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政大機構典藏 > 商學院 > 企業管理學系 > 期刊論文 > Item 140.119/72748

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/72748

Title:	Applying Multivariate Time Series Model on Sales Forecasting of Technological Products
Authors:	邱奕嘉;Shyu, J.Z. Chiu, Y.C.;Shyu, J.Z.
Contributors:	科管所
Keywords:	technology marketing;vector autoregression;Litterman Bayesian Vector Autoregression;forecasting
Date:	2004
Issue Date:	2015-01-09 13:11:08 (UTC+8)
Abstract:	Sales forecasting plays a crucial role in conducting marketing and mix strategies in technological industries. However, traditional sales forecasting methods focus only on customer behaviour and other quantitative variables. This paper proposes multivariate time series models, using the vector autoregression (VAR) model and the Litterman Bayesian vector autoregression (LBVAR) model, for sales forecasting in technological industries. In this study, macroeconomic data are considered to be useful leading indicators and are included in the VAR and LBVAR models. The LBVAR model possesses superior Bayesian statistics in small sample forecasting and holds the VAR model dynamic properties. An empirical study of Taiwan`s portable computer industry is used to examine the VAR and LBVAR models to validate the informative effect of macroeconomic data on sales forecasting. As a result, multivariate time series models with macroeconomic data appear to be useful models for technological product sales forecasting.
Relation:	International Journal of Technology Management, 27(2/3), 306-319
Data Type:	article
Appears in Collections:	[企業管理學系] 期刊論文

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