 Omnichannel product selection and shelf space planning optimizationYajing Chen, Zhimin Wu and Yunlong Wang Omega, 2024, vol. 127, issue C Abstract: As the retail industry is evolving toward an omnichannel paradigm, we study a product selection and shelf space planning problem faced by omnichannel retailers. We aim to maximize aggregated profits across channels by determining the optimal product offerings for the offline and online channels while optimizing the allocation of limited shelf space to these products in brick-and-mortar stores. Furthermore, the showroom effect of physical stores on online sales is also taken into account. We propose a corresponding model that jointly optimizes these decisions. To solve the nonlinear nonconvex model of practical scale, we first reformulate it into a mixed integer quadratic programming by exploring the structural properties. Next, we use the reformulation linearization technique to further improve the computational speed. Our numerical studies validate the efficiency of the proposed solution approach. In addition, we derive some managerial insights, including that retailers should adopt joint optimization and consider how the involved effects and parameters may influence their profits and decisions. Keywords: Omnichannel retailing; Product selection; Shelf space planning; Reformulation linearization technique (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jomega:v:127:y:2024:i:c:s0305048324000410 Ordering information: This journal article can be ordered from DOI: 10.1016/j.omega.2024.103074 Access Statistics for this article Omega is currently edited by B. Lev More articles in Omega from Elsevier |
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