Управленец

2218-5003

2686-7923

10.29141/2218-5003-2025-16-5-5

MCGSYO

https://upravlenets.usue.ru/ru/-2025/1760

Механизмы адаптации потребителей к алгоритмическому ценообразованию

Mechanisms of consumer adaptation to algorithmic pricing

Куркова

Дина Николаевна

Куркова

Дина Николаевна

Kurkova

Dina N.

KurkovaDN@my.msu.ruКурбацкий

Алексей Николаевич

Курбацкий

Алексей Николаевич

Kurbatskii

Aleksey N.

KurbatskiiAN@my.msu.ru

Lomonosov Moscow State University (Moscow, Russia)Московский государственный университет имени М.В. Ломоносова (г. Москва, РФ)

11112025

16567831607202527082025

CC BY-NC 4.0

Алгоритмическое ценообразование создает вызовы ценовой непрозрачности и динамики. Исследование направлено на выявление и классификацию механизмов адаптации потребителей к алгоритмическому ценообразованию через интеграцию мотивов, практик и контекстуальных факторов, а также сегментацию потребителей на основе выявленных паттернов. Методологическая основа работы включает комплексное рассмотрение адаптации с позиций: экономических теорий (рациональный выбор Г. Беккера, ценовая чувствительность К. Монро), психологических концепций (справедливость Л. Болтона, теория привычек Ф. Лалли) и социологических подходов (социальный капитал П. Бурдье). Использованы методы опроса, латентный классовый анализ (LCA), дисперсионный анализ (ANOVA) и мультиноминальная логистическая регрессия. Информационной базой послужили первичные данные анкетирования 313 российских потребителей в период с апреля по май 2025 г. В результате выделены три сегмента потребителей с уникальными адаптивными стратегиями: «цифровые рационалисты» (36 %), ориентированные на экономию и удобство, «контролирующие оптимизаторы» (30 %), чувствительные к ценам и стремящиеся к справедливости, и «скидочные энтузиасты» (34 %), превращающие экономию в социально-игровую практику и мотивированные психологическим вознаграждением. Ключевыми детерминантами сегментации выступили возраст, уровень дохода, место проживания и цифровая грамотность. Результаты вносят вклад в понимание нелинейных механизмов адаптации и могут быть использованы компаниями для корректировки алгоритмов ценообразования с учетом адаптивных практик потребителей; потребителями – для повышения осведомленности и принятия осознанных решений в цифровой среде; органами государственного регулирования – для разработки мер по защите прав потребителей от алгоритмической дискриминации.

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.

алгоритмическое ценообразование;адаптация потребителей;цифровая адаптация;адаптивные практики;поведенческая сегментация.

algorithmic pricing;consumer adaptation;digital adaptation;adaptive practices;behavioural segmentation.

Исследование выполнено при финансовой поддержке Российского научного фонда в рамках гранта № 25-18-00319 «Экономико-демографический анализ качества жизни населения в России».

The study was funded by the Russian Science Foundation, project No. 25-18-00319 “Economic and demographic analysis of the population’s quality of life in Russia”.

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