Optimal return and refund polices for perishable food items with online grocery shopping

ABSTRACT

The purpose of this paper is to help online grocery retailers determine the optimal return and refund policies for perishable grocery items. Three refund policies and two return requirements are modelled: no-refund, full-refund and partial-refund, with or without product return. We first derive the optimal refund policy under two scenarios, where either product return is or is not required for refund. We further analyse how market conditions impact the optimal policies. Lastly, we investigate when product return should be required for refund. Our results show that a more generous refund policy should be offered if the product has a higher profit margin, if an unsatisfactory product has a large negative impact on consumer utility, and if consumers have high return costs when product return is required for refund. Our results also show that it is optimal not to require the unwanted product to be returned when consumer’s return cost and product return rate are above certain threshold values. This paper fills the gap in the literature on return and refund policies in an online grocery setting. The findings of this paper provide explicit guidance to online grocery businesses on how to optimally determine the return and refund policies.

KEYWORDS:

• Online grocery shopping
• return
• refund policy
• consumer utility
• modelling

Data availability statement

Data sharing is not applicable to this article as no new data were created or analysed in this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Yang Li

Yang Li is an Associate Professor in Supply Chain Management in the College of Business, California State University, Sacramento. She obtained her Ph.D. in Operations Management from the Fuqua School of Business, Duke University, in 2013. Yang Li’s research interests include, Dynamic Pricing, Revenue Management, Sustainability, Ecommerce, Inventory Management, and Supply Chain Management. Her research appeared in Management Science, International Journal of Production Research, International Journal of Production Economics, Journal of Retailing and Consumer Services and others.

Kunpeng Li

Kunpeng Li is currently an Associate Professor in the Department of Systems and Operations Management at the California State University, Northridge. She holds a Ph.D. in Operations Management from the University of Illinois, Urbana-Champaign. Dr Li’s research interests are quantitative analysis in supply chain and operations management. She has published in leading academic journals such as Production and Operations Management, Decision Sciences, International Journal of Production Research, etc.

Amir Gharehgozli

Amir Gharehgozli is an Industrial Engineer with a Ph.D. in Technology and Operations Management from the Rotterdam School of Management. His research interests are the applications of Business Analytics and Decision Sciences in Supply Chain Management, Technology and Operations Management, Information Systems, Facility and Distribution Logistics, and Production Planning; in particular, studying recent innovations and technological advancements in these areas. His research findings have been published in highly scientific journals and presented in international conferences. He also reviews for top tier journals. He has had the opportunity to put theory into practice by working in ING Bank and consulting on different industry projects in close collaboration with Port Authorities and Supply Chain and Logistics companies. He is currently an Associate Professor and Director of Master of Science in Business Analytics with the David Nazarian College of Business and Economics at the California State University, Northridge, where in recognition of his outstanding research, teaching and service work, he is awarded and appointed as the Carande Family Fellow.