An empirical examination of initial trust in mobile banking
Abstract
Purpose The purpose of this paper is to examine the effect of initial trust on mobile banking user adoption. Design/methodology/approach Based on the valid responses collected from a survey questionnaire, structural equation modeling (SEM) technology was employed to examine the research model. Findings The results indicate that structural assurance and information quality are the main factors affecting initial trust, whereas information quality and system quality significantly affect perceived usefulness. Initial trust affects perceived usefulness, and both factors predict the usage intention of mobile banking. Research limitations/implications The sample was mainly composed of users having rich mobile Internet experience, which may affect their trust in mobile banking. Future research needs to generalize these results to other samples, such as those users without much mobile Internet experience. Originality/value Extant research has mainly adopted information technology adoption theories such as TAM to explain mobile user behavior, and has seldom examined the effect of initial trust on mobile banking user adoption. However, the high perceived risk and low switching cost highlight the necessity to build initial trust to facilitate user behavior. This research fills the gap.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Trust in digital services depends on how people perceive the risks, benefits and trustworthiness of the provider.
“The finding aligns with previous study that trust in digital services depends on how people perceive the risks, benefits and trustworthiness of the provider (Zhou, 2011).”
From Feeling Watched: A Phenomenological Exploration of Consumer Discomfort and Data Privacy Concerns in E-Commerce Personalized Email Marketing (2025) · cites this paper as Zhou, 2011
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314 · see citing works
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190 · see citing works
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194 · see citing works
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941 · see citing works
On the Evaluation of Structural Equation Models
Bagozzi, R. P., & Yi, Y. (1988) · Journal of the Academy of Marketing Science · doi:10.1007/bf02723327 · Cited by 26,163 · see citing works
Trust and TAM in Online Shopping: An Integrated Model1
Gefen, D., Karahanna, E., & Straub, D. W. (2003) · MIS Quarterly · doi:10.2307/30036519 · Cited by 8,635 · see citing works
Agarwal, R., & Karahanna, E. (2000) · MIS Quarterly · doi:10.2307/3250951 · Cited by 4,726 · see citing works
Building Effective Online Marketplaces with Institution-Based Trust
Pavlou, P. A., & Gefen, D. (2004) · Information Systems Research · doi:10.1287/isre.1040.0015 · Cited by 2,516 · see citing works
A Comparison of Online Trust Building Factors between Potential Customers and Repeat Customers
National University of Singapore, S., Kim, H.-W., Xu, Y., National University of Singapore, S., Koh, J., & Electronics, S. (2004) · Journal of the Association for Information Systems · doi:10.17705/1jais.00056 · Cited by 452 · see citing works
Web Strategies to Promote Internet Shopping: Is Cultural-Customization NeedeD?1
Sia, C. L., Lim, K. H., Leung, K., Lee, M. K. O., Huang, W. W., & Benbasat, I. (2009) · MIS Quarterly · doi:10.2307/20650306 · Cited by 342 · cited 1× · see citing works
“Brand association and portal affiliation also affect online consumers’ initial trust (Delgado-Ballester and Hernandez-Espallardo, 2008; Sia et al., 2009).”
Background
Flagged first, then by citations
Cited by
Sorted by citations
Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM
Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.06.004 · Cited by 808 · see citing works
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
Acceptance of mobile banking framework in Pakistan
Afshan, S., & Sharif, A. (2016) · Telematics and Informatics · doi:10.1016/j.tele.2015.09.005 · Cited by 376 · see citing works
Towards an understanding of consumers’ FinTech adoption: The case of Open Banking
Chan, R., Troshani, I., Rao Hill, S., & Hoffmann, A. (2022) · International Journal of Bank Marketing · doi:10.1108/ijbm-08-2021-0397 · Cited by 281 · see citing works
Roles of perceived value and individual differences in the acceptance of mobile coupon applications
Liu, F., Zhao, X., Chau, P. Y. K., & Tang, Q. (2015) · Internet Research · doi:10.1108/intr-02-2014-0053 · Cited by 218 · see citing works
Gupta, K., & Arora, N. (2019) · South Asian Journal of Business Studies · doi:10.1108/sajbs-03-2019-0037 · Cited by 208 · see citing works
What makes consumers trust and adopt FinTech? An empirical investigation in China
Roh, T., Yang, Y. S., Xiao, S., & Park, B. I. (2024) · Electronic Commerce Research · doi:10.1007/s10660-021-09527-3 · Cited by 164 · see citing works
Factors affecting consumers’ mobile payment behavior: A meta-analysis
Liu, Z., Ben, S., & Zhang, R. (2019) · Electronic Commerce Research · doi:10.1007/s10660-019-09349-4 · Cited by 152 · see citing works
Chawla, D., & Joshi, H. (2023) · Global Business Review · doi:10.1177/0972150920924506 · Cited by 144 · see citing works
Mobile application user behavior in the developing countries: A survey in Iran
Hajiheydari, N., & Ashkani, M. (2018) · Information Systems · doi:10.1016/j.is.2018.05.004 · Cited by 73 · see citing works
Kim, J. W., Jo, H. I., & Lee, B. G. (2019) · Journal of Digital Contents Society · doi:10.9728/dcs.2019.20.1.41 · Cited by 30 · see citing works
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
Building trust in cybernetic payment network: Insights from an emerging economy
Ahmed, S., Ahmed, R., Ashrafi, D. M., Ahmed, E., & Annamalah, S. (2024) · Journal of Open Innovation: Technology, Market, and Complexity · doi:10.1016/j.joitmc.2024.100331 · Cited by 13 · see citing works
Rahayu, T. A., Purnamasari, V. F. W., Rizky, M. A., Rahyadi, I., & Mani, L. (2025) · PaperASIA · doi:10.59953/paperasia.v41i1b.313 · Cited by 1 · see citing works
“The finding aligns with previous study that trust in digital services depends on how people perceive the risks, benefits and trustworthiness of the provider (Zhou, 2011).”
- Authors
- Zhou, T.
- Affiliations
- Hangzhou Dianzi University (CN)
- Corresponding author
- Zhou, Tao
- ORCID
- Zhou, Tao
- Venue
- Internet Research
- Publisher
- Emerald
- Published
- 2011-08-12
- Volume
- 21
- Issue
- 5
- Pages
- 527-540
- ISSN
- 1066-2243 (ISSN-L)
- OpenAlex
- W2139794205
- Cited by
- 589
- References
- 10
- Citations by year
- 2026: 38 · 2025: 45 · 2024: 46 · 2023: 54 · 2022: 54 · 2021: 59 · 2020: 52 · 2019: 43 · 2018: 47 · 2017: 29 · 2016: 27 · 2015: 39 · 2014: 29 · 2013: 17 · 2012: 9
- FWCI
- 42.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Internet Research (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- mobile banking, initial trust, technology adoption, perceived usefulness, information quality, structural assurance, system quality, intention to use, risk perception, switching costs, technology acceptance model
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
