Environmental efficiency analysis based on relational two-stage DEA model

2016 ◽  
Vol 50 (4-5) ◽  
pp. 965-977 ◽  
Author(s):  
Xiao Shi
Keyword(s):  
Efficiency Analysis ◽  
Environmental Efficiency ◽  
Two Stage ◽  
Dea Model

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

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Xiao Shi
Keyword(s):  
Production System ◽  
Production Systems ◽  
Efficiency Analysis ◽  
Environmental Efficiency ◽  
Accurate Information ◽  
Two Stage ◽  
Dea Model ◽  
Chinese Industry ◽  
Dea Models ◽  
Stage System

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.

scholarly journals The Environmental Efficiency Analysis Based on the Three-Step Method for Two-Stage Data Envelopment Analysis

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7028
Author(s):  
Qingyou Yan ◽  
Fei Zhao ◽  
Xu Wang ◽  
Tomas Balezentis
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Cooperative Game ◽  
Environmental Efficiency ◽  
Data Envelopment ◽  
Step Method ◽  
Two Stage ◽  
Dea Model ◽  
The Status ◽  
Dea Models

This paper suggests that the efficiency of a system (decision-making unit) and its subsystem cannot be properly measured using a two-stage data envelopment analysis (DEA) model either in cooperative or non-cooperative evaluation. Indeed, the existing methods subjectively determine the status of the subsystems in the whole system. The two-stage DEA models, either cooperative game or non-cooperative game, are used to analyze the environmental efficiency. However, when the actual relationship between the two subsystems is inconsistent with the subjective relationship assumptions, the overall efficiency of the system and the efficiency of each subsystem will be biased. The conventional two-stage DEA models require predetermining the relationship between the subsystems within the system based on the subjective judgment of the decision-maker. Based on this, this paper proposes a three-step method to solve the two-stage DEA. First, the position relation among subsystems is determined according to the optimal weights through the model. According to the status relationship among subsystems, the decision units are grouped, and the two-stage DEA model of cooperative game or non-cooperative game is used to analyze the efficiency in each group. This method reduces the subjectivity of decision making and analyzes the efficiency of each decision unit applying the most appropriate two-stage DEA model to find the source of inefficiency. Finally, this paper verifies the rationality and validity of the method by analyzing the water use efficiency of industrial systems in China. It is found that most regions in China value economic development more than environmental protection (as evidenced by the DEA weights). What is more, the method proposed by the paper can be generalized for any two-stage DEA problem.

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