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  Deterrence through punishment can resolve collective risk dilemmas in carbon emission games

Jiang, L.-L., Chen, Z., Perc, M., Wang, Z., Kurths, J., Moreno, Y. (2023): Deterrence through punishment can resolve collective risk dilemmas in carbon emission games. - Chaos, 33, 4, 043127.
https://doi.org/10.1063/5.0147226

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 Creators:
Jiang, Luo-Luo1, Author
Chen, Zhi1, Author
Perc, Matjaž1, Author
Wang, Zhen1, Author
Kurths, Jürgen2, Author              
Moreno, Yamir1, Author
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Collective risk social dilemmas are at the heart of the most pressing global challenges we are facing today, including climate change mitigation and the overuse of natural resources. Previous research has framed this problem as a public goods game (PGG), where a dilemma arises between short-term interests and long-term sustainability. In the PGG, subjects are placed in groups and asked to choose between cooperation and defection, while keeping in mind their personal interests as well as the commons. Here, we explore how and to what extent the costly punishment of defectors is successful in enforcing cooperation by means of human experiments. We show that an apparent irrational underestimation of the risk of being punished plays an important role, and that for sufficiently high punishment fines, this vanishes and the threat of deterrence suffices to preserve the commons. Interestingly, however, we find that high fines not only avert freeriders, but they also demotivate some of the most generous altruists. As a consequence, the tragedy of the commons is predominantly averted due to cooperators that contribute only their “fair share” to the common pool. We also find that larger groups require larger fines for the deterrence of punishment to have the desired prosocial effect.

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Language(s): eng - English
 Dates: 2023-04-132023-04-13
 Publication Status: Finally published
 Pages: 8
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1063/5.0147226
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Sustainable Development
Model / method: Game Theory
Model / method: Nonlinear Data Analysis
OATYPE: Green Open Access
 Degree: -

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Title: Chaos
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 33 (4) Sequence Number: 043127 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: American Institute of Physics (AIP)