Demographic Pricing in the Digital Age: Assessing Fairness Perceptions in Algorithmic versus Human-Based Price Discrimination

Advancements in data analytics and increased access to consumer data have revolutionized companies’ price discrimination capabilities. These technological advancements have not only changed how prices are determined but also who determines them, with companies increasingly relying on algorithms rather than humans to set prices. We examine consumers’ fairness perceptions of demographic price discrimination—a prevalent yet controversial practice that can trigger considerable consumer backlash—and find that it depends on who is responsible for setting prices. Consumers view demographic-based price discrimination as more fair when prices are determined by algorithms (vs. humans), which is driven by consumers feeling less judged by algorithms than by people, and believing algorithms’ decisions are less exploitative and more justified. Accordingly, we find that consumers’ favorable evaluations of algorithmic pricing attenuate under a more common and less contentious form of price discrimination (i.e., temporal-based) and when the price discrimination serves a prosocial goal.