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The role of self selection, usage uncertainty and learning in the demand for local telephone service

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  • Sridhar Narayanan

    ()

  • Pradeep Chintagunta

    ()

  • Eugenio Miravete

    ()

Abstract

Telephone services are often characterized by the presence of ‘fixed’ plans, involving only a fixed monthly fee, as well as ‘measured’ plans, with both fixed fees and per-unit charges for usage. Consumers are faced with the decisions of which plan to choose and how much to use the phone and these decisions are not, in general, independent. Due to the presence of a time lag between plan choice and usage decisions, consumers are uncertain about usage at the plan-choice stage. We develop a structural discrete/continuous model of plan choice and usage decisions of consumers that accounts for such uncertainty. Prior research has also found that consumers switch less often from fixed plans to measured plans to gain from potential savings than vice versa. Consumer uncertainty regarding their mean usage levels and different rates of learning by consumers in the two plans is a potential explanation for this phenomenon. We extend our discrete/continuous model to account for consumer learning about their mean usage and estimate different rates of learning for the two types of plans. We estimate our model using data from the 1986 Kentucky local telephone tariff experiment. Even in the absence of any price variation over time, we are able to measure the price elasticities both of usage and of choice of plan. Using our parameter estimates, we simulate the effects of the introduction of a metered plan in a market with only a fixed plan and vice versa, on both firm revenues and consumer surplus. We also find that consumers learn very rapidly if they are on the measured plan but learn very slowly when they are on the fixed plan. We investigate an alternative assumption on the nature of the learning process in which only consumers in the measured plan have an opportunity to learn. We find that our empirical results are robust to this change of specification. We conduct counterfactual simulations to simulate enhanced calling plans from the firm and consumer points of view. Additional simulations to measure the value of information in this category are also carried out. We compute the value of both complete information, where the entire uncertainty about future usage is resolved, as well as that of limited information, where the consumer's uncertainty about mean usage is resolved, but the uncertainty about specific month-to-month usage remains. We find that the value of information is modest. We also find that a large proportion of the value of information is that about the mean usage, with the value of the information about a specific month's usage being relatively small. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Sridhar Narayanan & Pradeep Chintagunta & Eugenio Miravete, 2007. "The role of self selection, usage uncertainty and learning in the demand for local telephone service," Quantitative Marketing and Economics (QME), Springer, vol. 5(1), pages 1-34, March.
  • Handle: RePEc:kap:qmktec:v:5:y:2007:i:1:p:1-34
    DOI: 10.1007/s11129-006-9015-z
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    References listed on IDEAS

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    Cited by:

    1. Patrick Bajari & Jeremy Fox & Stephen Ryan, 2008. "Evaluating wireless carrier consolidation using semiparametric demand estimation," Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 299-338, December.
    2. Ching-I Huang, 2008. "Estimating demand for cellular phone service under nonlinear pricing," Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 371-413, December.
    3. Szymanowski, M.G., 2009. "Consumption-based learning about brand quality : Essays on how private labels share and borrow reputation," Other publications TiSEM b12825d8-5e21-4437-adda-b, Tilburg University, School of Economics and Management.
    4. Grajek, Michal & Kretschmer, Tobias, 2009. "Usage and diffusion of cellular telephony, 1998-2004," International Journal of Industrial Organization, Elsevier, vol. 27(2), pages 238-249, March.
    5. repec:bri:cmpowp:13/321 is not listed on IDEAS
    6. Elliot Anenberg, 2012. "Information frictions and housing market dynamics," Finance and Economics Discussion Series 2012-48, Board of Governors of the Federal Reserve System (U.S.).
    7. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    8. Schlereth, Christian & Stepanchuk, Tanja & Skiera, Bernd, 2010. "Optimization and analysis of the profitability of tariff structures with two-part tariffs," European Journal of Operational Research, Elsevier, vol. 206(3), pages 691-701, November.
    9. Sergio Da Silva & Gustavo Manfrim, 2007. "Estimating demand elasticities of fixed telephony in Brazil," Economics Bulletin, AccessEcon, vol. 12(5), pages 1-9.
    10. repec:eee:ijrema:v:30:y:2013:i:3:p:219-235 is not listed on IDEAS
    11. Juanjuan Zhang, 2010. "The Sound of Silence: Observational Learning in the U.S. Kidney Market," Marketing Science, INFORMS, vol. 29(2), pages 315-335, 03-04.
    12. repec:aen:journl:ej38-6-pon is not listed on IDEAS
    13. Michaela Draganska & Sanjog Misra & Victor Aguirregabiria & Pat Bajari & Liran Einav & Paul Ellickson & Dan Horsky & Sridhar Narayanan & Yesim Orhun & Peter Reiss & Katja Seim & Vishal Singh & Raphael, 2008. "Discrete choice models of firms’ strategic decisions," Marketing Letters, Springer, vol. 19(3), pages 399-416, December.
    14. repec:ebl:ecbull:v:12:y:2007:i:5:p:1-9 is not listed on IDEAS
    15. Sudarshan, Anant, 2013. "Deconstructing the Rosenfeld curve: Making sense of California's low electricity intensity," Energy Economics, Elsevier, vol. 39(C), pages 197-207.
    16. Inderst, Roman & Peitz, Martin, 2012. "Informing consumers about their own preferences," International Journal of Industrial Organization, Elsevier, vol. 30(5), pages 417-428.
    17. Inderst, Roman & Peitz, Martin, 2008. "Selling Service Plans to Differentially Informed Customers," ZEW Discussion Papers 08-125, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
    18. Raghuram Iyengar & Kamel Jedidi & Skander Essegaier & Peter J. Danaher, 2011. "The Impact of Tariff Structure on Customer Retention, Usage, and Profitability of Access Services," Marketing Science, INFORMS, vol. 30(5), pages 820-836, September.
    19. repec:eee:ijrema:v:29:y:2012:i:2:p:167-180 is not listed on IDEAS
    20. repec:spr:jecstr:v:6:y:2017:i:1:d:10.1186_s40008-017-0066-y is not listed on IDEAS
    21. Tim Burnett, 2014. "The Impact of Service Bundling on Consumer Switching Behaviour: Evidence from UK Communication Markets," The Centre for Market and Public Organisation 14/321, Department of Economics, University of Bristol, UK.
    22. Bölcskei, Vanda, 2010. "A távbeszélő-szolgáltatások keresleti modelljeinek áttekintése - különös tekintettel a vezetékes és mobilszolgáltatások közötti helyettesítés becslésére
      [A review of the demand models of telephone
      ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 517-535.

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