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The role of (personal) network effects and switching costs in determining mobile users' choice

  • Research Article
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Journal of Information Technology

Abstract

Network effects and switching costs are two major economic forces in information technology industries. Although the consequences of these mechanisms on competition and firm strategy have been well documented in the literature, research on their impact on customer behavior has received less attention. In this study, the authors investigate the role of personal network effects and switching costs in explaining customer choice in the Spanish mobile telecommunications industry. Personal network effects are present when an individual user's utility increases more when some individuals adopt (social network) than when others do. Switching costs refer to costs associated with the process of switching from one provider to another. In addition, this paper studies the drivers of personal network effects and switching behavior. The results reveal that personal network effects and switching costs play a key role in determining mobile users' choice: the probability that a customer selects a mobile phone company increases with the number of members of her social network already subscribed to that firm, and switching costs are significantly present in the mobile phone market making switching providers costly. Concerning the drivers of both mechanisms, the authors find that relationship characteristics (length, depth and breadth) and demographics differently affect personal network effects perceptions and consumer switching behavior. Implications for decision makers are discussed.

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Notes

  1. Price or tariff-mediated effects are the terms used in the literature to refer to this type of network effects (Laffont et al., 1998).

  2. This quotation from The Economist in 2007 perfectly illustrates our assertion: ‘Although mobile phones make it easier to keep in regular touch with a wide group of friends, for example, it turns out that a typical user spends 80% of his or her time communicating with just four other people’ (Economist, 2007).

  3. On 30 May 1996, the European Commission wrote a ‘warning letter’ and sent it to all GSM network operators and all manufacturers of handsets in the EU alerting them about the anti-competitive effects of the SIMLock feature. The Commission also wrote to ETSI, the European Telecommunications Standards Institute, which was proposing to standardize this feature as part of the GSM standard (European Commission, 1996).

  4. The assumption that the random disturbances are mutually independent is the origin of the Independence from Irrelevant Alternatives property (IIA property), which is one of the most frequently discussed aspects of the conditional logit approach. This property states that the ratio of the choice probabilities of any two alternatives is independent of the systematic utilities of any other alternatives (Ben-Akiva and Lerman, 1985), and it implies a proportionate pattern of substitution across alternatives. Alternative modeling approaches have recently been developed to alleviate some of the negative consequences of the IIA property, including multinomial probit, nested logit, generalized extreme value and mixed logit models.

  5. In our model, we assume that the choices made by the members of the personal network are exogenous. However, rather than selecting companies individually, these choices may respond to joint decisions by members who belong to the network. We reserve this issue for future research.

  6. Customer churn, customer attrition and customer defection are the terms that refer to loss of clients. In recent years, there has been an increasing interest among academics to understand this phenomenon. Kim and Yoon (2004) empirically investigate the determinants of subscriber churn in the Korean mobile phone market and find that satisfaction with service attributes (call quality, tariffs, handsets, brand image) and relationship duration significantly affect customer churn intentions. In a study of customer churn in the same market, Ahn et al. (2006) find that switching costs, service quality and customer usage are important determinants of churn. Models to predict churn have also been the focus of researchers in recent years (Lemmens and Croux, 2006; Neslin et al., 2006).

  7. Four with the entry of Yoigo at the end of 2006, but this is outside of our research window.

  8. France Telecom acquired Amena in July 2005 and, at the end of 2006, Amena became Orange.

  9. Penetration rate is usually measured as the quotient between the number of mobile phones and the population. In most European countries, this ratio is above 100%, which means that most people have one mobile phone (and some people have even more than one).

  10. A set of control questions was included in the questionnaire to assess the validity of the responses provided by the participants.

  11. In this table, a somewhat surprising distribution of market shares can be observed. Real data at the end of 2006 (Merrill Lynch, 2008) shows the following distribution of market shares: 45.6% Movistar, 30.7% Vodafone and 23.6% Orange. The differences with the figures of the sample might respond to the segment analyzed in our study. Amena (currently Orange) focused its marketing strategy on attracting and retaining young customers. Therefore, the bias could be related to the type of users in the survey.

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Acknowledgements

Financial support from the Spanish Ministry of Education and Science and FEDER (projects SEJ2005-01856 and SEJ2005-05968) and the Regional Government of Aragón (S09-PM062) is gratefully acknowledged. Juan Pablo Maicas also acknowledges financial aid from the Secretary of State of Universities and Research provided through ‘Estancias de movilidad en el extranjero “José Castillejo” para jóvenes doctores’ (JC2008-00222) and from CAI through ‘Programa Europa,’ and the hospitality of the Cass Business School (City University of London). We thank the Associate Editor and two anonymous reviewers for their helpful comments.

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  1. Departamento de Economia y Dirección de Empresas, University of Zaragoza, Zaragoza, Spain

    Juan Pablo Maicas, Yolanda Polo & Francisco Javier Sese

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  1. Juan Pablo Maicas
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Correspondence to Juan Pablo Maicas.

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Maicas, J., Polo, Y. & Sese, F. The role of (personal) network effects and switching costs in determining mobile users' choice. J Inf Technol 24, 160–171 (2009). https://doi.org/10.1057/jit.2008.35

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