Published at : 31 Jul 2026
Volume : IJtech
Vol 17, No 4 (2026)
DOI : https://doi.org/10.14716/ijtech.v17i4.8603
| Vardan Aleksanyan | Faculty of Economics and Management, Yerevan State University, Yerevan, 0025, Armenia |
| Hovhannes Asatryan | 1. Department of Macroeconomic Problems and Finance, The Institute of Economics after M. Kotanyan, Yerevan, 0015, Armenia 2. Department of Research and Development, Armenian State University of Econ |
| Karlen Khachatryan | Faculty of Economics and Management, Yerevan State University, Yerevan, 0025, Armenia |
This study examines the socio-economic sustainability outcomes of digital banking adoption in Armenia through a two-layer conceptual model in which technology-acceptance constructs serve as antecedents and four perceived sustainability outcomes (financial inclusion, economic benefit, business enablement, and inclusive participation) serve as analytical endpoints. Drawing on survey data from 410 respondents and a supplementary sustainability-perception measurement block, the model was estimated using PLS-SEM with bootstrapping (5,000 resamples). The results identify institutional trust as the dominant predictor of digital banking adoption (= 0.36, t = 4.89, p < 0.001), while classical TAM constructs—perceived usefulness (
= 0.11, p = 0.195), perceived ease of use (
= 0.07, p = 0.328), and perceived risk (
=-0.04, p = 0.448)—do not retain explanatory power once trust is included. Behavioural intention strongly predicts actual usage (
= 0.67, t = 10.32, p < 0.001), with the antecedent layer explaining 52% of the variance in intention and 61% in usage. Actual usage significantly and positively predicts all four sustainability outcomes (p < 0.001), with the strongest effect on perceived inclusive participation (
= 0.41) and financial inclusion (
= 0.34), and weaker effects on economic benefit (
= 0.25) and business enablement (
= 0.19). Bootstrapped indirect effects analysis confirms that the trust-adoption-sustainability chain is empirically coherent: trust propagates to all four sustainability outcomes through the adoption mechanism (indirect effects ranging from 0.046 to 0.099, 95% bias-corrected CIs excluding zero), with the strongest propagation to inclusion-oriented outcomes. These findings reposition technology-acceptance research within a socio-economic sustainability framework and provide empirical evidence that institutional trust, rather than usability attitudes, is the binding constraint on the inclusive and sustainable transformation of financial systems in transitional economies.
Digital banking adoption; Financial inclusion; Institutional trust; Socio-economic sustainability; Transitional economy
Adian, I.,
Doumbia, D., Gregory, N., Ragoussis, A., Reddy, A., & Timmis, J. (2020).
Small and medium enterprises in the pandemic: Impact, responses, and the role
of development finance (Policy Research Working Paper). World Bank. https://documents1.worldbank.org/curated/en/729451600968236270/pdf/Small-and-Medium-Enterprises-in-the-Pandemic-Impact-Responses-and-the-Role-of-Development-Finance.pdf
Aleksanyan, V., Asatryan, H., Minta, S., &
Khachatryan, K. (2026). Uncovering the determinants of the transition to
digital agriculture: A survey-based tobit analysis. Economia Agro-Alimentare /
Food Economy - Open Access, 28 (1). https://doi.org/10.3280/ecag2026oa20705
Almaiah, M.,
Al-Otaibi, S., Shishakly, R., Hassan, L., Lutfi, A., Alrawad, M., Qatawneh, M.,
& Alghanam, O. (2023). Investigating the role of perceived risk, perceived
security and perceived trust on smart m-banking application using sem.
Sustainability. https://doi.org/10.3390/su15139908
Alnemer, H.
(2022). Determinants of digital banking adoption in the kingdom of saudi
arabia: A technology acceptance model approach. Digital Business. https://doi.org/10.1016/j.digbus.2022.100037
Aron, J. (2018).
Mobile money and the economy: A review of the evidence. The World Bank Research
Observer, 33 (2), 135–188. https://doi.org/10.1093/wbro/lky001
Asatryan, H.,
Erkoyan, A., Muradyan, M., Berberyan, V., Nalbandyan, H., Harutyunyan, A.,
& Poghosyan, S. (2025). Spillover effects of the russian-ukrainian conflict
on the armenian economy: A multiple period approach. Cogent Social Sciences, 11
(1). https://doi.org/10.1080/23311886.2025.2591459
Central Bank of
Armenia. (2022). Annual report 2022 (tech. rep.). Central Bank of Armenia. https://www.cba.am/file_manager/Annual-reports/Annual%20Report%202022%20eng.pdf
Cheng, T. C. E., Lam, D. Y. C., & Yeung, A. C.
L. (2006). Adoption of internet banking: An empirical study in hong
kong. Decision Support Systems, 42 (3), 1558–1572. https://doi.org/10.1016/j.dss.2006.01.002
Demirg¨u¸c-Kunt, A., Klapper, L., Singer, D.,
Ansar, S., & Hess, J. (2018). The global findex database 2017:
Measuring financial inclusion and the fintech revolution. World Bank. https://doi.org/10.1596/978-1-4648-1259-0
Demirg¨u¸c-Kunt,
A., & Singer, D. (2017). Financial inclusion and inclusive growth: A review
of recent empirical evidence (tech. rep.). World Bank.
European Bank for
Reconstruction and Development. (2021). Armenia diagnostic paper: Enhancing
financial inclusion (tech. rep.). EBRD.
Gefen, D., Karahanna, E., & Straub, D. W.
(2003). Trust and tam in online shopping: An integrated model. MIS
Quarterly, 27 (1), 51–90. https://doi.org/10.2307/30036519
Gu, H., Zhang, T., Lu, C., & Song, X. (2020). Assessing
trust and risk perceptions in the sharing economy: An empirical study. Journal
of Management Studies. https://doi.org/10.1111/joms.12678
Hair, J. F.,
Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated
and expanded assessment of pls-sem in information systems research. Industrial
Management & Data Systems, 117 (3), 442–458. https://doi.org/10.1108/imds-04-2016-0130
Hakobyan, A.,
& Margaryan, Z. (2025). Impact of the russian-ukrainian armed conflict on
the financial performance of armenia’s banking sector. Banks and Bank Systems,
20 (1). https://doi.org/10.21511/bbs.20(1).2025.27
Hambardzumyan, A.
(2023). Embracing finance 4.0: The opportunity for armenian banks to transform
and thrive. Messenger of Armenian State University of Economics. https://doi.org/10.52174/1829-0280_2023.1-19
Harutyunyan, G.,
Manucharyan, M., Muradyan, M., & Asatryan, H. (2024). Digital literacy of
the armenian society: Assessment and determinants. Cogent Social Sciences, 10
(1). https://doi.org/10.1080/23311886.2024.2398652
Hayes, A. F.
(2022). Introduction to mediation, moderation, and conditional process
analysis: A regression-based approach (3rd). Guilford Press.
Haykyants, A.,
& Ghukasyan, S. (2022). The factor of consumer rights protection as a
criterion for social system development. WISDOM, 22 (2). https://doi.org/10.24234/wisdom.v22i2.807
Hurani, J., &
Abdel-Haq, M. K. (2025). Factors influencing fintech adoption among bank
customers in palestine: An extended technology acceptance model approach.
International Journal of Financial Studies, 13 (1), 11. https://doi.org/10.3390/ijfs13010011
Japaridze, D., Kupets, O., Melnyk, T., Lariushin,
T., Kasimov, E., & Hovhanisyan, A. (2011). Development in eastern
europe and the south caucasus. OECD Publishing. https://doi.org/10.1787/9789264113039-en
Klapper, L., El-Zoghbi, M., & Hess, J. (2017).
Achieving the sustainable development goals: The role of financial
inclusion (tech. rep.). CGAP / World Bank.
Kock, N. (2015).
Common method bias in pls-sem: A full collinearity assessment approach.
International Journal of e-Collaboration, 11 (4), 1–10. https://doi.org/10.4018/ijec.2015100101
Kumar, A.,
Dhingra, S., Batra, V., & Purohit, H. (2020). A framework of mobile banking
adoption in india. Journal of Open Innovation: Technology, Market, and
Complexity, 6 (2), 40. https://doi.org/10.3390/joitmc6020040
Legris, P.,
Ingham, J., & Collerette, P. (2002). Why do people use information
technology? a critical review of the technology acceptance model. Information
& Management, 40 (3), 191–204. https://doi.org/10.1016/S0378-7206(01)00143-4
Majidli, F.
(2020). International comparative and competitive advantage of post-soviet
countries in tourism. Research in World Economy, 11 (5), 369. https://doi.org/10.5430/rwe.v11n5p369
Minasyan, D.
(2024). Banking stability modelling for armenia: Decision tree approach.
ALTERNATIVE. https://doi.org/10.55528/18292828-2024.2-116
Nushikyan, I.
(2024). The innovative transformation in the ra banking system. Economics,
Finance and Accounting. https://doi.org/10.59503/29538009-2024.2.14-121
Paquin, J. (2022).
Institutions and the informal economy: Tax morale of small businesses in
armenia and georgia. In A. Polese (Ed.), Informality, labour mobility and
precariousness (pp. 113–138). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-82499-0_6
Patel, K. J.,
& Patel, H. J. (2017). Adoption of internet banking services in gujarat: An
extension of tam with perceived security and social influence. International
Journal of Bank Marketing, 36 (1), 147–169. https://doi.org/10.1108/IJBM-08-2016-0104
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y.,
& Podsakoff, N. P. (2003). Common method biases in behavioral
research: A critical review of the literature and recommended remedies. Journal
of Applied Psychology, 88 (5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
Poghosyan, S.,
Manucharyan, M., Martirosyan, G., Azatyan, L., & Asatryan, H. (2024).
Leslie matrix matching approach in labor market studies. Cogent Arts &
Humanities, 11 (1). https://doi.org/10.1080/23311983.2024.2426364
Preacher, K. J.,
& Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing
and comparing indirect effects in multiple mediator models. Behavior Research
Methods, 40 (3), 879–891. https://doi.org/10.3758/BRM.40.3.879
Raza, A., &
Tursoy, T. (2024). Technology acceptance model and fintech: An evidence from
italian banking industry. Revista Mexicana de Economía y Finanzas, 20 (1). https://doi.org/10.21919/remef.v20i1.993
Sarstedt, M.,
Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural
equation modeling. In Springer ebooks (pp. 1–47). Springer. https://doi.org/10.1007/978-3-319-05542-8_15-2
Tharimala, S., Reddy, G., & Sowmyasree, V.
(2024). Impact of financial literacy on behavioural intentions towards
digital banking using tam: A study in presence of personality traits. 2024
First International Conference for Women in Computing (InCoWoCo), 1–8. https://doi.org/10.1109/InCoWoCo64194.2024.10863365
United Nations.
(2015). Transforming our world: The 2030 agenda for sustainable development. https://sdgs.un.org/2030agenda
Venkatesh, V.,
Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of
information technology: Toward a unified view. MIS Quarterly, 27 (3), 425–478. https://doi.org/10.2307/30036540
Venkatesh, V.,
& Davis, F. D. (2000). A theoretical extension of the technology acceptance
model: Four longitudinal field studies. Management Science, 46 (2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11972
World Bank.
(2023). Financial inclusion data: Armenia (tech. rep.). World Bank. https://globalfindex.worldbank.org