) parametrically correct for any bias in the point forecast conditional on the recent demand history and (2) non …Forecasting critical fractiles of the lead time demand distribution is an important problem for operations managers … fractile when demand is serially correlated. Starting from a user-defined but potentially misspecified forecasting model, we …

relationship between a change in trend growth rates and forecast bias, as suggested in the literature, breaks down when only …-cycle states. We show that forecasts for recessions are subject to a large negative systematic forecast error (forecasters … overestimate growth), while forecasts for recoveries are subject to a positive systematic forecast error. Forecasts made for …

Sales and operations planning (S&OP) is a key business process to match customer demand with supply capabilities in the …

The article deals with the genesis of the theory of financial planning and forecasting in Western countries, revealed … its characteristics and shows the complexity of financial planning and forecasting for corporations. …

relation between incomes and expenses. Budgeting becomes a systematic economic practice that assumes the development of a …

forecasting return flows that exploit the fact that future returns are a function of past sales. In particular we assess the value … of return forecasting at an operational level, specifically inventory control. We conclude with implications for supply …

priori in the management of production, inventory, and distribution. In practice, one has to attempt to forecast the timing … and the amount of product returns, by hypothesizing about the return flow properties. To do so, historic data on demand …

Croston's method and its modifications are the most commonly used methods in sporadic demand of product stock … simulation method. The aim of this article is to introduce sporadic demand product stock management method based on dynamic …

priori in the management of production, inventory, and distribution. In practice, one has to attempt to forecast the timing … and the amount of product returns, by hypothesizing about the return flow properties. To do so, historic data on demand …