This study examines the use of forecast combination to improve the accuracy of forecasts of cumulative demand. A forecast combination methodology based on least absolute value (LAV) regression analysis is developed and is applied to partially accumulated demand data from an actual manufacturing operation. The accuracy of the proposed model is compared with the accuracy of common alternative approaches that use partial demand data. Results indicate that the proposed methodology outperforms the alternative approaches.
Utley, J. and Gaylord May, J. (2010), "A comparison of combination forecasts for cumulative demand", Lawrence, K. and Klimberg, R. (Ed.) Advances in Business and Management Forecasting (Advances in Business and Management Forecasting, Vol. 7), Emerald Group Publishing Limited, Bingley, pp. 97-110. https://doi.org/10.1108/S1477-4070(2010)0000007009Download as .RIS
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