Abstract
In this study, a secondary factor analysis of multiple populations with a structured mean was applied to the independent, and mean values were decomposed into common and unique components. In this manner, a method for discovering the most effective model was proposed. In order to ensure the practical effectiveness of this method, the data of Brand Japan from 2004 to 2006 was analyzed. This data was composed of 1,000 brands and 15 variables. As a result, some models fitted to the data well in all variations of models, and the best model could be decided by interpreting meanings. This model was applied to the brand data, and factor scores were calculated for every construct. Characteristics of every brand were discovered by observing its movement.
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