Consumer Fairness Perceptions of Human- vs. AI-Driven Dynamic Pricing
(A2026-134080)

AUTHORS

Alexander Hem, Kristiania University College; Anders Mathias Mamen, Kristiania University College

ABSTRACT

This study investigates how consumers evaluate the fairness of dynamic pricing in grocery stores, comparing human-designed algorithms with AI-driven systems. Using data from a U.S. online sample, we find that human-based pricing is perceived as fairer than AI pricing. Transparency mediates this effect, as AI systems are viewed as less transparent. Technological anxiety further shapes responses, with differences between human and AI pricing emerging only among consumers with moderate anxiety levels. Wastefulness with money also moderates perceptions, with the effect of algorithm type on fairness strongest among consumers low in wastefulness. Overall, the results highlight the roles of transparency, cognitive ease, and individual differences in shaping fairness evaluations and offer guidance for retailers adopting AI-driven pricing, such as adding clearer explanations and transparency cues to digital shelf labels.