Generative AI in retail platform operations: Considering supplier effort exertion and consumer skepticism

In recent years, a growing number of retail platforms have integrated generative artificial intelligence (GAI) technology into their operations, as exemplified by Amazon’s GAI-powered “Rufus” shopping assistant and JD.com’s “JD Jingyan” intelligent recommendation system. However, alongside the proliferation of AI applications, some consumers have grown skeptical about the reliability of GAI. Against this backdrop, it remains unclear whether retail platforms should adopt GAI and what impacts such adoption may exert on heterogeneous suppliers, consumer surplus, and social welfare. To investigate these issues, this paper develops theoretical stylized models and derives some key managerial implications. The findings indicate that the retail platform will inevitably adopt GAI, as any suppliers who make efforts to effectively utilize GAI will benefit the platform. Moreover, when the proportion of GAI-skeptical consumers is relatively small or the effort cost is sufficiently low, one supplier’s investment in GAI utilization compels the rival to follow suit, leading to mutual effort exertion as the Nash equilibrium. Conversely, one supplier’s effort will induce its competitor to enter the market without exerting effort, resulting in a Nash equilibrium where only one supplier invests in GAI utilization. Besides, a brand supplier is more likely to exert effort in leveraging GAI and exerts more efforts than an ordinary supplier, particularly when market competition intensifies. While the ordinary supplier may only outperform the brand supplier in effort when market competition is relatively subdued. Finally, we demonstrate that GAI adoption ultimately enhances both consumer surplus and social welfare.