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Title Lateral inventory share-based models for IoT-enabled E-commerce sustainable food supply networks
ID_Doc 65305
Authors Ekren, BY; Mangla, SK; Turhanlar, EE; Kazancoglu, Y; Li, G
Title Lateral inventory share-based models for IoT-enabled E-commerce sustainable food supply networks
Year 2021
Published
DOI 10.1016/j.cor.2021.105237
Abstract This research investigates lateral inventory share-based business models for e-grocery networks where online groceries are inter-connected in an Internet of Things (loT) 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 (s,S) 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 polilndiacy 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. (C) 2021 Elsevier Ltd. All rights reserved.
Author Keywords Lateral-inventory; Industry 4.0; e-Grocery; B2B; Sustainable food supply chain network; Food waste
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
EID WOS:000632975200010
WoS Category Computer Science, Interdisciplinary Applications; Engineering, Industrial; Operations Research & Management Science
Research Area Computer Science; Engineering; Operations Research & Management Science
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