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

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  • Emily Bacon

    (Swansea University, Bay Campus)

  • Michael D. Williams

    (Swansea University, Bay Campus)

  • Gareth H. Davies

    (Swansea University, Bay Campus)

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 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.

Suggested Citation

  • Emily Bacon & Michael D. Williams & Gareth H. Davies, 2023. "On the Combinatory Nature of Knowledge Transfer Conditions: A Mixed Method Assessment," Information Systems Frontiers, Springer, vol. 25(3), pages 1039-1061, June.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:3:d:10.1007_s10796-021-10127-7
    DOI: 10.1007/s10796-021-10127-7
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