This research investigated the impact of digital financial literacy (DFL), digital payments experience (DPE) and perceived risk (PR) on the willingness to adopt (WTA) the Central Bank Digital Currency (CBDC), with trust (TR) and likelihood of adoption (LOA) serving as interplay factors. This research examines the interplay of these dimensions using the Unified Theory of Acceptance and Use of Technology framework and applies structural equation modelling for a quantitative analysis via a meticulously designed questionnaire administered to 590 respondents across the cities involved in the first round of pilot testing in India. The analysis of data was performed through Smart-PLS 4, examining the influence of TR and LOA by bootstrapping with 5,000 samples, which assessed the direct and mediating effects among the variables, alongside the implementation of IPMA analysis for the target constructs. DFL, DPE and PR substantially affect TR and LOA and they serve as significant mediators in the relationship among these factors and users’ WTA CBDC. The research offers policymakers a chance to tackle issues of trust and the adoption probability, since these were the primary determinants influencing behavioural intention.
AffandiY., RidhwanM. M., TrinugrohoI., & Hermawan AdiwibowoD. (2024). Digital adoption, business performance, and financial literacy in ultra-micro, micro, and small enterprises in Indonesia. Research in International Business and Finance, 70. https://doi.org/10.1016/j.ribaf.2024.102376
2.
AjzenI. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
3.
AliM., RazaS. A., KhamisB., PuahC. H., & AminH. (2021). How perceived risk, benefit and trust determine user Fintech adoption: A new dimension for Islamic finance. Foresight, 23(4), 403–420. https://doi.org/10.1108/FS-09-2020-0095
4.
AljaradatA., & ShuklaS. K. (2025). Trust and cybersecurity in digital payment adoption: Socioeconomic insights from India. Journal of Business and Socio-Economic Development. https://doi.org/10.1108/JBSED-04-2025-0119
5.
AndolfattoD. (2021). Assessing the impact of central bank digital currency on private banks. Economic Journal, 131(634), 525–540. https://doi.org/10.1093/ej/ueaa073
6.
ApanasevicT., MarkendahlJ., & ArvidssonN. (2016). Stakeholders’ expectations of mobile payment in retail: Lessons from Sweden. International Journal of Bank Marketing, 34(1), 37–61. https://doi.org/10.1108/IJBM-06-2014-0064
7.
ArauzA., GarrattR., & RamosF. D. F. (2021). Dinero Electrónico: The rise and fall of Ecuador’s central bank digital currency. Latin American Journal of Central Banking, 2(2), 100030. https://doi.org/10.1016/j.latcb.2021.100030
8.
BalversR. J., & McDonaldB. (2021). Designing a global digital currency. Journal of International Money and Finance, 111. https://doi.org/10.1016/j.jimonfin.2020.102317
9.
BarberN., KuoP., BishopM., & GoodmanR. (2012). Measuring psychographics to assess purchase intention and willingness to pay. Journal of Consumer Marketing, 29(4), 280–292. https://doi.org/10.1108/07363761211237353
10.
BechM., & GarrattR. (2017). Central bank cryptocurrencies. BIS Quarterly Review. https://www.bis.org/publ/qtrpdf/r_qt1709f.pdf
11.
BecksE., ZdankinP., MatkovicV., & WeisT. (2023). Complexity of smart home setups: A qualitative user study on smart home assistance and implications on technical requirements. Technologies, 11(1). https://doi.org/10.3390/technologies11010009
12.
BrickJ. M., & WilliamsD. (2013). Explaining rising nonresponse rates in cross-sectional surveys. Annals of the American Academy of Political and Social Science, 645(1), 36–59. https://doi.org/10.1177/0002716212456834
13.
ChatterjeeI., ChakrabortiS., & TonoT. (2024). A comparative study of bitcoin price prediction during pre-Covid19 and whilst-Covid19 period using time series and machine learning models. Discover Analytics, 2(1). https://doi.org/10.1007/s44257-024-00024-z
14.
ChenC. S. (2013). Perceived risk, usage frequency of mobile banking services. Managing Service Quality, 23(5), 410–436. https://doi.org/10.1108/MSQ-10-2012-0137
15.
ChoithaniT., ChowdhuryA., PatelS., PatelP., PatelD., & ShahM. (2024). A comprehensive study of artificial intelligence and cybersecurity on bitcoin, crypto currency and banking system. Annals of Data Science, 11(1), 103–135. https://doi.org/10.1007/s40745-022-00433-5
16.
ChoungY., ChatterjeeS., & PakT. Y. (2023). Digital financial literacy and financial well-being. Finance Research Letters, 58. https://doi.org/10.1016/j.frl.2023.104438
17.
ChuaB. L., Amare AyalewZ., KimS., HanH., & HaH. (2025). Consumer multifaceted trust of central bank digital currency (CBDC) payment in travel and tourism. Technological Forecasting and Social Change, 217. https://doi.org/10.1016/j.techfore.2025.124166
18.
ClaessensS., CongL. W., MoshirianF., & ParkC. Y. (2024). Opportunities and challenges associated with the development of fintech and central bank digital currency. Journal of Financial Stability, 73. https://doi.org/10.1016/j.jfs.2024.101280
19.
CornelliG., FrostJ., GambacortaL., SinhaS., & TownsendR. M. (2024). The organisation of digital payments in India-lessons from the Unified Payments Interface (UPI). https://www.bis.org/publ/bppdf/bispap152_e_rh.pdf
20.
DashG., & PaulJ. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173. https://doi.org/10.1016/j.techfore.2021.121092
21.
DavisF. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
22.
DesaiR. (2024). Analysing consumer switching behaviour and financial antecedents to determine the intention to use central bank digital currency: Evidence from the Indian economy. Asia Pacific Journal of Marketing and Logistics. https://doi.org/10.1108/APJML-05-2024-0669
23.
DingS., CuiT., WuX., & DuM. (2022). Supply chain management based on volatility clustering: The effect of CBDC volatility. Research in International Business and Finance, 62. https://doi.org/10.1016/j.ribaf.2022.101690
24.
DwivediY. K., RanaN. P., JeyarajA., ClementM., & WilliamsM. D. (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y
25.
FosterB., Sukono, & JohansyahM. D. (2022). Analysis of the effect of financial literacy, practicality and consumer lifestyle on the use of chip‐based electronic money using sem. Sustainability, 14(1). https://doi.org/10.3390/su14010032
26.
FornellC., & LarckerD. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18. https://doi.org/10.1177/002224378101800313
27.
FouilletC., GuérinI., & ServetJ. M. (2021). Demonetization and digitalization: The Indian government’s hidden agenda. Telecommunications Policy, 45(2). https://doi.org/10.1016/j.telpol.2020.102079
28.
GhoshA., ChattopadhayS., & BasuB. (2024). Multi-scale analysis of rural and urban areas: A case study of Indian districts. European Physical Journal B, 97(1). https://doi.org/10.1140/epjb/s10051-023-00642-8
29.
GibbonsF. X., GerrardM., BlantonH., & RussellD. W. (1998). Reasoned action and social reaction: Willingness and intention as independent predictors of health risk. Journal of Personality and Social Psychology, 74(5), 1164–1180. https://doi.org/10.1037/0022-3514.74.5.1164
30.
GiovanisA., AthanasopoulouP., AssimakopoulosC., & SarmaniotisC. (2019). Adoption of mobile banking services: A comparative analysis of four competing theoretical models. International Journal of Bank Marketing, 37(5), 1165–1189. https://doi.org/10.1108/IJBM-08-2018-0200
31.
GuptaM., TanejaS., SharmaV., SinghA., Rupeika-ApogaR., & JangirK. (2023). Does previous experience with the Unified Payments Interface (UPI) affect the usage of Central Bank Digital Currency (CBDC)?Journal of Risk and Financial Management, 16(6). https://doi.org/10.3390/jrfm16060286
32.
GuptaS., PandeyD. K., El AmmariA., & SahuG. P. (2023). Do perceived risks and benefits impact trust and willingness to adopt CBDCs?Research in International Business and Finance, 66. https://doi.org/10.1016/j.ribaf.2023.101993
33.
HairJ. F., HowardM. C., & NitzlC. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. https://doi.org/10.1016/j.jbusres.2019.11.069
34.
HairJ. F., HultG. T. M., RingleC. M., SarstedtM., DanksN. P., & RayS. (2021). An introduction to structural equation modelling. In Partial least squares structural equation modeling (PLS-SEM) using R. Classroom companion: Business (pp. 1–29). Springer. https://doi.org/10.1007/978-3-030-80519-7_1
35.
HairJ. F., RingleC. M., & SarstedtM. (2013). partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1–2), 1–12. https://doi.org/10.1016/j.lrp.2013.01.001
36.
HairJ. F., RisherJ. J., SarstedtM., & RingleC. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
37.
HairJ., HollingsworthC. L., RandolphA. B., & ChongA. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management and Data Systems, 117(3), 442–458. https://doi.org/10.1108/IMDS-04-2016-0130
38.
HaqueMd. A., & ShoaibM. (2023). e₹: The digital currency in India: Challenges and prospects. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 3(1), 100107. https://doi.org/10.1016/j.tbench.2023.100107
39.
HenselerJ., RingleC. M., & SarstedtM. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
40.
JarvenpaaS. L., TractinskyN., SaarinenL., & VitaleM. (1999). Consumer trust in an internet store: A cross-cultural validation. Journal of Computer-Mediated Communication, 5(2). https://doi.org/10.1111/j.1083-6101.1999.tb00337.x
41.
Kass-HannaJ., LyonsA. C., & LiuF. (2022). Building financial resilience through financial and digital literacy in South Asia and Sub-Saharan Africa. Emerging Markets Review, 51. https://doi.org/10.1016/j.ememar.2021.100846
42.
KaurH., KaurR., MagoM., SinghM., & MehtaK. (2024). Exploring factors affecting central bank digital currency adoption: A perspective from generation Z. Metamorphosis: A Journal of Management Research, 23(2), 126–141. https://doi.org/10.1177/09726225241286932
43.
KaurH., MehtaK., & MagoM. (2025). Understanding factors influencing CBDC usage intentions among Indian households: Applying an extended UTAUT model. NMIMS Management Review, 33(2), 87–102. https://doi.org/10.1177/09711023251339858
44.
KaurP., DhirA., BodhiR., SinghT., & AlmotairiM. (2020). Why do people use and recommend m-wallets?Journal of Retailing and Consumer Services, 56. https://doi.org/10.1016/j.jretconser.2020.102091
45.
KeshavA., & SinhaA. R. (2025). Analysing the prospects, global advancements, and legal barriers to the introduction of central bank digital currency in India. International Journal of Process Management and Benchmarking, 20(4). https://doi.org/10.1504/IJPMB.2025.147401
46.
KeshavA., & SinhaR. A. (2024). Digital money in the Indian context: An in-depth exploration of its evolution, implications, and future prospects within the framework of central bank digital currency. Journal Electrical Systems, 20(1). https://doi.org/10.52783/jes.686
47.
KesmodelU. S. (2018). Cross-sectional studies: What are they good for?Acta Obstetricia et Gynecologica Scandinavica, 97(4), 388–393. https://doi.org/10.1111/aogs.13331
48.
KhanW. A., & AbideenZ. U. (2023). Effects of behavioural intention on usage behaviour of digital wallet: The mediating role of perceived risk and moderating role of perceived service quality and perceived trust. Future Business Journal, 9(1). https://doi.org/10.1186/s43093-023-00242-z
49.
KlobasJ. E., McGillT., & WangX. (2019). How perceived security risk affects intention to use smart home devices: A reasoned action explanation. Computers and Security, 87. https://doi.org/10.1016/j.cose.2019.101571
50.
KockN., & HadayaP. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227–261. https://doi.org/10.1111/isj.12131
51.
KrishnanL. P., VakiliniaI., ReddivariS., & AhujaS. (2023). Scams and solutions in cryptocurrencies: A survey analyzing existing machine learning models. Information, 14(3). https://doi.org/10.3390/info14030171
52.
KumarM., SinghJ. B., & SharmaS. K. (2025). Evolving ‘affordances’ and ‘constraints’ in mobile payment use: A study of Indian micro-enterprises’ UPI adoption process. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-09-2023-0455
53.
KumarP., PillaiR., KumarN., & TabashM. I. (2023). The interplay of skills, digital financial literacy, capability, and autonomy in financial decision making and well-being. Borsa Istanbul Review, 23(1), 169–183. https://doi.org/10.1016/j.bir.2022.09.012
54.
LaboureM., H.-P.MüllerM., HeinzG.SinghS., & KöhlingS. (2021). Cryptocurrencies and CBDC: The route ahead. Global Policy, 12(5), 663–676. https://doi.org/10.1111/1758-5899.13017
55.
LaradiS., ElfekairA., RehmanH. M., HannaD., & AlrawadM. (2025). Continuance intention of m-banking adoption: The dynamics of UTAUT3, trust and attitudes. FIIB Business Review. https://doi.org/10.1177/23197145251358049
56.
LeeY., SonB., ParkS., LeeJ., & JangH. (2021). A survey on security and privacy in blockchain-based central bank digital currencies. Journal of Internet Services and Information Security, 11(3), 16–29. https://doi.org/10.22667/JISIS.2021.08.31.016
57.
LeongL. Y., HewT. S., OoiK. B., & WeiJ. (2020). Predicting mobile wallet resistance: A two-staged structural equation modeling-artificial neural network approach. International Journal of Information Management, 51. https://doi.org/10.1016/j.ijinfomgt.2019.102047
58.
LongT. Q., MorganP. J., & YoshinoN. (2023). Financial literacy, behavioral traits, and ePayment adoption and usage in Japan. Financial Innovation, 9(1). https://doi.org/10.1186/s40854-023-00504-3
59.
LountR. B., & PettitN. C. (2012). The social context of trust: The role of status. Organizational Behavior and Human Decision Processes, 117(1), 15–23. https://doi.org/10.1016/j.obhdp.2011.07.005
60.
LusardiA., & MitchellO. S. (2013). The economic importance of financial literacy: Theory and evidence. http://www.nber.org/papers/w18952
61.
LyonsA. C., Kass-HannaJ., LiuF., GreenleeA. J., & Zeng. (2020). Building financial resilience through financial and digital literacy in South Asia and Sub-Saharan Africa. https://www.adb.org/sites/default/files/publication/574821/adbi-wp1098.pdf
62.
MaC., WuJ., SunH., ZhouX., & SunX. (2023). Enhancing user experience in digital payments: A hybrid approach using SEM and neural networks. Finance Research Letters, 58. https://doi.org/10.1016/j.frl.2023.104376
63.
MaierC., ThatcherJ. B., GroverV., & DwivediY. K. (2023). Cross-sectional research: A critical perspective, use cases, and recommendations for IS research. International Journal of Information Management, 70. https://doi.org/10.1016/j.ijinfomgt.2023.102625
64.
Ministry of Finance. (2022). Central bank digital currency (digital rupee-e₹) India: One of the pioneers in introducing CBDC. https://static.pib.gov.in/WriteReadData/specificdocs/documents/2022/dec/doc2022121139201.pdf
65.
MorganP. J., & LongT. Q. (2020). Financial literacy, financial inclusion, and savings behavior in Laos. Journal of Asian Economics, 68. https://doi.org/10.1016/j.asieco.2020.101197
66.
MorganP. J., & TrinhL. Q. (2019). Determinants and impacts of financial literacy in the Laos PDR (ADBI Working Paper Series). Asian Development Bank Institute. https://www.adb.org/publications/determinants-and-impacts-financial-literacy-lao-pdr
67.
OsakweC. N., OgunmokunO. A., ElgammalI., & KwartengM. A. (2025). Individuals’ attitudes and their adoption intentions of central bank digital currency: Combining theories and analytics for deeper insights. Technological Forecasting and Social Change, 210. https://doi.org/10.1016/j.techfore.2024.123857
68.
OziliP. K. (2022). Can central bank digital currency increase financial inclusion? Arguments for and against. https://mpra.ub.uni-muenchen.de/110786/
69.
OzturkcanS., SenelK., & OzdincM. (2022). Framing the central bank digital currency (CBDC) revolution. Technology Analysis and Strategic Management. https://doi.org/10.1080/09537325.2022.2099261
70.
PanettaI. C., LeoS., & Delle FoglieA. (2023). The development of digital payments: Past, present, and future—From the literature. Research in International Business and Finance, 64. https://doi.org/10.1016/j.ribaf.2022.101855
71.
PavlouP. A., & FygensonM. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly: Management Information Systems, 30(1), 115–143. https://doi.org/10.2307/25148720
72.
PhonthanukitithawornC., SellittoC., & FongM. W. L. (2016). A comparative study of current and potential users of mobile payment services. Sage Open, 6(4). https://doi.org/10.1177/2158244016675397
73.
PomeryE. A., GibbonsF. X., Reis-BerganM., & GerrardM. (2009). From willingness to intention: Experience moderates the shift from reactive to reasoned behavior. Personality and Social Psychology Bulletin, 35(7), 894–908. https://doi.org/10.1177/0146167209335166
74.
QuB., WeiL., & ZhangY. (2022). Factors affecting consumer acceptance of electronic cash in China: An empirical study. Financial Innovation, 8(1). https://doi.org/10.1186/s40854-021-00312-7
75.
RahardjaU., ChenS. C., LinY. C., TsaiT. C., AiniQ., KhanA., OgandaF. P., DewiE. R., ChoY. C., & HsuC. H. (2023). Evaluating the mediating mechanism of perceived trust and risk toward cryptocurrency: An empirical research. Sage Open, 13(4). https://doi.org/10.1177/21582440231217854
76.
RahayuR., AliS., AuliaA., & HidayahR. (2022). The current digital financial literacy and financial behavior in Indonesian millennial generation. Journal of Accounting and Investment, 23(1), 78–94. https://doi.org/10.18196/jai.v23i1.13205
77.
RamtiyalB., VermaD., & RathoreA. S. (2024). Role of risk perception and situational factors in mobile payment adoption among small vendors in unorganised retail. Electronic Commerce Research, 24(4), 2693–2731. https://doi.org/10.1007/s10660-022-09657-2
78.
RavikumarT., SureshaB., PrakashN., VaziraniK., & KrishnaT. A. (2022). Digital financial literacy among adults in India: Measurement and validation. Cogent Economics and Finance, 10(1). https://doi.org/10.1080/23322039.2022.2132631
79.
RBI. (2022). Concept note on central bank digital currency FinTech Department Reserve Bank of India. https://rbidocs.rbi.org.in/rdocs/PublicationReport/Pdfs/CONCEPTNOTEACB531172E0B4DFC9A6E506C2C24FFB6.PDF
RingleC. M., & SarstedtM. (2016). Gain more insight from your PLS-SEM results the importance-performance map analysis. Industrial Management and Data Systems, 116(9), 1865–1886. https://doi.org/10.1108/IMDS-10-2015-0449
82.
RingleC. M., SarstedtM., SinkovicsN., & SinkovicsR. R. (2023). A perspective on using partial least squares structural equation modelling in data articles. Data in Brief, 48. https://doi.org/10.1016/j.dib.2023.109074
83.
RossiS. (2025). Central bank digital currencies: Much ado about nothing?Review of Political Economy. https://doi.org/10.1080/09538259.2024.2445752
84.
Rupeika-ApogaR., BuleL., & PetrovskaK. (2022). Digital transformation of small and medium enterprises: Aspects of public support. Journal of Risk and Financial Management, 15(2). https://doi.org/10.3390/jrfm15020045
85.
SaiediE., BroströmA., & RuizF. (2021). Global drivers of cryptocurrency infrastructure adoption. Small Business Economics, 57(1), 353–406. https://doi.org/10.1007/s11187-019-00309-8
86.
SaroyR., AwasthyS., SinghN. K., AdkiS. M., & DhalS. (2022). The impact of COVID-19 on digital payment habits of Indian households. Buletin Ekonomi Moneter Dan Perbankan, 25, 19–42. https://doi.org/10.21098/bemp.v25i0.1823
87.
ShahzadM. F., XuS., LimW. M., HasnainM. F., & NusratS. (2024). Cryptocurrency awareness, acceptance, and adoption: The role of trust as a cornerstone. Humanities and Social Sciences Communications, 11(1). https://doi.org/10.1057/s41599-023-02528-7
88.
SindakisS., & ShowkatG. (2024). The digital revolution in India: Bridging the gap in rural technology adoption. Journal of Innovation and Entrepreneurship, 13(1). https://doi.org/10.1186/s13731-024-00380-w
89.
SinghV., & YadavM. (2025). User adoption of digital currency: A systematic review and future agenda using TCCM approach. Central Bank Review, 25(1). https://doi.org/10.1016/j.cbrev.2024.100183
90.
SivathanuB. (2019). Adoption of digital payment systems in the era of demonetization in India: An empirical study. Journal of Science and Technology Policy Management, 10(1), 143–171. https://doi.org/10.1108/JSTPM-07-2017-0033
91.
TronnierF., HarborthD., & BikerP. (2023). Applying the extended attitude formation theory to central bank digital currencies. Electronic Markets, 33(1). https://doi.org/10.1007/s12525-023-00638-3
92.
TronnierF., HarborthD., & HammP. (2022). Investigating privacy concerns and trust in the digital Euro in Germany. Electronic Commerce Research and Applications, 53. https://doi.org/10.1016/j.elerap.2022.101158
93.
UpadhyayN., UpadhyayS., AbedS. S., & DwivediY. K. (2022). Consumer adoption of mobile payment services during COVID-19: Extending meta-UTAUT with perceived severity and self-efficacy. International Journal of Bank Marketing, 40(5), 960–991. https://doi.org/10.1108/IJBM-06-2021-0262
94.
VenkateshV., MorrisM. G., DavisG. B., & DavisF. D. (2003). User acceptance of information technology: Toward a unified view. Source: MIS Quarterly, 27(3). https://doi.org/10.2307/30036540
95.
WangZ., SamuelR. N., ChenX., XuB., & HuangW. (2023). Central bank digital currencies: Consumer data-driven sustainable operation management policy. Technological Forecasting and Social Change, 196. https://doi.org/10.1016/j.techfore.2023.122867
96.
WuB., AnX., WangC., & ShinH. Y. (2022). Extending UTAUT with national identity and fairness to understand user adoption of DCEP in China. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-10927-0
97.
WuJ., LiuX., & ZhangC. (2024). Unveiling the influencing mechanism underlying users’ adoption and recommend intentions of central bank digital currency: A behavioral reasoning theory perspective. Journal of Retailing and Consumer Services, 81. https://doi.org/10.1016/j.jretconser.2024.104050
98.
XinH., TechatassanasoontornA. A., & TanF. B. (2015). Antecedents of consumer trust in mobile payment adoption. Journal of Computer Information Systems, 55(4), 1–10. https://doi.org/10.1080/08874417.2015.11645781
99.
YadavV., & DasA. (2025). Digital payments in India: How demonetization and COVID-19 shaped adoption?Economics Letters, 246. https://doi.org/10.1016/j.econlet.2024.112074
