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Behavioral Patterns In Social Networks

Author

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  • Anna Conte
  • Daniela T. Di Cagno
  • Emanuela Sciubba

Abstract

type="main" xml:id="ecin12191-abs-0001"> In this article, we focus on the analysis of individual decision-making for the formation of social networks, using experimentally generated data. We analyze the determinants of the individual demand for links under the assumption of agents' static expectations and identify patterns of behavior that correspond to three specific objectives: players propose links so as to maximize expected profits (myopic best response strategy); players attempt to establish the largest number of direct links (reciprocator strategy); and players maximize expected profits per direct link (opportunistic strategy). These strategies explain approximately 74% of the observed choices. We demonstrate that they are deliberately adopted and, by means of a finite mixture model, well identified and separated in our sample . ( JEL C33, C35, C90, D85)

Suggested Citation

  • Anna Conte & Daniela T. Di Cagno & Emanuela Sciubba, 2015. "Behavioral Patterns In Social Networks," Economic Inquiry, Western Economic Association International, vol. 53(2), pages 1331-1349, April.
    • Handle: RePEc:bla:ecinqu:v:53:y:2015:i:2:p:1331-1349
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    File URL: http://hdl.handle.net/10.1111/ecin.2015.53.issue-2
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    Cited by:

    1. Wirth, Herbert & Kulczycka, Joanna & Hausner, Jerzy & Koński, Maciej, 2016. "Corporate Social Responsibility: Communication about social and environmental disclosure by large and small copper mining companies," Resources Policy, Elsevier, vol. 49(C), pages 53-60.
    2. Alberti, Federica & Conte, Anna & Di Cagno, Daniela T. & Sciubba, Emanuela, 2024. "On the relational aspects of trust and trustworthiness: Results from a laboratory experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 219(C), pages 214-230.
    3. Daniela Cagno & Arianna Galliera & Werner Güth & Noemi Pace, 2018. "Behavioral patterns and reduction of sub-optimality: an experimental choice analysis," Theory and Decision, Springer, vol. 85(2), pages 151-177, August.
    4. Carrillo, Juan D. & Gaduh, Arya, 2021. "Dynamics and stability of social and economic networks: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1144-1176.
    5. Liangjie Xia & Tingting Guo & Juanjuan Qin & Xiaohang Yue & Ning Zhu, 2018. "Carbon emission reduction and pricing policies of a supply chain considering reciprocal preferences in cap-and-trade system," Annals of Operations Research, Springer, vol. 268(1), pages 149-175, September.
    6. Witte, Marc J., 2025. "Why Do Workers Make Job Referrals? Experimental Evidence from Ethiopia," IZA Discussion Papers 18258, IZA Network @ LISER.

    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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