Banking “on-the-go”: examining consumers’ adoption of mobile banking services
Open accessAbstract
Purpose: This paper aims to examine consumers’ adoption of mobile technology to facilitate their banking services and activities, and to investigate the factors influencing their adoption and engagement. Design/methodology/approach: An online survey is used to test proposed relationships between factors and consumers’ mobile banking adoption. Structural equation modeling is performed to analyze consumers’ intentions toward mobile banking. Findings: Traditional technology acceptance model factors – perceived usefulness and perceived ease of use – are identified as effective factors in influencing consumers to adopt mobile technology for facilitating banking services. Moreover, technology safety concerns, including reliability and privacy factors, are found to play an important role in motivating consumers to embrace mobile banking. The “fun” feature of the technology and consumers’ innovativeness characteristics are considered important in influencing mobile banking adoption. Trust in the banks has its predominant role in mobile technology adoption for banking services. Practical implications: A bank gaining trust from its clients is key to active adoption of mobile banking technology. Bankers are advised to pay more attention to reliability and privacy features when designing and promoting mobile banking technology to consumers. Moreover, advertisements to bank clients should stress the “fun” aspects of the mobile banking apps to attract them to the use of mobile banking technology. Originality/value: This paper investigates the factors influencing bank consumers to adopting mobile banking apps to facilitate their banking services. Nine key factors in the technology adoption area are examined to provide a comprehensive understanding of bank clients’ use of mobile banking apps, which advances the understanding of mobile technology applied in the banking industry in the literature.
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In the context of mobile systems and digital platforms, habit is a critical factor influencing usage.
“In the context of mobile systems and digital platforms, habit is a critical factor influencing usage [34].”
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035 · see citing works
Technology Acceptance Model 3 and a Research Agenda on Interventions
Venkatesh, V., & Bala, H. (2008) · Decision Sciences · doi:10.1111/j.1540-5915.2008.00192.x · Cited by 8,159 · see citing works
Value-based Adoption of Mobile Internet: An empirical investigation
Kim, H.-W., Chan, H. C., & Gupta, S. (2007) · Decision Support Systems · doi:10.1016/j.dss.2005.05.009 · Cited by 2,084 · see citing works
Baptista, G., & Oliveira, T. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.04.024 · Cited by 922 · see citing works
McCole, P., Ramsey, E., & Williams, J. (2010) · Journal of Business Research · doi:10.1016/j.jbusres.2009.02.025 · Cited by 403 · see citing works
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A meta-analysis of antecedents and consequences of trust in mobile commerce
Sarkar, S., Chauhan, S., & Khare, A. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.008 · Cited by 375 · see citing works
User Innovativeness and Fintech Adoption in Indonesia
Setiawan, B., Nugraha, D. P., Irawan, A., Nathan, R. J., & Zoltan, Z. (2021) · Journal of Open Innovation: Technology, Market, and Complexity · doi:10.3390/joitmc7030188 · Cited by 267 · see citing works
Fintech Adoption Drivers for Innovation for SMEs in Indonesia
Nugraha, D. P., Setiawan, B., Nathan, R. J., & Fekete-Farkas, M. (2022) · Journal of Open Innovation: Technology, Market, and Complexity · doi:10.3390/joitmc8040208 · Cited by 188 · see citing works
Abu-Taieh, E. M., AlHadid, I., Abu-Tayeh, S., Masa’deh, R., Alkhawaldeh, R. S., Khwaldeh, S., & Alrowwad, A. (2022) · Journal of Open Innovation: Technology, Market, and Complexity · doi:10.3390/joitmc8030120 · Cited by 156 · see citing works
Jeilani, A., & Hussein, A. (2025) · BMC Health Services Research · doi:10.1186/s12913-025-12414-4 · Cited by 105 · see citing works
Fintech and Financial Health in Vietnam during the COVID-19 Pandemic: In-Depth Descriptive Analysis
Nathan, R. J., Setiawan, B., & Quynh, M. N. (2022) · Journal of Risk and Financial Management · doi:10.3390/jrfm15030125 · Cited by 103 · see citing works
Financial technology adoption among small and medium enterprises in Ghana
Krah, R., Tetteh, L. A., Boateng, A., & Amankwa, R. F. (2024) · Cogent Business & Management · doi:10.1080/23311975.2024.2321786 · Cited by 36 · see citing works
“…to the characteristics of the unit of analysis, this model has emerged as one of the most extensively utilised in the realm of scholarly investigation (Zhang et al., 2018). in order to investigate what motivates fintech adoption, this study categories the constructs along two dimensions:…”
A Meta-Analysis of Trust in Mobile Banking: The Moderating Role of Cultural Dimensions
Kumar, P., Chauhan, S., Gupta, P., & Jaiswal, M. P. (2023) · International Journal of Bank Marketing · doi:10.1108/ijbm-02-2022-0075 · Cited by 34 · see citing works
Taneja, S., Ali, L., Siraj, A., Ferasso, M., Luthra, S., & Kumar, A. (2024) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2024.3395130 · Cited by 26 · see citing works
Dahmani, M., & Ben Youssef, A. (2023) · Platforms · doi:10.3390/platforms1010005 · Cited by 15 · see citing works
“In the context of mobile systems and digital platforms, habit is a critical factor influencing usage [34].”
BackgroundVardari, L., & Hameli, K. (2025) · Global Knowledge, Memory and Communication · doi:10.1108/gkmc-02-2025-0137 · Cited by 7 · see citing works
An Empirical Study of User Acceptance Behaviours of Internet Banking in Tunisia Using UTAUT2 Model
Nasri, W. (2021) · International Journal of Innovation in the Digital Economy · doi:10.4018/ijide.2021100102 · Cited by 4 · see citing works
- Authors
- Zhang, T., Lu, C., & Kizildag, M.
- Affiliations
- University of Central Florida (US)
- The Ohio State University (US)
- Venue
- International Journal of Quality and Service Sciences
- Publisher
- Emerald
- Published
- 2018-09-17
- Volume
- 10
- Issue
- 3
- Pages
- 279-295
- ISSN
- 1756-669X (ISSN-L)
- OpenAlex
- W2888884503
- Cited by
- 239
- References
- 6
- Citations by year
- 2026: 14 · 2025: 25 · 2024: 44 · 2023: 48 · 2022: 49 · 2021: 28 · 2020: 20 · 2019: 11
- FWCI
- 20.94
- Type
- journal article
- Language
- en
- Open access
- Locations
- International Journal of Quality and Service Sciences (publishedVersion)
- Journal of International Crisis and Risk Communication Research (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Keywords
- mobile banking, technology adoption, technology acceptance model, perceived usefulness, perceived ease of use, trust in banks, privacy concerns, security concerns, user innovativeness, fun factors, mobile banking applications, consumer behavior
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