ArticleHeliyon2023
Factors that impacted mobile-payment adoption in China during the COVID-19 pandemic.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Exploring the relationship between smartphone use diversity and depressive symptoms among older adults.BMC public health · 2025Article
- The impact of artificial intelligence on behavioral intentions to use mobile banking in the post-COVID-19 era.Frontiers in artificial intelligence · 2025Article
- Determinants affecting the medical students adoption of mobile learning: extended UTAUT.BMC medical education · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Unified Theory of Acceptance and Use of Technology (UTAUT) is a potential paradigm for explaining technology adoption and can be applied to a wide range of scenarios. During the COVID-19 (C-19) outbreak in China, mobile-payment platforms (Mpayment) were used extensively in everyday life because they allowed people to avoid direct and indirect connections during transactions, adhere to social-distancing guidelines, and support social-economic stabilization. By exploring the technological and psychological variables that influenced user Mpayment-adoption intentions during the C-19 pandemic, this study broadens the literature on technology adoption in emergency circumstances and expands the UTAUT. A total of 593 complete samples were collected online, with SPSS used for data analysis. The empirical findings reveal that performance expectancy, trust, perceived security, and social influence all had a significant influence on Mpayment acceptance during the C-19 outbreak, with social distancing having the greatest impact, followed by fear of C-19. Interestingly, perceived-effort expectancy had a negative influence on payment acceptance. These findings suggest that future studies should apply the expanded model to different countries and areas to investigate the impact of the C-19 pandemic on Mpayment acceptance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.