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Can Gen-AI promote community group buying? A tripartite evolutionary game analysis

Author

Listed:
  • Zhou, Fuli
  • Zhang, Chenchen
  • Tiwari, Sunil
  • Huang, Xingjun
  • Basu, Preetam

Abstract

As a new retail model, community group buying (CGB) quickly caught consumers' attention with its relatively preferential prices and high delivery efficiency. However, issues such as delayed response and unsatisfactory after-sales service have severely plagued the further development of CGB. Generative AI (Gen-AI), as a disruptive innovation of artificial intelligence, offers significant potential for CGB promotion due to its excellent performance. This paper endeavors to introduce Gen-AI to the CGB scenario, and a tripartite evolutionary game model is formulated to help better understand the stakeholders' behavior including the supplier, CGB platform, and group leaders. The evolutionary stable strategies of participants under different constraints are scrutinized, which assists in exploring the impact of Gen-AI empowerment on the decision strategies of the three involved parties. Besides, simulation experiments are performed to investigate the impact of different parameter changes on the game's tripartite decisions. Results indicate that the costs, profits, and potential risks associated with Gen-AI empowerment are crucial considerations for the supplier and platform. Moreover, even with Gen-AI empowerment, the platform's revenue may decline if customers reduce their purchase frequency due to passive service from the group leader. As a result, the platform is more inclined to adopt Gen-AI empowerment when the group leader provides active service.

Suggested Citation

  • Zhou, Fuli & Zhang, Chenchen & Tiwari, Sunil & Huang, Xingjun & Basu, Preetam, 2026. "Can Gen-AI promote community group buying? A tripartite evolutionary game analysis," International Journal of Production Economics, Elsevier, vol. 291(C).
    • Handle: RePEc:eee:proeco:v:291:y:2026:i:c:s0925527325002063
    DOI: 10.1016/j.ijpe.2025.109721
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