The lay abstract featured today (for Assessing the Impact on Sales of Competing Nearby Supermarkets by Daniel González Ibáñez, Xavier Puig) is from Applied Stochastic Models in Business and Industry with the full Open Access article now available to read here.
How to cite
and , Assessing the Impact on Sales of Competing Nearby Supermarkets, Applied Stochastic Models in Business and Industry 41, no. 6 (2025): e70048, https://doi.org/10.1002/asmb.70048.
Lay Abstract
Supermarkets operate in one of the most competitive sectors of modern economies. In many regions, several major chains compete for the same consumers, and even small differences in store location, pricing strategy, or product assortment can significantly affect sales. Understanding how the proximity of competing stores influences performance is therefore essential for effective business decision-making.
This study presents a statistical model designed to measure how nearby competitors affect supermarket sales, not only at the overall level but also for specific product categories. The model, based on a hierarchical Bayesian framework, allows each brand to quantify the monetary effect of every competing supermarket within its area of influence. By analysing real sales data, the model produces a matrix of coefficients that indicate how much each competitor’s presence influence sales in distinct product categories.
The findings reveal that competitive effects are far from uniform: while certain product categories are strongly influenced by the closeness of particular rival brands, others remain relatively unaffected. This information enables supermarket managers to make more informed strategic decisions, such as where to open new stores, how to design the product mix in each location, or how to position themselves against specific competitors.
By turning complex market interactions into practical and interpretable results, this research provides a valuable tool for retail management and contributes to a deeper understanding of how competition shapes consumer choices in the supermarket industry.