論文

査読有り 筆頭著者
2019年9月

Government Regulations on Closed-Loop Supply Chain with Evolutionarily Stable Strategy

SUSTAINABILITY
  • Ziang Liu
  • ,
  • Tatsushi Nishi

11
18
開始ページ
5030
終了ページ
5030
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.3390/su11185030
出版者・発行元
MDPI

The government plays a critical role in the promotion of recycling strategy among supply chain members. The purpose of this study is to investigate the optimal government policies on closed-loop supply chains and how these policies impact the market demand and the returning strategies of manufacturers and retailers. This paper presents a design of closed-loop supply chains under government regulation by considering a novel three-stage game theoretic model. Firstly, Stackelberg models are adopted to describe the one-shot game between the manufacturer and the retailer in a local market. Secondly, based on the Stackelberg equilibriums, a repeated and dynamic population game is developed. Thirdly, the government analyzes the population game to find the optimal tax and subsidy policies in the whole market. To solve the proposed model, the idea of backward induction is adopted. The results suggest that, by collecting tax and allocating subsidy, the government can influence the market demands and return rates. The centralized supply chain structure is always preferred for the government and the market. The government prefers to allocate subsidy to low-pollution, low-profit remanufactured products. The environmental attention of the government affects the subsidy policy.

リンク情報
DOI
https://doi.org/10.3390/su11185030
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000489104700216&DestApp=WOS_CPL
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85072648677&origin=inward 本文へのリンクあり
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85072648677&origin=inward
ID情報
  • DOI : 10.3390/su11185030
  • eISSN : 2071-1050
  • ORCIDのPut Code : 61874183
  • SCOPUS ID : 85072648677
  • Web of Science ID : WOS:000489104700216

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