Predicting Mobile-Commerce Adoption from Past Browsing and Shopping Behaviors at e-Commerce

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In our second study on mobile commerce, we came up with a way to target customers who are more likely to adopt mobile commerce based on their past browsing and purchasing behaviors at the e-commerce site. Summarized below are key findings from this work.

In this study, we predict mobile channel adoptions of e-marketplace users with their browsing and purchasing behaviors at the e-marketplace before its addition of the mobile channel. Analyzing a data-set from a large e-marketplace in South Korea that introduced mobile channel to its existing online channel reveals that access and search behaviors before the mobile channel addition could be good predictors for the mobile channel adoption. Specifically, order time dispersion (behavioral proxies of needs for anytime access) is negatively related to the time to adopt the mobile channel, whereas the ratio of orders followed by keyword or category search, the mean number of product classes per order, and the mean display ranks of orders (behavioral proxies of needs for active search, search breadth and search depth, respectively) are positively related to. In addition to access and search behaviors, we considered information privacy related behaviors, transaction risk related behaviors, assurance seeking behaviors, and order preferences on time, day, and product categories. Our findings shed new lights on the adoption research stream by demonstrating a prediction of a new IT adoption of individuals based on their past behaviors. We also contribute to the emerging literature on mobile commerce by identifying significant predictors for the mobile channel adoption. Finally, we provide a scoring heuristics, which can be applied to target potential mobile channel adopters without estimating the proposed model. 

*Joint work with Yongsok Bang, Kunsoo Han, and Animesh Animesh; Under review at Management Science 

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