ECONOMETRIC MODELING OF THE INFLUENCE OF MERCHANDISING PARAMETERS (SHELF SPACE SHARE, DISPLAY LEVEL, PLANOGRAM) ON THE PROBABILITY OF BRAND CHOICE AND THE DEMAND STRUCTURE IN THE CATEGORY

Within the framework of the study, the author conducted an econometric analysis of how the physical parameters of retail shelf display shape consumer choice and the configuration of market demand in the fast-moving consumer goods (FMCG) category. Using the empirical base for 2024–2025, the explanatory and predictive validity of classical multinomial logit specifications is compared with modern weighted linear discrete choice models aimed at a more flexible accounting for observation heterogeneity and variability of selling conditions. The key determinants considered are the share of shelf space, the vertical placement position (eye, hand, and floor levels), as well as planogram execution quality, interpreted as the degree of correspondence between the actual display and the prescribed standards. Particular emphasis is placed on integrating analytical models with artificial intelligence and dynamic forecasting tools in shelf-space management tasks, which makes it possible to move from static regulations to adaptive data-driven decisions. The results obtained indicate that local adaptation of planograms at the level of specific retail outlets, combined with discipline in display compliance, provides a statistically significant increase in sales ranging within 10–30%. At the same time, vertical positioning associated with the golden shelf effect retains the status of the leading factor determining the probability of brand choice; its influence strengthens in an environment of increasing competitive pressure from retailers’ private labels.