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The evolution of sales forecasting management: a 20-year longitudinal study of forecasting practices


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    (Texas Tech University, Lubbock, Texas, USA)


    (University of Tennessee, Knoxville, Tennessee, USA)


    (College of Business and Economics, Lehigh University, Bethlehem, Pennsylvania, USA)


    (University of Oregon, Eugene, Oregon, USA)

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    This paper presents results of a survey designed to discover how sales forecasting management practices have changed over the past 20 years as compared to findings reported by Mentzer and Cox (1984) and Mentzer and Kahn (1995). An up-to-date overview of empirical studies on forecasting practice is also presented. A web-based survey of forecasting executives was employed to explore trends in forecasting management, familiarity, satisfaction, usage, and accuracy among companies in a variety of industries. Results revealed decreased familiarity with forecasting techniques, and decreased levels of forecast accuracy. Implications for managers and suggestions for future research are presented.  Copyright © 2006 John Wiley & Sons, Ltd.

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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 25 (2006)
    Issue (Month): 5 ()
    Pages: 303-324

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    Handle: RePEc:jof:jforec:v:25:y:2006:i:5:p:303-324

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    Cited by:
    1. Robert Rieg, 2010. "Do forecasts improve over time?: A case study of the accuracy of sales forecasting at a German car manufacturer," International Journal of Accounting and Information Management, Emerald Group Publishing, vol. 18(3), pages 220-236, September.
    2. Xu, Bing & Ouenniche, Jamal, 2012. "A data envelopment analysis-based framework for the relative performance evaluation of competing crude oil prices' volatility forecasting models," Energy Economics, Elsevier, vol. 34(2), pages 576-583.
    3. Hong Chen, 2010. "Using Financial and Macroeconomic Indicators to Forecast Sales of Large Development and Construction Firms," The Journal of Real Estate Finance and Economics, Springer, vol. 40(3), pages 310-331, April.
    4. Leeuw, S. de & Vis, I.F.A. & Jonkman, S.N., 2009. "Logistics aspects of emergency preparedness in flood disaster prevention," Serie Research Memoranda 0044, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    5. Asimakopoulos, Stavros & Dix, Alan, 2013. "Forecasting support systems technologies-in-practice: A model of adoption and use for product forecasting," International Journal of Forecasting, Elsevier, vol. 29(2), pages 322-336.
    6. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E. & Fildes, Robert & Goodwin, Paul, 2009. "The effects of integrating management judgement into intermittent demand forecasts," International Journal of Production Economics, Elsevier, vol. 118(1), pages 72-81, March.
    7. Smith, Carlo D. & Mentzer, John T., 2010. "Forecasting task-technology fit: The influence of individuals, systems and procedures on forecast performance," International Journal of Forecasting, Elsevier, vol. 26(1), pages 144-161, January.
    8. Davis, Donna F. & Mentzer, John T., 2007. "Organizational factors in sales forecasting management," International Journal of Forecasting, Elsevier, vol. 23(3), pages 475-495.
    9. 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.
    10. Davydenko, Andrey & Fildes, Robert, 2013. "Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 510-522.
    11. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
    12. Williams, Brent D. & Waller, Matthew A. & Ahire, Sanjay & Ferrier, Gary D., 2014. "Predicting retailer orders with POS and order data: The inventory balance effect," European Journal of Operational Research, Elsevier, vol. 232(3), pages 593-600.
    13. Song, Haiyan & Gao, Bastian Z. & Lin, Vera S., 2013. "Combining statistical and judgmental forecasts via a web-based tourism demand forecasting system," International Journal of Forecasting, Elsevier, vol. 29(2), pages 295-310.
    14. Hosoda, Takamichi & Disney, Stephen M., 2009. "Impact of market demand mis-specification on a two-level supply chain," International Journal of Production Economics, Elsevier, vol. 121(2), pages 739-751, October.


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