Understanding Individuals’ Adoption of Digital Currency Electronic Payment in China: A Dual-Stage Analysis of PLS-SEM and BPNN
Xiaoxiao Gong,
Yang Zhang,
Menghan Wang and
Xuetao Jiang
SAGE Open, 2025, vol. 15, issue 3, 21582440251367811
Abstract:
As the Digital Currency Electronic Payment (DCEP) pilot is implemented, identifying the factors that influence individuals’ attitudes and adoption of DCEP is paramount for its wider promotion. Grounded on the Push-Pull-Mooring model and Status Quo Bias theory, this paper proposes a predictive model of individuals’ intention to adopt DCEP, which was tested through a questionnaire survey of 395 individuals adopting DCEP and validated by a structural equation modeling (SEM) and back-propagation neural network (BPNN) analysis. The findings reveal that individuals’ attitudes toward DCEP are pivotal in determining their adoption. Specifically, perceived compatibility, subjective norms, network externalities, social self-image, perceived government policy, and perceived credibility have significant positive effects on attitudes, while perceived cost exerts negative influences. Additionally, subjective norms and perceived government policy positively reinforce perceived credibility. Furthermore, individual financial knowledge moderates the relationship between attitude and adoption intention. This study offers both theoretical insights and practical guidance to facilitate the progress of DCEP pilots and enhance their adoption.
Keywords: digital currency electronic payment; back propagation neural network; status quo bias theory; push-pull-mooring model; structural equation modeling (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/21582440251367811 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:15:y:2025:i:3:p:21582440251367811
DOI: 10.1177/21582440251367811
Access Statistics for this article
More articles in SAGE Open
Bibliographic data for series maintained by SAGE Publications ().