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Me and you and everyone we know: An empirical analysis of local network effects in mobile communications

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  • Corrocher, Nicoletta
  • Zirulia, Lorenzo

Abstract

This paper investigates the importance that consumers assign to local network effects, i.e. the extent to which they take account of their contacts' mobile operators when choosing a provider for themselves. The authors identify individual characteristics that affect the importance consumers attach to local network effects. The study relies on a survey of 193 Italian students. The results show that consumers are highly heterogeneous with respect to the importance they give to the operators chosen by their friends/family members in choosing which provider to use. This heterogeneity is associated with individual innovativeness and patterns of mobile phone usage. For instance, consumers who are more interested in local network effects are typically more-aware users, who use voice services quite intensively. These consumers, who pay attention to local network effects, spend comparatively little proportional to the intensity of their mobile usage.

Suggested Citation

  • Corrocher, Nicoletta & Zirulia, Lorenzo, 0. "Me and you and everyone we know: An empirical analysis of local network effects in mobile communications," Telecommunications Policy, Elsevier, vol. 33(1-2), pages 68-79, February.
  • Handle: RePEc:eee:telpol:v:33:y::i:1-2:p:68-79
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    References listed on IDEAS

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    Cited by:

    1. Czajkowski, Mikołaj & Sobolewski, Maciej, 2016. "Estimating call externalities in mobile telephony," 27th European Regional ITS Conference, Cambridge (UK) 2016 148706, International Telecommunications Society (ITS).
    2. Mikołaj Czajkowski & Maciej Sobolewski, 2016. "Strategic use of external benefits for entry deterrence: the case of a mobile telephony market," Working Papers 2016-27, Faculty of Economic Sciences, University of Warsaw.
    3. Muck, Johannes, 2012. "The Effect of On-net/Off-net Differentiation and Heterogeneous Consumers on Network Size in Mobile Telecommunications – An Agent-based Approach," 19th ITS Biennial Conference, Bangkok 2012: Moving Forward with Future Technologies - Opening a Platform for All 72477, International Telecommunications Society (ITS).
    4. Liangjie Zhao & Wenqi Duan, 2014. "Simulating the Evolution of Market Shares: The Effects of Customer Learning and Local Network Externalities," Computational Economics, Springer;Society for Computational Economics, vol. 43(1), pages 53-70, January.
    5. Muck, Johannes, 2012. "The effect of on-net / off-net differentiation and heterogeneuous consumers on network size in mobile telecommunications : an agent-based aporoach," 23rd European Regional ITS Conference, Vienna 2012 60355, International Telecommunications Society (ITS).
    6. Karacuka, Mehmet & Çatık, A. Nazif & Haucap, Justus, 2013. "Consumer choice and local network effects in mobile telecommunications in Turkey," Telecommunications Policy, Elsevier, vol. 37(4), pages 334-344.
    7. Zucchini, Leon & Claussen, Jörg & Trüg, Moritz, 2013. "Tariff-mediated network effects versus strategic discounting: Evidence from German mobile telecommunications," International Journal of Industrial Organization, Elsevier, vol. 31(6), pages 751-759.
    8. Andreas Deckert & Robert Klein, 2014. "Simulation-based optimization of an agent-based simulation," Netnomics, Springer, vol. 15(1), pages 33-56, July.

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