AI 中介如何影响零售市场：收入效应与商品组合优化

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Abstract:AI shopping assistants increasingly influence which products consumers consider. We study retail assortment planning under AI mediation, where a retailer chooses a catalog, an AI intermediary forms a customer-facing shortlist, and the customer chooses from that shortlist according to a multinomial logit model. We consider both deterministic mediation, in which the AI follows a fixed segment-specific ranking, and stochastic mediation based on the Plackett-Luce model.
Empirically, we construct a dataset of product rankings from leading AI models, estimate Plackett-Luce ranking models, and evaluate their predictive performance on held-out assortments. Combining these estimates with synthetic customer preferences, we find that accounting for AI mediation can materially change optimal assortments and revenue. Across the tested capacity configurations, ignoring mediation yields mean revenue losses between 2.52% and 11.37% relative to the PL optimum. A much simpler deterministic plug-in, based only on the ordering of fitted AI utilities, performs substantially better, with mean losses of at most 0.53%.
Motivated by this performance, we study assortment optimization under deterministic mediation. We characterize its computational complexity and show that, for any fixed number of customer segments, the problem admits a fully polynomial-time approximation scheme.

Subjects:	Artificial Intelligence (cs.AI); General Economics (econ.GN); Optimization and Control (math.OC)
Cite as:	arXiv:2610.12917 [cs.AI]
	(or arXiv:2610.12917v1 [cs.AI] for this version)
	https://doi.org/10.48550/arXiv.2610.12917 arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Marouane Ibn Brahim [view email]
[v1] Fri, 9 Oct 2026 03:06:18 UTC (173 KB)