The researchers explore how a business-to-business (B2B) policy, i.e. lateral-inventory share policy, should be designed to optimize business profitability.
Sachin Kumar Mangla, Assistant Professor, Jindal Global Business School, O.P. Jindal University, India; Visiting Research Fellow, Plymouth Business School, University of Plymouth, United Kingdom.
Banu Yetkin Ekren, Department of Industrial Engineering, Yasar University, Turkey.
Ecem Eroglu Turhanlara, Department of Industrial Engineering, Yasar University, Turkey.
Yigit Kazancoglu, Department of International Logistics Management, Yasar University, Turkey.
Guo Lie, School of Management and Economics, Beijing Institute of Technology, China; Center for Energy and Environmental Policy Research, Beijing Institute of Technology, China; Sustainable Development Research Institute for Economy and Society of Beijing, China.
This research investigates lateral inventory share-based business models for e-grocery networks where online groceries are inter-connected in an Internet of Things (IoT) environment. Recently, managing food supplies has become a very important issue due to the onset of unexpected conditions such as natural disasters (earthquakes, tsunamis, floods, droughts etc.) and pandemics.
In this paper, we aim to design sustainable food supply chain networks for e-commerce food companies (e.g. e-groceries) by applying lateral inventory share policies after the consideration of the existence of strategic alliances between organizations.
We aim to minimize food waste as well as back orders resulting in more sustainable networks. Further, we explore how a business-to-business (B2B) policy (i.e. lateral-inventory share policy) should be designed to optimize business (i.e. e-groceries) profitability.
We optimize the re-order and up-to () inventory levels of e-groceries for the pre-defined sharing policies by using a simulation optimization approach. The optimal results show that having a lateral inventory share poliIndiacy in food networks is more efficient compared to a non-lateral policy.
Also, at the optimal points of the considered policies, lateral inventory share ratio is usually observed to be larger than 50% on average, meaning that more than half of customer orders are met by lateral inventory share.
Published in: Computers and Operations Research
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