Title

Nonstationary brand variables in category management: A cointegration perspective

Authors

Authors

J. J. Jiang; M. S. Zhong; G. Klein;H. G. Chen

Comments

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Abbreviated Journal Title

Decis. Sci.

Keywords

PRICE PROMOTIONS; TIME-SERIES; MODEL-SPECIFICATION; SCANNER DATA; UNIT-ROOT; PROFITABILITY; STATIONARITY; STATISTICS; SYSTEMS; DEMAND; Management

Abstract

Category-management models serve to assist in the development of plans for pricing and promotions of individual brands. Techniques to solve the models can have problems of accuracy and interpretability because they are susceptible to spurious regression problems due to nonstationary time-series data. Improperly stated nonstationary systems can reduce the accuracy of the forecasts and undermine the interpretation of the results. This is problematic because recent studies indicate that sales are often a nonstationary time-series. Newly developed correction techniques can account for nonstationarity by incorporating error-correction terms into the model when using a Bayesian Vector Error-Correction Model. The benefit of using such a technique is that shocks to control variates can be separated into permanent and temporary effects and allow cointegration of series for analysis purposes. Analysis of a brand data set indicates that this is important even at the brand level. Thus, additional information is generated that allows a decision maker to examine controllable variables in terms of whether they influence sales over a short or long duration. Only products that are nonstationary in sales volume can be manipulated for long-term profit gain, and promotions must be cointegrated with brand sales volume. The brand data set is used to explore the capabilities and interpretation of cointegration.

Journal Title

Decision Sciences

Volume

35

Issue/Number

1

Publication Date

1-1-2004

Document Type

Article

Language

English

First Page

101

Last Page

128

WOS Identifier

WOS:000220042100005

ISSN

0011-7315

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