Exploring Consumer Perceptions of Fairness in Human-Developed vs. AI-Based Pricing Algorithms
(A2025-125851)

AUTHORS

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

ABSTRACT

This study investigates consumer perceptions of price fairness in the context of dynamic pricing by comparing human-designed algorithms to AI-driven algorithms. We propose that human developed algorithms are perceived as fairer due to their relative transparency. Using a sample of 600 English Premier League fans, our findings show that participants rate human algorithms significantly fairer than AI-driven ones. Transparency mediates this relationship, with AI algorithms being perceived as less transparent. Technology anxiety further moderates perceptions, with low-anxiety consumers favoring human algorithms, while high-anxiety individuals show reduced differentiation. These results suggest that simplifying interfaces and enhancing transparency could mitigate fairness concerns in AI pricing. Our research provides theoretical insights into algorithmic pricing and practical implications for businesses adopting AI systems.