文献类型：期刊文献

英文题名：A GIS-based green supply chain model for assessing the effects of carbon price uncertainty on plastic recycling

作者：Ren, Hongtao[1];Zhou, Wenji[2];Guo, Ying[3];Huang, Lizhen[2];Liu, Yongping[2];Yu, Yadong[1];Hong, Liyun[4];Ma, Tieju[1,5]

机构：[1]East China Univ Sci & Technol, Sch Business, Shanghai, Peoples R China;[2]Norwegian Univ Sci & Technol NTNU, Dept Mfg & Civil Engn, Gjovik, Norway;[3]Cent South Univ, Sch Energy Sci & Engn, Changsha, Hunan, Peoples R China;[4]Zhejiang Dev & Planning Inst, Hangzhou, Zhejiang, Peoples R China;[5]Int Inst Appl Syst Anal, Laxenburg, Austria

年份：2020

卷号：58

期号：6

起止页码：1705

外文期刊名：INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

收录：;EI(收录号：20194807748575);WOS:【SCI-EXPANDED(收录号:WOS:000498380800001)】；

基金：The authors thank the financial support from the National Natural Science Foundation of China [grant numbers 71961137012, 71571069, 71704055, 71874055], the National Social Science Fund of China [grant number 19BGL273] and the Scientific Project of Hunan Province of China [grant number 2013RS4051].

语种：英文

外文关键词：green supply chain; reverse logistics; decision support systems; uncertainty; emissions trading; circular economy

摘要：Recycling plastic can abate the environmental pollution as well as CO2 emissions by saving the carbon-intensive feedstock input. The uncertain carbon price places significant effects on the establishment and operation of the whole supply chain. This study develops a green supply chain model combined with geographic information system (GIS) to account for carbon price uncertainty and evaluate its effects on the closed-loop supply chain (CLSC) of plastic recycling. A two-stage stochastic programming model is constructed, in which the stochastic variable, CO2 price is modelled as a geometric Brownian motion process. Six scenarios are designed with respect to price expectation and volatility. A case study is performed with the GIS information of the plastic supply chain in Zhejiang province, China. The results illustrate that triggering the establishment of reverse logistics requires a carbon price threshold significantly beyond the current level. Lower price volatility would facilitate the decision-making of investment into the reverse logistics. Mechanisms to alleviate the market variation shall be introduced. A sound market condition is desired to obtain the optimal balance that encourages the CLSC without creating extra pressure on the firms. The proposed modelling framework can be easily applied to other sectors with similar characteristics.