A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries. Issue 7 (3rd July 2019)

• Record Type: Journal Article
• Authors: Emrouznejad, Ali; Yang, Guo-liang; Amin, Gholam R.
• Is Part Of: Journal of the Operational Research Society. Volume 70:Issue 7(2019)
• Page Start: 1079
• Page End: 1090
• Publication Date: 2019-07-03
• Subjects: Data envelopment analysis -- Inverse DEA -- CO2 emissions -- manufacturing industries; Operations research -- Periodicals; 658.4034
• DOI: 10.1080/01605682.2018.1489344
• Languages: English
• ISSNs: 0160-5682

Abstract

Abstract: This paper aims to address the problem of allocating the CO2 emissions quota set by government goal in Chinese manufacturing industries to different Chinese regions. The CO2 emission reduction is conducted in a three-stage phases. The first stage is to obtain the total amount CO2 emission reduction from the Chinese government goal as our total CO2 emission quota to reduce. The second stage is to allocate the reduction quota to different two-digit level manufacturing industries in China. The third stage is to further allocate the reduction quota for each industry into different provinces. A new inverse data envelopment analysis (InvDEA) model is developed to achieve our goal to allocate CO2 emission quota under several assumptions. At last, we obtain the empirical results based on the real data from Chinese manufacturing industries.