A GIS-based green supply chain model for assessing the effects of carbon price uncertainty on plastic recycling. Issue 6 (18th March 2020)

• Record Type: Journal Article
• Authors: Ren, Hongtao; Zhou, Wenji; Guo, Ying; Huang, Lizhen; Liu, Yongping; Yu, Yadong; Hong, Liyun; Ma, Tieju
• Is Part Of: International journal of production research. Volume 58:Issue 6(2020)
• Page Start: 1705
• Page End: 1723
• Publication Date: 2020-03-18
• Subjects: green supply chain -- reverse logistics -- decision support systems -- uncertainty -- emissions trading -- circular economy; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2019.1693656
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : 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.