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Underlying Consumer Heterogeneity in Markets for Subscription-Based IT Services with Network Effects

Author

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  • Marius F. Niculescu

    (College of Management, Georgia Institute of Technology, Atlanta, Georgia 30308)

  • Hyoduk Shin

    (Kellogg School of Management, Northwestern University, Evanston, Illinois 60208)

  • Seungjin Whang

    (Graduate School of Business, Stanford University, Stanford, California 95305)

Abstract

In this paper we explore the underlying consumer heterogeneity in competitive markets for subscription-based information technology services that exhibit network effects. Insights into consumer heterogeneity with respect to a given service are paramount in forecasting future subscriptions, understanding the impact of price and information dissemination on market penetration growth, and predicting the adoption path for complementary products that target the same customers as the original service. Employing a continuous-time utility model, we capture the behavior of a continuum of consumers who are differentiated by their intrinsic valuations from using the service. We study service subscription patterns under both perfect and imperfect information dissemination. In each case, we first specify the conditions under which consumer rational behavior supported by the utility model can explain a general observed adoption path, and if so, we explicitly derive the analytical closed-form expression for the consumer valuation distribution. We further explore the impact of awareness and distribution skewness on adoption. In particular, we highlight the practical forecasting importance of understanding the information dissemination process in the market as observed past adoption may be explained by several distinct awareness and heterogeneity scenarios that may lead to divergent adoption paths in the future. Moreover, we show that in the later part of the service lifecycle the subscription decision for new customers can be driven predominantly by information dissemination instead of further price markdowns. We also extend our results to time-varying consumer valuation scenarios. Furthermore, based on our framework, we advance a set of heuristic methods to be applied to discrete-time real industry data for estimation and forecasting purposes. In an empirical exercise, we apply our methodology to the Japanese mobile voice services market and provide relevant managerial insights from the analysis.

Suggested Citation

  • Marius F. Niculescu & Hyoduk Shin & Seungjin Whang, 2012. "Underlying Consumer Heterogeneity in Markets for Subscription-Based IT Services with Network Effects," Information Systems Research, INFORMS, vol. 23(4), pages 1322-1341, December.
    • Handle: RePEc:inm:orisre:v:23:y:2012:i:4:p:1322-1341
    DOI: 10.1287/isre.1120.0422
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    as
    1. Doganoglu, Toker & Grzybowski, Lukasz, 2007. "Estimating network effects in mobile telephony in Germany," Information Economics and Policy, Elsevier, vol. 19(1), pages 65-79, March.
    2. Madden, Gary & Coble-Neal, Grant, 2004. "Economic determinants of global mobile telephony growth," Information Economics and Policy, Elsevier, vol. 16(4), pages 519-534, December.
    3. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    4. Garth Saloner & Andrea Shepard, 1995. "Adoption of Technologies with Network Effects: An Empirical Examination of the Adoption of Teller Machines," RAND Journal of Economics, The RAND Corporation, vol. 26(3), pages 479-501, Autumn.
    5. Kathleen R. Conner, 1995. "Obtaining Strategic Advantage from Being Imitated: When Can Encouraging "Clones" Pay?," Management Science, INFORMS, vol. 41(2), pages 209-225, February.
    6. Dan Horsky, 1990. "A Diffusion Model Incorporating Product Benefits, Price, Income and Information," Marketing Science, INFORMS, vol. 9(4), pages 342-365.
    7. Harikesh Nair, 2007. "Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 239-292, September.
    8. Rabik Ar Chatterjee & Jehoshua Eliashberg, 1990. "The Innovation Diffusion Process in a Heterogeneous Population: A Micromodeling Approach," Management Science, INFORMS, vol. 36(9), pages 1057-1079, September.
    9. Stephen Morris & Hyun Song Shin, 2006. "Inertia of Forward-Looking Expectations," American Economic Review, American Economic Association, vol. 96(2), pages 152-157, May.
    10. Sanjeev Dewan & Dale Ganley & Kenneth L. Kraemer, 2010. "Complementarities in the Diffusion of Personal Computers and the Internet: Implications for the Global Digital Divide," Information Systems Research, INFORMS, vol. 21(4), pages 925-940, December.
    11. Shlomo Kalish, 1983. "Monopolist Pricing with Dynamic Demand and Production Cost," Marketing Science, INFORMS, vol. 2(2), pages 135-159.
    12. Anirudh Dhebar & Shmuel S. Oren, 1986. "Dynamic Nonlinear Pricing in Networks with Interdependent Demand," Operations Research, INFORMS, vol. 34(3), pages 384-394, June.
    13. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    14. Joe A. Dodson, Jr. & Eitan Muller, 1978. "Models of New Product Diffusion Through Advertising and Word-of-Mouth," Management Science, INFORMS, vol. 24(15), pages 1568-1578, November.
    15. Marius F. Niculescu & Seungjin Whang, 2012. "Research Note ---Codiffusion of Wireless Voice and Data Services: An Empirical Analysis of the Japanese Mobile Telecommunications Market," Information Systems Research, INFORMS, vol. 23(1), pages 260-279, March.
    16. Rossella Argenziano, 2008. "Differentiated networks: equilibrium and efficiency," RAND Journal of Economics, RAND Corporation, vol. 39(3), pages 747-769, September.
    17. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    18. Jang, Show-Ling & Dai, Shau-Chi & Sung, Simona, 2005. "The pattern and externality effect of diffusion of mobile telecommunications: the case of the OECD and Taiwan," Information Economics and Policy, Elsevier, vol. 17(2), pages 133-148, March.
    19. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
    20. Shlomo Kalish, 1985. "A New Product Adoption Model with Price, Advertising, and Uncertainty," Management Science, INFORMS, vol. 31(12), pages 1569-1585, December.
    21. Cheng, Hsing Kenneth & Tang, Qian Candy, 2010. "Free trial or no free trial: Optimal software product design with network effects," European Journal of Operational Research, Elsevier, vol. 205(2), pages 437-447, September.
    22. Bruce Robinson & Chet Lakhani, 1975. "Dynamic Price Models for New-Product Planning," Management Science, INFORMS, vol. 21(10), pages 1113-1122, June.
    23. Matthew Mitchell & Andrzej Skrzypacz, 2006. "Network externalities and long-run market shares," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 29(3), pages 621-648, November.
    24. Inseong Song & Pradeep Chintagunta, 2003. "A Micromodel of New Product Adoption with Heterogeneous and Forward-Looking Consumers: Application to the Digital Camera Category," Quantitative Marketing and Economics (QME), Springer, vol. 1(4), pages 371-407, December.
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