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Bargaining with algorithms: How consumers respond to offers proposed by algorithms versus humans

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  • Shen, Zhengyu
  • Jin, Liyin

Abstract

The rapid integration of artificial intelligence (AI) into negotiations has catalyzed a transformative change in the retail industry. This study analyzes consumer responses to AI negotiators—a scenario becoming more common as retailers employ sophisticated algorithms in negotiation practices. Through five studies spanning B2C, B2B, and C2C negotiations, the findings reveal that consumers tend to make fewer adjustments to their counteroffers when bargaining with algorithms, persuaded of algorithms’ decision-making precision and comprehensive market intelligence. Notably, this confidence in algorithmic accuracy has a disproportionate effect on individuals from lower socioeconomic backgrounds, which can be mitigated by casting doubt on AI's infallibility. These insights do not merely provide retailers with a tactical advantage in utilizing AI for negotiations but also highlight the necessity for a more profound and ethical interaction with technology. Understanding the dynamics of human‒algorithm interaction in negotiation contexts allows retailers and brands to navigate this new terrain with greater efficacy and mindfulness.

Suggested Citation

  • Shen, Zhengyu & Jin, Liyin, 2024. "Bargaining with algorithms: How consumers respond to offers proposed by algorithms versus humans," Journal of Retailing, Elsevier, vol. 100(3), pages 345-361.
    • Handle: RePEc:eee:jouret:v:100:y:2024:i:3:p:345-361
    DOI: 10.1016/j.jretai.2024.05.001
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    References listed on IDEAS

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    Cited by:

    1. Yuhao Fu & Nobuyuki Hanaki & Haitao Wang, 2026. "Do Humans Bargain Differently with AI? Evidence from Alternating-Offer Games," ISER Discussion Paper 1311, Institute of Social and Economic Research, The University of Osaka.

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