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Modeling and Analysis of Interorganizational Knowledge Transfer Considering Reputation Mechanisms

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  • Xiaoxia Huang

    (School of Management, Northwestern Polytechnical University, Xi’an 710072, China)

  • Peng Guo

    (School of Management, Northwestern Polytechnical University, Xi’an 710072, China)

  • Xiaonan Wang

    (School of Management, Northwestern Polytechnical University, Xi’an 710072, China)

  • Ding Wang

    (School of Management, Northwestern Polytechnical University, Xi’an 710072, China)

Abstract

Transferring a quantity of credible knowledge is a key sustainable competitive advantage for multi-agent cooperation in an interorganizational network (ION). This study presents simulation research to identify the impacts of reputation mechanisms in interorganizational knowledge transfer through systematic evolutionary game theory, addressing the sustainability of knowledge transfer behaviors in innovation, R&D, and low green carbon. The simulation results showed that an agent’s reputation provides information about having valuable knowledge, which can reduce some of the opportunistic behaviors of knowledge transfer faced by knowledge agents. Regardless of its form, we found that reputation distribution significantly promotes interorganizational knowledge transfer behaviors. In addition, higher reputation thresholds and more significant differences in the impact of high and low reputations prominently contribute to knowledge transfer efficiency and effectiveness. The relationship between reputation mechanisms and the efficiency and effectiveness of knowledge transfer is examined. This study sheds light on the sustainable management of interorganizational projects from reputation mechanisms.

Suggested Citation

  • Xiaoxia Huang & Peng Guo & Xiaonan Wang & Ding Wang, 2021. "Modeling and Analysis of Interorganizational Knowledge Transfer Considering Reputation Mechanisms," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:24:p:14020-:d:706061
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    References listed on IDEAS

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    Cited by:

    1. Rangga Almahendra, 2023. "Disentangling Learning Network Dilemma: A Small-World Effect in a Globalized World," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    2. Stanislav Avsec, 2023. "Design Thinking to Envision More Sustainable Technology-Enhanced Teaching for Effective Knowledge Transfer," Sustainability, MDPI, vol. 15(2), pages 1-26, January.
    3. Shumei Wang & Yaoqun Xu, 2022. "Complex Network-Based Evolutionary Game for Knowledge Transfer of Social E-Commerce Platform Enterprise’s Operation Team under Strategy Imitation Preferences," Sustainability, MDPI, vol. 14(22), pages 1-34, November.

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