IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0110788.html
   My bibliography  Save this article

Know Thy Neighbor: Costly Information Can Hurt Cooperation in Dynamic Networks

Author

Listed:
  • Alberto Antonioni
  • Maria Paula Cacault
  • Rafael Lalive
  • Marco Tomassini

Abstract

People need to rely on cooperation with other individuals in many aspects of everyday life, such as teamwork and economic exchange in anonymous markets. We study whether and how the ability to make or break links in social networks fosters cooperate, paying particular attention to whether information on an individual's actions is freely available to potential partners. Studying the role of information is relevant as information on other people's actions is often not available for free: a recruiting firm may need to call a job candidate's references, a bank may need to find out about the credit history of a new client, etc. We find that people cooperate almost fully when information on their actions is freely available to their potential partners. Cooperation is less likely, however, if people have to pay about half of what they gain from cooperating with a cooperator. Cooperation declines even further if people have to pay a cost that is almost equivalent to the gain from cooperating with a cooperator. Thus, costly information on potential neighbors' actions can undermine the incentive to cooperate in fluid networks.

Suggested Citation

  • Alberto Antonioni & Maria Paula Cacault & Rafael Lalive & Marco Tomassini, 2014. "Know Thy Neighbor: Costly Information Can Hurt Cooperation in Dynamic Networks," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-8, October.
  • Handle: RePEc:plo:pone00:0110788
    DOI: 10.1371/journal.pone.0110788
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0110788
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0110788&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0110788?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Miyaji, Kohei & Wang, Zhen & Tanimoto, Jun & Hagishima, Aya & Kokubo, Satoshi, 2013. "The evolution of fairness in the coevolutionary ultimatum games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 13-18.
    2. Matthew O. Jackson & Tomas Rodriguez-Barraquer & Xu Tan, 2012. "Social Capital and Social Quilts: Network Patterns of Favor Exchange," American Economic Review, American Economic Association, vol. 102(5), pages 1857-1897, August.
    3. Francisco C Santos & Jorge M Pacheco & Tom Lenaerts, 2006. "Cooperation Prevails When Individuals Adjust Their Social Ties," PLOS Computational Biology, Public Library of Science, vol. 2(10), pages 1-8, October.
    4. Siddharth Suri & Duncan J Watts, 2011. "Cooperation and Contagion in Web-Based, Networked Public Goods Experiments," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-18, March.
    5. Jelena Grujić & Constanza Fosco & Lourdes Araujo & José A Cuesta & Angel Sánchez, 2010. "Social Experiments in the Mesoscale: Humans Playing a Spatial Prisoner's Dilemma," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-9, November.
    6. Greiner, Ben, 2004. "An Online Recruitment System for Economic Experiments," MPRA Paper 13513, University Library of Munich, Germany.
    7. Frédéric Schneider & Roberto A. Weber, 2013. "Long-term commitment and cooperation," ECON - Working Papers 130, Department of Economics - University of Zurich.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tatsuya Sasaki & Hitoshi Yamamoto & Isamu Okada & Satoshi Uchida, 2017. "The Evolution of Reputation-Based Cooperation in Regular Networks," Games, MDPI, vol. 8(1), pages 1-16, January.
    2. Sibilla Di Guida & The Anh Han & Georg Kirchsteiger & Tom Lenaerts & Ioannis Zisis, 2021. "Repeated Interaction and Its Impact on Cooperation and Surplus Allocation—An Experimental Analysis," Games, MDPI, vol. 12(1), pages 1-19, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Floriana Gargiulo & José J Ramasco, 2012. "Influence of Opinion Dynamics on the Evolution of Games," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
    2. Michael Foley & Rory Smead & Patrick Forber & Christoph Riedl, 2021. "Avoiding the bullies: The resilience of cooperation among unequals," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.
    3. Takahiro Ezaki & Naoki Masuda, 2017. "Reinforcement learning account of network reciprocity," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-8, December.
    4. Jelena Grujić & Torsten Röhl & Dirk Semmann & Manfred Milinski & Arne Traulsen, 2012. "Consistent Strategy Updating in Spatial and Non-Spatial Behavioral Experiments Does Not Promote Cooperation in Social Networks," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-8, November.
    5. Milena Tsvetkova & Claudia Wagner & Andrew Mao, 2018. "The emergence of inequality in social groups: Network structure and institutions affect the distribution of earnings in cooperation games," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-16, July.
    6. Alberto Antonioni & Maria Paula Cacault & Rafael Lalive & Marco Tomassini, 2013. "Coordination on Networks: Does Topology Matter?," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    7. Deng, Lili & Zhang, Xingxing & Wang, Cheng, 2021. "Coevolution of spatial ultimatum game and link weight promotes fairness," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    8. Tsvetkova, Milena & Wagner, Claudia & Mao, Andrew, 2018. "The emergence of inequality in social groups: network structure and institutions affect the distribution of earnings in cooperation games," LSE Research Online Documents on Economics 89716, London School of Economics and Political Science, LSE Library.
    9. Yali Dong & Cong Li & Yi Tao & Boyu Zhang, 2015. "Evolution of Conformity in Social Dilemmas," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-12, September.
    10. Dennie van Dolder & Vincent Buskens, 2014. "Individual Choices in Dynamic Networks: An Experiment on Social Preferences," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-16, April.
    11. Jillian J Jordan & David G Rand & Samuel Arbesman & James H Fowler & Nicholas A Christakis, 2013. "Contagion of Cooperation in Static and Fluid Social Networks," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-10, June.
    12. Manapat, Michael L. & Nowak, Martin A. & Rand, David G., 2013. "Information, irrationality, and the evolution of trust," Journal of Economic Behavior & Organization, Elsevier, vol. 90(S), pages 57-75.
    13. Simon D Angus & Jonathan Newton, 2020. "Collaboration leads to cooperation on sparse networks," PLOS Computational Biology, Public Library of Science, vol. 16(1), pages 1-11, January.
    14. Paul E Smaldino & Mark Lubell, 2011. "An Institutional Mechanism for Assortment in an Ecology of Games," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-7, August.
    15. Li, Yan & Ye, Hang, 2015. "Effect of migration based on strategy and cost on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 76(C), pages 156-165.
    16. Britta Hoyer & Stephanie Rosenkranz, 2018. "Determinants of Equilibrium Selection in Network Formation: An Experiment," Games, MDPI, vol. 9(4), pages 1-25, November.
    17. Sergio Sousa, 2010. "Small-scale changes in wealth and attitudes toward risk," Discussion Papers 2010-11, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    18. Yamada, Katsunori & Sato, Masayuki, 2013. "Another avenue for anatomy of income comparisons: Evidence from hypothetical choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 89(C), pages 35-57.
    19. Franziska Tausch & Jan Potters & Arno Riedl, 2014. "An experimental investigation of risk sharing and adverse selection," Journal of Risk and Uncertainty, Springer, vol. 48(2), pages 167-186, April.
    20. Simeon Schudy & Verena Utikal, 2015. "Does imperfect data privacy stop people from collecting personal health data?," TWI Research Paper Series 98, Thurgauer Wirtschaftsinstitut, Universität Konstanz.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0110788. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.