PROGNOSING CONSUMPTION IN THE DIGITAL ECONOMY: MODERN APPROACHES AND MODELS
Zarikeyeva, Eshimova, Miyasar Maratovna, Sholpan YawmitbaevnaUniversity of Innovation Technologies
ABI
Аннотация
This article explores the theoretical and practical aspects of forecasting consumption volumes in the digital economy. The study analyzes the integration of traditional econometric models with modern digital technologies, specifically Big Data and Machine Learning methods. Ways to improve the accuracy of demand forecasting based on "consumer footprints" generated through digital platforms are highlighted. The article concludes with scientific proposals for optimizing market conditions and efficient resource allocation by forecasting consumption volumes.
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