Adaptive Management of Personalised Demand Based on Synergetic Interaction of Digital Retail Ecosystems

The contemporary paradigm of consumer demand is characterised by a transition from the industrial model of mass consumption to the economy of individualised solutions. In this context, retail enterprises face the challenge of not only forecasting demand but also ensuring the operational delivery of personalised value to the end consumer in real time. This determines the relevance of the present study, which is aimed at bridging the gap between the forecasting of personalised demand and its operational implementation. The aim of the research is to develop an adaptive management model for personalised demand that synergetically integrates retailers’ digital ecosystems into a closed loop, where the forecast and the response are combined into a single continuous process. To achieve this aim, the following tasks are addressed: identifying unresolved problems in the operationalisation of personalised demand forecasts, substantiating the architecture of an adaptive digital circuit, and incorporating the factor of operational resilience into the system for evaluating personalisation effectiveness. The methodological basis of the study comprises content analysis of current academic sources, simulation modelling of consumer behaviour, and neural network methods for processing unstructured feedback data. The analytical review identified two interrelated problems: the “delay tax”, which entails substantial financial losses for retailers, and the “hypersegmentation paradox”, in which the deepening customisation comes into conflict with profitability. To overcome these problems, the linear forecasting model previously developed by the author has been transformed into a three-module adaptive model that combines forecasting, interactive value prototyping, and automated feedback. The operational viability factor, which supplements economic and technological criteria, has additionally been introduced into the performance evaluation system. The developed model ensures continuous verification of forecasts and incorporates an embedded mechanism for tracking the threshold of economically viable customisation.

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