Backroom effect on perishable inventory management with IoT information

Abstract

We introduce an original concept of the backroom effect for perishable products when the deterioration rate in a backroom is lower than that on retail shelves. With IoT-generated real-time information about the perishable products, this phenomenon has a significant impact on joint shelf-space and inventory decisions. We define the deterioration rate gap, formulate the perceived on-shelf product freshness, and describe the freshness-dependent demand distribution, with continuous backroom-shelf replenishment. Assuming that demand depends on both perceived freshness and shelf level, we develop a decision-making model that simultaneously determines the inventory replenishment policy and the shelf space allocation for multiple items. To facilitate the solution process, we propose a hybrid solution approach by combining genetic algorithm (GA) and variable neighbourhood search (VNS). The results provide a prioritised inventory policy for item selection that incorporates the deterioration improvement. The results of the performance analysis show that a policy considering the backroom effect achieves increased profit when the backroom/shelf deterioration gap increases. The optimal solutions for the problems with large backroom/shelf gap also show that the practitioner should increase the ordering quantity, which is contradictory to the outcome of traditional models.

Keywords:

• Backroom effect
• shelf-space
• inventory management
• perishable product
• IoT

Acknowledgments

The authors want to thank the three anonymous reviewers for their valuable comments and suggestions that have helped improving this paper. The authors would like to thank Qiuchen Gu (East China University of Science and Technology, China) for her help with the AMPL programming.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Key Program of National Natural Science of China (72032001), the National Natural Science Foundation of China (71972071), the National Natural Science Foundation of China (71671067), and the Fundamental Research Funds for the Central Universities.

Notes on contributors

Lin Li

Lin Li is an associate professor at East China University of Science and Technology, Shanghai, China. She received her Ph.D. in Management Science and Engineering from Tongji University, Shanghai, China, in 2010. Her research interests include perishable products supply chain management, omnichannel retailing, and production scheduling. Her research articles have been published in several Journals including, amongst others, Journal International Journal of Production Research, Journal of the Operational Research Society, and System Engineering Theory & Practice.

Ou Tang

Ou Tang is Professor of Production Economics at Linköping University, Sweden. His research includes production and inventory modelling, closed loop supply chains, supply chain risk management, sustainable supply chains, China related operations management issues, and energy policies. He has published more than 100 scientific articles in international journals including European Journal of Operational Research, International Journal of Production Economics, International Journal of Production Research, Production and Operations Management and others. He serves as editor for the International Journal of Production Economics and is the past president of International Society of Inventory Research.

Wei Zhou

Wei Zhou is professor of Information and Operations Management at ESCP Business School. His areas of research interests are in supply chain management, knowledge-based systems, effectively utilising information for decision support through analytical models, simulation and data analytics.

Tijun Fan

Tijun Fan received the Ph.D. degree from the Huazhong University of Science and Technology of China, Wuhan, Hubei, China, in 2003. He is a Professor of operations and supply chain management with East China University of Science and Technology, Shanghai, China. His research has been published several journals such as Production and Operations Management, Energy Economics, the European Journal of Operational Research, Transportation Research Part D, the International Journal of Production Economics, among others. His research interests include operations management, logistics management, and supply chain management.