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

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Author Info

  • 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

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File URL: http://hdl.handle.net/10.1007/s11129-006-9015-z
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Bibliographic Info

Article provided by Springer in its journal Quantitative Marketing and Economics.

Volume (Year): 5 (2007)
Issue (Month): 1 (March)
Pages: 1-34

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Handle: RePEc:kap:qmktec:v:5:y:2007:i:1:p:1-34

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Web page: http://www.springerlink.com/link.asp?id=111240

Related research

Keywords: Self-selection; Uncertainty; Value of information; Discrete/continuous models; Learning models; Telecommunications; Optional calling plans;

References

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  1. Nair, Harikesh S. & Dube, Jean-Pierre & Chintagunta, Pradeep, 2004. "Accounting for Primary and Secondary Demand Effects with Aggregate Data," Research Papers 1949, Stanford University, Graduate School of Business.
  2. Ching-I Huang, 2008. "Estimating demand for cellular phone service under nonlinear pricing," Quantitative Marketing and Economics, Springer, vol. 6(4), pages 371-413, December.
  3. Eugenio J. Miravete, 2003. "Choosing the Wrong Calling Plan? Ignorance and Learning," American Economic Review, American Economic Association, vol. 93(1), pages 297-310, March.
  4. Harvey S. Rosen & Kenneth A. Small, 1981. "Applied Welfare Economics with Discrete Choice Models," NBER Working Papers 0319, National Bureau of Economic Research, Inc.
  5. Anja Lambrecht & Katja Seim & Bernd Skiera, 2007. "Does Uncertainty Matter? Consumer Behavior Under Three-Part Tariffs," Marketing Science, INFORMS, vol. 26(5), pages 698-710, 09-10.
  6. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
  7. Nickolay V. Moshkin & Ron Shachar, 2002. "The Asymmetric Information Model of State Dependence," Marketing Science, INFORMS, vol. 21(4), pages 435-454, August.
  8. Jin, Ginger Zhe & Sorensen, Alan T., 2006. "Information and consumer choice: The value of publicized health plan ratings," Journal of Health Economics, Elsevier, vol. 25(2), pages 248-275, March.
  9. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
  10. Park, Rolla Edward & Mitchell, Bridger M. & Wetzel, Bruce M. & Alleman, James H., 1983. "Charging for local telephone calls : How household characteristics affect the distribution of calls in the GTE Illinois experiment," Journal of Econometrics, Elsevier, vol. 22(3), pages 339-364, August.
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Citations

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Cited by:
  1. 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.
  2. repec:ebl:ecbull:v:12:y:2007:i:5:p:1-9 is not listed on IDEAS
  3. Bölcskei, Vanda, 2010. "A távbeszélő-szolgáltatások keresleti modelljeinek áttekintése - különös tekintettel a vezetékes és mobilszolgáltatások közötti helyettesítés becslésére
    [A review of the demand
    ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 517-535.
  4. 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.
  5. Ching-I Huang, 2008. "Estimating demand for cellular phone service under nonlinear pricing," Quantitative Marketing and Economics, Springer, vol. 6(4), pages 371-413, December.
  6. Patrick Bajari & Jeremy Fox & Stephen Ryan, 2008. "Evaluating wireless carrier consolidation using semiparametric demand estimation," Quantitative Marketing and Economics, Springer, vol. 6(4), pages 299-338, December.
  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. Peitz, Martin & Inderst, Roman, 2012. "Informing Consumers about their own Preferences," Working Papers 12-07, University of Mannheim, Department of Economics.
  9. Tim Burnett, 2014. "The Impact of Service Bundling on Consumer Switching Behaviour: Evidence from UK Communication Markets," The Centre for Market and Public Organisation 13/321, Department of Economics, University of Bristol, UK.
  10. Sudarshan, Anant, 2013. "Deconstructing the Rosenfeld curve: Making sense of California's low electricity intensity," Energy Economics, Elsevier, vol. 39(C), pages 197-207.
  11. 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.
  12. Sergio Da Silva & Gustavo Manfrim, 2007. "Estimating demand elasticities of fixed telephony in Brazil," Economics Bulletin, AccessEcon, vol. 12(5), pages 1-9.
  13. Agnieszka Wolk & Bernd Skiera, 2010. "Tariff-Specific Preferences and Their Influence on Price Sensitivity," BuR - Business Research, German Academic Association for Business Research, vol. 3(1), pages 70-80, May.
  14. 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.).

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