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Long‐term forecasting with innovation diffusion models: The impact of replacement purchases

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  • Wagner A. Kamakura
  • Siva K. Balasubramanian

Abstract

The model presented in this paper integrates two distinct components of the demand for durable goods: adoptions and replacements. The adoption of a new product is modeled as an innovation diffusion process, using price and population as exogenous variables. Adopters are expected to eventually replace their old units of the product, with a probability which depends on the age of the owned unit, and other random factors such as overload, style‐changes etc. It is shovn that the integration of adoption and replacement demand components in our model yields quality sales forecasts, not only under conditions where detailed data on replacement sales is available, but also when the forecaster's access is limited to total sales data and educated guesses on certain elements of the replacement process.

Suggested Citation

  • Wagner A. Kamakura & Siva K. Balasubramanian, 1987. "Long‐term forecasting with innovation diffusion models: The impact of replacement purchases," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 6(1), pages 1-19.
    • Handle: RePEc:wly:jforec:v:6:y:1987:i:1:p:1-19
    DOI: 10.1002/for.3980060102
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    References listed on IDEAS

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    Cited by:

    1. Aslan Lotfi & Zhengrui Jiang & Ali Lotfi & Dipak C. Jain, 2023. "Estimating Life Cycle Sales of Technology Products with Frequent Repeat Purchases: A Fractional Calculus-Based Approach," Information Systems Research, INFORMS, vol. 34(2), pages 409-422, June.

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