This paper aims to discuss the low carbon supply chain practices in China’s textile industry. To curb greenhouse gas emissions, the Chinese government has launched restrict regulatory system and imposed the energy consumption constraint in the textile industry to guarantee the achievability of low carbon economy. The authors aim to examine how the energy consumption constraint affects the optimal decisions of the supply chain members and address the supply chain coordination issue.
The authors conduct two case studies from Chinese textile companies and examine the impact of energy consumption constraints on their production and operations management. Based on the real industrial practices, the authors then develop a simple analytical model for a low carbon supply chain in which it consists of one single retailer and one single manufacturer, and the manufacturer determines the choice of clean technology for energy efficiency improvement and emission reduction.
From the case studies, the authors find that the textile companies develop clean technologies to reduce carbon emission in production process under the energy consumption enforcement. In this analytical model, the authors derive the optimal decisions of the supply chain members and reveal that supply chain coordination can be achieved if the manufacturer properly sets the reservation wholesale price (WS) despite the production capacity can fulfill partial market demand under a WS (or cost sharing) contract. The authors also find that the cost-sharing contract may induce the manufacturer to increase the investment of clean technology and reduce the optimal WS.
This paper discusses low carbon supply chain practices in China’s textile industry and contributes toward green supply chain development. Managerial implications are identified, which are beneficial to the entire textile industry in the developing countries.
Shen, B., Ding, X., Chen, L. and Chan, H.L. (2017), "Low carbon supply chain with energy consumption constraints: case studies from China’s textile industry and simple analytical model", Supply Chain Management, Vol. 22 No. 3, pp. 258-269. https://doi.org/10.1108/SCM-05-2015-0197
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