Title

Vector Error-Correction Models in a consumer packaged goods category forecasting decision support system

Authors

Authors

M. S. Zhong; R. A. Pick; G. Klein;J. J. Jiang

Comments

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Abbreviated Journal Title

J. Comput. Inf. Syst.

Keywords

marketing decision support; category management; forecasting; stationarity; Vector Error Correction Model (VECM); SCANNER DATA; UNIT-ROOT; COINTEGRATION; MANAGEMENT; SPECIFICATION; STATISTICS; VARIABLES; BENEFITS; DEMAND; BVAR; Computer Science, Information Systems

Abstract

A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.

Journal Title

Journal of Computer Information Systems

Volume

46

Issue/Number

1

Publication Date

1-1-2005

Document Type

Article

Language

English

First Page

25

Last Page

34

WOS Identifier

WOS:000232379000004

ISSN

0887-4417

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