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Assessing the Impact of Market Disturbances Using Intervention Analysis

Author

Listed:
  • Dean W. Wichern

    (University of Wisconsin--Madison)

  • Richard H. Jones

    (University of Wisconsin--Madison)

Abstract

A recurring problem confronting marketing operatives at all levels is assessing the impact of market disturbances. The disturbances may be caused by marketing mix manipulations of the firm itself, by its competitors or by fundamental external changes in the environment in which the firm operates. This article discusses a technique, intervention analysis, by which the impact of such disturbances can be assessed. The technique is used to examine the effects of Proctor and Gamble's promotion of the American Dental Association endorsement of Crest on the market shares of Crest and Colgate dentifrice during the years 1958-1963.

Suggested Citation

  • Dean W. Wichern & Richard H. Jones, 1977. "Assessing the Impact of Market Disturbances Using Intervention Analysis," Management Science, INFORMS, vol. 24(3), pages 329-337, November.
    • Handle: RePEc:inm:ormnsc:v:24:y:1977:i:3:p:329-337
    DOI: 10.1287/mnsc.24.3.329
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    Cited by:

    1. Yuehjen Shao & Yue-Fa Lin & Soe-Tsyr Yuan, 1999. "Integrated application of time series multiple-interventions analysis and knowledge-based reasoning," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(6), pages 755-766.
    2. Andrew Greinke, 2005. "Imposing Capital Controls on Credit Unions: An Analysis of Regulatory Intervention in Australia," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 76(3), pages 437-460, September.
    3. Bratina Danijel & Faganel Armand, 2008. "Forecasting the Primary Demand for a Beer Brand Using Time Series Analysis," Organizacija, Sciendo, vol. 41(3), pages 116-124, May.
    4. Hyun Joo Chang, 2007. "Explaining Welfare Caseload Reduction in New York State: The Effect of Policy or Economy?," International Review of Public Administration, Taylor & Francis Journals, vol. 12(1), pages 105-117, July.
    5. Ceren Eda Can & Gul Ergun & Refik Soyer, 2022. "Bayesian Analysis of Proportions via a Hidden Markov Model," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 3121-3139, December.
    6. Robert Noland & Mohammed Quddus & Washington Ochieng, 2008. "The effect of the London congestion charge on road casualties: an intervention analysis," Transportation, Springer, vol. 35(1), pages 73-91, January.

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