Enhancing retail operations: Dynamic fulfilment strategies in omnichannel retail

This study explores the trend of in-store fulfillment in omnichannel retail, where nearby store inventories are utilized for online order fulfillment. This model presents advantages such as faster delivery, cost reduction, improved stock management, increased sales, and enhanced customer satisfaction. Operational challenges include determining the optimal fulfillment location for online orders. Investigating a retailer with online and brick-and-mortar stores, this paper addresses dynamic order fulfillment decisions considering customer demand and shipping cost uncertainties. The study employs Stochastic Dynamic Programming for shorter periods and the Genetic Algorithm for longer periods, revealing that the Genetic Algorithm provides solutions closely approximating optimal.

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Publication Details

Journal
Serbian Journal of Management
Published
2025-01-01
DOI
https://doi.org/10.5937/sjm20-54499
Primary Topic
Consumer Retail Behavior Studies
Type
article
Field-Weighted Citation Impact
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article

Enhancing retail operations: Dynamic fulfilment strategies in omnichannel retail

Abdullah Hulusi Kökçam, Željko Stević, Mahmut Baydaş, Safìye Turgay et al.
1 links
Serbian Journal of Management
Consumer Retail Behavior Studies
article

Enhancing retail operations: Dynamic fulfilment strategies in omnichannel retail

Abdullah Hulusi Kökçam, Željko Stević, Mahmut Baydaş, Safìye Turgay, Sinem Dayanıklı, Jasmina Bunevska-Talevska, Hümeysa İskender
article en

Abstract

This study explores the trend of in-store fulfillment in omnichannel retail, where nearby store inventories are utilized for online order fulfillment. This model presents advantages such as faster delivery, cost reduction, improved stock management, increased sales, and enhanced customer satisfaction. Operational challenges include determining the optimal fulfillment location for online orders. Investigating a retailer with online and brick-and-mortar stores, this paper addresses dynamic order fulfillment decisions considering customer demand and shipping cost uncertainties. The study employs Stochastic Dynamic Programming for shorter periods and the Genetic Algorithm for longer periods, revealing that the Genetic Algorithm provides solutions closely approximating optimal.

Serbian Journal of ManagementVol. 20(1)
Openalex Percentile: Top 83%
Consumer Retail Behavior Studies
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