Mechanisms of consumer adaptation to algorithmic pricing

Algorithmic pricing poses challenges of price non-transparency and dynamics. The paper identifies and classifies the mechanisms of consumer adaptation to algorithmic pricing through integration of motives, practices, and contextual factors, as well as segments consumers based on the patterns revealed. The methodological framework incorporates a comprehensive examination of adaptation from the perspectives of economic theories (Becker’s rational choice, Monroe’s price sensitivity), psychological concepts (Bolton’s fairness theory, Lally’s habits theory), and sociological approaches (Bourdieu’s social capital). The study employs the survey method, latent class analysis (LCA), ANOVA, and multinomial logistic regression. The information base consists of primary survey data obtained in the period of April–May, 2025 from 313 Russian consumers. We have identified three consumer segments with unique adaptive strategies: “digital rationalists” (36%) focused on savings and convenience; “controlling optimizers” (30%) sensitive to prices and striving for fairness; and “discount enthusiasts” (34%), who turn saving into a socialgamifying practice and are motivated by psychological reward. Key determinants of the segmentation include age, income level, place of residence, and digital literacy. The findings contribute to the understanding of non-linear adaptation mechanisms and can be used by companies to adjust pricing algorithms considering consumers’ adaptive practices; by consumers – to enhance awareness and make informed decisions in the digital environment; and by government regulators – to develop measures that protect consumer rights from algorithmic discrimination.