IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpgt/0502018.html
   My bibliography  Save this paper

Forecasting for Marketing

Author

Listed:
  • 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.

Suggested Citation

  • J. S. Armstrong & R. Brodie, 2005. "Forecasting for Marketing," General Economics and Teaching 0502018, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpgt:0502018
    Note: Type of Document - pdf; pages: 20
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/get/papers/0502/0502018.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Deirdre N. McCloskey & Stephen T. Ziliak, 1996. "The Standard Error of Regressions," Journal of Economic Literature, American Economic Association, vol. 34(1), pages 97-114, March.
    2. Robert Ferber, 1956. "Are Correlations Any Guide to Predictive Value?," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 5(2), pages 113-121, June.
    3. Armstrong, J. Scott & Overton, Terry, 1971. "Brief vs. comprehensive descriptions in measuring intentions to purchase," MPRA Paper 81697, University Library of Munich, Germany.
    4. Jerry Wind & Paul E. Green & Douglas Shifflet & Marsha Scarbrough, 1989. "Courtyard by Marriott : Designing a Hotel Facility with Consumer-Based Marketing Models," Interfaces, INFORMS, vol. 19(1), pages 25-47, February.
    5. 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.
    6. Dalrymple, Douglas J., 1975. "Sales forecasting methods and accuracy," Business Horizons, Elsevier, vol. 18(6), pages 69-73, December.
    7. 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.
    8. Steven P. Schnaars, 1986. "An Evaluation of Rules for Selecting an Extrapolation Model on Yearly Sales Forecasts," Interfaces, INFORMS, vol. 16(6), pages 100-107, December.
    9. JS Armstrong & Fred Collopy, 2004. "Causal Forces: Structuring Knowledge for Time-series Extrapolation," General Economics and Teaching 0412003, University Library of Munich, Germany.
    10. Fred Collopy & J. Scott Armstrong, 1992. "Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations," Management Science, INFORMS, vol. 38(10), pages 1394-1414, October.
    11. Alison Hubbard Ashton & Robert H. Ashton, 1985. "Aggregating Subjective Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 31(12), pages 1499-1508, December.
    12. Dalrymple, Douglas J., 1987. "Sales forecasting practices: Results from a United States survey," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 379-391.
    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. Tyebjee, Tyzoon T., 1987. "Behavioral biases in new product forecasting," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 393-404.
    15. 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.
    16. Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
    17. 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 273-283, July.
    18. 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.
    19. Donald S. Tull, 1967. "The Relationship of Actual and Predicted Sales and Profits in New-Product Introductions," The Journal of Business, University of Chicago Press, vol. 40, pages 233-233.
    20. 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.
    21. JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jerzy Witold Wiśniewski, 2021. "Forecasting in Small Business Management," Risks, MDPI, vol. 9(4), pages 1-17, April.
    2. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    3. 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.
    4. Jung, Sang Hoon & Jeong, Yong Jin, 2020. "Twitter data analytical methodology development for prediction of start-up firms’ social media marketing level," Technology in Society, Elsevier, vol. 63(C).
    5. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. J. Scott Armstrong & Kesten C. Green, 2005. "Demand Forecasting: Evidence-based Methods," Monash Econometrics and Business Statistics Working Papers 24/05, Monash University, Department of Econometrics and Business Statistics.
    2. JS Armstrong, 2004. "Forecasting for Environmental Decision Making," General Economics and Teaching 0412023, University Library of Munich, Germany.
    3. J. S. Armstrong & R. Brodie & S. McIntyre, 2005. "Forecasting Methods for Marketing:* Review of Empirical Research," General Economics and Teaching 0502023, University Library of Munich, Germany.
    4. Armstrong, J. Scott & Collopy, Fred & Yokum, J. Thomas, 2005. "Decomposition by causal forces: a procedure for forecasting complex time series," International Journal of Forecasting, Elsevier, vol. 21(1), pages 25-36.
    5. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    6. Sanders, N. R., 1997. "The impact of task properties feedback on time series judgmental forecasting tasks," Omega, Elsevier, vol. 25(2), pages 135-144, April.
    7. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    8. Webby, Richard & O'Connor, Marcus, 1996. "Judgemental and statistical time series forecasting: a review of the literature," International Journal of Forecasting, Elsevier, vol. 12(1), pages 91-118, March.
    9. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    10. Leitner, Johannes & Leopold-Wildburger, Ulrike, 2011. "Experiments on forecasting behavior with several sources of information - A review of the literature," European Journal of Operational Research, Elsevier, vol. 213(3), pages 459-469, September.
    11. Goodwin, Paul, 2002. "Integrating management judgment and statistical methods to improve short-term forecasts," Omega, Elsevier, vol. 30(2), pages 127-135, April.
    12. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
    13. Welch, Eric & Bretschneider, Stuart & Rohrbaugh, John, 1998. "Accuracy of judgmental extrapolation of time series data: Characteristics, causes, and remediation strategies for forecasting," International Journal of Forecasting, Elsevier, vol. 14(1), pages 95-110, March.
    14. JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, University Library of Munich, Germany.
    15. F Caniato & M Kalchschmidt & S Ronchi, 2011. "Integrating quantitative and qualitative forecasting approaches: organizational learning in an action research case," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 413-424, March.
    16. Lawrence, M. & O'Connor, M., 1996. "Judgement or models: The importance of task differences," Omega, Elsevier, vol. 24(3), pages 245-254, June.
    17. Remus, William & O'Connor, Marcus & Griggs, Kenneth, 1995. "Does reliable information improve the accuracy of judgmental forecasts?," International Journal of Forecasting, Elsevier, vol. 11(2), pages 285-293, June.
    18. Lawrence, Michael & O'Connor, Marcus & Edmundson, Bob, 2000. "A field study of sales forecasting accuracy and processes," European Journal of Operational Research, Elsevier, vol. 122(1), pages 151-160, April.
    19. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    20. Fildes, Robert, 2006. "The forecasting journals and their contribution to forecasting research: Citation analysis and expert opinion," International Journal of Forecasting, Elsevier, vol. 22(3), pages 415-432.

    More about this item

    Keywords

    forecasting; marketing;

    JEL classification:

    • A - General Economics and Teaching

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpgt:0502018. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.