Dynamic Pricing in Digital Environments
A Review of its Evolution and Impact on Consumers’ Perceptions of Value, Fairness and Trust
Keywords:
dynamic pricing, consumer behavior, perceived fairness, trust, e-commerceAbstract
The growth of e-commerce, the availability of transactional and behavioral data, and the automation of commercial decisions have intensified the use of dynamic pricing strategies. Although these practices have a long tradition in revenue management, their expansion into digital retail environments raises new questions about their impact on consumer behavior. This article presents a narrative literature review on dynamic pricing, perceived fairness, trust, and algorithmic pricing. The review shows that the discussion cannot be limited to the economic efficiency of adjusting prices according to demand, inventory, or competition: it must also consider how consumers interpret the legitimacy of the pricing process. The literature suggests that price variations may be accepted when they are perceived as coherent, explainable, and linked to recognizable market conditions; however, they may generate resistance when perceived as discriminatory, opaque, or abusive. The article concludes that the implementation of dynamic pricing in e-commerce requires the integration of economic, behavioral, and ethical criteria, particularly when algorithms or personal data are involved.
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References
Bitran, G. & Caldentey, R. (2003). An overview of pricing models for revenue management. Manufacturing & Service Operations Management, 5(3), 203-229. https://doi.org/10.1287/msom.5.3.203.16031
Bolton, L. E., Warlop, L. & Alba, J. W. (2003). Consumer perceptions of Price (un)fairness. Journal of Consumer Research, 29(4), 474-491. https://doi.org/10.1086/346244
Calvano, E., Calzolari, G., Denicolò, V. & Pastorello, S. (2020). Artificial intelligence, algorithmic pricing, and collusion. American Economic Review, 110(10), 3267-3297. https://doi.org/10.1257/aer.20190623
Campbell, M. C. (1999). Perceptions of price unfairness: Antecedents and consequences. Journal of Marketing Research, 36(2), 187-199. https://doi.org/10.1177/002224379903600204
den Boer, A. V. (2015). Dynamic pricing and learning: Historical origins, current research, and new directions. Surveys in Operations Research and Management Science, 20(1), 1-18. https://doi.org/10.1016/j.sorms.2015.03.001
Elmaghraby, W. & Keskinocak, P. (2003). Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions. Management Science, 49(10), 1287-1309. https://doi.org/10.1287/mnsc.49.10.1287.17315
European Commission. (2018). Consumer market study on online market segmentation through personalised pricing/offers in the European Union. Directorate-General for Justice and Consumers. https://commission.europa.eu/publications/consumer-market-study-online-market-segmentation-through-personalised-pricingoffers-european-union_en
Garbarino, E. & Lee, O. F. (2003). Dynamic pricing in internet retail: Effects on consumer trust. Psychology & Marketing, 20(6), 495-513. https://doi.org/10.1002/mar.10084
Haws, K. L. & Bearden, W. O. (2006). Dynamic pricing and consumer fairness perceptions. Journal of Consumer Research, 33(3), 304-311. https://doi.org/10.1086/508435
Huang, J.-H., Chang, C.-T. & Chen, C. Y.-H. (2005). Perceived fairness of pricing on the Internet. Journal of Economic Psychology, 26(3), 343-361. https://doi.org/10.1016/j.joep.2004.04.001
Kahneman, D., Knetsch, J. L. & Thaler, R. H. (1986). Fairness as a constraint on profit seeking: Entitlements in the market. American Economic Review, 76(4), 728-741.
Kimes, S. E. (1994). Perceived fairness of yield management. Cornell Hotel and Restaurant Administration Quarterly, 35(1), 22-29. https://doi.org/10.1016/0010-8804(94)90041-8
Narahari, Y., Raju, C. V. L., Ravikumar, K. & Shah, S. (2005). Dynamic pricing models for electronic business. Sādhanā, 30(2-3), 231-256. https://doi.org/10.1007/BF02706246
OECD. (2018). Personalised pricing in the digital era. OECD Competition Committee. https://doi.org/10.1787/db4d9c9c-en
OECD. (2021). The effects of online disclosure about personalised pricing on consumers: Results from a lab experiment in Ireland and Chile. OECD Digital Economy Papers, 303. https://doi.org/10.1787/1ce1de63-en
Talluri, K. T. & Van Ryzin, G. J. (2004). The theory and practice of revenue management. Springer.
Thaler, R. H. (1985). Mental accounting and consumer choice. Marketing Science, 4(3), 199-214. https://doi.org/10.1287/mksc.4.3.199
Vomberg, A., Homburg, C. & Sarantopoulos, P. (2025). Algorithmic pricing: Effects on consumer trust and price search. International Journal of Research in Marketing, 42(4), 1166-1186. https://doi.org/10.1016/j.ijresmar.2024.10.006
Xia, L., Monroe, K. B. & Cox, J. L. (2004). The price is unfair! A conceptual framework of price fairness perceptions. Journal of Marketing, 68(4), 1-15. https://doi.org/10.1509/jmkg.68.4.1.42733
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22. https://doi.org/10.1177/002224298805200302
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