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Social goods dilemmas in heterogeneous societies

Author

Listed:
  • Alex McAvoy

    (Harvard University)

  • Benjamin Allen

    (Emmanuel College)

  • Martin A. Nowak

    (Harvard University
    Harvard University)

Abstract

Prosocial behaviours are encountered in the donation game, the prisoner’s dilemma, relaxed social dilemmas and public goods games. Many studies assume that the population structure is homogeneous, meaning that all individuals have the same number of interaction partners or that the social good is of one particular type. Here, we explore general evolutionary dynamics for arbitrary spatial structures and social goods. We find that heterogeneous networks, in which some individuals have many more interaction partners than others, can enhance the evolution of prosocial behaviours. However, they often accumulate most of the benefits in the hands of a few highly connected individuals, while many others receive low or negative payoff. Surprisingly, selection can favour producers of social goods even if the total costs exceed the total benefits. In summary, heterogeneous structures have the ability to strongly promote the emergence of prosocial behaviours, but they also create the possibility of generating large inequality.

Suggested Citation

  • Alex McAvoy & Benjamin Allen & Martin A. Nowak, 2020. "Social goods dilemmas in heterogeneous societies," Nature Human Behaviour, Nature, vol. 4(8), pages 819-831, August.
    • Handle: RePEc:nat:nathum:v:4:y:2020:i:8:d:10.1038_s41562-020-0881-2
    DOI: 10.1038/s41562-020-0881-2
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    Citations

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    Cited by:

    1. Xu Chen & Xuan Di & Zechu Li, 2023. "Social Learning for Sequential Driving Dilemmas," Games, MDPI, vol. 14(3), pages 1-12, May.
    2. Wang, Chaoqian & Szolnoki, Attila, 2022. "Involution game with spatio-temporal heterogeneity of social resources," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    3. Chaoqian Wang & Matjaž Perc & Attila Szolnoki, 2024. "Evolutionary dynamics of any multiplayer game on regular graphs," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    4. Li, Wen-Jing & Chen, Zhi & Jin, Ke-Zhong & Wang, Jun & Yuan, Lin & Gu, Changgui & Jiang, Luo-Luo & Perc, Matjaž, 2022. "Options for mobility and network reciprocity to jointly yield robust cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    5. Yao Meng & Sean P. Cornelius & Yang-Yu Liu & Aming Li, 2024. "Dynamics of collective cooperation under personalised strategy updates," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    6. Li, Wen-Jing & Chen, Zhi & Wang, Jun & Jiang, Luo-Luo & Perc, Matjaž, 2023. "Social mobility and network reciprocity shape cooperation in collaborative networks," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    7. Kamran Kaveh & Alex McAvoy & Krishnendu Chatterjee & Martin A Nowak, 2020. "The Moran process on 2-chromatic graphs," PLOS Computational Biology, Public Library of Science, vol. 16(11), pages 1-18, November.
    8. Alex McAvoy & Andrew Rao & Christoph Hauert, 2021. "Intriguing effects of selection intensity on the evolution of prosocial behaviors," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-21, November.
    9. Jayles, Bertrand & Cheong, Siew Ann & Herrmann, Hans J., 2022. "Interactions between communities improve the resilience of multicultural societies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    10. Wang, Chaoqian, 2024. "Evolution of trust in structured populations," Applied Mathematics and Computation, Elsevier, vol. 471(C).
    11. Zhang, Wei, 2024. "Network reciprocity and inequality: The role of additional mixing links among social groups," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    12. Xiaochen Wang & Lei Zhou & Alex McAvoy & Aming Li, 2023. "Imitation dynamics on networks with incomplete information," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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