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Pricing Patterns of Cellular Phones and Phonecalls: A Segment-Level Analysis

Author

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  • Dipak C. Jain

    (J. L. Kellogg Graduate School of Management, Northwestern University, Evanston, Illinois 60208-2001)

  • Eitan Muller

    (Recanati Graduate School of Business, Tel Aviv University, Ramat-Aviv, Tel Aviv 69978, Israel)

  • Naufel J. Vilcassim

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089-1421)

Abstract

One expectation of the U.S. Federal Communications Commission (FCC) in the early stages of the cellular communications industry was that the presence of two licensees in each market would ensure competition, and thereby result in declining prices over time for both cellular phones (handsets) and phonecalls. However, industry observers have noted recently that although the price of handsets has declined over time, the price of the phonecalls has not. We investigate this interesting pricing issue by modeling the market interaction between the providers of cellular services and also their interaction with customers using a game theoretic framework. A critical assumption in the development of our model is that there exist segments of customers with different valuations, usage levels, and price sensitivities for cellular service. Empirically, we provide support for the existence of two customer segments (viz., Business/Professional and Personal) from both secondary data on industry usage and revenue, and primary data collected from a conjoint analysis study of cellular service customers. From the latter source, we also establish that the Business/Professional customers are more sensitive to prices of phonecalls than the Personal segment. From our analytical model, we characterize the conditions under which penetration and skimming pricing strategies for the handsets are profit-maximizing from the sellers' standpoint, and derive the corresponding price of phonecalls. One of our main analytical results is that a competitive structure can result in lower prices over time for the handset, but higher prices for the phonecalls, depending on production costs of the handset. We are thus able to provide a theoretical explanation for the observed price patterns for the handset and phonecalls.

Suggested Citation

  • Dipak C. Jain & Eitan Muller & Naufel J. Vilcassim, 1999. "Pricing Patterns of Cellular Phones and Phonecalls: A Segment-Level Analysis," Management Science, INFORMS, vol. 45(2), pages 131-141, February.
    • Handle: RePEc:inm:ormnsc:v:45:y:1999:i:2:p:131-141
    DOI: 10.1287/mnsc.45.2.131
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    References listed on IDEAS

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    1. In-Koo Cho & David M. Kreps, 1987. "Signaling Games and Stable Equilibria," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(2), pages 179-221.
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    Cited by:

    1. Mesak, Hani I. & Bari, Abdullahel & Babin, Barry J. & Birou, Laura M. & Jurkus, Anthony, 2011. "Optimum advertising policy over time for subscriber service innovations in the presence of service cost learning and customers' disadoption," European Journal of Operational Research, Elsevier, vol. 211(3), pages 642-649, June.
    2. Hongjai Rhee & Sangkyu Rhee, 2009. "An Analysis Of Equilibrium Relationship Between Price Elasticity And Expenditure Level: A Case Study Of Korean Mobile Market Data," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 34(2), pages 69-83, December.
    3. Jacob Goldenberg & Barak Libai & Eitan Muller & Renana Peres, 2006. "Blazing Saddles: the early and mainstream markets in the High-Tech product life cycle," Israel Economic Review, Bank of Israel, vol. 4(2), pages 85-108.
    4. Vogelsang, Ingo, 2010. "The relationship between mobile and fixed-line communications: A survey," Information Economics and Policy, Elsevier, vol. 22(1), pages 4-17, March.
    5. Ferrer, Juan-Carlos & Mora, Hugo & Olivares, Francisco, 2010. "On pricing of multiple bundles of products and services," European Journal of Operational Research, Elsevier, vol. 206(1), pages 197-208, October.
    6. Kim, Young Joo & Hwang, Hark, 2009. "Incremental discount policy of cell-phone carrier with connection success rate constraint," European Journal of Operational Research, Elsevier, vol. 196(2), pages 682-687, July.
    7. Ting Zhu & Hongju Liu & Pradeep Chintagunta, 2015. "Wireless Carriers’ Exclusive Handset Arrangements: an Empirical Look at the iPhone," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(2), pages 177-190, June.
    8. Tristan Gagnon-Bartsch & Antonio Rosato, 2024. "Quality Is in the Eye of the Beholder: Taste Projection in Markets with Observational Learning," American Economic Review, American Economic Association, vol. 114(11), pages 3746-3787, November.
    9. Amit Mehra & Gireesh Shrimali, 2008. "Introduction of Software Products and Services Through "Public" Beta Launches," Working Papers 08-11, NET Institute.
    10. Muller, Eitan, 2020. "Delimiting disruption: Why Uber is disruptive, but Airbnb is not," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 43-55.
    11. Vidyanand Choudhary, 2010. "Use of Pricing Schemes for Differentiating Information Goods," Information Systems Research, INFORMS, vol. 21(1), pages 78-92, March.
    12. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    13. G. E. Fruchter & R. C. Rao & M. Shi, 2006. "Dynamic Network-Based Discriminatory Pricing," Journal of Optimization Theory and Applications, Springer, vol. 128(3), pages 581-604, March.
    14. Chen, Yi-Ting & Sun, Edward W. & Lin, Yi-Bing, 2020. "Merging anomalous data usage in wireless mobile telecommunications: Business analytics with a strategy-focused data-driven approach for sustainability," European Journal of Operational Research, Elsevier, vol. 281(3), pages 687-705.
    15. Prins, Remco & Verhoef, Peter C. & Franses, Philip Hans, 2009. "The impact of adoption timing on new service usage and early disadoption," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 304-313.

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