ArticleBehavioral sciences (Basel, Switzerland)2024
Understanding Users' App-Switching Behavior During the Mobile Search: An Empirical Study from the Perspective of Push-Pull-Mooring Framework.
Article in Behavioral sciences (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Fear vs. temptation: a push-pull-mooring perspective on users' continuance intention toward AI face-swapping technology.Frontiers in psychology · 2026Article
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Authors and funding
2 authors.
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Abstract
With the rapid development of mobile applications (apps), various types of mobile apps have become the main channels for smartphone interaction. The user's app switching behavior in mobile search tasks has also received attention from academia. This article uses the push-pull-mooring (PPM) theoretical model to determine the three influencing factors of push, pull, and mooring that affect user's app switching behavior in mobile search. Data were collected from 374 respondents using a structural equation model. This study can deepen the understanding of app switching in user mobile search from the perspectives of information source selection, user information search path, etc. This study found that in terms of pushing factors, the complexity of search tasks positively affects users' willingness to switch apps. In terms of pulling factors, the attractiveness of alternative products and users' follow-up activities will positively affect their switching willingness. Meanwhile, inertia serves as a mooring variable to regulate the relationship between push-pull factors and user switching intentions. This research highlights key insights on user behavior, follow-up activities, and the role of switching costs and inertia, contributing to the broader literature on information-seeking behavior. It also provides actionable recommendations for app developers to enhance search experiences and retain users by integrating personalized, multi-modal features.
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