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Pricing Digital Goods: Discontinuous Costs and Shared Infrastructure

Author

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  • Ke-Wei Huang

    (Department of Information Systems, National University of Singapore, Singapore 117543)

  • Arun Sundararajan

    (Leonard N. Stern School of Business, New York University, New York, New York 10012)

Abstract

In this paper, we analyze a model of usage pricing for digital products with discontinuous supply functions. This model characterizes a number of information technology-based products and services for which variable increases in demand are fulfilled by the addition of blocks of computing or network infrastructure. Such goods are often modeled as information goods with zero variable costs; in fact, the actual cost structure resembles a mixture of zero marginal costs and positive periodic fixed costs. This paper discusses the properties of a general solution for the optimal nonlinear pricing of such digital goods. We show that the discontinuous cost structure can be accrued as a virtual constant variable cost. This paper applies the general solution to solve two related extensions by first investigating the optimal technology capacity planning when the cost function is both discontinuous and declining over time, and then characterizing the optimal costing for the discontinuous supply when it is shared by several business profit centers. Our findings suggest that the widely adopted full cost recovery policies are typically suboptimal.

Suggested Citation

  • Ke-Wei Huang & Arun Sundararajan, 2011. "Pricing Digital Goods: Discontinuous Costs and Shared Infrastructure," Information Systems Research, INFORMS, vol. 22(4), pages 721-738, December.
  • Handle: RePEc:inm:orisre:v:22:y:2011:i:4:p:721-738
    DOI: 10.1287/isre.1100.0283
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    References listed on IDEAS

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    Cited by:

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    2. Martimort, David & Stole, Lars A., 2022. "Participation constraints in discontinuous adverse selection models," Theoretical Economics, Econometric Society, vol. 17(3), July.
    3. Mingdi Xin & Arun Sundararajan, 2020. "Nonlinear Pricing of Software with Local Demand Inelasticity," Information Systems Research, INFORMS, vol. 31(4), pages 1224-1239, December.
    4. Joan Calzada & Tommaso M. Valletti, 2012. "Intertemporal Movie Distribution: Versioning When Customers Can Buy Both Versions," Marketing Science, INFORMS, vol. 31(4), pages 649-667, July.
    5. Yuan Fang & Bin Shen & Yifan Cao, 2022. "To Share or Not to Share? The Optimal Technology Investment in a Virtual Product Supply Chain," Sustainability, MDPI, vol. 14(19), pages 1-30, October.
    6. Xiaoshuai Fan & Ying‐Ju Chen & Christopher S. Tang, 2023. "Allocating scarce resources in the presence of private information and heterogeneous favoritism," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2068-2086, July.
    7. James Fan & Christopher Griffin, 2014. "Optimal Digital Product Maintenance with a Continuous Revenue Stream," Papers 1412.8624, arXiv.org, revised Feb 2017.
    8. Yasushi Masuda & Seungjin Whang, 2021. "Digitization and profitability," Information Systems and e-Business Management, Springer, vol. 19(2), pages 389-403, June.
    9. Dan Ma & Abraham Seidmann, 2015. "Analyzing Software as a Service with Per-Transaction Charges," Information Systems Research, INFORMS, vol. 26(2), pages 360-378, June.
    10. Ana Isabel Torres & César Lapa Barros & Amélia Ferreira Silva & Ricardo Jorge Silva, 2022. "The Pay What You Want pricing strategy applied to digital products: an essay," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(5), pages 529-537, October.
    11. Wenbo Cai & Ying-Ju Chen, 2017. "Channel management and product design with consumers’ probabilistic choices," International Journal of Production Research, Taylor & Francis Journals, vol. 55(3), pages 904-923, February.
    12. Ying-Ju Chen & Ke-Wei Huang, 2016. "Pricing Data Services: Pricing by Minutes, by Gigs, or by Megabytes per Second?," Information Systems Research, INFORMS, vol. 27(3), pages 596-617.

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