Biobjective optimization model for store selection for BOPS service in omni-channel retail chain

Owing to the relentless stress on innovative solutions for businesses to succeed in a highly customer-dominated market, the process of having an omni-channel supply chain has become crucial for the Indian retail industry. Thus, retailers are finding ways for launching services like buy online pickup in store (BOPS) in such a way that they are beneficial for them. The problem addressed in the current research is that of a multichannel retailer who wants to provide a BOPS fulfilment option to its customers. The pickup points are to be set up at the existing retail store locations of the retail firm. For this purpose, a biobjective mathematical programming model is developed for: 1) identifying existing retail stores which should be expanded as pick-up points, and 2) determining the expansion capacity of the selected retail stores. Weighted goal programming technique is utilized to achieve a tradeoff between the objectives of cost minimization and utility achievement of retail stores under various constraints incorporating demand requirements, budgetary restrictions on expansion, optimum capacity utilization, and the performance scores of the retail stores evaluated on the basis of criteria like accessibility, attractiveness, etc. The model is validated using the case of an Indian multichannel retail firm. From the results obtained, it can be concluded that adopting an all-inclusive strategy for retail store selection is not beneficial for retailers. Also, the results point out that the performance of the retail store is an important factor to consider while selecting the retail store for pickup points.