Abstract
Although online shopping has been shown to interact with travel behavior in several ways, most studies to date focused on individual-level behavior in non-representative, geographically limited samples, making it difficult to derive clear profiles of shoppers. Using the 2017 US National Household Travel Survey, which included information on online shopping frequency, we estimated a latent class model to identify different shopper types (classes) that exhibited distinct travel and online shopping behavior. We found four classes: time-pressured shoppers, dual-channel shoppers, traditional shoppers, and infrequent shoppers and travelers, that differed in terms of sociodemographic characteristics and stages of life. Our results suggest that this heterogeneity may extend to the effects of online shopping on shopping travel, for instance, with substitution effects being dominant for one class whereas complementarity effects may be dominant for another. These findings can inform the design of tailored policies to mitigate the sustainability impacts of online shopping while also addressing the various classes’ needs. Further research is needed to untangle the complex relationships between online shopping and travel behavior, especially considering this heterogeneity and the modification effect.
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