On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment

Bacon, Emily; Williams, Michael; Davies, Gareth

doi:10.1007/s10796-021-10127-7

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On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment

Emily Bacon

, Michael Williams, Gareth Davies

Information Systems Frontiers, Volume: 25, Issue: 3

Swansea University Authors: Emily Bacon , Michael Williams, Gareth Davies

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DOI (Published version): 10.1007/s10796-021-10127-7

Abstract

Organisations are increasingly creating inter-organisational ecosystem partnerships to innovate openly. Despite effective knowledge management significantly supporting ecosystem infrastructures, empirical insights into the importance of and interdependencies between conditions for successful knowled...

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Published in:	Information Systems Frontiers
ISSN:	1387-3326 1572-9419
Published:	Springer Science and Business Media LLC 2021
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa56601
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first_indexed	2021-03-29T15:12:33Z
last_indexed	2023-01-11T14:35:55Z
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spelling	v2 56601 2021-03-29 On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment a14bd1b9041528e38772df1b50a59e3b 0000-0001-9933-3902 Emily Bacon Emily Bacon true false 075aa59a486ba89485d9068decf7814b Michael Williams Michael Williams true false 0fa6da2da22b7dce598291b581746188 0000-0001-7872-7574 Gareth Davies Gareth Davies true false 2021-03-29 BBU Organisations are increasingly creating inter-organisational ecosystem partnerships to innovate openly. Despite effective knowledge management significantly supporting ecosystem infrastructures, empirical insights into the importance of and interdependencies between conditions for successful knowledge exchange across ecosystem contexts remain unexplored within existing literature. This study implements a mixed-method approach to ascertain which conditions are responsible for knowledge transfer success across innovation ecosystems. Interpretive Structural Modelling was employed to analyse questionnaires with key ecosystem stakeholders, in order to impose a hierarchical structure upon the conditions. The configurational nature of these conditions, and their combinations into solutions for success was ascertained through analysing semi-structured interviews using fuzzy-set Qualitative Comparative Analysis. Results reveal multiple, mutually exclusive pathways to knowledge transfer success, grouped into three solution types, increasing understanding of the interrelated nature of the knowledge transfer conditions. Limitations and implications for future research are provided. Journal Article Information Systems Frontiers 25 3 Springer Science and Business Media LLC 1387-3326 1572-9419 Digital transformation; FsQCA; ISM; Ecosystem; Innovation; Knowledge transfer 13 4 2021 2021-04-13 10.1007/s10796-021-10127-7 COLLEGE NANME Business COLLEGE CODE BBU Swansea University 2023-07-11T14:39:32.0769970 2021-03-29T16:11:01.1911573 Faculty of Humanities and Social Sciences School of Management - Business Management Emily Bacon 0000-0001-9933-3902 1 Michael Williams 2 Gareth Davies 0000-0001-7872-7574 3 56601__19667__2a8bd747b09b483b8d67199d1e1cf535.pdf 56601.pdf 2021-04-16T18:13:23.4693210 Output 1651845 application/pdf Version of Record true ©The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/
title	On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment
spellingShingle	On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment Emily Bacon Michael Williams Gareth Davies
title_short	On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment
title_full	On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment
title_fullStr	On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment
title_full_unstemmed	On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment
title_sort	On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment
author_id_str_mv	a14bd1b9041528e38772df1b50a59e3b 075aa59a486ba89485d9068decf7814b 0fa6da2da22b7dce598291b581746188
author_id_fullname_str_mv	a14bd1b9041528e38772df1b50a59e3b_*_Emily Bacon 075aa59a486ba89485d9068decf7814b__Michael Williams 0fa6da2da22b7dce598291b581746188_**_Gareth Davies
author	Emily Bacon Michael Williams Gareth Davies
author2	Emily Bacon Michael Williams Gareth Davies
format	Journal article
container_title	Information Systems Frontiers
container_volume	25
container_issue	3
publishDate	2021
institution	Swansea University
issn	1387-3326 1572-9419
doi_str_mv	10.1007/s10796-021-10127-7
publisher	Springer Science and Business Media LLC
college_str	Faculty of Humanities and Social Sciences
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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
document_store_str	1
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description	Organisations are increasingly creating inter-organisational ecosystem partnerships to innovate openly. Despite effective knowledge management significantly supporting ecosystem infrastructures, empirical insights into the importance of and interdependencies between conditions for successful knowledge exchange across ecosystem contexts remain unexplored within existing literature. This study implements a mixed-method approach to ascertain which conditions are responsible for knowledge transfer success across innovation ecosystems. Interpretive Structural Modelling was employed to analyse questionnaires with key ecosystem stakeholders, in order to impose a hierarchical structure upon the conditions. The configurational nature of these conditions, and their combinations into solutions for success was ascertained through analysing semi-structured interviews using fuzzy-set Qualitative Comparative Analysis. Results reveal multiple, mutually exclusive pathways to knowledge transfer success, grouped into three solution types, increasing understanding of the interrelated nature of the knowledge transfer conditions. Limitations and implications for future research are provided.
published_date	2021-04-13T14:39:28Z
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On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment

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