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Evolutionary analysis of platform–influencer–consumer interactions in livestreaming commerce

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  • Zhang, Ziye
  • Li, Zhiyuan
  • Wang, Tianfu
  • Guo, Kai

Abstract

This study examines trust mechanisms and strategic behaviors in livestreaming commerce employing evolutionary game theory. We construct a tripartite model to analyze interactions between platforms, influencers, and consumers to examine monitoring strategies, promotional authenticity, and purchase decisions. Using replicator dynamics and stability analysis, we identify three evolutionary stable strategies and reveal that system stability depends on monitoring costs, reputational effects, and trust-based utility gains. The findings demonstrate how calibrated incentive mechanisms and regulatory frameworks can foster sustainable ecosystem development, contributing to digital commerce governance literature.

Suggested Citation

  • Zhang, Ziye & Li, Zhiyuan & Wang, Tianfu & Guo, Kai, 2025. "Evolutionary analysis of platform–influencer–consumer interactions in livestreaming commerce," Finance Research Letters, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:finlet:v:81:y:2025:i:c:s1544612325004271
    DOI: 10.1016/j.frl.2025.107164
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    JEL classification:

    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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