CoChat
Sign Up
Cited by 156Technology Adoption and User BehaviourHealth, Technology, Consumer BehaviorCustomer Service Quality and Loyalty

Continued Intention to Use of M-Banking in Jordan by Integrating UTAUT, TPB, TAM and Service Quality with ML

Open access
Abu-Taieh, Evon M., AlHadid, Issam, Abu-Tayeh, Sabah, Masa’deh, Ra’ed, Alkhawaldeh, Rami S., Khwaldeh, Sufian, Alrowwad, Ala’aldin·2022·Journal of Open Innovation: Technology, Market, and Complexity
DOI 10.3390/joitmc8030120
Open this paper in CoChat — free accountOpen PDF

Abstract

Mobile banking is a service provided by a bank that allows full remote control of customers' financial data and transactions with a variety of options to serve their needs.With m-banking, the banks can cut down on operational costs whilst maintaining client satisfaction.This research examined the most crucial factors that could predict the Jordanian customer's continued intention toward the use of m-banking.Following the proposed model, the research was conducted by using a self-conducted questionnaire and the responses were collected electronically from a convenience sample of 403 Jordanian customers of m-banking through social networks.The suggested model was adapted from the theory of planned behavior (TPB), the unified theory of acceptance and use of technology (UTAUT), and the technology acceptance model (TAM).The research model was further expanded by considering the factors of service quality and moderating factors (age, gender, educational level, and Internet experience).The collected data of customers were analyzed, validated, and verified by using a structural equation modeling (SME) approach including a confirmatory factor analysis (CFA), in addition to machine learning (ML) methods, artificial neural network (ANN), support vector machine (SMO), bagging reduced error pruning tree (RepTree), and random forest.Results showed that effort expectancy, performance expectancy, perceived risk, perceived trust, social influence, and service quality impacted behavioral intention, whereas facilitating conditions did not.Furthermore, behavioral intention impacted upon word of mouth and facilitating conditions (the latter regarding the continued intention to use m-banking), and had the highest coefficient value.Results also confirmed that all moderating factors affect the behavioral intention to continue using m-banking applications.

Integrity signals

Registry

Crossref · 10.3390/joitmc8030120

Cites

101 of 101 references verified0 citation errors · 0 not checkable

Statistics

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

Claims the paper makes

We couldn’t retrieve this paper’s full text, 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?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Abu-Taieh, E. M., AlHadid, I., Abu-Tayeh, S., Masa’deh, R., Alkhawaldeh, R. S., Khwaldeh, S., & Alrowwad, A.
Affiliations
University of Jordan (JO)
Corresponding author
Abu-Taieh, Evon M.
ORCID
Venue
Journal of Open Innovation: Technology, Market, and Complexity
Publisher
Elsevier BV
Published
2022-09
Volume
8
Issue
3
Pages
120
ISSN
2199-8531 (ISSN-L)
DOI
10.3390/joitmc8030120
OpenAlex
W4285496049
Cited by
156
References
101
Citations by year
2026: 22 · 2025: 49 · 2024: 44 · 2023: 36 · 2022: 5
FWCI
28.03
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Open Innovation Technology Market and Complexity (publishedVersion, cc-by-nc-nd)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Econstor (Econstor) (submittedVersion, cc-by)
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, behavioral intention, UTAUT, theory of planned behavior, technology acceptance model, service quality, risk perception, perceived trust, social influence, word of mouth, moderators

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