Market Response, Competitive Behavior, and Time Series Analysis

Abstract

The author's principal objective is to present a framework for market analysis which specifically models primary demand, competitive reaction, and feedback effects of the market variables. The approach is an extension of earlier work by Clarke and by Lambin, Naert, and Bultez on the relationship among the elasticities of the marketing variables. The author develops this framework and formulates an approach for empirical applications based on principles of time series analysis. In particular, Granger's well-known causality definition is used in conjunction with Box-Jenkins analysis to find the nonzero elements in the marketing model. These principles are applied empirically to the case of a city pair of the U.S. domestic air travel market, where three major airlines compete on the basis of flight scheduling and advertising. The analysis reveals that flight scheduling has a market-expansive or a competitive effect, depending on the competitor, and that advertising does not have a significant impact on performance. In addition, several patterns of competitive reactions are found. The author offers observations on the theoretical and empirical aspects of this approach to marketing model building.