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Demand Forecasting in the Early Stage of the Technology's Life Cycle Using Bayesian update

Author

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  • Chul-Yong Lee
  • Jongsu Lee

    () (Technology Management, Economics and Policy Program(TEMEP), Seoul National University)

Abstract

Forecasting demand for new technology for which few historical data observations are available is difficult but essential to successful marketing. The current study suggests an alternative forecasting methodology based on a hazard rate model using stated and revealed preferences. In estimating the hazard rate, information is derived initially through conjoint analysis based on a consumer survey and then updated using Bayes¡¯ theorem with available market data. Based on the results of the empirical analysis, the model described here can significantly improve demand forecasting for newly introduced technologies.

Suggested Citation

  • Chul-Yong Lee & Jongsu Lee, 2009. "Demand Forecasting in the Early Stage of the Technology's Life Cycle Using Bayesian update," TEMEP Discussion Papers 200903, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Apr 2009.
  • Handle: RePEc:snv:dp2009:200903
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    File URL: ftp://147.46.237.98/DP-03.pdf
    File Function: First version, 2009
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    References listed on IDEAS

    as
    1. John Calfee & Clifford Winston & Randolph Stempski, 2001. "Econometric Issues In Estimating Consumer Preferences From Stated Preference Data: A Case Study Of The Value Of Automobile Travel Time," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 699-707, November.
    2. Kim, Yunhee & Lee, Jeong-Dong & Heshmati, Almas, 2008. "Analysis of Pay Inequality and its Impacts on Growth and Performance in the Korean Manufacturing Industry," IZA Discussion Papers 3774, Institute for the Study of Labor (IZA).
    3. Hannan, Timothy H & McDowell, John M, 1987. "Rival Precedence and the Dynamics of Technology Adoption: An Empirical Analysis," Economica, London School of Economics and Political Science, vol. 54(214), pages 155-171, May.
    4. Tai-Yoo Kim & Almas Heshmati & Jihyun Park, 2009. "Perspectives on the Decelerating Agricultural society," TEMEP Discussion Papers 200901, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jan 2009.
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    Keywords

    demand forecasting; conjoint analysis; Bayesian update; telematics service;

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