Environmental Efficiency Evaluation of Chinese Industry Systems by Using Non-Cooperative Two-Stage DEA Model

Xiao Shi

Mathematical Problems in Engineering, 2019, vol. 2019, 1-10

Abstract:

In evaluating the environmental efficiency analysis of Chinese industry systems, data envelopment analysis (DEA) has been a popular method. However, the production system is often treated as a black box in conventional DEA models. This study considers the internal structure of the production system to evaluate the environmental efficiency, which is characterized as a two-stage system, i.e., production subsystem and pollutant treatment subsystem. And, in reality, some subsystems in two-stage production systems are not equally important, and this kind of two-stage systems usually has the feature that one subsystem dominates the other. Thus, we consider the leader and follower relationship in the environmental efficiency analysis. A new non-cooperative two-stage DEA model considering undesirable intermediates and undesirable outputs is proposed to calculate the environmental efficiency. The proposed method is then applied to 30 regional industry systems of China in the year 2010. Thus, each DMU’s environmental efficiencies for the overall system as well as both subsystems could be analyzed by the proposed approach. More accurate information could be provided for environmental management.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2019/9208367.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2019/9208367.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:9208367

DOI: 10.1155/2019/9208367

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().