Integrating Technological and Behavioral Perspectives in the Adoption of China’s Digital Currency (e-CNY): A Systematic Literature Review

Despite rapid pilot expansion, public uptake of China’s central bank digital currency, e-CNY, remains uneven. This study synthesizes evidence on e-CNY adoption and develops an integrative perspective that connects technology acceptance with behavioral and cognitive mechanisms. Following Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) 2020, we searched Scopus, Web of Science, ScienceDirect, SpringerLink, and CNKI for studies published from January 2014 to December 2025. After screening and eligibility assessment, 62 studies were included and coded using thematic synthesis. The evidence converges on three determinant clusters: technological adaptability (performance expectancy, effort expectancy, social influence, facilitating conditions), behavioral and cognitive determinants (institutional trust, perceived risk, financial literacy, awareness), and contextual moderators (merchant acceptance, policy communication, regional infrastructure, and demographics). Across studies, institutional trust and perceived risk show the most consistent and substantial associations with adoption intention, while effective government communication and a dense merchant ecosystem reduce uncertainty and strengthen perceived usefulness. Building on these findings, we propose an integrative framework that links Unified Theory of Acceptance and Use of Technology (UTAUT) constructs to behavioral and cognitive mechanisms and outline a Theory–Context–Characteristics–Methodology (TCCM)-based agenda for future research on CBDC (Central Bank Digital Currency) adoption dynamics. The results offer actionable implications for central banks on privacy design, communication strategies, and inclusion-oriented deployment to support sustainable CBDC diffusion. The review also highlights gaps in post adoption behavior, privacy perception measurement, and cross-regional comparisons, and calls for longitudinal, experimental, and mixed method designs to validate causal mechanisms in real world CBDC use.