Journal article 276 views 76 downloads
A panel fsQCA investigation on European regional innovation
Technological Forecasting and Social Change, Volume: 199, Start page: 123042
Swansea University Authors: David Pickernell , Paul Jones
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DOI (Published version): 10.1016/j.techfore.2023.123042
Abstract
Taking an evolutionary economic geography perspective, we build on literature on innovation modes, the aim of this study being to explain variations in SME innovation performance across European regions over time. Drawing on five waves of data from the EU Regional Innovation Scoreboard between 2011...
Published in: | Technological Forecasting and Social Change |
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ISSN: | 0040-1625 1873-5509 |
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Elsevier BV
2024
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URI: | https://cronfa.swan.ac.uk/Record/cronfa65067 |
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2024-11-25T14:15:18Z |
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2024-04-10T10:00:37.6675356 v2 65067 2023-11-22 A panel fsQCA investigation on European regional innovation 913bd73da00d7df4f5038f6f144b235e 0000-0003-0912-095X David Pickernell David Pickernell true false 21e2660aaa102fe36fc981880dd9e082 0000-0003-0417-9143 Paul Jones Paul Jones true false 2023-11-22 CBAE Taking an evolutionary economic geography perspective, we build on literature on innovation modes, the aim of this study being to explain variations in SME innovation performance across European regions over time. Drawing on five waves of data from the EU Regional Innovation Scoreboard between 2011 and 2019, our sample includes 221 regions across 27 EU Member States, as well as Norway, UK, Serbia, and Switzerland. We apply nascent panel fuzzy-set Qualitative Comparative Analysis to explore how different combinations of SME innovation modes explain innovation performance across different EU regions (i.e. geographical scope) as well as within different EU regions over time (i.e. temporal stability). Findings show that whether DUI or STI modes are more effective in the context of SMEs crucially depends on the timeframe considered, but also the geographical location of SMEs. The study offers novel insights into the diverse and complex nature through which regional innovation evolves over time, advancing understanding on regionalization as well as temporality of SME innovation modes in Europe. It also provides an important basis for discussing innovation policy across Europe. Journal Article Technological Forecasting and Social Change 199 123042 Elsevier BV 0040-1625 1873-5509 STI, DUI innovation modes, Europe, Regions, Policy, Panel fsQCA 1 2 2024 2024-02-01 10.1016/j.techfore.2023.123042 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University SU Library paid the OA fee (TA Institutional Deal) Swansea University 2024-04-10T10:00:37.6675356 2023-11-22T10:04:40.8290873 Faculty of Humanities and Social Sciences School of Management - Business Management Malcolm Beynon 1 David Pickernell 0000-0003-0912-095X 2 Martina Battisti 3 Paul Jones 0000-0003-0417-9143 4 65067__29260__a0f3deab998b482aa7e6db9256ede7ec.pdf 65067.VOR.pdf 2023-12-13T14:23:49.7378431 Output 2631155 application/pdf Version of Record true © 2023 The Author(s). Published by Elsevier Inc. Distributed under the terms of a Creative Commons Attribution 4.0 International License (CC BY 4.0). true eng https://creativecommons.org/licenses/by/4.0/ |
title |
A panel fsQCA investigation on European regional innovation |
spellingShingle |
A panel fsQCA investigation on European regional innovation David Pickernell Paul Jones |
title_short |
A panel fsQCA investigation on European regional innovation |
title_full |
A panel fsQCA investigation on European regional innovation |
title_fullStr |
A panel fsQCA investigation on European regional innovation |
title_full_unstemmed |
A panel fsQCA investigation on European regional innovation |
title_sort |
A panel fsQCA investigation on European regional innovation |
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913bd73da00d7df4f5038f6f144b235e 21e2660aaa102fe36fc981880dd9e082 |
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913bd73da00d7df4f5038f6f144b235e_***_David Pickernell 21e2660aaa102fe36fc981880dd9e082_***_Paul Jones |
author |
David Pickernell Paul Jones |
author2 |
Malcolm Beynon David Pickernell Martina Battisti Paul Jones |
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Journal article |
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Technological Forecasting and Social Change |
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199 |
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Swansea University |
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0040-1625 1873-5509 |
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10.1016/j.techfore.2023.123042 |
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Elsevier BV |
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description |
Taking an evolutionary economic geography perspective, we build on literature on innovation modes, the aim of this study being to explain variations in SME innovation performance across European regions over time. Drawing on five waves of data from the EU Regional Innovation Scoreboard between 2011 and 2019, our sample includes 221 regions across 27 EU Member States, as well as Norway, UK, Serbia, and Switzerland. We apply nascent panel fuzzy-set Qualitative Comparative Analysis to explore how different combinations of SME innovation modes explain innovation performance across different EU regions (i.e. geographical scope) as well as within different EU regions over time (i.e. temporal stability). Findings show that whether DUI or STI modes are more effective in the context of SMEs crucially depends on the timeframe considered, but also the geographical location of SMEs. The study offers novel insights into the diverse and complex nature through which regional innovation evolves over time, advancing understanding on regionalization as well as temporality of SME innovation modes in Europe. It also provides an important basis for discussing innovation policy across Europe. |
published_date |
2024-02-01T14:29:22Z |
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