系统管理学报2017，Vol.26Issue(5)：947-956,10.
混合碳政策下供应链减排决策优化
Optimal Decision of Carbon Emission Reduction in Supply Chain Based on Mixed Carbon Policy
摘要
Abstract
This paper built a two-echelon supply chain decision model based on the policy of carbon trading-carbon tax (Environmental taxes),in which we studied the effect of mixed carbon policies on the supply chain pricing,production capacity,profit,emission reduction rate and the optimal proportion of compensated quota,bidding price,as well as the mixed strategies.Then we introduced a protocol of priority in purchasing the low-carbon material and the contract of carbon emission restriction-benefit sharing to coordinate the supply chain,then we obtained the Nash-equilibrium mode of emission reduction that can not only reduce the level of carbon emission but also improve the supply chain's social welfare.The results show that:(1) High strength carbon policy is not necessarily an effective incentive for enterprises to reduce emission,while improving the consumer acceptance of low-carbon products and increasing the activity of carbon market could lead a supply chain benign emission reduction.(2) The optimal proportion of compensated quota for China is 3.4％ under the model proposed in this paper.The supporting mechanism of compensated quota-cost subsidies can not only improve carbon market activity but also leave out the high pollution and out-date productivity by the effect of bidding cost and transfer payment.(3) The centralized decision mode can achieve Pareto-improvement of emission reduction efficiency with price-limit strategy.Finally,the numerical examples demonstrated the validity of the model.关键词
碳政策/低碳供应链/碳减排/碳交易/碳税Key words
carbon policy/low-carbon supply chain/carbon emission reduction/carbon trading/carbon tax分类
管理科学引用本文复制引用
程永伟,穆东,马婷婷..混合碳政策下供应链减排决策优化[J].系统管理学报,2017,26(5):947-956,10.基金项目
国家自然科学基金面上项目(71473013,71772016) （71473013,71772016）
教育部人文社科研究青年基金资助项目(17YJC630203) （17YJC630203）
北京物资学院校级重大项目(2017XJZD05) （2017XJZD05）
北京物资学院科技协同攻关团队建设项目(2017GG06) （2017GG06）
