Evidence map›Paper›PMID 34381969›Full record

ArticleiScience2021

Combination of institutional incentives for cooperative governance of risky commons.

Weiwei Sun, Linjie Liu, Xiaojie Chen, Attila Szolnoki, Vítor V Vasconcelos

Abstract read
In one paragraph

Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Revisiting institutional punishment in the N-person prisoner's dilemma.Theory in biosciences = Theorie in den Biowissenschaften · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Weiwei SunSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.
Linjie LiuSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.
Xiaojie ChenSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.
Attila SzolnokiInstitute of Technical Physics and Materials Science, Centre for Energy Research, P.O. Box 49, Budapest 1525, Hungary.
Vítor V VasconcelosInformatics Institute, University of Amsterdam, Science Park 904, 1098XH Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Finding appropriate incentives to enforce collaborative efforts for governing the commons in risky situations is a long-lasting challenge. Previous works have demonstrated that both punishing free-riders and rewarding cooperators could be potential tools to reach this goal. Despite weak theoretical foundations, policy makers frequently impose a punishment-reward combination. Here, we consider the emergence of positive and negative incentives and analyze their simultaneous impact on sustaining risky commons. Importantly, we consider institutions with fixed and flexible incentives. We find that a local sanctioning scheme with pure reward is the optimal incentive strategy. It can drive the entire population toward a highly cooperative state in a broad range of parameters, independently of the type of institutions. We show that our finding is also valid for flexible incentives in the global sanctioning scheme, although the local arrangement works more effectively.

Indexed as

Decision scienceGlobal changeNature conservationSocial sciences

Identifiers

PMID34381969
PMCPMC8334382

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.