A causal based inventory forecasting model for an electronics capital equipment manufacturer
Hicks, John E.
Gue, Kevin R.
Liao, Shu S.
Liao, Shu S.
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With declining budgets for making inventory decisions throughout the business sector, the Navy, and the Department of Defense, the need for accurate inventory demand forecasting is becoming an increasingly important issue. The need for accurate forecasts and adequate inventory models is integral to cost savings, attaining customer service levels, and to the climate of both for profit and public sector organizations. This thesis develops a forecasting model that attempts to predict future demand by considering several causal factors that might reflect future demand for items. Our results suggest that the model is no better than the current demand-based model, either because our factors did not contain sufficient predictive power, or perhaps because no such factors exist
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