Forecasting for Marketing
AbstractResearch 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by EconWPA in its series General Economics and Teaching with number 0502018.
Length: 20 pages
Date of creation: 04 Feb 2005
Date of revision:
Note: Type of Document - pdf; pages: 20
Contact details of provider:
Web page: http://188.8.131.52
Find related papers by JEL classification:
- A - General Economics and Teaching
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
- Fred Collopy & J. Scott Armstrong, 1992.
"Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations,"
INFORMS, vol. 38(10), pages 1394-1414, October.
- 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.
- JS Armstrong & Fred Collopy, 2004. "Integration of Statistical Methods and Judgment for Time Series," General Economics and Teaching 0412024, EconWPA.
- JS Armstrong & Terry Overton, 2005. "Brief vs. Comprehensive Descriptions in Measuring Intentions to Purchase," General Economics and Teaching 0502032, EconWPA.
- 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.
- 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.
- Dalrymple, Douglas J., 1975. "Sales forecasting methods and accuracy," Business Horizons, Elsevier, vol. 18(6), pages 69-73, December.
- 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.
- Tyebjee, Tyzoon T., 1987. "Behavioral biases in new product forecasting," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 393-404.
- 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.
- 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, May.
- Alison Hubbard Ashton & Robert H. Ashton, 1985. "Aggregating Subjective Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 31(12), pages 1499-1508, December.
- 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.
- 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.
- JS Armstrong & Fred Collopy, 2004. "Causal Forces: Structuring Knowledge for Time-series Extrapolation," General Economics and Teaching 0412003, EconWPA.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).
If references are entirely missing, you can add them using this form.