Online retailers continue to face persistently high rates of shopping cart abandonment, yet progress in understanding this phenomenon has been hindered by inconsistent and conflicting definitions. This research reconceptualizes shopping cart abandonment by proposing a conceptual refinement along two dimensions: category-level analysis and a category-specific decision window.
Drawing on multiple unique datasets from leading Chinese e-commerce platforms, this research conducts three empirical analyses to demonstrate the conceptual clarity and empirical robustness of this refinement.
The pilot study establishes the feasibility of category-level measurement by demonstrating that shopping cart abandonment can be meaningfully operationalized at the category level. Study 1a identifies category-specific decision windows across three product categories. Study 1b shows that incorporating these category-specific decision windows into the measurement framework significantly reduces over-identification. Studies 2 and 3 further illustrate the managerial implications of the refinement. Specifically, Study 2 provides evidence that retargeting at the category level can effectively reduce marketing costs, and Study 3 reveals that aligning promotional timing with category-specific windows improves conversion rates.
This research is based on data from large B2C retailers in China, where the category-specific decision windows may be influenced by retailers' reputation and advanced infrastructure. Future research could examine the stability and generalizability of this analysis across countries, retailer types and consumer segments.
E-commerce platform managers can accurately identify shopping cart abandonment by adopting a category-level approach. Moreover, leveraging category-specific decision windows offers financial benefits by improving the efficiency of marketing resource allocation.
This research advances theoretical understanding of online shopping cart abandonment and provides actionable guidance for optimizing marketing interventions in e-commerce contexts.
