Best Performance Frontiers for Buy-Online-Pickup-in-Store order fulfilment

MacCarthy, Bart L.; Zhang, Lina; Muyldermans, Luc

Abstract

With the proliferation of omni-channel retailing, Buy-Online-Pickup-in-Store (BOPS) retail services have gained increasing popularity as they have benefits for both customers and retailers. However, using conventional retail stores to fulfil orders received online whilst also serving walk-in customers is challenging for retailers, particularly when a high customer service level is promised to online customers (e.g., order by a certain time and pick up in store after a specific time later the same day). This paper examines store picking operations for same day BOPS services. Specifically, we derive Best Performance Frontiers (BPFs) for single wave and multi-wave order picking. New relationships, propositions, and results are presented to determine the minimum picking rate needed in stores to guarantee a target service level, the number of picking waves a retailer should launch in an ordering cycle, and the timing of picking waves. We also examine demand surge scenarios with different order arrival rates in an ordering cycle. Insights and implications of the results are discussed for retailers that seek to benchmark their current BOPS performances and understand how to schedule and improve the picking of online orders in conventional retail stores and the picking rates needed to guarantee a desired service level for online customers.

Citation

MacCarthy, B. L., Zhang, L., & Muyldermans, L. (2019). Best Performance Frontiers for Buy-Online-Pickup-in-Store order fulfilment. International Journal of Production Economics, 211, 251-264. https://doi.org/10.1016/j.ijpe.2019.01.037

• Journal Article Type: Article
• Acceptance Date: Jan 26, 2019
• Online Publication Date: Feb 2, 2019
• Publication Date: 2019-05
• Deposit Date: Feb 5, 2019
• Publicly Available Date: Aug 3, 2020
• Journal: International Journal of Production Economics
• Print ISSN: 0925-5273
• Electronic ISSN: 0925-5273
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 211
• Pages: 251-264
• DOI: https://doi.org/10.1016/j.ijpe.2019.01.037
• Keywords: Management Science and Operations Research; Economics and Econometrics; Industrial and Manufacturing Engineering; General Business, Management and Accounting
• Public URL: https://nottingham-repository.worktribe.com/output/1519282
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0925527319300453
• Contract Date: Feb 5, 2019