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Social Interactions, Network Fluidity and Network Effects

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Abstract

This paper asks how much the strength of network effects depends on the stability and structure of the underlying social network. I answer this using extensive micro-data on all potential adopters of a firm's internal video-messaging system and their subsequent video-messaging. This firm's New York office had to be relocated due to the terrorist attacks of 2001 which lead to a physical re-organization of teams in that city but not in other comparable cities. I study the consequences of this disruption for adoption of video-messaging and the size of network effects. I find evidence that generally network effects are based on direct social interactions. Potential adopters react to adoption only by people they wish to communicate with: They are not affected by adoption by other people. However, when there is a disruption to the social network and communication patterns become less predictable, users become more responsive to adoption by a broader group of users.

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File URL: http://www.netinst.org/Tucker_08-30.pdf
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Bibliographic Info

Paper provided by NET Institute in its series Working Papers with number 08-30.

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Length: 27 pages
Date of creation: Oct 2008
Date of revision:
Handle: RePEc:net:wpaper:0830

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Web page: http://www.NETinst.org/

Related research

Keywords: Network Effects; Local Networks; Stability; Option-Value;

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References

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  1. Pindyck, Robert S., 1993. "Investments of uncertain cost," Journal of Financial Economics, Elsevier, vol. 34(1), pages 53-76, August.
  2. repec:att:wimass:9127 is not listed on IDEAS
  3. Nicholas Bloom, 2007. "The Impact of Uncertainty Shocks," NBER Working Papers 13385, National Bureau of Economic Research, Inc.
  4. Edward P. Lazear, 2000. "The Power of Incentives," American Economic Review, American Economic Association, vol. 90(2), pages 410-414, May.
  5. Arun Sundararajan, 2004. "Local Network Effects and Network Structure," Industrial Organization 0412011, EconWPA.
  6. Gale, Douglas & Kariv, Shachar, 2003. "Bayesian learning in social networks," Games and Economic Behavior, Elsevier, vol. 45(2), pages 329-346, November.
  7. Marc Rysman, 2004. "Competition Between Networks: A�Study of the Market for Yellow�Pages," Review of Economic Studies, Wiley Blackwell, vol. 71(2), pages 483-512, 04.
  8. Jenkins, Stephen P, 1995. "Easy Estimation Methods for Discrete-Time Duration Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(1), pages 129-38, February.
  9. Eduardo S. Schwartz & Carlos Zozaya-Gorostiza, 2003. "Investment Under Uncertainty in Information Technology: Acquisition and Development Projects," Management Science, INFORMS, vol. 49(1), pages 57-70, January.
  10. Manski, Charles F, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Wiley Blackwell, vol. 60(3), pages 531-42, July.
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Cited by:
  1. Elsner, Wolfram & Heinrich, Torsten, 2009. "A simple theory of 'meso'. On the co-evolution of institutions and platform size--With an application to varieties of capitalism and 'medium-sized' countries," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(5), pages 843-858, October.
  2. Elsner, Wolfram & Schwardt, Henning, 2012. "Trust and Arena Size. Expectations, Trust, and Institutions Co-Evolving, and Their Critical Population and Group Sizes," MPRA Paper 40393, University Library of Munich, Germany.

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