Types of Mobile Retail Consumers’ Shopping Behaviors from the Perspective of Time

The aim of this research is to explore consumers’ shopping behavior on mobile apps and to mine different types of consumers. We have selected the mobile Taobao app as our research target and designed two simulated shopping tasks—goal-oriented shopping and exploratory-based shopping—based on consumers’ need-states to examine consumers’ shopping journeys. We have also investigated the effect of the time factor which has been regarded as an important incentive (i.e., saves time and is convenient) for consumers to shop by using mobile apps. We used a k-means clustering algorithm based on nine features of the interface of a mobile app to analyze types of consumers’ online shopping behaviors. Our results have shown that there are five types of consumers which are transitional-oriented, price-sensitive, recommendation-adopting, information-consuming, and comparing groups. Our results reveal that the time factor is a primary means to differentiate consumers’ mobile shopping behaviors instead of need-states. The most obvious difference between the five groups of consumers is that the transitional-oriented group spent the least time browsing information in the app whereas the information consumption group spent the most. Interestingly, both groups went to their shopping carts frequently and consequently made purchase decisions. While the comparing group spent a great deal of time on checking, comparing, and evaluating information, they seldom went to the shopping cart page. In conclusion, we have found that consumers’ shopping behavior on mobile apps is deeply affected by the factor of time and exhibited different shopping journeys among groups. Our findings can provide a reference for mobile retailers to refine their app interfaces and develop marketing strategies tailored to different types of consumers.