Shopping Trip Choice Prediction for Assessing Store Relocation: a Joint Data-Driven and Behavioural Modelling Approach

Hounwanou Sonagnon (), Comi Antonio (), Gonzalez-Feliu Jesus () and Gondran Natacha ()
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Hounwanou Sonagnon: Institut VEDECOM, 23 bis allée des Marronniers, 78000 Versailles, France
Comi Antonio: University of Rome Tor Vergata, Department of Enterprise Engineering, 00133, Rome, Italy
Gonzalez-Feliu Jesus: Excelia Business School, Center of Research in Innovation and Intelligence in Management, 102 rue de Coureilles, 17000 La Rochelle, France
Gondran Natacha: Mines Saint-Etienne, CNRS, Univ Jean Monnet, Univ Lumière Lyon 2, Univ Lyon 3 Jean Moulin, ENS Lyon, ENTPE, ENSA Lyon, UMR 5600 EVS, Institut Henri Fayol, F - 42023 Saint-Etienne France

LOGI – Scientific Journal on Transport and Logistics, 2025, vol. 16, issue 1, 104-115

Abstract: This paper proposes and tests a methodology to analyse end consumers’ choices in terms of shopping destination for a store selling culture products, comparing a city centre location to a peripheral one. The proposed methodology begins with a stated preferences survey and incorporates a conditional tree classification algorithm to pre-select the predictors (attributes), then used to develop a discrete choice model. To validate the methodology, a real-world case study was carried out, including a survey with over one thousand customer responses. The findings reveal noteworthy insights into customer attitudes toward relocation, distinguishing frequent from non-frequent users and examining factors such as travel distance and visit frequency. These results offer valuable guidance for retailers and policy makers in shaping city logistics scenarios, highlighting the potential transformations in urban freight flows driven by changes in retail land use.

Keywords: Shopping trip behaviour; conditional-inference-tree; logit model; destination choice (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:logitl:v:16:y:2025:i:1:p:104-115:n:1010

DOI: 10.2478/logi-2025-0010

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