Integrated retail decisions with multiple selling periods and customer segments: Optimization and insights
| dc.contributor.author | Ghoniem, Ahmed S. | |
| dc.contributor.author | Maddah, Bacel S. | |
| dc.contributor.department | Department of Industrial Engineering and Management | |
| dc.contributor.faculty | Maroun Semaan Faculty of Engineering and Architecture (MSFEA) | |
| dc.contributor.institution | American University of Beirut | |
| dc.date.accessioned | 2025-01-24T11:31:43Z | |
| dc.date.available | 2025-01-24T11:31:43Z | |
| dc.date.issued | 2015 | |
| dc.description.abstract | Integrating retail decisions on such aspects as assortment, pricing, and inventory greatly improves profitability. We examine a multi-period selling horizon where a retailer jointly optimizes assortment planning, pricing, and inventory decisions for a product line of substitutable products, in a market with multiple customer segments. Focusing on fast-moving retail products, the problem is modeled as a mixed-integer nonlinear program where demand is driven by exogenous consumer reservation prices and endogenous assortment and pricing decisions. A mixed-integer linear reformulation is developed, which enables an exact solution to large problem instances (with up to a hundred products) in manageable times. Empirical evidence is provided in support of a classical deterministic maximum-surplus consumer choice model. Computational results and managerial insights are discussed. We find that the optimal assortment and pricing decisions do not exhibit a simple, intuitive structure that could be analytically characterized, which reflects the usefulness of optimization approaches to numerically identify attractive trade-offs for the decision-maker. We also observe that suboptimal inventory policies significantly decrease profitability, which highlights the importance of integrated decision-making. Finally, we find that the seasonality of consumer preferences and supply costs present an opportunity for boosting the profit via higher inventory levels and wider assortments. © 2015 Elsevier Ltd. | |
| dc.identifier.doi | https://doi.org/10.1016/j.omega.2015.02.002 | |
| dc.identifier.eid | 2-s2.0-84924691863 | |
| dc.identifier.uri | http://hdl.handle.net/10938/27545 | |
| dc.language.iso | en | |
| dc.publisher | Elsevier Ltd | |
| dc.relation.ispartof | Omega (United Kingdom) | |
| dc.source | Scopus | |
| dc.subject | Assortment planning | |
| dc.subject | Dynamic lot-sizing | |
| dc.subject | Mathematical programming | |
| dc.subject | Optimization modeling | |
| dc.subject | Pricing and inventory | |
| dc.subject | Commerce | |
| dc.subject | Decision making | |
| dc.subject | Economic and social effects | |
| dc.subject | Integer programming | |
| dc.subject | Nonlinear programming | |
| dc.subject | Profitability | |
| dc.subject | Sales | |
| dc.subject | Customers segments | |
| dc.subject | Inventory decisions | |
| dc.subject | Multi-period | |
| dc.subject | Optimisations | |
| dc.subject | Optimization models | |
| dc.subject | Pricing decision | |
| dc.subject | Productline | |
| dc.subject | Costs | |
| dc.title | Integrated retail decisions with multiple selling periods and customer segments: Optimization and insights | |
| dc.type | Article |
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