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

    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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