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Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach / David Pickernell, Paul Jones, Malcolm J. Beynon

Entrepreneurship and Regional Development, Volume: 31, Issue: 1-2, Pages: 82 - 103

Swansea University Author: Paul Jones

Abstract

This study, utilizes an innovative methodological approach, fuzzy-set Qualitative Comparative Analysis (fsQCA), investigating the drivers of heterogeneous geographies characterizing English Local Economic Partnerships (LEPs). The fsQCA technique offers a novel configurational alternative to regressi...

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Published in: Entrepreneurship and Regional Development
ISSN: 0898-5626 1464-5114
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa45361
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spelling 2021-01-19T11:07:38.0316692 v2 45361 2018-11-01 Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach 21e2660aaa102fe36fc981880dd9e082 0000-0003-0417-9143 Paul Jones Paul Jones true false 2018-11-01 BBU This study, utilizes an innovative methodological approach, fuzzy-set Qualitative Comparative Analysis (fsQCA), investigating the drivers of heterogeneous geographies characterizing English Local Economic Partnerships (LEPs). The fsQCA technique offers a novel configurational alternative to regression-based approaches investigating the effects of clustering in conjunction with firm-level innovation, university third-sector activity (TSA) and entrepreneurship, on LEPs innovation performance. The findings, offer contributions to the theories of industrial clusters and innovation, regional innovation systems, knowledge spillovers and entrepreneurial university innovation within LEPs. First, supporting fsQCAs, no individual variable generates either a positive/negative innovation outcome. Second, while all positive innovation recipes include presence of the cluster variable, for negative innovation recipes, only one does not identify absence of clustering as relevant. Given that the cluster variable does not appear in any recipes without at least one of the other variables suggests activity concentration does not exist in isolation to generate innovation outcomes without other localized conditions existing, e.g. firm-level innovation. Third, there is evidence for the non-cluster-based aspects of knowledge spillover theory of entrepreneurship with respect to university activity and the entrepreneurial university concept. Instead, roles of entrepreneurship and university TSA, while important, appear to be more peripheral and geographically context specific. Journal Article Entrepreneurship and Regional Development 31 1-2 82 103 0898-5626 1464-5114 Innovation, clusters, entrepreneurship, LEP, fsQCA 1 1 2019 2019-01-01 10.1080/08985626.2018.1537149 https://www.tandfonline.com/doi/full/10.1080/08985626.2018.1537149 COLLEGE NANME Business COLLEGE CODE BBU Swansea University 2021-01-19T11:07:38.0316692 2018-11-01T08:28:43.2406968 School of Management Business David Pickernell 1 Paul Jones 0000-0003-0417-9143 2 Malcolm J. Beynon 3 0045361-01112018113936.pdf ERDfinalcleancopy(1).pdf 2018-11-01T11:39:36.3070000 Output 1066968 application/pdf Accepted Manuscript true 2020-04-29T00:00:00.0000000 true eng
title Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach
spellingShingle Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach
Paul, Jones
title_short Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach
title_full Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach
title_fullStr Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach
title_full_unstemmed Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach
title_sort Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach
author_id_str_mv 21e2660aaa102fe36fc981880dd9e082
author_id_fullname_str_mv 21e2660aaa102fe36fc981880dd9e082_***_Paul, Jones
author Paul, Jones
author2 David Pickernell
Paul Jones
Malcolm J. Beynon
format Journal article
container_title Entrepreneurship and Regional Development
container_volume 31
container_issue 1-2
container_start_page 82
publishDate 2019
institution Swansea University
issn 0898-5626
1464-5114
doi_str_mv 10.1080/08985626.2018.1537149
college_str School of Management
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hierarchy_parent_id schoolofmanagement
hierarchy_parent_title School of Management
department_str Business{{{_:::_}}}School of Management{{{_:::_}}}Business
url https://www.tandfonline.com/doi/full/10.1080/08985626.2018.1537149
document_store_str 1
active_str 0
description This study, utilizes an innovative methodological approach, fuzzy-set Qualitative Comparative Analysis (fsQCA), investigating the drivers of heterogeneous geographies characterizing English Local Economic Partnerships (LEPs). The fsQCA technique offers a novel configurational alternative to regression-based approaches investigating the effects of clustering in conjunction with firm-level innovation, university third-sector activity (TSA) and entrepreneurship, on LEPs innovation performance. The findings, offer contributions to the theories of industrial clusters and innovation, regional innovation systems, knowledge spillovers and entrepreneurial university innovation within LEPs. First, supporting fsQCAs, no individual variable generates either a positive/negative innovation outcome. Second, while all positive innovation recipes include presence of the cluster variable, for negative innovation recipes, only one does not identify absence of clustering as relevant. Given that the cluster variable does not appear in any recipes without at least one of the other variables suggests activity concentration does not exist in isolation to generate innovation outcomes without other localized conditions existing, e.g. firm-level innovation. Third, there is evidence for the non-cluster-based aspects of knowledge spillover theory of entrepreneurship with respect to university activity and the entrepreneurial university concept. Instead, roles of entrepreneurship and university TSA, while important, appear to be more peripheral and geographically context specific.
published_date 2019-01-01T04:05:58Z
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