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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

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

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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
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URI: https://cronfa.swan.ac.uk/Record/cronfa56601
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first_indexed 2021-03-29T15:12:33Z
last_indexed 2021-10-30T03:20:33Z
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spelling 2021-10-29T18:05:02.9821695 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 0 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 2021-10-29T18:05:02.9821695 2021-03-29T16:11:01.1911573 School of Management Business 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 ┬ęThe 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
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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
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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 School of Management
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hierarchy_top_title School of Management
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hierarchy_parent_title School of Management
department_str Business{{{_:::_}}}School of Management{{{_:::_}}}Business
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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 2021-04-13T04:12:19Z
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