Beyond the SKU: a conceptual refinement of shopping cart abandonment in e-commerce

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications 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. Originality/value This research advances theoretical understanding of online shopping cart abandonment and provides actionable guidance for optimizing marketing interventions in e-commerce contexts.

Authors

Institutions

Publication Details

Journal
Industrial Management & Data Systems
Published
2026-09-01
DOI
https://doi.org/10.1108/imds-02-2026-0237
Primary Topic
Consumer Market Behavior and Pricing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Beyond the SKU: a conceptual refinement of shopping cart abandonment in e-commerce

Jiyao Xun, Lu Meng, Lijing Wang, Zelin Zhang
Industrial Management & Data Systems
Consumer Market Behavior and Pricing
article

Beyond the SKU: a conceptual refinement of shopping cart abandonment in e-commerce

Jiyao Xun, Lu Meng, Lijing Wang, Zelin Zhang
article en

Abstract

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications 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. Originality/value This research advances theoretical understanding of online shopping cart abandonment and provides actionable guidance for optimizing marketing interventions in e-commerce contexts.

Industrial Management & Data Systems
Beijing Technology and Business University (CN), Brandon University (CA), Xi’an Jiaotong-Liverpool University (CN), Renmin University of China (CN)
National Natural Science Foundation of China
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Consumer Market Behavior and Pricing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.