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An extended UTAUT model to explain the adoption of mobile banking
Abstract
This research attempts to identify the factors leading to the adoption of mobile banking and the degree of influence of each one of the factors in Thailand. It proposes a comprehensive framework that extends the existing UTAUT model with important constructs such as perceived credibility, perceived cost, and perceived convenience. A three-pronged approach, consisting of an extensive review of the literature, expert interviews, and a field survey of mobile banking adoption is put forward. A field survey of respondents was undertaken with both convergent and discriminant validities being conducted. The results of the structural equation modeling show that performance expectancy, effort expectancy, social influence, perceived credibility, perceived convenience, and behavioral intention to use mobile banking posited a positive relationship. Contrary to previous studies, the hypotheses testing perceived that financial cost and facilitation conditions in the adoption of mobile banking were not supported. Discussions and conclusions including academic and practical implications are also presented.
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“it is also documented that other streams of studies reported no significant influence of facilitating conditions on the intention to use a technology [47,48,66].”
From A Study of the Adoption and Implementation of Enterprise Resource Planning (ERP): Identification of Moderators and Mediator (2020) · cites this paper as [48]
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“Furthermore, based on UTAUT, both Bhatiasevi (2016) and Zhou et al. (2010) concluded that PE significantly influences the continuous use of M-Banking.”
BackgroundMethodMerhi, M., Hone, K., & Tarhini, A. (2019) · Technology in Society · doi:10.1016/j.techsoc.2019.101151 · Cited by 555
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MethodAcceptance of mobile banking framework in Pakistan
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BackgroundInfluentialAcceptance of mobile banking in Islamic banks: Evidence from modified UTAUT model
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“As stated by Bhatiasevi (2015), popular models extensively used in the past shall be subject to new investigations, in order to test similarities and differences of the results from the perspective of others contexts.”
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“Table 2 - M-banking empirical studies Model/Theory Dependent Variable Source Constructs A tt it ud e B eh av io ur al c on tr ol C ul tu re E ff or t e xp ec ta nc y F ac il it at in g co nd it io ns H ab it H ed on ic m ot iv at io n In fo rm at io n qu al it y In te rf ac e qu al it y P er ce iv ed c om pa ti bi li…”
A study on factors affecting service quality and loyalty intention in mobile banking
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“Bhatiasevi (2016) extended the existing UTAUT model and applied SEM as the primary method to test model in the context of Thailand, the results showed a positive relationship between performance and effort expectancies, social influence, perceived credibility and convenience, behavioural intention…”
MethodCharacterizing Chinese consumers’ intention to use live e-commerce shopping
Zhou, M., Huang, J., Wu, K., Huang, X., Kong, N., & Campy, K. S. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101767 · Cited by 210
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Dhiman, N., Arora, N., Dogra, N., & Gupta, A. (2019) · Journal of Indian Business Research · doi:10.1108/jibr-05-2018-0158 · Cited by 209
Al‐Okaily, M., Alkhwaldi, A. F., Abdulmuhsin, A. A., Alqudah, H. M., & Al-Okaily, A. (2022) · Journal of financial reporting & accounting · doi:10.1108/jfra-12-2021-0476 · Cited by 201
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Adoption of mobile self-service retail banking technologies
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Adoption of mobile banking services
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Factors Affecting MOOC Usage by Students in Selected Ghanaian Universities
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“Their goal was to create a unified model by merging different models of technology adoption as well as results from several researchers in the area of technology adoption [19].”
BackgroundSaprikis, V., Avlogiaris, G., & Katarachia, A. (2020) · Journal of theoretical and applied electronic commerce research · doi:10.3390/jtaer16030030 · Cited by 136
Barriers in adoption of internet banking: A structural equation modeling - Neural network approach
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Chen, L., Rashidin, M. S., Song, F., Yi, W., Javed, S., & Wang, J. (2021) · SAGE Open · doi:10.1177/21582440211027875 · Cited by 124
“Social Influence Social influence is defined by Venkatesh et al. (2003, p. 451) “an individual perceives that important others believe he or she should use the new system,” the construct Social Influence is derived from the following notions: subjective norm from the Theory of Reasoned Action (TRA) (Fishbein & Ajzen,…”
BackgroundMethodInfluentialSustainable FinTech Innovation Orientation: A Moderated Model
Al‐Okaily, M., Natour, A. R. A., Shishan, F., Al-Dmour, A., Alghazzawi, R., & Alsharairi, M. A. (2021) · Sustainability · doi:10.3390/su132413591 · Cited by 98
Mobile banking: Exploring determinants of its adoption
Changchit, C., Lonkani, R., & Sampet, J. (2017) · Journal of Organizational Computing and Electronic Commerce · doi:10.1080/10919392.2017.1332145 · Cited by 90
“…use of new technology, such as smart-phones or tablet devices, people are influenced to adopt technologies used by their relatives and friends (Bhatiasevi 2015; Malaquias and Hwang 2016b; Kazi and Mannan 2013; PüSchel, Mazzon, and Hernandez 2010; Song 2015; Sripalawat, Thongmak, and Ngramyarn…”
BackgroundResultAlkawsi, G. A., Ali, N. B., & Baashar, Y. M. (2020) · IEEE Access · doi:10.1109/access.2020.2977060 · Cited by 90
Hong, C., Choi, E.-K., & Joung, H.-W. (2022) · Journal of Hospitality and Tourism Management · doi:10.1016/j.jhtm.2022.12.005 · Cited by 104
Investigating privacy concerns and trust in the digital Euro in Germany
Tronnier, F., Harborth, D., & Hamm, P. M. (2022) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2022.101158 · Cited by 92
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“Henceforth, prior studies observed serious reservations while using those fragmented theories because critics demonstrated negative sanctioning on those disjointed theories that failed to portray a holistic view of understanding of individual behavior during adoption and the actual use of technology [48].”
BackgroundKhan, I. U., Hameed, Z., Khan, S. N., Khan, S. U., & Khan, M. T. (2021) · Journal of Internet Commerce · doi:10.1080/15332861.2021.1882749 · Cited by 83
“The result is in line with earlier studies of (Bhatiasevi 2016; Gao and Deng 2012), reflecting that bank customers in both countries adopt the system to enhance their performance.”
BackgroundResultA Comparative Study of Users versus Non-Users’ Behavioral Intention towards M-Banking Apps’ Adoption
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“, [9,10,17,25,40,49,57,58]) aiming at improving the understanding of its acceptance so far, despite the fact that m-banking is still considered to be in the early stages of adoption [57].”
Backgroundde Blanes Sebastián, M. G., Antonovica, A., & Sarmiento Guede, J. R. (2023) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.122235 · Cited by 86
Mobile banking usage and gamification: the moderating effect of generational cohorts
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“A number of studies found that BI positively affects UB (Bhatiasevi, 2016).”
BackgroundHow does culture influence digital banking? A comparative study based on the unified model
Khan, I. U. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101822 · Cited by 66
Gamede, B. T., Ajani, O. A., & Afolabi, O. S. (2021) · International Journal of Higher Education · doi:10.5430/ijhe.v11n1p71 · Cited by 65
“According to Bhatiasevi (2016), the theory provides more clarity for technology acceptance in any study than other similar theories, thus making it significantly appropriate for this study.”
BackgroundInfluentialUsing the UTAUT model to analyze user intention to accept electronic payment systems in Serbia
Tomić, N. Z., Kalinić, Z., & Todorović, V. (2022) · Portuguese Economic Journal · doi:10.1007/s10258-022-00210-5 · Cited by 79
“Financial costs significantly affect use behavior , which contradicts the results obtained in studies by Jeong and Yoon (2013), Bhatiasevi (2015) and Oliveira et al. (2016).”
BackgroundResultMensah, I. K., & Khan, M. K. (2024) · SAGE Open · doi:10.1177/21582440241234230 · Cited by 107
“It rather contradicts the findings that pricing/ financial cost does not drive the intention to use mobile banking (Bhatiasevi, 2016; Malaquias & Silva, 2020).”
The Use of the UTAUT Model in the Adoption of E-Learning Technologies
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“TechnologyAcceptanceModel(TAM)scholarshavecontributedindevelopingtheUnifiedTheory ofAcceptanceandUseofTechnology(UTAUT)(Alalwanetal.,2017;Almuraqab&Jasimuddin, 2016;Bhatiasevi,2016;Dwivedietal.,2019;Almuraqabetal.,2017).”
Islam, M., Mamun, A. A., Afrin, S., Quaosar, G. M. A. A., & Uddin, M. A. (2022) · South Asian Journal of Human Resources Management · doi:10.1177/23220937221122329 · Cited by 74
“However, their empirical findings show that the integration of fragmented theories to generate a holistic view of understanding the intention and actual use of a given technology has been unsuccessful due to the diverse assumptions and beliefs of the disjointed theories (Bhatiasevi, 2016).”
BackgroundM-banking adoption from the developing countries perspective: A mediated model
Abdennebi, H. B. (2023) · Digital Business · doi:10.1016/j.digbus.2023.100065 · Cited by 56
Antecedents of mobile banking: UTAUT model
Savić, J., & Pešterac, A. (2019) · The European Journal of Applied Economics · doi:10.5937/ejae15-19381 · Cited by 53
“Bhatiasevi (2016) came to the same conclusion in his research conducted to identify the factors leading to the adoption of mobile banking in Thailand, as did Albashrawi et al. (2017) by observing a sample of U.S. bank clients.”
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“Although research has shown that FCON affects the use of technologies [40,53,65], a few studies have reported no substantial impact of it [38,39,78].”
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Ali, S., Javed, H. M. U., & Danish, M. (2021) · Environmental Science and Pollution Research · doi:10.1007/s11356-020-12163-3 · Cited by 43
“This study is consistent with previous studies (Bhatiasevi 2016; E. Tan and Lau 2016) as it does not examine the moderation effect of gender, age, experience, and voluntary use that are included in the initially developed model.”
ResultA Cultural Comparative Study of Mobile Banking Adoption Factors
Changchit, C., Klaus, T., Lonkani, R., & Sampet, J. (2019) · Journal of Computer Information Systems · doi:10.1080/08874417.2018.1541724 · Cited by 43
“…35 Safety 14 Effort expectancy 36,37 Security 40 Facilitating condition 2 Self-efficacy 27,33,35 Hedonic motivation 36 Social influence 24,31,37,41 Image 33 Subjective norm 35 Integrity 28 System reliability 40 Knowledge 30 Task technology fit 2,38 Nature of transaction 30 Technology…”
BackgroundIskandar, M., Hartoyo, H., & Hermadi, I. (2020) · International Review of Management and Marketing · doi:10.32479/irmm.9292 · Cited by 43
“Bhatiasevi (2015) added that the perception factor of credibility, and perceived comfort had a significant positive effect on behavioral intention to use mobile banking in Thailand in addition to the factors of effort expectancy, performance expectancy, and social influence.”
BackgroundBehavioral Stimulus for Using Bank Mestika Mobile Banking Services: UTAUT2 Model Perspective
Marpaung, F. K., Dewi, R. S., Grace, E., Sudirman, A., & Sugiat, M. A. (2021) · Golden Ratio of Marketing and Applied Psychology of Business · doi:10.52970/grmapb.v1i2.68 · Cited by 41
“Study (Bhatiasevi, 2015), with the context of the UTAUT model research on the adoption of mobile banking, concluded that performance expectations and behavioral intentions to use mobile banking suggest a positive relationship.”
An Investigation of Indian Generation Z Adoption of the Voice-Based Assistants (VBA)
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“This is supported by several previous studies conducted by Bhatiasevi (2016) and Venkatesh et al. (2003) on the UTAUT model found that performance expectancy, effort expectancy, and social influence are the important determinants of behavioral intention particularly in the case of the e-commerce…”
BackgroundResultPopova, Y., & Zagulova, D. (2022) · Informatics · doi:10.3390/informatics9010027 · Cited by 40
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“(Bhatiasevi, 2015; Gharaibeh et al., 2020; Tan and Leby Lau, 2016) • H3: The relationship between social influence and the behavioral influence to use MART is positive.”
BackgroundWu, G. Q., Yang, J., & Hu, Q. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.928735 · Cited by 46
“Bhatiasevi (2016) established an extended UTAUT model to explain the adoption of mobile banking by including perceived convenience as an influential variable.”
BackgroundHamakhan, Y. T. M. (2020) · Financial Innovation · doi:10.1186/s40854-020-00206-0 · Cited by 45
“…Factors is crated as second-order (higher-order components) contained from four sub-dimension indicators (lower-order components), which are including: performance expectancy, effort expectancy, and Facilitating Conditions (Venkatesh and Zhang 2010; Venkatesh et al. 2008, 2011a, b, 2016).”
BackgroundPersada, S. F., Dalimunte, I., Nadlifatin, R., Ardiansyahmiraja, B., Redi, A. A. N. P., Prasetyo, Y. T., Chin, J., & Lin, S. (2021) · International Journal of Business and Society · doi:10.33736/ijbs.3171.2021 · Cited by 36
“Several other tests, such as model fit (Bhatiasevi, 2016), reliability, and convergent validity, were prepared (Shin, 2009).”
MethodMamadiyarov, Z. T. (2021) · International Conference on Future Networks and Distributed Systems (ICFNDS) · doi:10.1145/3508072.3508119 · Cited by 34
“As a result of the development of information technology and the Internet, banks are changing the way they offer and use modern financial services, especially mobile internet and mobile technology (Bhatiasevi, 2016; Laukkanen, 2016; Oliveira et al., 2014).”
BackgroundUsing artificial intelligence for hiring talents in a moderated mechanism
Islam, M., Rahman, M. M., Taher, M. A., Quaosar, G. M. A. A., & Uddin, M. A. (2024) · Future Business Journal · doi:10.1186/s43093-024-00303-x · Cited by 49
“However, their empirical findings indicate that the integration of fragmented theories to generate a holistic comprehension of the intention and actual use of a given technology has failed due to the diverse assumptions and beliefs of the fragmented theories [42].”
What Explains the Adoption of Mobile Wallets? A Study from Merchants’ Perspectives
Gupta, S., Dhingra, S., Tanwar, S., & Aggarwal, R. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2104408 · Cited by 33
“These theories have been attributed to explain adoption mechanisms in various contexts, such as mobile payment (Bailey et al., 2017; Thakur & Srivastava, 2014), wearable devices (Chang et al., 2016), mobile banking (Bhatiasevi, 2016; Oliveira et al., 2014) and cloud computing (Gangwar et al., 2015).”
BackgroundGupta, S., & Dhingra, S. (2021) · Journal of Financial Services Marketing · doi:10.1057/s41264-021-00101-4 · Cited by 32
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
Nan, D., Kim, Y., Huang, J., Jung, H. S., & Kim, J. H. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.830152 · Cited by 31
“%) of the variance in consumers’ intentions, compared to other UTAUT-based empirical studies (Bhatiasevi, 2016; Madigan et al., 2017; Bawack and Kamdjoug, 2018; Patil et al., 2020; Wang et al., 2020).”
BackgroundResultSaha, P., & Kiran, K. B. (2022) · Journal of Advances in Management Research · doi:10.1108/jamr-01-2022-0022 · Cited by 31
Tronnier, F., & Qiu, W. (2024) · Quantitative Finance and Economics · doi:10.3934/qfe.2024006 · Cited by 33
Islam, M., Tamanna, A. K., & Islam, S. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e35302 · Cited by 58
“However, the findings of these previous studies also revealed that integrating different theories has been unsuccessful due to the diverse assumptions and beliefs of the theories involved [35].”
Eren, B. A. (2023) · Journal of Financial Services Marketing · doi:10.1057/s41264-023-00229-5 · Cited by 43
“It is accepted that PE comprises the expected benefits from the use of a technology, such as rapid response and high efficiency (Bhatiasevi 2015).”
de Moura, A. C., Gosling, M., Christino, J. M. M., & Macedo, S. B. (2017) · Revista Brasileira de Pesquisa em Turismo · doi:10.7784/rbtur.v11i2.1277 · Cited by 29
Taufiq-Hail, G. A.-M., Yusof, S. A. M., Rashid, A., El-Shekeil, I., & Lutfi, A. (2024) · Emerging Science Journal · doi:10.28991/esj-2024-08-03-02 · Cited by 28
“SmartPLS, a nonparametric method, mitigates concerns related to normalcy and data distribution issues [55, 56], is robust against missing data, and accommodates various scales.”
BackgroundMethodMobile payment adoption process: a serial of multiple mediation and moderation analysis
Oentoro, W. (2021) · The Bottom Line Managing Library Finances · doi:10.1108/bl-09-2020-0059 · Cited by 37
Chetioui, Y., Lebdaoui, H., & Hafid, N. (2023) · Journal of Islamic marketing · doi:10.1108/jima-08-2022-0232 · Cited by 40
Bardakçı, S., & Alkan, M. F. (2019) · Education and Information Technologies · doi:10.1007/s10639-019-09904-4 · Cited by 27
“The impact of these two components on behavioral intention was evidenced in a number of studies (i.e. Bhatiasevi 2016; Muraina et al. 2016; Tarhini et al. 2016; Tosuntaş et al. 2015; Wong et al. 2015).”
BackgroundResultInvestigating Mobile Banking Continuance Intention: A Mixed-Methods Approach
Hidayat-ur-Rehman, I., Ahmad, A., Khan, M. N., & Mokhtar, S. A. (2021) · Mobile Information Systems · doi:10.1155/2021/9994990 · Cited by 26
“*e findings confirm that the UTAUTmodel has a substantial predictive power to explain the intention to use Internet/m-banking [45].”
BackgroundLu, M.-P., & Kosim, Z. B. (2022) · Journal of Financial Services Marketing · doi:10.1057/s41264-022-00182-9 · Cited by 31
“The studies that examine adoption of technology for banking services with UTAUT model are well established (Martins et al. 2014; Bhatiasevi 2016; Sarfaraz 2017; Friadi et al. 2018; Savic and Vasic 2019; Singh and Srivastava 2020; Yang et al. 2021; Gupta and Dhingra 2022).”
InfluentialTalent acquisition and technology: A step towards sustainable development
Rehman, S., Ullah, A., Naseem, K., Elahi, A. R., & Erum, H. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.979991 · Cited by 26
“The concept of effort expectancy can be defined as the degree to observe an association between conveniences of the utilization of the system (Bhatiasevi, 2016).”
BackgroundWhy do people use fitness tracking devices in Thailand? An integrated model approach
Naglis, M., & Bhatiasevi, V. (2019) · Technology in Society · doi:10.1016/j.techsoc.2019.101146 · Cited by 25
User Perception of Mobile Banking Adoption: An Integrated Ttf-utaut Model
Ahmed, Z., Kader, M. A., Rashid, H. U., & Nurunnabi, M. (2017) · RePEc: Research Papers in Economics · Cited by 24
Predictors of behavioral intention to adopt e-AgriFinance app among the farmers in Sarawak, Malaysia
Omar, Q., Yap, C. S., Ho, P. L., & Keling, W. (2021) · British Food Journal · doi:10.1108/bfj-04-2021-0449 · Cited by 24
A posteriori segmentation of elderly internet users: applying PLS-POS
Arenas-Gaitán, J., Ramos, Á. F. V., & Peral, B. P. (2019) · Marketing Intelligence & Planning · doi:10.1108/mip-01-2019-0057 · Cited by 24
Bonang, D., Ismail, S. B., & Sukmana, R. (2024) · ISRA International Journal of Islamic Finance · doi:10.55188/ijif.v16is1.586 · Cited by 23
“These include mobile e-banking (Bhatiasevi, 2016; Abbas et al. , 2018), shopping behaviour (Celik, 2016; Soh et al. , 2020), hospitality and tourism (Gupta et al. , 2018; Kamboj & Joshi, 2021), e-learning (Rahi et al. , 2019; Gupta et al. , 2019; Abbad, 2021; Khan et al. , 2022), mobile commerce…”
ResultA meta-analysis of satisfaction in mobile banking: a contextual examination
Kumar, P., Chauhan, S., Kumar, S., & Gupta, P. (2023) · International Journal of Bank Marketing · doi:10.1108/ijbm-04-2023-0236 · Cited by 26
The Development of the Hospitality Sector Facing the Digital Challenge
Perinotto, A. R. C., de Araújo, S. M., Borges, V. D. P. C., Soares, J. R. R., Cardoso, L., & Santos, L. L. (2022) · Behavioral Sciences · doi:10.3390/bs12060192 · Cited by 22
Factors That Influence English Teachers’ Acceptance and Use of E-Learning Technologies
Alanezi, Y. H., & Alajmi, S. M. (2021) · International Education Studies · doi:10.5539/ies.v14n9p15 · Cited by 25
“FC is also combined from earlier models, such as compatibility, facilitating conditions, and perceived behavioural control (Bhatiasevi, 2015).”
MethodConsumers' Continuance Intention Use of Mobile Banking in Jakarta: Extending UTAUT Models with Trust
Saparudin, M., Rahayu, A., Hurriyati, R., Sultan, M. A., & Ramdan, A. M. (2020) · International Conference on Information Management and Technology (ICIMTech) · doi:10.1109/icimtech50083.2020.9211188 · Cited by 21
“This study supported prior researches [11], [17], [37], [38].”
ResultCardless Banking System in Malaysia: An Extended TAM
Ali, Q., Parveen, S., Yaacob, H. B., & Zaini, Z. (2021) · Risks · doi:10.3390/risks9020041 · Cited by 21
The Antecedents of Mobile Banking Adoption among Senior Citizens in Malaysia
Touchaei, S. A., & Hashim, N. H. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2161236 · Cited by 21
“Several MB adoption studies confirmed the significant contribution of EE (e.g., Alalwan et al., 2018; Bhatiasevi, 2016; Farzin et al., 2021; Purwanto & Loisa, 2020; Samsudeen et al., 2022; E. Tan et al., 2016), or its similar factors such as perceive ease of use from TAM model (e.g., Alalwan et…”
BackgroundResultInfluentialSusanto, S. A., Manek, M. V., Setiawan, R. A., & Mustikasari, F. (2023) · Devotion Journal of Research and Community Service · doi:10.59188/devotion.v4i8.544 · Cited by 21
“The theoretical foundation for understanding this relationship is based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, which integrates social cognitive theory and information technology acceptance (Bhatiasevi, 2016).”
BackgroundImplementation and evaluation of cloud-based e-learning in agricultural course
Chang, J.-H., Chiu, P., & Lai, C.-F. (2020) · Interactive Learning Environments · doi:10.1080/10494820.2020.1815217 · Cited by 21
“This indicates that students ’ use behavior toward the Platform will be decision-driven by important others and that their superiors have a signi fi cant in fl uence (Bhatiasevi, 2016; El-Masri & Tarhini, 2017).”
BackgroundPerception of Financial Auditor on Usage of Computer Assisted Audit Techniques
Handoko, B. L., Ariyanto, S., & Warganegara, D. L. (2018) · International Conference on Computational Intelligence and Applications (ICCIA) · doi:10.1109/iccia.2018.00052 · Cited by 23
“This result is support previous research by [21]; [22]; [23], but do not support research conducted by [7]; [19]; [20].”
ResultFactors Influencing Smartphone Adoption: A Study in the Indian Bottom of the Pyramid Context
Baishya, K., & Samalia, H. V. (2019) · Global Business Review · doi:10.1177/0972150919856961 · Cited by 20
“This result is consistent with existing literature on a variety of technologies (Bhatiasevi, 2016; Casey & Wilson-Evered, 2012; Venkatesh et al., 2003).”
BackgroundResultDeterminants of Mobile Banking Adoption
Changchit, C., Lonkani, R., & Sampet, J. (2018) · Journal of Global Information Management · doi:10.4018/jgim.2018100109 · Cited by 19
Determinants of intention to use Islamic mobile banking: Evidence from millennial generation
Kholid, M. N. (2019) · Jurnal Ekonomi & Keuangan Islam · doi:10.20885/jeki.vol5.iss2.art2 · Cited by 18
“This result is in line with previous research (Baptista & Oliveira, 2015; Bhatiasevi, 2016; Evon, 2016; Raza et al., 2019).”
BackgroundResultInfluentialExamining the Contributing Factors for Cloud Computing Adoption in a Developing Country
Yaokumah, W., & Amponsah, R. A. (2017) · International Journal of Enterprise Information Systems · doi:10.4018/ijeis.2017010102 · Cited by 21
Antecedents of user satisfaction and trust in digital banking: an examination of the ISSM factors
Chang, W., Chan, C. L., & Hsieh, Y. (2025) · International Journal of Bank Marketing · doi:10.1108/ijbm-04-2024-0232 · Cited by 17
Social Stratification, Self-Image Congruence, and Mobile Banking in Colombian Cities
Mesías, J. F. T., van Klyton, A. C., & Zúñiga-Collazos, A. (2021) · Journal of International Consumer Marketing · doi:10.1080/08961530.2021.1955426 · Cited by 18
“This relationship was also evidenced for mobile banking (Bhatiasevi 2016; Farah, Hasni, and Abbas 2018; Giovanis et al. 2019; Mutahar et al., 2018).”
BackgroundAdoption of electronic commerce by individuals in Bangladesh
Azam, M. S., Morsalin, M., Rakib, M. R. H. K., & Pramanik, S. A. K. (2021) · Information Development · doi:10.1177/02666669211052523 · Cited by 23
“Most empirical studies in developing countries also support the assumption that cognitive costs have a negative impact on users ’ intentions to use e-commerce services (Bhatiasevi, 2016; Boadi et al., 2007).”
BackgroundMethodFarhat, R., Yang, Q., Ahmed, M. A. O., & Hasan, G. (2025) · Sustainability · doi:10.3390/su17041431 · Cited by 17
Papathomas, A., Konteos, G., & Avlogiaris, G. (2025) · Information · doi:10.3390/info16020137 · Cited by 35
Anjani, W., & Mukhlis, I. (2022) · Jurnal Ekonomi Akuntansi dan Manajemen · doi:10.19184/jeam.v21i1.30570 · Cited by 16
“Penelitian Bhatiasevi (2016) dan Rahi et al. (2019) menjelaskan bahwa pengaruh sosial berhubungan secara langsung dengan minat seseorang dalam mengadopsi layanan mbanking maupun internet banking.”
BackgroundSouth African rural students’ adoption and use of learning management systems
Afolabi, O. S., & Ajani, O. A. (2023) · International Journal of Research in Business and Social Science (2147-4478) · doi:10.20525/ijrbs.v12i4.2521 · Cited by 16
“Bhatiasevi (2016) posits that the theory clarifies technology adoption better than other similar theories, making it suitable for this investigation.”
BackgroundKim, J.-H., & Kang, E. (2023) · Sustainability · doi:10.3390/su15108309 · Cited by 27
Behavioral routes to loyalty across gender on m-banking usage
Windasari, N. A., & Albashrawi, M. A. (2020) · Review of International Business and Strategy · doi:10.1108/ribs-06-2020-0073 · Cited by 16
Continuance Intention of m-Banking Adoption: The Dynamics of UTAUT3, Trust and Attitudes
Laradi, S., Elfekair, A., Rehman, H. M., Hanna, D. B., & Alrawad, M. (2025) · FIIB Business Review · doi:10.1177/23197145251358049 · Cited by 14
Metadata
- Authors
- Bhatiasevi, V.
- Affiliations
- Mahidol University (TH)
- Corresponding author
- Bhatiasevi, Veera
- ORCID
- Bhatiasevi, Veera
- Venue
- Information Development
- Publisher
- SAGE Publications
- Published
- 2016-07-09
- Volume
- 32
- Issue
- 4
- Pages
- 799-814
- ISSN
- 0266-6669 (ISSN-L)
- 1741-6469
- OpenAlex
- W2159369755
- Cited by
- 237
- References
- 58
- Citations by year
- 2026: 5 · 2025: 22 · 2024: 26 · 2023: 36 · 2022: 37 · 2021: 43 · 2020: 23 · 2019: 26 · 2018: 9 · 2017: 6 · 2016: 2
- FWCI
- 11.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Development (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
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Keywords
- mobile banking, technology adoption, UTAUT model, perceived credibility, perceived convenience, perceived cost, performance expectancy, effort expectancy, social influence, behavioral intention
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