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  • Bayesian network revealing pathways to workplace innovation and career satisfaction in the public service

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    Panuwatwanich422928-Accepted.pdf (1.078Mb)
    File version
    Accepted Manuscript (AM)
    Author(s)
    Wipulanusat, Warit
    Panuwatwanich, Kriengsak
    Stewart, Rodney A
    Arnold, Stewart L
    Wang, Jue
    Griffith University Author(s)
    Stewart, Rodney A.
    Year published
    2020
    Metadata
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    Abstract
    This paper examined the innovation process in the Australian Public Service (APS) using a Bayesian network (BN) founded on an empirically derived structural equation model. The focus of the BN was to examine the impact of leadership style and organisational culture on workplace innovation and career satisfaction in the APS. Using scenario analysis, the best combination of managerial actions for enhancing APS career satisfaction was determined. The results emphasise the benefit of encouraging management to adopt a transformational leadership style and instilling innovative culture in their organisation. In addition, innovative ...
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    This paper examined the innovation process in the Australian Public Service (APS) using a Bayesian network (BN) founded on an empirically derived structural equation model. The focus of the BN was to examine the impact of leadership style and organisational culture on workplace innovation and career satisfaction in the APS. Using scenario analysis, the best combination of managerial actions for enhancing APS career satisfaction was determined. The results emphasise the benefit of encouraging management to adopt a transformational leadership style and instilling innovative culture in their organisation. In addition, innovative culture was a key driver of workplace innovation, which served to improve the career satisfaction of APS employees. Implications are discussed to propose practical strategies for organisations wish to encourage innovation among employees.
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    Journal Title
    Journal of Management Analytics
    Volume
    7
    Issue
    2
    DOI
    https://doi.org/10.1080/23270012.2020.1749900
    Copyright Statement
    This is an Author's Accepted Manuscript of an article published in Journal of Management Analytics, 7 (2), pp. 253-280, 20 Apr 2020, copyright Taylor & Francis, available online at: https://doi.org/10.1080/23270012.2020.1749900
    Subject
    Information and computing sciences
    Business systems in context
    Human resources and industrial relations
    Strategy, management and organisational behaviour
    Social Sciences
    Social Sciences, Mathematical Methods
    Mathematical Methods In Social Sciences
    innovation
    public sectors
    Publication URI
    http://hdl.handle.net/10072/397581
    Collection
    • Journal articles

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