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Dynamic pricing for subscription services

Author

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  • Fruchter, Gila E.
  • Sigué, Simon P.

Abstract

This paper investigates the use of pricing schemes in subscription services that consist of various combinations of activation, subscription, and cancellation fees. When customers exclusively consider what is directly perceivable, the activation fee starts low and increases as the network grows (penetration strategy), whereas the cancellation fee starts high and decreases as the network grows (skimming strategy). The activation and cancellation fees take various other forms otherwise. The subscription fee remains low at the early stages and increases only when a reasonable number of subscribers is secured. Finally, the authors discuss the theoretical and managerial implications of their findings.

Suggested Citation

  • Fruchter, Gila E. & Sigué, Simon P., 2013. "Dynamic pricing for subscription services," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2180-2194.
    • Handle: RePEc:eee:dyncon:v:37:y:2013:i:11:p:2180-2194
    DOI: 10.1016/j.jedc.2013.05.003
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    References listed on IDEAS

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    1. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    2. Rao, Vithala R, 1984. "Pricing Research in Marketing: The State of the Art," The Journal of Business, University of Chicago Press, vol. 57(1), pages 39-60, January.
    3. Shlomo Kalish, 1983. "Monopolist Pricing with Dynamic Demand and Production Cost," Marketing Science, INFORMS, vol. 2(2), pages 135-159.
    4. Hartl, Richard F., 1987. "A simple proof of the monotonicity of the state trajectories in autonomous control problems," Journal of Economic Theory, Elsevier, vol. 41(1), pages 211-215, February.
    5. Andrés Musalem & Yogesh V. Joshi, 2009. "—How Much Should You Invest in Each Customer Relationship? A Competitive Strategic Approach," Marketing Science, INFORMS, vol. 28(3), pages 555-565, 05-06.
    6. 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.
    7. Peter J. Danaher, 2002. "Optimal Pricing of New Subscription Services: Analysis of a Market Experiment," Marketing Science, INFORMS, vol. 21(2), pages 119-138, February.
    8. Bass, Frank M, 1980. "The Relationship between Diffusion Rates, Experience Curves, and Demand Elasticities for Consumer Durable Technological Innovations," The Journal of Business, University of Chicago Press, vol. 53(3), pages 51-67, July.
    9. 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.
    10. Michael Lewis, 2005. "Research Note: A Dynamic Programming Approach to Customer Relationship Pricing," Management Science, INFORMS, vol. 51(6), pages 986-994, June.
    11. Ruth N. Bolton, 1998. "A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction," Marketing Science, INFORMS, vol. 17(1), pages 45-65.
    12. Anirudh Dhebar & Shmuel S. Oren, 1985. "Optimal Dynamic Pricing For Expanding Networks," Marketing Science, INFORMS, vol. 4(4), pages 336-351.
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    Cited by:

    1. Matthias Göcke & Svetlana Fedoseeva, 2016. "Optimal Monopolist Export Pricing with Dynamic Demand and Learning Curve Effects," Open Economies Review, Springer, vol. 27(3), pages 447-469, July.
    2. Mohit Tyagi & Nomesh B. Bolia, 2024. "Optimal pricing of subscription services in the restaurant industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(3), pages 262-273, June.

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