This study uses latent class modeling (LCM) to explore the effects of channel-specific perceptions, along with other variables, on purchase channel intention. Using data on book purchases collected from an Internet-based survey of two university towns in Northern California, we develop a latent class model with two segments (final N=373). Age turns out to be the only observed determinant of class membership, and in the intention model, the mostly-younger segment is more cost-sensitive and the mostly-older segment appears to be more conveni¬ence-sensitive. The results clearly demonstrate the effects on purchase intention of channel-specific perceptions, purchase experience, context and sociodemographics. Comparing the LCM to the unsegmented model and to models deterministically segmented on age indicates that the LCM is slightly better from the statistical perspective, but arguably weaker from the conceptual perspective. However, a model that interacts age with the explanatory variables in the conventional unsegmented model outperforms all the others (though not overwhelmingly so), including the LCM. Thus, our results suggest that using LCM as an initial stage in model exploration allows us to more intelligently specify a model where the taste heterogeneity is (potentially) specified deterministically in the end, which often yields a more parsimonious model, and may in fact fit the data better.
Internet/online shopping store shopping taste heterogeneity latent class model market segmentation