Closed-loop supply chain network design considering reshoring drivers

Yun Geon Kim, Byung Do Chung

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

The phenomenon of reshoring is enforced by governments in developed countries to strengthen the manufacturing industries and solve problems such as economic recession and job scarcity. Moreover, offshoring has become expensive for industries because of changes in the host countries, such as increasing labor and logistics costs and decreasing productivity. Therefore, this study formulated a supply chain model to determine whether manufacturing centers (MCs), suppliers, and reverse logistics facilities should relocate to their home country from the host country to maximize the total profit based on the level of reshoring drivers. We analyzed the effects of productivity-adjusted costs and reverse logistics on the reshoring decisions by conducting numerical experiments. First, the locations of other facilities in a supply chain network and consideration of reverse logistics can significantly influence the reshoring of the MCs. Second, reshoring can be enhanced in environments with productivity-adjusted costs depending on the characteristics of the host and home countries. Third, the effect of the reshoring policy may differ based on the process characteristics of the MCs. Therefore, companies need to adopt right-shoring strategies from the perspective of a supply chain network while considering the effect of reshoring drivers on the MCs. Furthermore, governments need to establish strategies for discriminative government budgeting based on the characteristics of the manufacturing processes and the home country when considering policies to promote the reshoring of companies.

Original languageEnglish
Article number102610
JournalOmega
Volume109
DOIs
Publication statusPublished - 2022 Jun

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) [grant number NRF-2020R1A2C1005489 ].

Publisher Copyright:
© 2022 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

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