Journal article 1138 views 267 downloads
Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach
Entrepreneurship and Regional Development, Volume: 31, Issue: 1-2, Pages: 82 - 103
Swansea University Authors: David Pickernell , Paul Jones
-
PDF | Accepted Manuscript
Download (1022.86KB)
DOI (Published version): 10.1080/08985626.2018.1537149
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...
Published in: | Entrepreneurship and Regional Development |
---|---|
ISSN: | 0898-5626 1464-5114 |
Published: |
2019
|
Online Access: |
Check full text
|
URI: | https://cronfa.swan.ac.uk/Record/cronfa45361 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
first_indexed |
2018-11-01T14:18:10Z |
---|---|
last_indexed |
2021-01-20T04:07:26Z |
id |
cronfa45361 |
recordtype |
SURis |
fullrecord |
<?xml version="1.0"?><rfc1807><datestamp>2021-01-19T11:07:38.0316692</datestamp><bib-version>v2</bib-version><id>45361</id><entry>2018-11-01</entry><title>Innovation performance and the role of clustering at the local enterprise level: a fuzzy-set qualitative comparative analysis approach</title><swanseaauthors><author><sid>913bd73da00d7df4f5038f6f144b235e</sid><ORCID>0000-0003-0912-095X</ORCID><firstname>David</firstname><surname>Pickernell</surname><name>David Pickernell</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>21e2660aaa102fe36fc981880dd9e082</sid><ORCID>0000-0003-0417-9143</ORCID><firstname>Paul</firstname><surname>Jones</surname><name>Paul Jones</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2018-11-01</date><deptcode>BBU</deptcode><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 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.</abstract><type>Journal Article</type><journal>Entrepreneurship and Regional Development</journal><volume>31</volume><journalNumber>1-2</journalNumber><paginationStart>82</paginationStart><paginationEnd>103</paginationEnd><publisher/><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0898-5626</issnPrint><issnElectronic>1464-5114</issnElectronic><keywords>Innovation, clusters, entrepreneurship, LEP, fsQCA</keywords><publishedDay>1</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2019</publishedYear><publishedDate>2019-01-01</publishedDate><doi>10.1080/08985626.2018.1537149</doi><url>https://www.tandfonline.com/doi/full/10.1080/08985626.2018.1537149</url><notes/><college>COLLEGE NANME</college><department>Business</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>BBU</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2021-01-19T11:07:38.0316692</lastEdited><Created>2018-11-01T08:28:43.2406968</Created><path><level id="1">Faculty of Humanities and Social Sciences</level><level id="2">School of Management - Business Management</level></path><authors><author><firstname>David</firstname><surname>Pickernell</surname><orcid>0000-0003-0912-095X</orcid><order>1</order></author><author><firstname>David</firstname><surname>Pickernell</surname><order>2</order></author><author><firstname>Paul</firstname><surname>Jones</surname><orcid>0000-0003-0417-9143</orcid><order>3</order></author><author><firstname>Malcolm J.</firstname><surname>Beynon</surname><order>4</order></author></authors><documents><document><filename>0045361-01112018113936.pdf</filename><originalFilename>ERDfinalcleancopy(1).pdf</originalFilename><uploaded>2018-11-01T11:39:36.3070000</uploaded><type>Output</type><contentLength>1066968</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><embargoDate>2020-04-29T00:00:00.0000000</embargoDate><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents><OutputDurs/></rfc1807> |
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 913bd73da00d7df4f5038f6f144b235e 0000-0003-0912-095X David Pickernell David Pickernell true false 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 Faculty of Humanities and Social Sciences School of Management - Business Management David Pickernell 0000-0003-0912-095X 1 David Pickernell 2 Paul Jones 0000-0003-0417-9143 3 Malcolm J. Beynon 4 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 David Pickernell 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 |
913bd73da00d7df4f5038f6f144b235e 21e2660aaa102fe36fc981880dd9e082 |
author_id_fullname_str_mv |
913bd73da00d7df4f5038f6f144b235e_***_David Pickernell 21e2660aaa102fe36fc981880dd9e082_***_Paul Jones |
author |
David Pickernell Paul Jones |
author2 |
David Pickernell 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 |
Faculty of Humanities and Social Sciences |
hierarchytype |
|
hierarchy_top_id |
facultyofhumanitiesandsocialsciences |
hierarchy_top_title |
Faculty of Humanities and Social Sciences |
hierarchy_parent_id |
facultyofhumanitiesandsocialsciences |
hierarchy_parent_title |
Faculty of Humanities and Social Sciences |
department_str |
School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management |
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 |
2019-01-01T03:57:08Z |
_version_ |
1763752886700867584 |
score |
11.037581 |