Table 1

Comparison of the present study with the recent literature reviews on CBDCs

Author (year)CountryTheory usedMediating mechanism(s)Moderating condition(s)Key findings
Tronnier and Qiu (2024) ChinaAPCO Model, TTF theoryN/AN/ASelf-efficacy, perceived vulnerabilities and control affected privacy concerns, which, together with TTF and government participation, influenced e-CNY adoption
Ozili (2024) China, Nigeria, Eastern Caribbean, BahamasSchumpeter’s Theory of Innovation, Romer’s Innovation-Growth ModelN/AN/AThe global fascination with cryptocurrencies and sustainable development influences the worldwide interest in CBDCs, such as e-CNY, e-Naira, D-Cash, and Sand Dollar
Xia et al. (2023) ChinaPPF, TTFRelative advantage, TTFN/APrivacy issues, TTF, users’ payment preferences, and governmental support positively influence CBDC users’ adoption intention. Furthermore, TTF was confirmed as a mediating mechanism in the model
Söilen and Benhayoun (2022) Asia, Europe, USA, Africa, OceaniaUTAUT, Institutional Trust TheoryTrustAge, gender, experiencePerformance expectancy and social influence significantly impact the behavioral intention. Trust was also recognized as a mediating tool in the model
Radic et al. (2022) China, Korea, USATPBN/AType of CBDCs (Digital US Dollar vs Digital Won vs e-CNY)Attitude, perceived behavioral control, perceived risk, and relative advantage are the critical factors of CBDCs adoption intention. Besides, the usage intention changes across different types of CBDCs
Wu et al. (2022) ChinaUTAUTPerceived valueN/AFinancial knowledge, perceived value, perceived convenience, and openness to innovation are the significant predictors of intention to use CBDC. Perceived value is also a critical mediating mechanism in the model
The present studyChinaDOI, UTAUT, TPBAttitudeTrust, self-efficacyCompatibility, observability, and effort expectancy drive trialability, which in turn significantly influences users’ attitudes and behavioral intentions towards e-CNY. Moreover, attitudes and perceived trust exert intervening effects within the model

Note(s): APCO stands for Antecedent Privacy Concerns and Outcomes model and N/A refers to not applicable

Source(s): Authors’ own design based on literature reviews

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