A Simulation Based Tool to Guide Periodic Changes in a Supermarket Layout

Jessica Dorismond (), Jose L. Walteros () and Rajan Batta ()
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Jessica Dorismond: University at Buffalo, The State University of New York
Jose L. Walteros: University at Buffalo, The State University of New York
Rajan Batta: University at Buffalo, The State University of New York

A chapter in Retail Space Analytics, 2023, pp 51-74 from Springer

Abstract: Abstract The purpose of this chapter is to develop an analytic tool to recommend changes to the block and detailed layouts of a supermarket in order to maximize the visibility of impulse items. The proposed tool employs a simulation model to analyze the quality of different potential block layouts. The simulation uses a path generation model that is leveraged on historical data to emulate the customer behavior and replicate the customer flows in the supermarket. A shelf allocation integer programming model determines the visibility of impulse items by taking into consideration the predicted customer flows and produces an optimal detailed layout as well as the overall score of the solution. We demonstrate the applicability of the proposed tool by solving the layout problem of a medium-sized supermarket in Western New York. Our results indicate that even minor alterations to the block and detailed layouts may have a significant impact on impulse purchases. We found two managerial insights. First, unlike traditional layout problems where block and detailed layouts do not directly affect each other, in a supermarket setting, the block and detailed layouts are not independent, implying that a change in the block layout can also trigger changes in the detailed layout. Second, changes in the customer buying patterns can imply a benefit in changing either the block, detailed, or both layouts; thus, a periodical reevaluation of the layouts is recommended.

Keywords: Supermarket layout; Facilities design; Variable neighborhood search; Simulation; K-Medoids (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-031-27058-1_4

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