Emrouznejad, Ali, Yang, Guoliang and Amin, Gholam R. (2019). A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries. Journal of the Operational Research Society, 70 (7), pp. 1079-1090.
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.
Publication DOI: | https://doi.org/10.1080/01605682.2018.1489344 |
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Divisions: | College of Business and Social Sciences > Aston Business School > Operations & Information Management College of Business and Social Sciences > Aston Business School |
Additional Information: | © 2018 Palgrave Macmillan Publishers Limited, part of Springer Nature. This is a post-peer-review, pre-copyedited version of an article published in Journal of the Operational Research Society. Funding: National Natural Science Foundation of China and Newton Fund from Royal Academy of Engineering. |
Uncontrolled Keywords: | Data envelopment analysis ,Inverse DEA ,CO2 emissions ,manufacturing industries |
Publication ISSN: | 1476-9360 |
Last Modified: | 18 Nov 2024 08:17 |
Date Deposited: | 13 Jun 2018 10:10 |
Full Text Link: | |
Related URLs: |
https://www.tan ... 82.2018.1489344
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2019 |
Published Online Date: | 2018-10-18 |
Accepted Date: | 2018-06-13 |
Authors: |
Emrouznejad, Ali
(
0000-0001-8094-4244)
Yang, Guoliang Amin, Gholam R. |