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  Communicating sentiment and outlook reverses inaction against collective risks

Wang, Z., Jusup, M., Guo, H., Shi, L., Geček, S., Anand, M., Perc, M., Bauch, C. T., Kurths, J., Boccaletti, S., Schellnhuber, H. J. (2020): Communicating sentiment and outlook reverses inaction against collective risks. - Proceedings of the National Academy of Sciences of the United States of America (PNAS), 117, 30, 17650-17655.
https://doi.org/10.1073/pnas.1922345117

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Wang, Zhen1, Autor
Jusup, Marko1, Autor
Guo, Hao1, Autor
Shi, Lei1, Autor
Geček, Sunčana1, Autor
Anand, Madhur1, Autor
Perc, Matjaž1, Autor
Bauch, Chris T.1, Autor
Kurths, Jürgen2, Autor              
Boccaletti, Stefano1, Autor
Schellnhuber, Hans Joachim2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: Collective risks permeate society, triggering social dilemmas in which working toward a common goal is impeded by selfish interests. One such dilemma is mitigating runaway climate change. To study the social aspects of climate-change mitigation, we organized an experimental game and asked volunteer groups of three different sizes to invest toward a common mitigation goal. If investments reached a preset target, volunteers would avoid all consequences and convert their remaining capital into monetary payouts. In the opposite case, however, volunteers would lose all their capital with 50% probability. The dilemma was, therefore, whether to invest one’s own capital or wait for others to step in. We find that communicating sentiment and outlook helps to resolve the dilemma by a fundamental shift in investment patterns. Groups in which communication is allowed invest persistently and hardly ever give up, even when their current investment deficits are substantial. The improved investment patterns are robust to group size, although larger groups are harder to coordinate, as evidenced by their overall lower success frequencies. A clustering algorithm reveals three behavioral types and shows that communication reduces the abundance of the free-riding type. Climate-change mitigation, however, is achieved mainly by cooperator and altruist types stepping up and increasing contributions as the failure looms. Meanwhile, contributions from free riders remain flat throughout the game. This reveals that the mechanisms behind avoiding collective risks depend on an interaction between behavioral type, communication, and timing.

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 Datum: 2020-07-152020
 Publikationsstatus: Final veröffentlicht
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1073/pnas.1922345117
PIKDOMAIN: RD4 - Complexity Science
PIKDOMAIN: Director Emeritus / Executive Staff / Science & Society
MDB-ID: No data to archive
Organisational keyword: RD4 - Complexity Science
Organisational keyword: Director Emeritus Schellnhuber
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Complex Networks
Working Group: Network- and machine-learning-based prediction of extreme events
 Art des Abschluß: -

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Titel: Proceedings of the National Academy of Sciences of the United States of America (PNAS)
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 117 (30) Artikelnummer: - Start- / Endseite: 17650 - 17655 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals410
Publisher: National Academy of Sciences (NAS)