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FORECASTING MODELS ABSTRACTS"Answers to Frequently Asked Questions (FAQ) in Forecasting"
J. SCOTT ARMSTRONG, University of Pennsylvania - Marketing Department
Much has been learned in the past half century about producing useful forecasts. Those new to the area may be interested in answers to some commonly asked questions.
"Assessing Forecast Model Performance in an ERP Environment"
PETER CATT, UNITEC New Zealand The paper aims to describe and apply a commercially oriented method of forecast performance measurement (cost of forecast error - CFE) and to compare the results with commonly adopted statistical measures of forecast accuracy in an enterprise resource planning (ERP) environment. The findings of the study support the adoption of CFE as a more relevant commercial decision-making measure than commonly applied statistical forecast measures. "Discrete Forecast Horizons for Two-Product Variants of the Dynamic Lot-Size Problem"
MILIND DAWANDE, University of Texas at Dallas - Department of Information Systems & Operations Management Motivated by the recent success of integer programming based procedures for computing discrete forecast horizons, we consider two-product variants of the classical dynamic lot-size model. In the first variant, we impose a warehouse capacity constraint on the total ending inventory of the two products in any period. In the second variant, the two products have both individual and joint setup costs for production. To our knowledge, there are no known procedures for computing forecast horizons for these variants. Under the assumption that future demands are discrete, we characterize forecast horizons for these two variants as feasibility/optimality questions in 0-1 mixed integer programs. A detailed computational study establishes the effectiveness of our approach and enables us to gain valuable insights into the behavior of minimal forecast horizons. | |||||||||
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Solicitation of Abstracts
This abstracting journal distributes working and accepted papers related to any aspect of forecasting, either theoretical, practical, computational or methodological that makes forecasting useful and relevant for decision and policy makers who require forecasts. The journal welcomes research focused on empirical studies, evaluation methodology, implementation research and ways of improving the practice of forecasting. Topics of interest include, but are not limited to, economic and econometric forecasting, financial forecasting, marketing forecasting, new products forecasting, production forecasting, technological forecasting, time series forecasting, forecasting applications in government and the military, implementation research, evaluation of forecasting methods as well as related aspects of forecasting in organizational behavior, political science, psychology, and social science.
Distribution ServicesIf your Institution is interested in learning more about increasing readership for its research by becoming a Partner in Publishing or starting a Research Paper Series, please email: PIP@SSRN.com. Distributed by:DirectorsOPER SUBJECT MATTER EJOURNALS MICHAEL C. JENSEN Please contact us at the above addresses with your comments, questions or suggestions for OPER-Sub.
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