Knowledge Based Entrepreneurship and Regional Economic Performance

2009 ◽  
pp. 65-75 ◽  
Author(s):  
David B. Audretsch ◽  
Werner Bönte ◽  
Max Keilbach
Keyword(s):  
Economic Performance ◽  
Regional Economic ◽  
Knowledge Based ◽  
Regional Economic Performance

Illusions of Clustering: A Systematic Evaluation on the Effects of Clusters on Regional Economic Performance in Korea

2021 ◽  
pp. 016001762110187
Author(s):  
Hyunha Shin ◽  
Junseok Hwang
Keyword(s):  
Economic Growth ◽  
Economic Performance ◽  
Local Governments ◽  
Regression Models ◽  
Regional Growth ◽  
Systematic Evaluation ◽  
Regional Innovation ◽  
Regional Economic ◽  
Pca Method ◽  
Regional Economic Performance

Korea has pursued a cluster-based policy to increase industrial competitiveness and to alleviate development gaps between the regions. However, local governments have often oversupplied clusters without an objective examination of the demands and conditions in the regions. Based on these concerns, this study analyses effects and interdependencies of factors related to regional innovation and growth in Korea. Employing a PCA method and a GLS regression models on panel data, we generated three composite factors, social, capacity, and clustering, and estimated their effects on regional economic performance. The results show that it is important to have a favorable socio-economic setting to foster growth by clusters. In addition, cluster-based policies may have weaker effects than expected, because the effect of R&D capacity on regional growth was stronger and longer lasting. Finally, some specific elements that most affected economic growth in Korea’s regions are identified. The overall results indicate favorable environments should be established beforehand to foster regional growth with clusters, which confirms “jobs follow people.”

Societal impact of university innovation

2018 ◽  
Vol 41 (11) ◽  
pp. 1309-1335 ◽  
Author(s):  
Benjamin Yeo
Keyword(s):  
Economic Performance ◽  
Significant Proportion ◽  
Economic Data ◽  
Regional Economic ◽  
Content Type ◽  
Economic Productivity ◽  
Multiple Variables ◽  
Regional Economic Performance ◽  
The Impact ◽  
University Patent

PurposeThis study aims to use university patent and regional economic data to investigate the current and future impact of university innovation, measured using multiple variables, on real economic productivity.Design/methodology/approachUsing university patent and regional economic data, regression models are built to determine the impact of university innovation on current and future regional economic performance.FindingsThe findings demonstrate that university innovation generates sustained impact on economic performance, but by itself, is insufficient in driving economic performance; and different measures of university innovation have different degrees of impact. University innovation makes up a small, albeit significant, proportion of the drivers of economic performance.Research limitations/implicationsThere are four implications. First, developing countries can leverage university–industry collaborations for economic growth. Second, innovation management must encourage continuous university innovation for sustainable economic productivity. Third, Science, Technology, Engineering and Mathematics (STEM) and non-STEM innovation warrant attention. Fourth, successful innovation policies should be tailored to their unique societal contexts.Originality/valueAlthough innovation is a driver of economic performance, there is a lack of studies that focus specifically on universities, operationalize performance using gross domestic product measures and take into account impact lags by exploring universities’ current and future impacts.

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