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Discrete Dynamics in Nature and Society
Volume 2017, Article ID 4379124, 11 pages
https://doi.org/10.1155/2017/4379124
Research Article

Mixed Carbon Policies Based on Cooperation of Carbon Emission Reduction in Supply Chain

1School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
2Academy of Modern Logistics Industry, Beijing Wuzi University, Beijing 101149, China

Correspondence should be addressed to Yongwei Cheng; moc.621@6891nahehc

Received 2 October 2016; Accepted 28 November 2016; Published 12 January 2017

Academic Editor: Paolo Renna

Copyright © 2017 Yongwei Cheng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper established cooperation decision model for a mixed carbon policy of carbon trading-carbon tax (environmental tax) in a two-stage - supply chain. For three different cooperative abatement situations, we considered the supplier driven model, the manufacturer driven model, and the equilibrium game model. We investigated the influence of mixed carbon policy with constraint of reduction targets on supply chain price, productivity, profits, carbon emissions reduction rate, and so on. The results showed that () high-strength carbon policies do not necessarily encourage enterprises to effectively reduce emissions, and increasing market acceptance of low carbon products or raising the price of carbon quota can promote the benign reduction; () perfect competitive carbon market has a higher carbon reduction efficiency than oligarch carbon market, but their optimal level of cooperation is the same and the realized reduction rate is in line with the intensity of carbon policy; () the policy sensitivity of the carbon trading mechanism is stronger than the carbon tax; “paid quota mechanism” can subsidize the cost of abatement and improve reduction initiative. Finally, we use a numerical example to solve the optimal decisions under different market situations, validating the effectiveness of model and the conclusions.