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Efficient Price and Capacity Choices under Uncertain Demand: An Empirical Analysis


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  • Koschat, Martin A
  • Srinagesh, Padmanabhan
  • Uhler, Linda J
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    Traditional economic analyses of the peak-load problem typically assume an unrealistic degree of regularity in demand during well-defined peak and off-peak periods. This issue is addressed through a comprehensive statistical model that separates demand into its systematic and stochastic components. This model is combined with a traditional economic model and applied to local telephone service, leading to substantive conclusions relevant for managerial decisions as well as further research, among them: (1) Neglecting the systematic and stochastic structure of demand may lead to inefficient tariffs. Efficient measured service structures typically price individual calls below incremental capacity cost. (2) Industry wide capacity decision rules that are exclusively driven by blockage probability targets during narrowly defined time periods may be economically inefficient. (3) For telephone service, spot pricing, which sets high prices during periods of actual congestion, has the potential to be considerably more efficient than traditional tariffs that set high prices during periods of expected congestion. Copyright 1995 by Kluwer Academic Publishers

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    Bibliographic Info

    Article provided by Springer in its journal Journal of Regulatory Economics.

    Volume (Year): 7 (1995)
    Issue (Month): 1 (January)
    Pages: 5-26

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    Handle: RePEc:kap:regeco:v:7:y:1995:i:1:p:5-26

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    Cited by:
    1. Joan Calzada Aymerich, 2003. "Access by Capacity and Peak-Load Pricing," Working Papers in Economics 108, Universitat de Barcelona. Espai de Recerca en Economia.
    2. Joan Calzada, 2007. "Capacity-based versus time-based access charges in telecommunications," Journal of Regulatory Economics, Springer, vol. 32(2), pages 153-172, October.
    3. Skiera, Bernd & Spann, Martin, 1999. "The ability to compensate for suboptimal capacity decisions by optimal pricing decisions," European Journal of Operational Research, Elsevier, vol. 118(3), pages 450-463, November.


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