Abstract
Previous applications using individual differences scaling (INDSCAL) have tended toward higher dimensionalities than in the case of one-mode two-way multidimensional scaling. The interpretation of the results obtained from INDSCAL has not always emphasized the way to visualize the solutions. To interpret the results more efficiently, this study proposes an approach that uses both low- and high-dimensional solutions of INDSCAL. Department store purchase data were analyzed using INDSCAL. This analysis examined the influences of store arrangement and season effects on multiple purchase behaviors. The results showed that consumers' multiple purchase behaviors are based on an image of the shop, the life stage of the consumers, and the layout of the department store. The store arrangement influences long-term purchase behaviors, which differ from period to period.
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