We use dummy variables indicating larger regions in both countries. Here we present the regression results computed separately in the two countries. The dependent variable is the entrepreneurship rate as defined as the number of start-ups per 1, employees in a region. All independent variables and control variables with the exception of the binary regional controls were z-standardized to avoid multicollinearity. OLS-regression is the standard analytic method in regional entrepreneurship research, e.
The places MSAs and LADs differ in their population sizes resulting in fewer individual observations from less populated regions in the personality datasets. An unwelcome side effect of these size differences is that the average regional scores of the Big Five traits from which we compute the entrepreneurial-culture indicator are based on different number of participating individuals see for details on this Section 1.
Innovation and Entrepreneurship
Therefore, all regressions are weighted by the number of respondents per region in the personality data set; this procedure gives greater weight to regions with more observations and thus a more precise measurement of the regional traits [ 60 ]. All regressions are weighted by the number of respondents per region in the personality data set, cf. In the next step we test for the hypothesized interaction effects.
Consistent with predictions, in both countries the local entrepreneurship rate was highest when high human capital came together with an entrepreneurial culture Fig 1 and when high industrial diversity came together with an entrepreneurial culture Fig 2. In fact, the positive effects of human capital and industry diversity are substantially weaker or even vanish in regions where the entrepreneurial culture is weak. Fig 3 US and 4 GB compare maps of the entrepreneurship rates Figs 3A and 4A , of the interaction between human capital and entrepreneurial culture Figs 3B and 4B , and of the interaction between industry diversity and entrepreneurial culture Figs 3C and 4C.
The wealthiest region in the US, San Jose—home of Silicon Valley, not only exhibits relatively high entrepreneurship rates but also high levels in both knowledge human capital, industry diversity and entrepreneurial culture. In contrast, regions in the US and GB with a combination of low knowledge and a low entrepreneurial culture exhibit low entrepreneurship rates e. B Fig 3B middle : Interaction groups between human capital and entrepreneurial culture in US regions. C Fig 3C bottom : Interaction groups between industry diversity and entrepreneurial culture in US regions.
Fig 3B should be interpreted as follows: Both variables, human capital and the entrepreneurial culture were splitted at the median.
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Regions in bright have below median values in human capital and the entrepreneurial culture. Regions in light blue are above median in either human capital or the entrepreneurial culture. Regions in dark blue have above the median values in human capital and entrepreneurial culture. Fig 3C is interpreted in the same way as Fig 3B while interaction groups are created for the variables industry diversity and entrepreneurial culture. The shapefile underlying these maps was kindly provided US Census geography. It contains Ordnance Survey data. B Fig 4B middle : Interaction groups between human capital and entrepreneurial culture in GB regions.
C Fig 4C right : Interaction groups between industry diversity and entrepreneurial culture in GB regions. Fig 4B should be interpreted as follows: Both variables, human capital and the entrepreneurial culture were splitted at the median. Fig 4C is interpreted in the same way as Fig 4B while interaction groups are created for the variables industry diversity and entrepreneurial culture.
The shapefile underlying these maps was kindly provided ONS Geography.
It contains Ordnance Survey data: Crown copyright and database right In GB these differences are even more pronounced. We conducted a series of nine robustness checks that consider a alternative personality-based measures of the local culture, b alternative spatial levels, c migration patterns, d representativeness issues regarding age and gender, and e alternative explanations of the findings e. Taken together, these additional tests provide a remarkably consistent picture that supports the statistical validity and robustness of our main findings i.
Although the start-up rate is a widely used and accepted indicator for general entrepreneurial activity [ 21 , 68 ]. An alternative measure focuses on high-impact firms [ 70 ], which has generally been measured as enterprises with exceptional growth [ 97 ]. For example, Henreckson and Sanandaji [ 71 ] use the presence of billionaire entrepreneurs in a cross-country analysis of entrepreneurial activity. For our within-country analyses we use a conceptually related measure: the fastest-growing US firms as listed by Fortune Magazine [ 72 ] and a comparable list of firms with the fastest growth published by the Sunday Times and Virgin for GB Fast Track These additional analyses of firms with exceptional growth underscore the statistical robustness of the knowledge-culture interaction effect, even when considering an alternative measure of entrepreneurship.
Our analyses, which were undertaken in two independent samples in the US and GB , attempted to bridge the two disparate disciplines of economics and psychology by testing the statistical interaction between knowledge and culture in regional entrepreneurship rates.
Our correlational data do not permit causal conclusions but they nonetheless revealed a robust and consistent statistical interaction, one which is consistent with theory and research on the psychological characteristics of entrepreneurs. Moreover, the effect survived a wide variety of robustness checks.
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Hence, even these correlational results can provide candidates to be tested in future research. Our results have several limitations. First, they are based on correlational data and cannot deliver strictly causal evidence. Second, we investigate only two knowledge resources, human capital and diversity of industries, and future studies could consider other measures of knowledge creation e. Third, our study investigates two Western innovation-driven economies. It is unclear whether our results also apply to other economies that are not primarily innovation-driven.
We hypothesize that neither knowledge creation nor the local culture alone are responsible for the entrepreneurial vitality, and subsequent economic prosperity, of a region. Rather, the success of a region in the contemporary globalized, innovation-driven economy may depend on the interplay between culture and knowledge creation. We further hypothesize that this culture-based perspective implies that a substantial amount of existing new knowledge—the potential for economic prosperity—in regions with lower levels of entrepreneurial culture may remain unexploited.
If so, then an entrepreneurial culture might be regarded as a boundary condition for the relationship between knowledge and entrepreneurship. The authors are grateful to Valeriya Mikhaylova and Patrick Schratz for their research assistance. Financial support by the Fritz-Thyssen-Stiftung Az.
Analyzed the data: MO MS.
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Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract In recent years, modern economies have shifted away from being based on physical capital and towards being based on new knowledge e. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Data Availability: The psychological data are from the Gosling-Potter Internet Project and BBC-LAB UK - The PI's in these projects can be contacted to gather these data e.
Introduction Successful and highly performing local economies generally have one thing in common—strong and robust entrepreneurial activity [ 1 , 2 ]. Methods By means of the correlational data we utilize it is possible to determine the degree to which the interaction between knowledge and entrepreneurial culture statistically predicts regional entrepreneurship rates. Entrepreneurial Culture Entrepreneurial Personality Profile In recent years, very big data sets have established the existence of robust regional variation in psychological characteristics; for example, characteristics such as personality and values differ systematically across regions within countries and covary predictably with the economic, social, and institutional parameters of a region [ 18 , 19 ].
Knowledge Resources The economics literature points to two key features of knowledge resources—human capital and industrial structure. Control Variables Beside knowledge and entrepreneurial culture, other regional characteristics can influence entrepreneurial activity. Results Here we present the regression results computed separately in the two countries.
Download: PPT. Table 1. Start-up rate, human capital, industry diversity, entrepreneurial culture, and interactions. Fig 1. Fig 2. Fig 3. Fig 4. Discussion Our analyses, which were undertaken in two independent samples in the US and GB , attempted to bridge the two disparate disciplines of economics and psychology by testing the statistical interaction between knowledge and culture in regional entrepreneurship rates. Supporting Information. S1 Information. References 1. Saxenian A. Regional Advantage.
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