IDEAS home Printed from https://ideas.repec.org/a/eee/matsoc/v84y2016icp109-118.html
   My bibliography  Save this article

Diffusion of behavior in network games with threshold dynamics

Author

Listed:
  • Huang, Jia-Ping
  • Koster, Maurice
  • Lindner, Ines

Abstract

In this paper we propose a generalized model of network games to incorporate preferences as an endogenous driving force of innovation. Individuals can choose between two actions: either to adopt a new behavior or stay with the default one. A key element is an individual threshold, i.e. the number or proportion of others who must take action before a given actor does so. This threshold represents an individual’s inclination to adopt the new behavior. The main novelty of the paper is to assume that the thresholds are endogenously determined. Agents change their inclination by exposition to other inclinations in the social network. This provides a coupled dynamical system of aggregate adoption rate and inclinations orchestrated by the network. With our model we are able to explain a variety of adoption behavior. Of particular interest is the existence of non-monotonic behavior of the aggregate adoption rate which is not possible in the benchmark model without inclination. Our model is therefore able to explain “sudden” outbreaks of collective action. This suggests to reinvent the common static and exogenous concept of a tipping point by defining it endogenously generated by the network.

Suggested Citation

  • Huang, Jia-Ping & Koster, Maurice & Lindner, Ines, 2016. "Diffusion of behavior in network games with threshold dynamics," Mathematical Social Sciences, Elsevier, vol. 84(C), pages 109-118.
    • Handle: RePEc:eee:matsoc:v:84:y:2016:i:c:p:109-118
    DOI: 10.1016/j.mathsocsci.2016.10.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165489616301305
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.mathsocsci.2016.10.007?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Matthew O. Jackson & Leeat Yariv, 2007. "Diffusion of Behavior and Equilibrium Properties in Network Games," American Economic Review, American Economic Association, vol. 97(2), pages 92-98, May.
    2. López-Pintado, Dunia, 2008. "Diffusion in complex social networks," Games and Economic Behavior, Elsevier, vol. 62(2), pages 573-590, March.
    3. Eger, Steffen, 2016. "Opinion dynamics and wisdom under out-group discrimination," Mathematical Social Sciences, Elsevier, vol. 80(C), pages 97-107.
    4. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    5. Dauhoo, Muhammad Zaid & Juggurnath, Diksha & Badurally Adam, Noure-Roukayya, 2016. "The stochastic evolution of rumors within a population," Mathematical Social Sciences, Elsevier, vol. 82(C), pages 85-96.
    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. Jia-Ping Huang & Yang Zhang & Juanxi Wang, 2023. "Dynamic effects of social influence on asset prices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 671-699, July.

    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. Tomas Rodriguez Barraquer, 2013. "From sets of equilibria to structures of interaction underlying binary games of strategic complements," Discussion Paper Series dp655, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    2. Lelarge, Marc, 2012. "Diffusion and cascading behavior in random networks," Games and Economic Behavior, Elsevier, vol. 75(2), pages 752-775.
    3. Daniel C. Opolot & Théophile T. Azomahou, 2021. "Strategic diffusion in networks through contagion," Journal of Evolutionary Economics, Springer, vol. 31(3), pages 995-1027, July.
    4. López-Pintado, Dunia, 2012. "Influence networks," Games and Economic Behavior, Elsevier, vol. 75(2), pages 776-787.
    5. Shin, Euncheol, 2017. "Monopoly pricing and diffusion of social network goods," Games and Economic Behavior, Elsevier, vol. 102(C), pages 162-178.
    6. Lamberson PJ, 2010. "Social Learning in Social Networks," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 10(1), pages 1-33, August.
    7. Vivi Alatas & Abhijit Banerjee & Arun G. Chandrasekhar & Rema Hanna & Benjamin A. Olken, 2016. "Network Structure and the Aggregation of Information: Theory and Evidence from Indonesia," American Economic Review, American Economic Association, vol. 106(7), pages 1663-1704, July.
    8. Tingqiang Chen & Binqing Xiao & Haifei Liu, 2018. "Credit Risk Contagion in an Evolving Network Model Integrating Spillover Effects and Behavioral Interventions," Complexity, Hindawi, vol. 2018, pages 1-16, March.
    9. Pongou, Roland & Serrano, Roberto, 2013. "Dynamic Network Formation in Two-Sided Economies," MPRA Paper 46021, University Library of Munich, Germany.
    10. Gong, Qingbin & Diao, Xundi, 2023. "The impacts of investor network and herd behavior on market stability: Social learning, network structure, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1388-1398.
    11. Boyer, Tristan & Jonard, Nicolas, 2014. "Imitation and efficient contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 100(C), pages 20-32.
    12. Giovanni Pegoretti & Francesco Rentocchini & Giuseppe Vittucci Marzetti, 2012. "An agent-based model of innovation diffusion: network structure and coexistence under different information regimes," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 145-165, October.
    13. Francesco Bogliacino & Giorgio Rampa, 2012. "Quality risk aversion, conjectures, and new product diffusion," Journal of Evolutionary Economics, Springer, vol. 22(5), pages 1081-1115, November.
    14. Oyama, Daisuke & Takahashi, Satoru, 2015. "Contagion and uninvadability in local interaction games: The bilingual game and general supermodular games," Journal of Economic Theory, Elsevier, vol. 157(C), pages 100-127.
    15. López-Pintado, Dunia & Meléndez-Jiménez, Miguel A., 2021. "Far above others," Journal of Economic Theory, Elsevier, vol. 198(C).
      • Dunia López-Pintado & Miguel A. Meléndez-Jiménez, 2018. "Far above others," Working Papers 18.12, Universidad Pablo de Olavide, Department of Economics.
    16. Michael Olabisi, 2019. "Bridging the enforcement gap in international trade: Participation in the New York Convention on arbitration," Journal of International Business Policy, Palgrave Macmillan, vol. 2(1), pages 86-109, March.
    17. H Peyton Young & Lucas Merrill Brown, 2016. "The Diffusion of a Social Innovation: Executive Stock Options from 1936," Economics Series Working Papers 777, University of Oxford, Department of Economics.
    18. Michel Grabisch & Agnieszka Rusinowska & Xavier Venel, 2019. "Diffusion in countably infinite networks," Documents de travail du Centre d'Economie de la Sorbonne 19017, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    19. Jia-Ping Huang & Maurice Koster & Ines Lindner, 2013. "Diffusion of Behavior in Network Games Orchestrated by Social Learning," Tinbergen Institute Discussion Papers 13-208/II, Tinbergen Institute.
    20. Itai Arieli & Yakov Babichenko & Ron Peretz & H. Peyton Young, 2018. "The Speed of Innovation Diffusion," Economics Papers 2018-W06, Economics Group, Nuffield College, University of Oxford.

    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:eee:matsoc:v:84:y:2016:i:c:p:109-118. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505565 .

    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.