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Author:

Cui, T. (Cui, T..) | Zhang, S. (Zhang, S..)

Indexed by:

Scopus

Abstract:

It’s difficult to guarantee the effect of the source classification of domestic waste only by government, so it’s necessary to rely on the participation of residents, social organizations and other forces. In this paper, by constructing the evolutionary game model of government, residents and social organizations, studies the evolutionary stability strategy, and uses matlab for simulation analysis. The results show that (1) When government loosely supervises and residents don’t participate in the classification, the frequency of participation of social organizations is not high, which is not conducive to the classification of waste sources. (2) When government strictly supervises and residents do not participate in the classification, social organizations are more active in participating, but the government’s management cost is too high. (3) When government loosely supervises and residents participate in classification, the participation rate of social organizations increases, and residents’ awareness of independent participation in waste classification is increased, also can achieve the desired objective waste classification. (4) When government strictly supervises and residents participate in classification, social organizations participate actively at the highest level, this form of positive attitudes by all three parties is also the best way to efficiently carry out waste classification at source. © 2022 WITPress. All rights reserved.

Keyword:

governance evolutionary game cooperative waste classification

Author Community:

  • [ 1 ] [Cui T.]School of Economics and Management, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Zhang S.]School of Economics and Management, Beijing University of Technology, Beijing, 100124, China

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Source :

International Journal of Sustainable Development and Planning

ISSN: 1743-7601

Year: 2022

Issue: 2

Volume: 17

Page: 523-529

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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