Abstract
The article systematises theoretical approaches to consumer basket choice under dynamic pricing. It substantiates the need to reconsider the traditional view of the consumer basket as a relatively stable consumption structure. The purpose of the study is to generalise theoretical approaches to consumer basket choice in a dynamic pricing environment, distinguish the main analytical interpretations of the consumer basket, and develop an original structural model of consumer basket choice in a digital pricing environment. The methodological framework combines theoretical generalisation, comparative analysis, structural-logical analysis, institutional analysis, and conceptual modelling. The study distinguishes among the normative, statistical, and microeconomic interpretations of the consumer basket and demonstrates that they differ in function, construction logic, and sensitivity to price changes. It is argued that dynamic pricing transforms not only the level of household expenditure but also the mechanism of basket formation. High-frequency price changes, cross-platform price dispersion, price personalisation, reference price effects, search costs, trust, and perceived price fairness generate a new logic of consumer choice in which households continuously adapt their purchasing structure to a volatile digital environment. The article develops an original structural model of the consumer basket choice system under dynamic pricing. The model combines external market conditions, the digital pricing environment, behavioural mechanisms of price perception, and resulting changes in actual consumption behaviour. Its distinctive feature is the inclusion of signalling feedback loops between aggregated user behaviour and platform pricing logic, as well as the distinction among three regimes of actual basket formation: stable, dynamically adaptive, and personalised-asymmetric. The framework also outlines directions for the operationalisation of model variables and for subsequent empirical testing.
References
1. European Central Bank. (2023). Digitalisation and the economy (Discussion Paper Series No. 23). https://www.ecb.europa.eu/pub/pdf/scpdps/ecb.dp23~6b1e40acca.en.pdf
2. Federal Trade Commission. (2025). FTC surveillance pricing study indicates wide range of personal data used to set individualised consumer prices. https://www.ftc.gov/news-events/news/press-releases/2025/01/ftc-surveillance-pricing-study-indicates-wide-range-personal-data-used-set-individualized-consumer
3. International Monetary Fund, International Labour Organization, United Nations Economic Commission for Europe, Eurostat, Organisation for Economic Co-operation and Development, & World Bank. (2025). Consumer price index manual: Theory. https://www.imf.org/en/-/media/files/publications/manuals-and-guides/2025/english/cpimea2025.pdf
4. Cabinet of Ministers of Ukraine. (2016, October 11). Pro zatverdzhennia naboriv produktiv kharchuvannia, naboriv neprodovolchykh tovariv ta naboriv posluh dlia osnovnykh sotsialnykh i demohrafichnykh hrup naselennia [On approval of food, non-food goods, and services baskets for major social and demographic population groups] (Resolution No. 780). https://zakon.rada.gov.ua/go/780-2016-%D0%BF (in Ukrainian)
5. Barylovych, O. M., & Nahorna, O. V. (2024). Osoblyvosti tsinovoi polityky pidpryiemstva u didzhytal-seredovyshchi [Features of enterprise pricing policy in the digital environment]. Efektyvna ekonomika, (2). https://doi.org/10.32702/2307-2105.2024.2.37 (in Ukrainian)
6. Oklander, I. M. (2023). Dynamichne tsinoutvorennia – prohresyvna tendentsiia tsyfrovoho marketynhu [Dynamic pricing as a progressive trend in digital marketing]. Problemy systemnoho pidkhodu v ekonomitsi, 1(90), 37–43. https://doi.org/10.32782/2520-2200/2023-1-5 (in Ukrainian)
7. Lunova, T. S. (2025). Dynamichne tsinoutvorennia yak innovatsiinyi instrument marketynhovoi tsinovoi polityky pidpryiemstva [Dynamic pricing as an innovative instrument of enterprise marketing pricing policy]. Naukovyi visnyk Natsionalnoi akademii statystyky, obliku ta audytu, (1–2). https://doi.org/10.31767/nasoa.1-2-2025.06 (in Ukrainian)
8. Kvasha, S. M., Vakulenko, V. L., Pavlenko, O. M., & Li, Y. (2024). Retrospektyvnyi analiz spozhyvchoho koshyka naselennia ta zminy v spozhyvanni produktiv kharchuvannia naselenniam Ukrainy [Retrospective analysis of the consumer basket and changes in food consumption of the population of Ukraine]. Ekonomichnyi prostir, (190), 330–334. https://doi.org/10.32782/2224-6282/190-59 (in Ukrainian)
9. Zhaldak, H. P., Rekun, S. S., & Kravchenko, V. Ya. (2025). Analitychni aspekty doslidzhennia povedinky spozhyvachiv v umovakh obmezhenosti biudzhetu [Analytical aspects of consumer behavior research under budget constraints]. Ekonomichnyi prostir, (202), 87–96. https://doi.org/10.30838/EP.202.87-96 (in Ukrainian)
10. Kopalle, P. K., Pauwels, K., Akella, L. Y., & Gangwar, M. (2023). Dynamic pricing: Definition, implications for managers, and future research directions. Journal of Retailing, 99(4), 580–593. https://doi.org/10.1016/j.jretai.2023.11.003
11. Ban, G.-Y., & Keskin, N. B. (2021). Personalized dynamic pricing with machine learning: High-dimensional features and heterogeneous elasticity. Management Science, 67(9), 5549–5568. https://doi.org/10.1287/mnsc.2020.3680
12. Prakash, D., & Spann, M. (2022). Dynamic pricing and reference price effects. Journal of Business Research, (152), 300–314. https://doi.org/10.1016/j.jbusres.2022.07.037
13. Shin, D., Vaccari, S., & Zeevi, A. (2023). Dynamic pricing with online reviews. Management Science, 69(2), 824–845. https://doi.org/10.1287/mnsc.2022.4387
14. Dubé, J.-P., & Misra, S. (2023). Personalized pricing and consumer welfare. Journal of Political Economy, 131(1), 131–189. https://doi.org/10.1086/720793
15. Nunan, D., & Di Domenico, M. (2022). Value creation in an algorithmic world: Towards an ethics of dynamic pricing. Journal of Business Research, (150), 451–460. https://doi.org/10.1016/j.jbusres.2022.06.032
16. Chenavaz, R. Y., & Dimitrov, S. (2025). Artificial intelligence and dynamic pricing: A systematic literature review. Journal of Applied Economics, 28(1), 2466140. https://doi.org/10.1080/15140326.2025.2466140
17. Menyhért, B., Cseres-Gergely, Z., Kvedaras, V., Mina, B., Pericoli, F., & Zec, S. (2024). Reference budget-based approach to absolute poverty measurement. In Measuring and monitoring absolute poverty in the European Union (pp. 91–122). Springer. https://doi.org/10.1007/978-3-031-63953-1_4
18. Eurostat. (2024). Harmonised Index of Consumer Prices (HICP): Manual 2024. Publications Office of the European Union. https://doi.org/10.2785/055028
19. Białek, J. (2023). Scanner data and the problem of selecting a price index formula. Central European Review of Economics & Finance, 44(3), 5–20. https://doi.org/10.24136/ceref.2023.011
20. Kiss, R., & Strasser, G. (2024). Inflation heterogeneity across households (ECB Working Paper No. 2898). European Central Bank. https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2898~29405f932f.en.pdf
21. Fox, K. J., Levell, P., & O’Connell, M. (2026). Inflation measurement with high-frequency data. Journal of Business & Economic Statistics, 44(1), 383–396. https://doi.org/10.1080/07350015.2025.2537392
22. Rudevska, V., & Slutskyi, B. (2025). Consumer price index in Ukraine: Methodological gaps and policy implications. Journal of Eastern European and Central Asian Research, 12(1). https://doi.org/10.15549/jeecar.v12i1.2087
23. Aparicio, D., Metzman, Z., & Rigobon, R. (2024). The pricing strategies of online grocery retailers. Quantitative Marketing and Economics, 22(1), 1–21. https://doi.org/10.1007/s11129-023-09273-w
24. 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
25. Wu, M., Ran, Y., & Zhu, S. X. (2022). Optimal pricing strategy: How to sell to strategic consumers? International Journal of Production Economics, (244), 108367. https://doi.org/10.1016/j.ijpe.2021.108367
26. Hufnagel, G., Schwaiger, M., & Weritz, L. (2022). Seeking the perfect price: Consumer responses to personalized price discrimination in e-commerce. Journal of Business Research, (143), 346–365. https://doi.org/10.1016/j.jbusres.2021.10.002
27. Alderighi, M., Nava, C. R., Calabrese, M., Christille, J.-M., & Salvemini, C. B. (2022). Consumer perception of price fairness and dynamic pricing: Evidence from Booking.com. Journal of Business Research, (145), 769–783. https://doi.org/10.1016/j.jbusres.2022.03.017
28. Jiang, Z.-Z., Zhao, J., Yi, Z., Chen, Y.-J., & Li, G. (2025). Pricing in the presence of strategic consumers and social learning under contingent pricing and price guarantee. Production and Operations Management, 34(10), 3063–3081. https://doi.org/10.1177/10591478251329858
29. Spann, M., Bertini, M., Koenigsberg, O., Zeithammer, R., Aparicio, D., Chen, Y., Fantini, F., Jin, G. Z., Morwitz, V. G., Popkowski Leszczyc, P. T. L., Vitorino, M. A., Yalcin Williams, G., & Yoo, H. (2025). Algorithmic pricing: Implications for marketing strategy and regulation. International Journal of Research in Marketing. Advance online publication. https://doi.org/10.1016/j.ijresmar.2025.05.001
30. Xu, L., Wei, Y., & Zhu, Y. (2025). Customer voice on two-sided platforms: The effect of surge pricing on customer complaints. Management Science, 71(8), 6729–6745. https://doi.org/10.1287/mnsc.2024.4992
31. Cachon, G. P., Dizdarer, T., & Tsoukalas, G. (2025). Pricing control and regulation on online service platforms. Management Science. Advance online publication. https://doi.org/10.1287/mnsc.2023.04078
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2026 Artem Chernousov