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Predicting Demand for Residential Solar Heating: An Attribute Method

Author

Listed:
  • M. K. Berkowitz

    (University of Toronto)

  • G. H. Haines

    (University of Toronto)

Abstract

This paper presents two models which allow long run demand for a new product to be estimated prior to any significant sales history. The specific product studied is residential solar heating in Canada. Both models are based on the concept that consumers react in their purchasing decisions to the inherent package of characteristics in a commodity. The use of survey information to enable specific numerical estimates to be made is exemplified. Directions for future research to improve the usefulness of such models are suggested.

Suggested Citation

  • M. K. Berkowitz & G. H. Haines, 1982. "Predicting Demand for Residential Solar Heating: An Attribute Method," Management Science, INFORMS, vol. 28(7), pages 717-727, July.
    • Handle: RePEc:inm:ormnsc:v:28:y:1982:i:7:p:717-727
    DOI: 10.1287/mnsc.28.7.717
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    Cited by:

    1. Brockett, Patrick L. & Charnes, Abraham & Cooper, William W. & Learner, David & Phillips, Fred Y., 1995. "Information theory as a unifying statistical approach for use in marketing research," European Journal of Operational Research, Elsevier, vol. 84(2), pages 310-329, July.

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