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Explaining clustering in social networks: towards an evolutionary theory of cascading benefits

Author

Listed:
  • Sheen S. Levine

    (Management Department, Lee Kong Chian School of Business, Singapore Management University, Singapore 178899, Singapore)

  • Robert Kurzban

    (Department of Psychology, 3720 Walnut Street, University of Pennsylvania, Philadelphia, PA 19104, USA)

Abstract
Individual and organizational actors enter into a large number of relationships that include benefiting others without ensuring the equality of reciprocal benefits. We suggest that actors have evolved mechanisms that guide them in the choice of exchange partners, even without conscious calculation or bookkeeping of gain and loss. One such mechanism directs actors to membership in clusters, which are homogenous groups of actors densely connected among themselves and only loosely connected to other groups. We suggest that clusters offer network externalities, which are not possible in sparse networks, thus conferring cascading benefits on the actors contained in those clusters. Using this logic, one can understand the omnipresence of clustering in social networks of individuals and firms. We review the benefits and challenges associated with clustering and use the logic of cascading benefits to derive empirical predictions. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • Sheen S. Levine & Robert Kurzban, 2006. "Explaining clustering in social networks: towards an evolutionary theory of cascading benefits," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 27(2-3), pages 173-187.
    • Handle: RePEc:wly:mgtdec:v:27:y:2006:i:2-3:p:173-187
    DOI: 10.1002/mde.1291
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    References listed on IDEAS

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    2. Timm Teubner & Sonia Camacho, 2023. "Facing Reciprocity: How Photos and Avatars Promote Interaction in Micro-communities," Group Decision and Negotiation, Springer, vol. 32(2), pages 435-467, April.
    3. Hassan M K Ghomrawi & Russell J Funk & Michael L Parks & Jason Owen-Smith & John M Hollingsworth, 2018. "Physician referral patterns and racial disparities in total hip replacement: A network analysis approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-10, February.
    4. Stienmetz, Jason L. & Fesenmaier, Daniel R., 2015. "Estimating value in Baltimore, Maryland: An attractions network analysis," Tourism Management, Elsevier, vol. 50(C), pages 238-252.
    5. Côme Billard, 2020. "Technology Contagion in Networks," Working Papers 2020.01, FAERE - French Association of Environmental and Resource Economists.
    6. Jesse Shore & Ethan Bernstein & David Lazer, 2015. "Facts and Figuring: An Experimental Investigation of Network Structure and Performance in Information and Solution Spaces," Organization Science, INFORMS, vol. 26(5), pages 1432-1446, October.
    7. Engel, Yuval & Kaandorp, Mariëtte & Elfring, Tom, 2017. "Toward a dynamic process model of entrepreneurial networking under uncertainty," Journal of Business Venturing, Elsevier, vol. 32(1), pages 35-51.
    8. Ebbes, Peter & Huang, Zan & Rangaswamy, Arvind, 2016. "Sampling designs for recovering local and global characteristics of social networks," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 578-599.
    9. Sheen S. Levine & Michael J. Prietula, 2012. "How Knowledge Transfer Impacts Performance: A Multilevel Model of Benefits and Liabilities," Organization Science, INFORMS, vol. 23(6), pages 1748-1766, December.
    10. Sheen S. Levine & Michael J. Prietula & Ann Majchrzak, 2022. "Advice in Crisis: Principles of Organizational and Entrepreneurial Resilience," Journal of Organization Design, Springer;Organizational Design Community, vol. 11(4), pages 145-168, December.
    11. Sanghita Basu & Mousumi Roy & Parimal Pal, 2019. "Corporate greening in a large developing economy: pollution prevention strategies," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(4), pages 1603-1633, August.

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