Features of the Consumer Behavior Model in the Digital Environment

Svetlana D. Suvorova –St. Petersburg Polytechnic University named after Peter the Great (Saint Petersburg, Russia), Oksana M. Kulikova –St. Petersburg State University of Industrial Technology and Design (Saint Petersburg, Russia), Yulia D. Sergiyenko –St. Petersburg State University of Industrial Technology and Design (Saint Petersburg, Russia).
Year: 2026
UDK: 366.1:004
Pages: 20–26
Language: russian
Section: Economics
Keywords: digital environment, price, information, and behavioral factors, consumer habits, consumer behavior model, digital markets
Abstract
The article examines the peculiarities of consumer behavior in the digital environment, which is characterized by high information transparency, the availability of alternatives and the active use of marketplaces. The relevance of the study is due to the development of e-commerce and increased competition in digital markets, which requires a deeper understanding of the factors influencing the purchase decision-making process. Within the framework of this study, the authors proposed a refined definition of the concept of “consumer behavior in the digital environment”, justified the need for a specific classification of interrelated factors (price, information, behavioral), allowing them to systematize their impact on consumer behavior at various stages of making a purchase decision. An algorithm has been developed for a model of consumer behavior in a digital environment, which shows that the process of making a purchase decision is cyclical, rather than linear, as in the traditional model. In conclusion, it is stated that the influence of factors is complex: price factors (price level, special offers, etc.) determine the choice at the stage of evaluating alternatives, informational (reviews, ratings, product descriptions, etc.) – form an idea of the product and reduce uncertainty, and behavioral (experience in using digital services, user habits and others) – ensure the formation of sustainable consumption patterns. The presented algorithm can be used in the development of marketing strategies in digital markets, as well as in the further study of consumer behavior.
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