Exploring customers' switching from native to lightweight apps: a push–pull–mooring framework perspective
Abstract
Purpose: Lightweight apps such as WeChat mini programs (WMPs) are an emerging mobile channel (m-channel) touchpoint that have gained remarkable popularity among consumers. Despite the focus of migration research on traditional m-channel touchpoints (e.g. native apps and mobile websites), but few researchers have examined why consumers switch from native to lightweight apps. Drawing on the push-pull-mooring framework, this study aims to identify the key factors influencing consumers' switching related to lightweight apps. Design/methodology/approach: The data were collected using a questionnaire survey of 416 WMP consumers and the proposed model was analyzed through structural equation modeling. Findings: The results show that the push effect, specifically, high privacy concern, nudges consumers away from native apps, whereas the pull effects, including relative ease of use, convenience of access and exit and socially-oriented interaction, entice consumers to lightweight apps. Further, consumer switching intention is influenced by habit and perceived technology control, both of which reflect the mooring effects. Switching intention also stands as an important precedent of actual behavior. Originality/value: This study is among the first theoretical explorations of consumer switching across m-channel touchpoints in the context of mobile commerce. For information system practice, these findings provide new insights for both incumbent providers and newcomers on how to retain existing shoppers as well as attract potential shoppers effectively.
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PPM has been widely adopted to examine user switching behavior in information systems research.
“PPM has been widely adopted to examine user switching behavior in information systems research, such as user switching between social networking sites (Chang et al., 2014) and user switching between mobile apps (Chen et al., 2022).”
From Understanding user switch of information seeking: From search engines to generative AI (2026) · cites this paper as Chen et al., 2022
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- Authors
- Chen, Y., Li, X., Li, Q., & Li, W.
- Affiliations
- University of Science and Technology of China (CN)
- Wuhu University (CN)
- State University of New York (US)
- Venue
- Industrial Management & Data Systems
- Publisher
- Emerald
- Published
- 2022-09-08
- Volume
- 122
- Issue
- 12
- Pages
- 2633-2656
- ISSN
- 0263-5577 (ISSN-L)
- 1758-5783
- OpenAlex
- W4294769763
- Cited by
- 20
- References
- 64
- Citations by year
- 2026: 1 · 2025: 10 · 2024: 4 · 2023: 5
- FWCI
- 3.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Industrial Management & Data Systems (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Information Systems › Mobile and Web Applications
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- customer switching, WeChat mini-program, native mobile applications, push-pull-mooring framework, mobile commerce, privacy concerns, nudging, habit, switching intention
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