Store location with multipurpose shopping trips and a new random utility customers’ choice model

Gonzalo Méndez-Vogel, Vladimir Marianov, Armin Lüer-Villagra, H. A. Eiselt

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


This paper addresses retail store location in a duopoly. One firm, the so-called leader, has already located several stores, while a second firm, the follower that offers a different product, considers locating its stores in the same area. Both products have some degree of complementarity. Marianov et al. (2018) studied this problem considering a customer decision rule that is binary (winner-take-all) and deterministic (there are no uncertainties related to customers’ behavior). In that work, they concluded that multipurpose shopping has a strong influence on optimal store location. This paper extends that work by introducing random utility customer choice rules based on the Multinomial Logit model. Along these lines, we propose the new Partially Binary Logit rule, applicable to the case in which all stores of a firm have identical attributes, except for their location. In this case, a customer always chooses the least cost trip store of the firm to purchase its product. We propose one nonlinear and three linear formulations for the follower location problem, and a Branch and Cut method for one of them. Two of the formulations have a good performance for instances of up to at least 200 nodes. We compare the binary, Multinomial Logit, and Partially Binary Logit rules by analyzing the captured markets and location patterns for a large set of randomly generated 100-node instances.

Original languageEnglish
Pages (from-to)708-721
Number of pages14
JournalEuropean Journal of Operational Research
Issue number2
Publication statusPublished - 1 Mar 2023


  • Customer behavior
  • Location
  • Multipurpose shopping
  • Random utility models

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management
  • Industrial and Manufacturing Engineering


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