Carbon Emissions Abatement (CEA) Allocation Based on Inverse Slack-Based Model (SBM)

doi:10.1007/s40305-020-00303-y

Journal of the Operations Research Society of China ›› 2021, Vol. 9 ›› Issue (3): 475-498.doi: 10.1007/s40305-020-00303-y

Carbon Emissions Abatement (CEA) Allocation Based on Inverse Slack-Based Model (SBM)

Xiao-Yin Hu^1,2, Jian-Shu Li^1,2, Xiao-Ya Li¹, Jin-Chuan Cui¹

1 Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China;
2 School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2019-06-11 Revised:2020-02-06 Online:2021-09-30 Published:2021-09-26
Contact: Jin-Chuan Cui,cjc@amss.ac.cn;Xiao-Yin Hu,hxy@amss.ac.cn;Jian-Shu Li,ljs@amss.ac.cn;Xiao-Ya Li,xyli@amss.ac.cn E-mail:cjc@amss.ac.cn;hxy@amss.ac.cn;ljs@amss.ac.cn;xyli@amss.ac.cn
Supported by:
This work is supported by Key Laboratory of Management, Decision and Information Systems, Chinese Academy of Sciences.

Abstract

Abstract: Carbon emissions abatement (CEA) is an important issue that draws attention from both academicians and policymakers. Data envelopment analysis (DEA) has been a popular tool to allocate the CEA, and most previous works are based on radial DEA models. However, as shown in our paper, these models may give biased results due to their ignorance of slackness. To avoid such problems, we propose an allocation model based on the slack-based model and multiple-objective nonlinear programming to find the CEA allocation plan, which can minimize the GDP loss. The property of nonconvexity makes the model difficult to solve. Thus, we construct an approximation algorithm to solve this model with guaranteed error bounds and complexity. In the empirical application, we take regions of china as an illustrative example and find there is a significant region gap in China. Hence, we group the regions into eastern, central, and western, and give the main results, as well as the superiority of our allocation models compared with radial models.

Key words: Carbon emissions abatement (CEA), Allocation, Data envelopment analysis (DEA), Inverse slack-based method (ISBM)

CLC Number:

Xiao-Yin Hu, Jian-Shu Li, Xiao-Ya Li, Jin-Chuan Cui. Carbon Emissions Abatement (CEA) Allocation Based on Inverse Slack-Based Model (SBM)[J]. Journal of the Operations Research Society of China, 2021, 9(3): 475-498.

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Carbon Emissions Abatement (CEA) Allocation Based on Inverse Slack-Based Model (SBM)

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