Article
Performance Measurement for the Recycling Production System
Using Cooperative Game Network Data Envelopment Analysis
Huang-Chu Huang
1
and Cheng-Feng Hu
2,
*
Citation: Huang, H.-C.; Hu, C.-F.
Performance Measurement for the
Recycling Production System Using
Cooperative Game Network Data
Envelopment Analysis. Sustainability
2021, 13, 11060. https://doi.org/
10.3390/su131911060
Academic Editors: João Carlos de
Oliveira Matias and Paolo Renna
Received: 30 July 2021
Accepted: 10 September 2021
Published: 7 October 2021
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1
Department of Telecommunication Engineering, National Kaohsiung University of Science and Technology,
Kaohsiung 82445, Taiwan; h4530@nkust.edu.tw
2
Department of Applied Mathematics, National Chiayi University, Chiayi 600355, Taiwan
* Correspondence: cfhu@mail.ncyu.edu.tw; Tel.: +886-5-271-7918
Abstract:
Resources scarcity and environmental degradation have made sustainable resource utiliza-
tion and environmental protection necessary worldwide. The development of the circular economy
is considered an approach for more appropriate economic and environmental management. This
work introduces a cooperative game network data envelopment analysis model for evaluating the
implementation effect of recycling production systems from a closed loop and centralized control
perspective. The factor efficiency analysis of the involved inputs and outputs is presented to provide
guidance for the factor dominance of subsystem efficiencies. An application for assessing the circular
economy of EU countries is provided to illustrate the validation of the proposed method. Our results
show that the average performance of the production subsystem is superior to that of the recy-
cling subsystem in EU countries. Furthermore, factor efficiency analysis reveals that the inefficient
environmental treatment input is the culprit in worse performance of the recycling subsystem. A
comparison of the proposed method with recent studies for circular economy performance evaluation
is also included.
Keywords:
environmental efficiency measurement; circular economy; network data envelopment
analysis; game theory
1. Introduction
Increasingly tight resource constraints and severe environmental degradation have
made the coordination between economic prosperity and environmental regulation a major
issue of concern to sustain our living world. The rise of the circular economy is one
of the most promising economic trends for sustaining the global ecological system and
developing industrial innovation. In a circular economy system, resources can be used
sustainably and cyclically to save resources and reduce pollution emissions, satisfying a
sustainable economic growth mode [
1
]. As a typical environment–economy linking system,
improving the eco-efficiency of the circular economy system has been gaining a lot of
attention and has played an importance role in the development of real economies and
environmental protection. Systematic literature reviews on circular economic performance
assessment methods have been presented recently [
2
,
3
]. Researchers adopted methods such
as life-cycle analysis [
4
], material flow analysis [
5
], and ecological footprint analysis [
6
]
to evaluate the eco-efficiencies of enterprises and industries. However, most of these
methods involve the use of subjective factors to determine the weights of indicators. Data
envelopment analysis (DEA) is a well-known frontier approach that effectively avoids
the subjectivity of weight determination and uses programming solvers to calculate the
input–output decision efficiency of decision making units (DMUs). It is the most efficient
tool available for assessing eco-efficiency.
Conventional DEA models regard the production system as a black box when measur-
ing efficiency, ignoring its internal structure. It has been found that ignoring the operations
of the components may produce efficiency measures that are misleading when a system
Sustainability 2021, 13, 11060. https://doi.org/10.3390/su131911060 https://www.mdpi.com/journal/sustainability
