TABLE 1. Estimates of the Constant Term and of Output Elasticity of Research and Development (R&D) Input in the Different Regions

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TABLE 1. Conditions for Higher and Lower Regional Innovation Systems Potential innovation, whereas a competitive culture, individualism, a “not invented here” mentality, and dissension would be typical of nonsystemic, weakly interactive innovation at the regional level. Moving to the organizational level of the firm, those with stronger systemic innovation potential will display trustful labor rela- tions, shopfloor cooperation, and a worker welfare orientation with emphasis on helping workers improve through a mentoring system and an openness to externalizing transactions and knowledge exchange with other firms and organiza- tions with respect to innovation. The weakly systemic firm characteristics would include antagonistic labor relations, workplace division, “sweating,” and a “teach yourself” attitude to worker improvement. Internalization of business functions would be strongly pronounced, and innovativeness might be limited to adaptation. Regarding the organization of governance, the embedded region will display inclusivity, monitoring, consultation, delegation, and networking propensities among its policy makers while the disembedded region will have organizations that tend to be exclusive, reactive, authoritarian, and hierarchical. These characteristics are summarized in Table 1.
TABLE 1. Conditions for Higher and Lower Regional Innovation Systems Potential innovation, whereas a competitive culture, individualism, a “not invented here” mentality, and dissension would be typical of nonsystemic, weakly interactive innovation at the regional level. Moving to the organizational level of the firm, those with stronger systemic innovation potential will display trustful labor rela- tions, shopfloor cooperation, and a worker welfare orientation with emphasis on helping workers improve through a mentoring system and an openness to externalizing transactions and knowledge exchange with other firms and organiza- tions with respect to innovation. The weakly systemic firm characteristics would include antagonistic labor relations, workplace division, “sweating,” and a “teach yourself” attitude to worker improvement. Internalization of business functions would be strongly pronounced, and innovativeness might be limited to adaptation. Regarding the organization of governance, the embedded region will display inclusivity, monitoring, consultation, delegation, and networking propensities among its policy makers while the disembedded region will have organizations that tend to be exclusive, reactive, authoritarian, and hierarchical. These characteristics are summarized in Table 1.
FIGURE 1. Schematic Illustration of the Structuring of Regional Systems of Innovation
FIGURE 1. Schematic Illustration of the Structuring of Regional Systems of Innovation
Source: Eastern Region Biotechnology Initiative (1999). TABLE 2. Shares of Biotechnology and Services Functions
Source: Eastern Region Biotechnology Initiative (1999). TABLE 2. Shares of Biotechnology and Services Functions
Note: SME = small and medium-sized enterprise. TABLE 3. Stylized Assessment of Different Sectoral Innovation Systems
Note: SME = small and medium-sized enterprise. TABLE 3. Stylized Assessment of Different Sectoral Innovation Systems
TABLE 1. Regional Differences in Modes of Technology Transfer *p = 10. **p = 05. ***p = 01.
TABLE 1. Regional Differences in Modes of Technology Transfer *p = 10. **p = 05. ***p = 01.
Source: The last five rows of the table are reproduced from Moore (1996), table 7.12. tp= 10, **p'= (05, ***p'= 01. TABLE 2. Regional Differences in Modes of Technology Acquisition
Source: The last five rows of the table are reproduced from Moore (1996), table 7.12. tp= 10, **p'= (05, ***p'= 01. TABLE 2. Regional Differences in Modes of Technology Acquisition
Note: All differences in proportions are significant at the .05 level except where marked with a supe1 script. a. The proportions are not significantly different between the two regions. TABLE 3. Regional Incidence of Collaborative Activity, by Type of Partner (% of firms)
Note: All differences in proportions are significant at the .05 level except where marked with a supe1 script. a. The proportions are not significantly different between the two regions. TABLE 3. Regional Incidence of Collaborative Activity, by Type of Partner (% of firms)
TABLE 4. Regional Differences in the Importance of Sources of Innovation number of firms involved is not large, this finding almost certainly reflects the lack of R&D facilities in Industrial Heartland subsidiaries or the presence of associated companies whose main R&D centers are located in other parts of Britain. South East subsidiaries, in contrast, are more likely to possess their own internal R&D activity and therefore rate access to group R&D less highly.
TABLE 4. Regional Differences in the Importance of Sources of Innovation number of firms involved is not large, this finding almost certainly reflects the lack of R&D facilities in Industrial Heartland subsidiaries or the presence of associated companies whose main R&D centers are located in other parts of Britain. South East subsidiaries, in contrast, are more likely to possess their own internal R&D activity and therefore rate access to group R&D less highly.
TABLE 4. Continued Note: t-test of the difference in mean values assumes unequal variances. Nonparametric Kruskal-Wallis test on median ranks used. The last three rows were reproduced from Hughes and Wood (1999, 19), table 3. Only statistically significant differences have been reported. *p = 10. **p = .05. ***p = 01.
TABLE 4. Continued Note: t-test of the difference in mean values assumes unequal variances. Nonparametric Kruskal-Wallis test on median ranks used. The last three rows were reproduced from Hughes and Wood (1999, 19), table 3. Only statistically significant differences have been reported. *p = 10. **p = .05. ***p = 01.
TABLE 5. Regional Differences in Objectives of Innovating Firms Note: t-test of the difference in mean values assumes unequal variances. Nonparametric Kruskal-Wallis test on median ranks used. *n — 10. **p = .05.
TABLE 5. Regional Differences in Objectives of Innovating Firms Note: t-test of the difference in mean values assumes unequal variances. Nonparametric Kruskal-Wallis test on median ranks used. *n — 10. **p = .05.
TABLE 6. Regional Differences in Perceived Barriers to Innovation
TABLE 6. Regional Differences in Perceived Barriers to Innovation
TABLE 6. Continued Note: t-test refers to the t-test of the difference in mean values assuming unequal variances. Nonparametric Kruskal-Wallis test on median ranks used. The last row is reported from Hughes and Wood (1999, 20), table 4. Only statistically significant differences have been reported. *p = 10. **p = .05. Athreye, Keeble / UK REGIONAL ECONOMIES
TABLE 6. Continued Note: t-test refers to the t-test of the difference in mean values assuming unequal variances. Nonparametric Kruskal-Wallis test on median ranks used. The last row is reported from Hughes and Wood (1999, 20), table 4. Only statistically significant differences have been reported. *p = 10. **p = .05. Athreye, Keeble / UK REGIONAL ECONOMIES
Note: Numbers in parentheses are the total number of valid responses in each region. The t-test reported assumes unequal variances. The last five rows of the table are reproduced from Kitson and Wilkinson (1996, 26), table 3.5. Only statistically significant differences have been reported. *p'= 10. **p= 05. ***p = :01. TABLE 7. Regional Differences in the Sources of Competitive Advantage
Note: Numbers in parentheses are the total number of valid responses in each region. The t-test reported assumes unequal variances. The last five rows of the table are reproduced from Kitson and Wilkinson (1996, 26), table 3.5. Only statistically significant differences have been reported. *p'= 10. **p= 05. ***p = :01. TABLE 7. Regional Differences in the Sources of Competitive Advantage
TABLE Al. Distribution of Sample of Firms by Region (% of all firms in a region)
TABLE Al. Distribution of Sample of Firms by Region (% of all firms in a region)
TABLE A2. Counties Included in the Two Regional Groupings We separated firms into two groups, innovators and non-innovators, depending on a firm’s response to the following question included in the postal questionnaire. We quote from the questionnaire, including the original emphasis and preface to the actual question:
TABLE A2. Counties Included in the Two Regional Groupings We separated firms into two groups, innovators and non-innovators, depending on a firm’s response to the following question included in the postal questionnaire. We quote from the questionnaire, including the original emphasis and preface to the actual question:
Source: European Regional Innovation Survey. TABLE 1. Metropolitan Innovation Survey
Source: European Regional Innovation Survey. TABLE 1. Metropolitan Innovation Survey
Source: Eurostat (1999) and the Organization for Economic Cooperation and Development (1999). Note: GDP = gross domestic product; R&D = research and development; EPO = European Patent Office. a. Share of patent applications to the EPO owned by foreign residents in total patents invented domestically. b. Share of patent applications to the EPO invented abroad in total patents owned by country residents. TABLE 2. National Innovation System in Comparison
Source: Eurostat (1999) and the Organization for Economic Cooperation and Development (1999). Note: GDP = gross domestic product; R&D = research and development; EPO = European Patent Office. a. Share of patent applications to the EPO owned by foreign residents in total patents invented domestically. b. Share of patent applications to the EPO invented abroad in total patents owned by country residents. TABLE 2. National Innovation System in Comparison
TABLE 3. Metropolitan Innovation Systems in Comparison Source: Eurostat (1999).
TABLE 3. Metropolitan Innovation Systems in Comparison Source: Eurostat (1999).
Source: European Regional Innovation Survey. a. Per 1,000 employees. TABLE 4. Selected Research and Development (R&D) Characteristics of Surveyed Firms in Manufacturing (1994-1996)
Source: European Regional Innovation Survey. a. Per 1,000 employees. TABLE 4. Selected Research and Development (R&D) Characteristics of Surveyed Firms in Manufacturing (1994-1996)
Source: European Regional Innovation Survey. a. Denotes number of new products per 1,000 employees. TABLE 5. Innovation Activities of Surveyed Firms (1994-1996)
Source: European Regional Innovation Survey. a. Denotes number of new products per 1,000 employees. TABLE 5. Innovation Activities of Surveyed Firms (1994-1996)
Source: European Regional Innovation Survey. a. In percentage of all firms. b. In percentage of all cooperating manufacturing firms. TABLE 6. Cooperation Partners of Innovating Manufacturing Firms
Source: European Regional Innovation Survey. a. In percentage of all firms. b. In percentage of all cooperating manufacturing firms. TABLE 6. Cooperation Partners of Innovating Manufacturing Firms
ABLE 7. Geographical Distribution of Cooperation Partners (percentage of cooperating firms) Source: European Regional Innovation Survey. Note: MA = manufacturing firms; PS = producer service firms (the geographic distribution of coop- eration partners is distinguished between manufacturing firms and research institutes); RI = research institutes.
ABLE 7. Geographical Distribution of Cooperation Partners (percentage of cooperating firms) Source: European Regional Innovation Survey. Note: MA = manufacturing firms; PS = producer service firms (the geographic distribution of coop- eration partners is distinguished between manufacturing firms and research institutes); RI = research institutes.
Source: European Regional Innovation Survey. a. Per 1,000 employees. TABLE 8. Selected Research and Development (R&D) Characteristics of Surveyed Firms in Producer Services (1994-1996)
Source: European Regional Innovation Survey. a. Per 1,000 employees. TABLE 8. Selected Research and Development (R&D) Characteristics of Surveyed Firms in Producer Services (1994-1996)
Source: European Regional Innovation Survey. a. Size distribution of firms cooperating with research institutes in percentages. TABLE 9. Cooperation of Research Institutes with Firms
Source: European Regional Innovation Survey. a. Size distribution of firms cooperating with research institutes in percentages. TABLE 9. Cooperation of Research Institutes with Firms
Source: European Regional Innovation Survey. a. Technology fields are in concordance with the ISI classification. b. Percentage of research institutes cooperating intensively in the respective technology field with man- ufacturing firms. c. Percentage of manufacturing firms cooperating intensively in the respective technology field with re- search institutes. TABLE 10. Relevance of Technology Fields for Innovations in Research Institutes and in Manufacturing Firms
Source: European Regional Innovation Survey. a. Technology fields are in concordance with the ISI classification. b. Percentage of research institutes cooperating intensively in the respective technology field with man- ufacturing firms. c. Percentage of manufacturing firms cooperating intensively in the respective technology field with re- search institutes. TABLE 10. Relevance of Technology Fields for Innovations in Research Institutes and in Manufacturing Firms
FIGURE 1. The Spatial Framework Analysis
FIGURE 1. The Spatial Framework Analysis
TABLE 2. Results of Negbin-Regressions of a Knowledge Production Function with Regiona| Dummy Variables Note: Asymptotic t values of the coefficient appear in parentheses. *p =.05. **p = 01.
TABLE 2. Results of Negbin-Regressions of a Knowledge Production Function with Regiona| Dummy Variables Note: Asymptotic t values of the coefficient appear in parentheses. *p =.05. **p = 01.
Note: Asymptotic t-values of the coefficient appear in parentheses. *p=.05,**p= OL, NEGATIVE BINOMIAL REGRESSIONS FOR THE NUMBER OF >ATENTS IN MANUFACTURING ENTERPRISES LOCATED IN SAXONY
Note: Asymptotic t-values of the coefficient appear in parentheses. *p=.05,**p= OL, NEGATIVE BINOMIAL REGRESSIONS FOR THE NUMBER OF >ATENTS IN MANUFACTURING ENTERPRISES LOCATED IN SAXONY
FIGURE 1. Hypothetical Evolution of Two Technological Systems (A and B) in the Spatial Innovation Systems Framework
FIGURE 1. Hypothetical Evolution of Two Technological Systems (A and B) in the Spatial Innovation Systems Framework
TABLE 1. A Typology of Regional Innovation Systems As these ideas are at an experimental stage, the names of the various types of RISs are obviously playful. Among other things, we do not aim to approximate real scales (from stars to candles). The real-world examples we provide are also only suggestive as no in-depth analyses of the places are carried out.
TABLE 1. A Typology of Regional Innovation Systems As these ideas are at an experimental stage, the names of the various types of RISs are obviously playful. Among other things, we do not aim to approximate real scales (from stars to candles). The real-world examples we provide are also only suggestive as no in-depth analyses of the places are carried out.
FIGURE 1. The Combination of Parameters Leading to Geographical Concentration Source: Krugman (199 1b, 498).
FIGURE 1. The Combination of Parameters Leading to Geographical Concentration Source: Krugman (199 1b, 498).
Related topics:
Human GeographyRegion growingNew Economic GeographyEconomic Growth and Regional Inequality
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