The Gaidar Institute's Industrial Organization and Infrastructure Economics Department presented a study on the factors behind dynamic and algorithmic pricing in the online segment. Detailed findings were published by Forbes.
The study focused on two segments most sensitive to automation, i.e., marketplaces and passenger air travel market. The analysis involved high-frequency microdata collected from the Wildberries marketplace and a dataset of airline ticket prices obtained from the Yandex Travel aggregator. Monitoring was conducted over an eight-month period, from March to October 2025. An econometric model was constructed for each market, including variables to control for month, day of week, time of day, product or carrier characteristics, as well as macroenvironmental indicators.
The analysis evidenced that ticket prices are higher on tourist and international routes, as well as in regions with higher economic development and smaller populations. This indicates that algorithms take into account the purchasing power of demand and route characteristics, adapting prices to specific consumer groups.
When analyzing the marketplace, price changes were recorded every three hours. The share of sellers using algorithms (marked by a high frequency of price revisions) ranged from 4% to 18% depending on the product category.
The study evidences that algorithms have already become a vital part of the economy: they influence not only prices but also competition. Instead of blanket bans, the study suggests identifying sellers with coincidently changing prices and monitoring sudden deviations in the aviation market. This will allow for the development of effective controls that will protect consumers while preserving the benefits of new technologies.