2022
DOI: 10.1108/ijbm-08-2021-0394
|View full text |Cite
|
Sign up to set email alerts
|

Exploring users' adoption intentions in the evolution of artificial intelligence mobile banking applications: the intelligent and anthropomorphic perspectives

Abstract: PurposeThe development of mobile technology has changed the traditional financial industry and banking sector. While traditional banks have adopted artificial intelligence (AI) techniques to deepen the development of mobile banking applications (apps), the current literature lacks research on the use of AI-based constructs to explore users' mobile banking app adoption intentions. To fill this gap, based on stimulus-organism-response (SOR) theory, two AI feature constructs as stimuli are considered, namely, per… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
57
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
6
3

Relationship

1
8

Authors

Journals

citations
Cited by 87 publications
(80 citation statements)
references
References 112 publications
0
57
0
Order By: Relevance
“…It will also serve as an information repository for users' monthly work achievements, which can be retrieved anywhere and anytime. Recent research reports similar pilot testing of mobile applications for the banking sector (Lee & Chen, 2022;Shahid et al, 2022), government services (Ali, 2021;Desmal et al, 2021) and online newspapers (Zheng et al, 2021). They report appropriate, positive acceptance of mobile applications for these industries.…”
Section: Resultsmentioning
confidence: 95%
“…It will also serve as an information repository for users' monthly work achievements, which can be retrieved anywhere and anytime. Recent research reports similar pilot testing of mobile applications for the banking sector (Lee & Chen, 2022;Shahid et al, 2022), government services (Ali, 2021;Desmal et al, 2021) and online newspapers (Zheng et al, 2021). They report appropriate, positive acceptance of mobile applications for these industries.…”
Section: Resultsmentioning
confidence: 95%
“…We conducted an additional analysis using the non-software industry samples (106 respondents from 46 teams) to examine whether the sample distribution affected the results. This supplementary analysis is possible since the sample size (106) is considered sufficient with the minimum sample size requirement of 60 and the rule of thumb of 10 cases per indicator (Lee and Chen 2022 ; Chin 1998 ) concerning the most complex variable, i.e., PD, which has 6 indicators in the model. According to Table 6 , the results showed that no difference exists in terms of the full sample group and non-software industry group, implying that the non-software industry samples do not skew the results of the full sample.…”
Section: Resultsmentioning
confidence: 99%
“…Overall, there are many applications of AI in banking services (Camacho et al. , 2022; Lee and Chen, 2022; Liu and Tao, 2022). As discussed earlier, banks have minimal dependence on technologies.…”
Section: Literature Reviewmentioning
confidence: 99%