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A Contingency Approach to Knowledge Management: Finding the Best Fit

Author

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  • Meliha Handzic

    (International Burch University, Sarajevo, Bosnia and Herzegovina)

  • Kursad Ozlen

    (Pamukkale University, Denizli, Turkey)

  • Nermina Durmic

    (International Burch University, Bosnia and Herzegovina)

Abstract

A contingency perspective of knowledge management recognises the need for a fit between knowledge management solutions (KMS) and decision making contexts which they support. In order to determine the best fit, a field survey was carried out to investigate the impact of two different types of KMS (technical and social) on decision makers' behaviour and performance in different decision contexts (simple and complex). The results provide partial support for the contingency view. As expected, the study identified social KMS as the best fit for complex contexts, based on subjects' superior performance from comparable adoption of both KMS. In contrast, the study identified that both KMS were an equally good fit for simple contexts, based on similar levels of subjects' performance, but social KMS was preferred in terms of adoption. These findings contribute to much needed empirical evidence for research and provide useful guidance for practice. However, their limitations warrant further study.

Suggested Citation

  • Meliha Handzic & Kursad Ozlen & Nermina Durmic, 2016. "A Contingency Approach to Knowledge Management: Finding the Best Fit," International Journal of Knowledge Management (IJKM), IGI Global, vol. 12(1), pages 31-44, January.
    • Handle: RePEc:igg:jkm000:v:12:y:2016:i:1:p:31-44
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    Cited by:

    1. John N. Walsh & Jamie O’Brien, 2017. "A Knowledge-Based Framework for Service Management," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1-31, December.
    2. Dmitry A. Ruban, 2022. "Analytical Review of Conjugation of the Ethical Bases of Artificial Intelligence Implementation and Ecologization in Corporate Governance," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 21(2), pages 390-418.

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