Constant technology innovation integrated with artificial intelligence in the digital era has elevated customers’ expectations from the banking services industry globally; however, the adoption is dissimilar and disproportionate across nations. This research study examines factors influencing the digital natives’ intention towards banking in India, employing the UTAUT3 framework with the impact of gender and location (rural and urban). To achieve UN Sustainable Development Goals of no poverty, gender equality and economic growth, a comprehensive, structured survey was carried out on rural and urban students in India. The Structured Equation Model was used to evaluate the relationship between these key factors, with the behavioural intention to use digital banking as a result controlled by performance efficiency, social standards, facilitating conditions, effort expectancy, habit and personal innovativeness. The findings provide an intensive distinction in the intention of a digital native to use innovative digital banking. The influence of gender on behavioural intention is significant among rural students compared to their urban counterparts. The results have significant consequences for financial institutions, compelling them to understand this local gap and adapt their strategies to seize it equally. In addition, regulatory bodies and politicians can structure the framework in such a way that it increases digital penetration to achieve sustainable development goals.
AgarwalR., & PrasadJ. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
2.
AhmedM. H., BogaleA. D., TilahunB., KalayouM. H., KleinJ., MengisteS. A., & EndehabtuB. F. (2020). Intention to use electronic medical record and its predictors among health care providers at referral hospitals, north-west Ethiopia, 2019: Using Unified Theory of Acceptance and Use Technology 2 (UTAUT2) model. BMC Medical Informatics and Decision Making, 20, 1–11.
3.
AhmedS., & SurS. (2021). Change in the uses pattern of digital banking services by Indian rural MSMEs during demonetization and Covid-19 pandemic-related restrictions. Vilakshan: XIMB Journal of Management, 20(1), 166–192.
4.
AjzenI. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
5.
AlalwanA. A., DwivediY. K., & RanaN. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110.
6.
Al-DebeiM. M., HujranO., & Al-AdwanA. S. (2024). Net valence analysis of iris recognition technology-based FinTech. Financial Innovation, 10(1), 59.
7.
AlkhowaiterW. A. (2020). Digital payment and banking adoption research in Gulf countries: A systematic literature review. International Journal of Information Management, 53, 102102.
8.
AlviS., NairS., & RamakrishnanS. (2023). Decoding I generation propensity for digital banking: Evidence from urban India. In 2023 International Conference on Computational Intelligence and Knowledge, Economy (ICCIKE) (pp. 140–144). IEEE. https://doi.org/10.1109/ICCIKE58312.2023.10094705
9.
AminH., HamidM. R. A., TanakinjalG. H., & LadaS. (2006). Undergraduate attitudes and expectations for mobile banking. Journal of Internet Banking and Commerce, 11(3), 2006–2012.
10.
AnandaS., DeveshS., & Al LawatiA. M. (2020). What factors drive the adoption of digital banking? An empirical study from the perspective of Omani retail banking. Journal of Financial Services Marketing, 25(1–2), 14–24.
11.
AndersonJ. C., & GerbingD. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411.
12.
AnggraeniR., HapsariR., & MuslimN. A. (2021). Examining factors influencing consumers intention and usage of digital banking: Evidence from Indonesian digital banking customers. Asia Pacific Management and Business Application, 9(3), 193–210.
13.
AysanA. F., & NanaevaZ. (2022). Fintech as a financial disruptor: A bibliometric analysis. FinTech, 1(4), 412–433.
14.
BagozziR. P., & PhillipsL. W. (1982). Representing and testing organizational theories: A holistic construal. Administrative Science Quarterly, 27, 459–489.
15.
BentlerP. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.
16.
Bernard AzolibeC., OkonkwoJ. J., & Obi-NwosuV. O. (2023). Technology-based banking and bank deposit: The Nigerian commercial banks’ experience. African Journal of Science, Technology, Innovation and Development, 15(1), 31–44. https://doi.org/10.1080/20421338.2021.2015164
17.
BollenK. A., & PearlJ. (2013). Eight myths about causality and structural equation models. In MorganS. L. (Ed.), Handbook of causal analysis for social research (pp. 301–328). Springer Netherlands.
18.
BrowneM. W., & CudeckR. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258.
19.
ByrneB. M. (1998). Structural equation modeling with LISREL, PRELIS, AND SIMPLIS: Basic concepts, applications, and programming (1st ed.). Psychology Press.
20.
CheungC. M. K., & LeeM. K. O. (2000). Trust in internet shopping: A proposed model and measurement instrument. In Proceedings of the AMCIS (pp. 681–689). Association for Information Systems.
21.
DewiC. K., & MohaidinZ. (2020). The role of personal innovation in online purchasing behavior among Indonesian consumers. In PratamaR. D. A., RahmanR. A., & PutraA. S. (Eds.), Advances in business, management and entrepreneurship (pp. 78–83). CRC Press.
22.
DhimanN., AroraN., DograN., & GuptaA. (2020). Consumer adoption of smartphone fitness apps: An extended UTAUT2 perspective. Journal of Indian Business Research, 12(3), 363–388.
23.
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, 719–734.
24.
FarooqM. S., SalamM., JaafarN., FayolleA., AyuppK., MarcovicM. R., & SajidA. (2017). Acceptance and use of lecture capture system (LCS) in executive business studies: Extending UTAUT2. Interactive Technology and Smart Education, 8(3), 161–171.
25.
FathimaJ. S. (2020). Challenge management of banking services-with special reference to virtual banking service challenges. Shanlax International Journal of Management, 7(3), 57–66.
26.
FishbeinM., & AjzenI. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley.
27.
FornellC., & LarckerD. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
28.
Glavee-GeoR., ShaikhA. A., & KarjaluotoH. (2017). Mobile banking services adoption in Pakistan: Are there gender differences?International Journal of Bank Marketing, 35(7), 1090–1114.
29.
Government of India. (n.d.). Census of India 2021: Circular, 2. Office of the Registrar General & Census Commissioner, India.
30.
GulzarR., BhatA. A., MirA. A., AthariS. A., & Al-AdwanA. S. (2024). Green banking practices and environmental performance: Navigating sustainability in banks. Environmental Science and Pollution Research International, 31(15), 23211–23226.
31.
GurendrawatiE., MusyaffiA. M., RofiqahI., WidawatiY., OktaviaR., & KarmilaE. (2023). Digital banking channel sustainability: Is it effective to use?Journal of Sustainability Science and Management, 18(4), 57–71.
32.
HairJ. F., BlackW. C., BabinB. J., & AndersonR. E. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
33.
HairJ. F., CelsiM., MoneyA., PhillipS., & PageM. (2016). The essentials of business research methods (2nd ed). Routledge.
34.
HairJ. F.Jr, HultG. T. M., RingleC. M., SarstedtM., DanksN. P., & RayS. (Eds.). (2021). Evaluation of reflective measurement models. In Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (pp. 75–90). Springer International Publishing.
35.
HanifahA., & WulandariC. D. (2024). Analysis of UTAUT application on digital bank usage in Jabodetabek. International Journal of Scientific Research and Management, 12(7), 6978–6989.
36.
HolmbeckG. N. (1997). Toward terminological, conceptual, and statistical clarity in the study of mediators and moderators: Examples from the child-clinical and pediatric psychology literatures. Journal of Consulting and Clinical Psychology, 65(4), 599.
37.
HooperD., CoughlanJ., & MullenM. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60.
38.
HoyleR. H. (Ed.). (1995). Structural equation modeling: Concepts, issues, and applications. Sage Publications.
39.
HuL. T., & BentlerP. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.
40.
HunterJ. E. (1982). Unidimensional measurement, second-order factor analysis, and causal models. Research in Organizational Behavior, 4, 267–299.
41.
IndriasariE., PrabowoH., GaolF. L., & PurwandariB. (2022). Intelligent digital banking technology and architecture: A systematic literature review. International Journal of Interactive Mobile Technologies, 16(19), 4–22.
42.
JohnO. P., & Benet-MartínezV. (2000). Measurement: Reliability, construct validation, and scale construction. In ReisH. T. & JuddC. M. (Eds.), Handbook of research methods in social and personality psychology (pp. 339–369). Cambridge University Press.
43.
JöreskogK. G. (1971). Simultaneous factor analysis in several populations. Psychometrika, 36(4), 409–426.
44.
KhucT. A., DoH. L., & PhamB. L. (2022). Factors influencing financial literacy of the poor in rural areas: Empirical research with the case of Vietnam. Journal of Eastern European and Central Asian Research, 9(4), 638–650.
45.
KiranaL. C., SimanjuntakM., & ZulbainarniN. (2024). A comprehensive analysis: Perception, innovativeness, and intention of consumers as determinant factors of mobile banking usage behavior. Journal Aplikasi Bisnis dan Manajement, 10(2), 520–520.
46.
LaradiS., ElfekairA., RehmanH. M., HannaD., & AlrawadM. (2025). Continuance intention of m-banking adoption: The dynamics of UTAUT - 3, trust and attitudes. FIIB Business Review. https://doi.org/10.1177/23197145251358049
47.
LinF. T., WuH. Y., & TranT. N. N. (2015). Internet banking adoption in a developing country: An empirical study in Vietnam. Information Systems and E-business Management, 13, 267–287.
48.
MalhotraN., HallJ., ShawM., & OppenheimP. (2004). Essentials of marketing research: An applied orientation. Deakin University.
49.
MegargelA., & ShankarararmanV. (2020). Digital banking accelerator: A service-oriented architecture starter kit for banks. IEEE Software, 38(3), 106–112.
50.
MeirantoW., FaisalF., & YuyettaE. N. A. (2024). The mediating role of effort expectation on digital banking behavior intention in the Indonesian bank industry: An integration of UGT-UTAUT. International Journal of Data and Network Science, 8(4), 2547–2562.
51.
MerA., & VirdiA. S. (2023). Modeling millennials’ adoption intentions of e-banking: Extending UTAUT with perceived risk and trust. FIIB Business Review, 12(4), 425–438.
52.
MoghniH., NassehifarV., & NateghT. (2020). Designing model for quality services in digital banking. Journal of Critical Review, 7, 679–690.
53.
MufarihM., JayadiR., & SugandiY. (2020). Factors influencing customers to use digital banking application in Yogyakarta, Indonesia. The Journal of Asian Finance, Economics and Business, 7(10), 897–907.
54.
MusyaffiA. M., SariD. A. P., & RespatiD. K. (2021). Understanding of digital payment usage during COVID-19 pandemic: A study of UTAUT extension model in Indonesia. The Journal of Asian Finance, Economics and Business, 8(6), 475–482.
55.
MuzururaJ., & ChigoraF. (2019). Consumers’ behavioural intention to adopt mobile banking in rural Sub-Saharan Africa using an extension of technology acceptance model: Lessons from Zimbabwe. International Journal of Business, Economics and Management, 6(6), 316–334.
56.
NambiarB. K., RamanathanH. N., RanaS., & PrasharS. (2019). Perceived service quality and customer satisfaction: A missing link in Indian banking sector. Vision, 23(1), 44–55.
NguyenT. T., NguyenH. T., MaiH. T., & TranT. T. M. (2020). Determinants of digital banking services in Vietnam: Applying UTAUT2 model. Asian Economic and Financial Review, 10(6), 680–697.
59.
OmariniA. (2017). The digital transformation in banking and the role of fintechs in the new financial intermediation scenario. International Journal of Finance, Economics and Trade, 1(1), 1–6.
60.
PavithraC. B. (2021). Factors affecting customers’ perception towards digital banking services. Turkish Journal of Computer and Mathematics Education, 12(11), 1608–1614.
61.
PhamD. K. (2022). Digital banking adoption in Vietnam: An application of UTAUT2 model. Webology, 19(1), 3243–3262.
62.
PuşcaşuE. A. (2022). The impact of financial systems on economic growth in European Union member countries. Proceedings of the International Conference on Business Excellence, 16(1), 722–731.
63.
RachmawatiI. K., BukhoriM., MajidahY., & HidayatullahS. (2020). Analysis of use of mobile banking with acceptance and use of technology (UTAUT). International Journal of Scientific and Technology Research, 9(8), 534–540.
64.
RahiS. (2017). Research design and methods: A systematic review of research paradigms, sampling issues and instruments development. International Journal of Economics & Management Sciences, 6(2), 1–5.
65.
RahiS., AlghizzawiM., & NgahA. H. (2023). Factors influence user’s intention to continue use of e-banking during COVID-19 pandemic: The nexus between self-determination and expectation confirmation model. EuroMed Journal of Business, 18(3), 380–396.
66.
RanganathanC., & GanapathyS. (2002). Key dimensions of business-to-consumer web sites. Information & Management, 39(6), 457–465.
67.
RaoY. V., & BuddeS. R. (2015). Banking technology innovations in India: Enhancing customer value and satisfaction. Indian Journal of Science and Technology, 8(33), 1–10.
68.
RBI. (n.d.). Report on currency and finance 2021–22. https://rbidocs.rbi.org.in/rdocs/Publications/PDFs/RCF26022021FUL14763733401448089D2B70141732D717.PDF
69.
RiquelmeH. E., & RiosR. E. (2010). The moderating effect of gender in the adoption of mobile banking. International Journal of Bank Marketing, 28(5), 328–341.
70.
RogersE. M., BurdgeR. J., & KorschingP. F. (1983). Diffusion of innovations (3rd ed.). Free Press.
71.
SafitriD., SofyanJ. F., NegoroD. A., & KusmayadiA. (2024). Analisis behavioral intention mobile banking dengan model UTAUT2. Innovative: Journal of Social Science Research, 4(3), 571–587.
72.
SairS. A., & DanishR. Q. (2018). Effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among Pakistani consumers. Pakistan Journal of Commerce and Social Sciences, 12(2), 501–520.
73.
SajidR., AyubH., MalikB. F., & EllahiA. (2023). The role of Fintech on bank risk-taking: Mediating role of bank’s operating efficiency. Frontiers in Psychology, 1, 7059307.
74.
SantosA. A. D., & PonchioM. C. (2021). Functional, psychological and emotional barriers and the resistance to the use of digital banking services. Innovation & Management Review, 18(3), 331–348.
75.
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.
76.
SchopphovenI. (1991). Values and consumption patterns: A comparison between rural and urban consumers in Western Germany. European Journal of Marketing, 25(12), 20–35.
77.
SinghA., & RaiA. (2020). Digital banking and financial inclusion: A review of literature. Journal of Economic Surveys, 34(3), 709–735.
78.
SunT., & WuG. (2004). Consumption patterns of Chinese urban and rural consumers. Journal of Consumer Marketing, 21(4), 245–253.
79.
TamilmaniK., RanaN. P., & DwivediY. K. (2019). Use of ‘habit’ is not a habit in understanding individual technology adoption: A review of UTAUT2 based empirical studies. In HattinghM., MattheeM., SmutsH., PappasI., DwivediY. K., & MäntymäkiM. (Eds.), Smart working, living and organising: IFIP WG 8.6 International Conference on transfer and diffusion of IT, TDIT (pp. 277–294). Springer.
80.
TarhiniA., El-MasriM., AliM., & SerranoA. (2016). Extending the UTAUT model to understand the customers’ acceptance and use of internet banking in Lebanon: A structural equation modeling approach. Information Technology & People, 29, 830–849.
81.
TrawnihA. A., Al-AdwanA. S., YaseenH., & Al-RahmiW. M. (2023). Determining perceptions of banking customers regarding fingerprint ATMs. Information Development, 41(4), 1356–1374.
82.
TugadeC., ReyesJ., & NarteaM. (2021). Components affecting intention to use digital banking among generation Y and Z: An empirical study from the Philippines. The Journal of Asian Finance, Economics and Business, 8(12), 509–518.
83.
VenkateshV., MorrisM. G., DavisG. B., & DavisF. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
84.
VenkateshV., ThongJ. Y., & XuX. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
85.
VenkateshV., ThongJ. Y., & XuX. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376.
86.
VijaiD. C. (2019). Artificial intelligence in the Indian banking sector: Challenges and opportunities. International Journal of Advanced Research, 7(5), 1581–1587.
87.
VirdiA. S., & MerA. (2023). Fintech and banking: An Indian perspective. In TvaronavičienėM. A. & SinhaS. (Eds.), Green finance instruments, fintech, and investment strategies: Sustainable portfolio management in the post-COVID era (pp. 261–281). Springer International Publishing.
88.
WindasariN. A., KusumawatiN., LarasatiN., & AmeliaR. P. (2022). Digital-only banking experience: Insights from Gen Y and Gen Z. Journal of Innovation & Knowledge, 7(2), 100170.
89.
WiryawanD., SetiawanH. G., KhoirulA. M., AmbarwatuS. D. A., & GuiA. (2023). Analysis of factors influencing the intention of using digital banking through social media. In 10th International Conference on Information Technology, Computer, and Electrical, Engineering (ICITACEE 2023) (pp. 137–142). IEEE.
