Advances in Business and Management Forecasting
Will be published approx. on 15. August 2002
Book
Hardback
208 pages
978-0-7623-0437-0 (ISBN)
Description
This volume is part of a blind refereed serial publication published on an annual basis. The objective of this research annual is to present studies in the application of forecasting methodologies to such areas as sales, marketing, and strategic decision making (an accurate, robust forecast is critical to effective decision making). It is the hope and direction of the research annual to become an applications- and practitioner-oriented publication. The topics include sales and marketing, forecasting, new product forecasting, judgementally-based forecasting, the application of surveys to forecasting, forecasting for strategic business decisions, improvements in forecasting accurate and sales response models.
More details
Series
Language
English
Place of publication
United States
Publishing group
Emerald Publishing Limited
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 16 mm
Weight
482 gr
ISBN-13
978-0-7623-0437-0 (9780762304370)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
Forecasting Accuracy and Methods: Obtaining a seasonal index for forecasting when the data contain a trend; How to make accurate market share forecasts with structural response models; What to do when sales forecasts are not accurate enough; The relationship between accuracy and expenditure forecasting; Forecast model selection - Genetic Algorithm Neutral Network approach; Forecasting practices of MBAs; Forecasting ARIMA methods - a comparison of internet and fractionally different models. Forecasting Applications: Regression forecast modeling -a case study; Managing to retain sales forecaster; Consistent judgmental directional probability exchange rate prediction; Communicating revenue uncertainty using revenue semaphores.