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Forecasting for Marketing

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Author Info

  • J. S. Armstrong

    (The Wharton School)

  • R. Brodie

    (University of Auckland)

Abstract

Research on forecasting is extensive and includes many studies that have tested alternative methods in order to determine which ones are most effective. We review this evidence in order to provide guidelines for forecasting for marketing. The coverage includes intentions, Delphi, role playing, conjoint analysis, judgmental bootstrapping, analogies, extrapolation, rule-based forecasting, expert systems, and econometric methods. We discuss research about which methods are most appropriate to forecast market size, actions of decision makers, market share, sales, and financial outcomes. In general, there is a need for statistical methods that incorporate the manager's domain knowledge. This includes rule-based forecasting, expert systems, and econometric methods. We describe how to choose a forecasting method and provide guidelines for the effective use of forecasts including such procedures as scenarios.

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File URL: http://128.118.178.162/eps/get/papers/0502/0502018.pdf
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Bibliographic Info

Paper provided by EconWPA in its series General Economics and Teaching with number 0502018.

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Length: 20 pages
Date of creation: 04 Feb 2005
Date of revision:
Handle: RePEc:wpa:wuwpgt:0502018

Note: Type of Document - pdf; pages: 20
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Web page: http://128.118.178.162

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Keywords: forecasting; marketing;

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References

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  1. JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, EconWPA.
  2. Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
  3. Alison Hubbard Ashton & Robert H. Ashton, 1985. "Aggregating Subjective Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 31(12), pages 1499-1508, December.
  4. Lawrence, Michael J. & Edmundson, Robert H. & O'Connor, Marcus J., 1985. "An examination of the accuracy of judgmental extrapolation of time series," International Journal of Forecasting, Elsevier, vol. 1(1), pages 25-35.
  5. Fred Collopy & JS Armstrong, 2004. "Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations," General Economics and Teaching 0412004, EconWPA.
  6. Armstrong, J Scott & Collopy, Fred, 2001. "Identification of Asymmetric Prediction Intervals through Causal Forces," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(4), pages 273-83, July.
  7. JS Armstrong & Terry Overton, 2005. "Brief vs. Comprehensive Descriptions in Measuring Intentions to Purchase," General Economics and Teaching 0502032, EconWPA.
  8. JS Armstrong & Fred Collopy, 2004. "Causal Forces: Structuring Knowledge for Time-series Extrapolation," General Economics and Teaching 0412003, EconWPA.
  9. Makridakis, Spyros & Hibon, Michele & Lusk, Ed & Belhadjali, Moncef, 1987. "Confidence intervals: An empirical investigation of the series in the M-competition," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 489-508.
  10. Patricia M. West & Patrick L. Brockett & Linda L. Golden, 1997. "A Comparative Analysis of Neural Networks and Statistical Methods for Predicting Consumer Choice," Marketing Science, INFORMS, vol. 16(4), pages 370-391.
  11. Robert C. Blattberg & Stephen J. Hoch, 1990. "Database Models and Managerial Intuition: 50% Model + 50% Manager," Management Science, INFORMS, vol. 36(8), pages 887-899, August.
  12. Tyebjee, Tyzoon T., 1987. "Behavioral biases in new product forecasting," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 393-404.
  13. F. Thomas Juster, 1966. "Consumer Buying Intentions and Purchase Probability: An Experiment in Survey Design," NBER Books, National Bureau of Economic Research, Inc, number just66-2.
  14. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
  15. Dalrymple, Douglas J., 1975. "Sales forecasting methods and accuracy," Business Horizons, Elsevier, vol. 18(6), pages 69-73, December.
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Cited by:
  1. Bonache, Adrien, 2008. "Les ventes de produits innovants à la mode sont-elles chaotiques? Le cas des ventes de Game Boy au Japon
    [Are innovative and fashion goods sales chaotic? The case of Game Boy sales in Japan]
    ," MPRA Paper 12964, University Library of Munich, Germany.
  2. Canback, Staffan & D'Agnese, Frank, 2007. "Where in the world is the market? : The income distribution approach to understanding consumer demand in emerging countries," MPRA Paper 13854, University Library of Munich, Germany.

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