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A cohort analysis of household vehicle expenditure in the US and Japan.pdf

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A cohort analysis of household vehicle expenditure in the US and Japan

A cohort analysis of household vehicle expenditure in the U.S. and Japan: A possibility of generational marketing Kosei Fukuda Published online: 30 April 2009 # Springer Science + Business Media, LLC 2009 Abstract This paper shows the usefulness of cohort analysis for generational marketing. Aggregate data classified by age and period are decomposed into age, period, and generational cohort effects. We compare two cohort-analysis models, the constrained multiple regression model and the Bayesian cohort model. The empirical results that are common to the household vehicle expenditure ratio in the U.S. and Japan are as follows: (1) among a total of three effects, the period effect is the smallest; (2) with the exception of the latest birth cohort, the cohort effect shows a clear upward trend; (3) the age effect decreases in the 20s and 30s, and next increases with a peak detected in the late 50s, and finally decreases. We provide marketing implications for cohort segmentation and forecasting. Keywords Age–period–cohort decomposition . Bayesian cohort model . Constrained multiple regression model . Generational marketing . Household vehicle expenditure ratio 1 Introduction Since the seminal work of Reynolds and Rentz (1981), cohort analysis has gained recognition in the field of marketing literature. A cohort can be defined as an aggregate of individuals who experienced the same events within the same time interval (Ryder 1965), and who are usually connected by birth timing. Cohort analysis is a method designed to separate age, period, and cohort effects in order to examine consumer behaviors (Rentz et al. 1983). In the present study, cohort analysis and age– period–cohort decomposition are used interchangeably. These three effects have different causes (Reynolds and Rentz 1981): biological, psychological, and social aging for the age effect; environmental changes for the period effect; and historical Market Lett (2010) 21:53–64 DOI 10.1007/s11002-009-9077-2 K. Fukuda