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dc.contributor.authorHuang, Ke-Wei-
dc.contributor.authorSundararajan, Arun-
dc.description.abstractOn-demand computing provides a new way for companies to manage and use their IT infrastructure. This model of corporate computing radically changes the way companies pay for their IT infrastructure, basing it on "pay per use" rather than on the fixed infrastructure investments such companies are accustomed to. A clear theoretical understanding of pricing on-demand computing is thus central to the viability and growth of this nascent industry. We contribute towards such an understanding in this paper by modeling the optimal pricing of on-demand computing while taking four critical factors into account: the costs of deploying IT in-house, the business value of this IT, the scale of the provider’s on-demand computing infrastructure, and the variable costs of providing on-demand computing. Three distinct pricing models emerge as optimal among all possible pricing functions for on-demand computing. These models describe when volume discounting, free usage and demand caps should be used to manage demand appropriately and profitably. We also outline a likely path that the transformation towards on-demand computing will follow — under which low-usage customers are targeted initially, followed by a broadening of the market, and finally, a focus on profiting from inducing adoption by high-usage customers — and prescribe how the associated pricing models should evolve appropriately.en
dc.format.extent441454 bytes-
dc.publisherStern School of Business, New York Universityen
dc.titlePricing Models for On-Demand Computingen
dc.typeWorking Paperen
dc.description.seriesInformation Systems Working Papers SeriesEN
Appears in Collections:CeDER Working Papers
IOMS: Information Systems Working Papers

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