CoChat
Sign Up
Cited by 343Technology Adoption and User BehaviourHealth, Technology, Consumer BehaviorFinTech, Crowdfunding, Digital Finance

The DOI matches its Crossref record; 53 of the 54 references it cites were found in a registry or an index.

Online banking adoption: an empirical analysis

Yee‐Loong Chong, Alain, Ooi, Keng‐Boon, Lin, Binshan, Tan, Boon‐In·2010·International Journal of Bank Marketing
DOI 10.1108/02652321011054963
Open this paper in CoChat — free account

Abstract

Purpose This paper aims to empirically examine the factors that affect the adoption of online banking in Vietnam. Perceived usefulness, perceived ease of use, trust and government support were examined to determine if these factors are affecting online banking adoption. Design/methodology/approach A survey was distributed to 156 respondents in Vietnam with 103 usable samples giving a response rate of 66 percent. Data were analyzed by employing correlation and multiple regression analysis. Findings The results showed that perceived usefulness, trust and government support all positively associated with the intention to use online banking in Vietnam. Contrary to the technology acceptance model, perceived ease of use was found to be not significant in this study. Research limitations/implications This study was conducted in Vietnam and future research can use this model to study the adoption of online banking in other countries. Practical implications The results allow banks' decision makers to develop strategies that can increase the adoption of online banking. Banks should improve the security and privacy of the web sites, which will increase the trust of users. Banks should also create features which are useful to users and make sure users are aware of these features. Lastly, government should also play a role to support banks in their efforts to increase online banking adoption. Originality/value The findings allow the factors that can influence the adoption of online bankin…

Overview

Integrity signals

Registry

Crossref · 10.1108/02652321011054963

Cites

53 of 53 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Citations

Cites

Show all 54 references

Research works printed but not linked: 2

  1. Nunnally, J. (1978), Psychometric Theory, McGraw‐Hill, New York, NY.
  2. Rogers, E.M. (1995), Diffusion of Innovations, The Free Press, New York, NY.

Cited by

Sorted by citations

Items 101–200 of 343

Related

See all

Metadata

Authors
Yee‐Loong Chong, A., Ooi, K., Lin, B., & Tan, B.
Affiliations
  • Tunku Abdul Rahman University of Management and Technology (MY)
  • Louisiana State University in Shreveport (US)
ORCID
Venue
International Journal of Bank Marketing
Publisher
Emerald
Published
2010-06-15
Volume
28
Issue
4
Pages
267-287
ISSN
0265-2323 (ISSN-L)
DOI
10.1108/02652321011054963
OpenAlex
W1981781071
Cited by
343
References
54
Citations by year
2026: 8 · 2025: 10 · 2024: 27 · 2023: 35 · 2022: 31 · 2021: 34 · 2020: 19 · 2019: 26 · 2018: 17 · 2017: 25 · 2016: 22 · 2015: 30 · 2014: 23 · 2013: 20 · 2012: 8
FWCI
24.80
Type
journal article
Language
en
Open access
closed
Licence
www.emerald.com/insight/site-policies (tdm)
Locations
International Journal of Bank Marketing (publishedVersion)
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 › Management Information Systems › FinTech, Crowdfunding, Digital Finance
Keywords
online banking adoption, technology acceptance model, perceived usefulness, perceived ease of use, trust in banks, government support, privacy and security, intention to use, Vietnam

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