By Kenneth D. Lawrence, Michael D. Geurts
"Advances in enterprise and administration Forecasting" is a blind refereed serial book released on an annual foundation. the target of this examine annual is to offer cutting-edge reviews within the program of forecasting methodologies to such components as revenues, advertising and marketing, and strategic choice making. (An exact, powerful forecast is necessary to potent choice making.) it's the wish and path of the study annual to develop into an purposes- and practitioner-oriented booklet. the themes will mostly contain revenues and advertising, forecasting, new product forecasting, judgmentally dependent forecasting, the appliance of surveys to forecasting, forecasting for strategic enterprise judgements, advancements in forecasting accuracy, and revenues reaction versions. it's either the desire and course of the editorial board to stimulate the curiosity of the practitioners of forecasting to tools and methods which are suitable.
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Extra info for Advances in Business and Management Forecasting, Volume 4 (Advances in Business and Management Forecasting) (Advances in Business and Management Forecasting)
Y ðtjtÞ ¼ F ðtÞ Ã Y ðt À 1jt À 1Þ þ UðtÞ þ KðtÞ Ã ½PÀ1 ðtÞ Ã ZðtÞ À MðtÞ Ã Y ðtjt À 1Þ ð11Þ Eq. (11) has two components. The ﬁrst is the prior forecast Y(t|tÀ1) ¼ F(t) * Y(tÀ1|tÀ1)+U(t) from (3). The second is the feedback-guidance control PÀ1(t) * Z(t)ÀM(t) * Y(t|tÀ1) of (14) multiplied by the weight K(t). The posterior forecast Y(t|t) of (11) equals the prior forecast Y(t|tÀ1) plus the correction factor K(t) * [PÀ1(t) * Z(t)ÀM(t) * Y(t|tÀ1)]. If the future signal PÀ1(t) * Z(t) is signaling lower sales than do the prior ofﬁcial forecast Y(t|tÀ1), the difference PÀ1(t) * Z(t)ÀM(t) * Y(t|tÀ1) will be negative.
1970). Least squares estimation: From Gauss to Kalman. IEEE Spectrum, 7, 63–68. Wilks, S. S. (1950). Mathematical statistics. New Jersey: Princeton University Press. INVENTORY-SHIPMENT RATIO TIME SERIES MODELS FOR DURABLE AND NON-DURABLE PRODUCTS Supriya Mitra ABSTRACT This paper proposes the inventory-shipment (I-S) ratio time series model to capture the dynamics of inventory and sales simultaneously over time. We discuss the business implications of trends in this ratio and also illustrate the effectiveness of this ratio in capturing just-in-time trends.
Departments with a high inventory/sales mix ratio often use more discounting to sell off their products, and therefore receive a lower return. Departments with low ratios often receive a higher return. In many businesses, this ratio remains relatively unchanged from year to year, so even a small change requires investigation. Thus, the I-S ratio is not only an appropriate measure of the dynamics between inventory and sales, but also merits modeling as a separate entity. , (Rajagopalan & Malhotra (2001) and Gaur, Fisher, & Raman (2005)), have attempted to empirically model and analyze this ratio.
Advances in Business and Management Forecasting, Volume 4 (Advances in Business and Management Forecasting) (Advances in Business and Management Forecasting) by Kenneth D. Lawrence, Michael D. Geurts