DO WE STILL NEED HUMAN IN DIGITAL BANKING? REDESIGN OF ARTIFICIALLY INTELLIGENT DEVICE USE ACCEPTANCE (AIDUA) MODEL MODERATED BY GENDER DIFFERENCES
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Candra Kartika(1)
Faculty of Economics and Business, Universitas STIKUBANK
-
Ignatius Hari Santoso(2*)
Faculty of Economics and Business, Universitas STIKUBANK
(*) Corresponding Author
Keywords:
Social Influence, Performance Expectancy, Perceived Intrusiveness, Hedonic Motivation, Willingness to Use AI Device, Digital Banking
Abstract
This study modifies and tests the Artificially Intelligent Device Use Acceptability (AIDUA) model in the Indonesian setting to assess consumer acceptability of Artificially Intelligent Devices (AIDs) in digital banking services. The study specifically examines how performance expectancy, hedonic incentive, social influence, and perceived intrusiveness influence users' desire to use AIDs. It also looks at how gender regulates this willingness. 96 legitimate respondents with prior experience with AI-based digital banking services provided data for the study, which used a quantitative explanatory research approach. Both measurement and structural models were evaluated through the use of Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0. The findings indicate that hedonic motivation, social influence, and perceived intrusiveness significantly affect willingness to use AIDs, while performance expectancy does not. Additionally, gender does not moderate the relationship between the cognitive constructs and behavioral intention. The model explains 94.8% of the variance in users' willingness, suggesting strong explanatory power. The results suggest that, from a practical perspective, financial institutions should place more emphasis on AI interfaces that are emotionally compelling, socially acceptable, and privacy-preserving than just performance advantages. This study contributes to our understanding of AI's adoption in banking and offers valuable insights for developing digital banking systems that are inclusive and trustworthy.
Keywords: Social Influence; Performance Expectancy; Perceived Intrusiveness; Hedonic Motivation; Willingness to use AI Device; Digital Banking
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References
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Belanche, D., Casalo, L.V., Flavian, C., & Schepers, J. (2022). Service robots or human staff? Understanding the impact of anthropomorphism and other drivers on customer acceptance of AI-based technologies in services. Journal of Service Management, 33(2), 317-336.
Berger, E.S., Von-Briel, F., Davidson, P., & Kuckertz, A. (2021). Digital or not- the future of entrepreneurship and innovation. Journal of Business Research, 125, 436-442.
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Castelo, N., Bos, M.W., & Lehmann, D.R. (2019). Task-dependent algorithm aversion. Journal of Marketing Research, 56(5), 809-825.
Chatterjee, S., Riana, N.P., Tamilmani, K., & Sharma, A. (2021). The adoption of artificial intelligence in the banking sector: a thematic analysis and future research agenda. Journal of Enterprise Information Management, 34(6), 1649-1675.
Chi, O.H., Denton, G., Gursoy, D. (2020). Artificially intelligent device use in service delivery: a systematic review, synthesis, and research agenda. Journal of Hospitality Marketing and Management, 29(7), 757-786.
Cimpeanu, I.A., Dragomir, D.A., Zota, R.D. (2023). Banking chatbots: How artificial intelligence help the banks. Proceeding of the International Conference on Business Excellence, 17(1), 1716-1727.
Ding, S., Lin, J., & Zhang, Z. (2020). Influences of reference group on users’ purchase intention in network communities: from the Perspective of trial purchase and upgrade purchase. Sustainability, 12(24), 10619,
https://doi.org/10.3390/su122410619
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Festinger, L. (1962). A theory of cognitive dissonance. Stanford University Press, Stanford, C.A.
Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50
Ghazwani, S., van Esch, P., Cui, Y., & Gala, P. (2022). Artificial intelligence, financial anxiety and cashier-less checkouts: a Saudi Arabian perspective. International Journal of Bank Marketing, 40(6), 1200-1216.
Goudey, A., & Bonnin, G. (2016). Must smart objects look human? Study of the impact of anthroporphism on the acceptance of companion robots. Recherche at Application en Marketing, 31(2), 2-20.
Gursoy, D., Chi, O.H., Lu, L., & Nunkoo, R. (2019). Consumer acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169.
Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2019). When to use and how to report the resut of PLS-SEM. European Business Review, 31(1), 2-24, https://doi.org/10.1108/EBR-11-2018-0203
Hair, J.F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V.G. (2014). Partial least square structural equation modeling (PLS-SEM): an emerging tool in business research. European Business Review, 26(2), 106-121, https://doi.org/10.1108/EBR-10-2013-0128
Hair, J.F., Hult, G.T.M., Ringle, C.M., & Sarstedt, M. (2022). A Primer on partial least square structural equation modeling (PLS-SEM), 3rd edition, SAGE Publication.
Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., & Ray, S. (2021). Partial least square structural equation modeling (PLS-SEM) using R: a Workbook. Springer Internationa Publishing, https://doi.org/10.1007/978-3-030-80519-7
Hameed, S., & Nigam, A. (2022). Exploring India’s generation z perspective on enabled internet banking service. Foresight, 25(2), 287-302.
Hamzah, M.I., Maelah, R., & Ismail, N. (2022). Emotional engagement and the adoption of AI-based chatbots in Islamic banking. Journal of Islamic Marketing, 13(3), 637-659.
Hanlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: on the past, present and future of artificial intelligence. California Management Review, 61(4), 5-14.
Hermann, H., & Masawi, B. (2022). Three and a half decades of artificial intelligence in banking, financial service and insurance: a systematic evolutionary review. Strategic Change, 31(6), 549-569.
Huang, M.H., & Rust, R.T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
Jung, Y., Mende, M., Haubl, G. (2021). Conversational robo advisors as surrogates of trust: Onboarding experience, firm perception, and consumer financial decision making. Journal of the Academy of Marketing Science, 49, 659-676.
Kasula, V.K. (2023). AI driven banking: a Review on transforming the financial sector. World Journal of Advanced Research and Reviews, 20(2), 1461-1465.
Kelly, S., Kaye, S.A., Oviedo-Tespalacious, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925, 1-33.
Laukanen, T., & Kyriakos, M. (2023). Cross-cultural consumer trust in digital banking: a comparative analysis. International Journal of bank Marketing, 41(2), 233-251
Lazarus, R.S. (1991). Cognition and motivation in emotion. American Psychologist, 46(4), 352-367.
Liebana-Cabanillas, F., Molinillo, S., & Garcia, F.J. (2023). Exploring privacy and trust in AI-enabled banking platforms. Technological Forecasting and Social Change, 187, 122227.
Liu, X., Marchewka, J.T., Lu, J., & Yu, C.S. (2020). Understanding the influence of social norms and reference groups on innovation adoption: an empirical study of mobile payment users. International Journal of Innovation Management, 52, 102040, https://doi.org/10.1016/j.ijinfomgt.2020.102040
Lin, H., Chi, O.H., & Gursoy, D. (2020). Antecedents of customer acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing and Management, 29(5), 530-549.
Lu, L., Cai, R., & Gursoy, D. (2020). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 87, 102378, https://doi.org/10.1016/j.ijhm.2020.102378.
Marakarkandy, B., Yajnik, N., & Dasgupta, C. (2017). Enabling digital banking adoption: an empirical examination of Indian consumers. Technological Forecasting and Social Change, 123, 191-201.
Milojevic, N., & Redzepagic, S. (2021). Prospects of artificial intelligence and machine learning application in banking risk management. Journal of Central Banking Theory and Practice, 10(3), 41-57.
Nguyen, T.H., Ngo, L.V., & Northey, G. (2023). Digital transformation and generational differences in banking : is the gap closing? Journal of Retailing and Consumer Services, 71, 103151.
Northey, G., Hunter, V., Mulcahy, R., Choong, K., & Mehmet, M. (2022). Man vs machine: how artificial intelligence in banking influences consumer beliefs in financial advice. International Journal of Bank Marketing, 40(6), 1182-1199.
Oliveira T., Thomas, M., Baptista, G., Campos, F. (2016). Mobile payment: understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior,61, 404-414.
Ologun, V.O,, Olugbade, A., Azuikpe, P.F., Adegbite, M.A., Lawal, O.A., & John, S. (2025). Smart tech, scared users: a Behavioral analysis of AI powered solutions for cyber threat induced customer complaint in low income countries. iRASD Journal of Management, 7(1), 10-26.
Pande, S., & Gupta, K.P. (2022). Indian customers acceptance of service robots in restaurant service. Behavior and Information Technology, 42(12), 1946-1967.
Pedrosa, L. (2025). The role of artificial intelligence in mobile banking: Decoding portugese consumer perceptions and intentions to engage. Future Business Journal, 11, 125, https://doi.org/10.1186/s43093-025-00510-0
Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226.
Pitardi, V., Marriot, H.R. (2021). Alexa, she’s not human but…unveiling the drivers of consumer trust in voice-based artificial intelligence. Psychology and Marketing, 38(4), 626-642.
Prebensen, N.K., & Rosengren, S. (2016). Experience value as a function of hedonic and utilitarian dominant services. International Journal of Contemporary Hospitality Management, 28(1), 113-135.
Prensky, M. (2015). Digital natives, digital imigrants: do they really exist? Educational Technology, 45(4), 1-8.
Rahi, S., Ghani, M.A., Alnaser, F.M., & Ngah, A.H. (2021). Adoption of digital banking: extending the role of
technology acceptance model (TAM) with e-customer service and customer satisfaction. Journal of Open Innovation : Technology Market and Complexity,7(1), 1-24.
Roy, P., Ramaprasad, B.S., Chakraborty, M., Prabhu, N., & Rao, S. (2020). Customer acceptance of use of artificial intelligence in hospitality services: an Indian hospitality sector perspective. Global Business Review, 25(3), 1-20.
Santoso, I.H., Nurcholis, L., & Kartika, E. (2020). Intention to use mobile banking application: gender based. Jurnal Penelitian Ekonomi dan Bisnis, 5(2), 203-211.
Setiawan, B., Phan, T.D., Medina, J., Wieriks, M., Nathan, R.J., & Fekete-Farkas, M. (2023). Quest for financial inclusion via digital financial services (fintech) during COVID 19 pandemic: Case study of women in Indonesia. Journal of Financial Service Marketing, 29, 459-473, https://doi.org/10.1057/s41264-023-00217-9
Setiawan, B. (2024). A multigroup analysis of gender in adopting fintech services in Indonesia. Enrichment: Journal of Management, 14(2), 238-248, https://doi.org/10.35335/enrichment.v14i2.1891
Shin, D.H., & Park, Y.J. (2017). Understanding the perceived privacy risk of using e-government service. Government Information Quarterly, 34(3), 389-399.
Sohn, K., & Kwon, O. (2020). Technology acceptance theories and factors influencing artificial intelligence-based intelligent product. Telematics and Informatics, 47, 101324, 1-14.
Tariq, M., Maryam, S.Z., & Shaheen, W.A. (2024). Cognitive factors and actual usage of fintech innovation: Exploring the UTAUT framework for digital banking. Heliyon, 10(4), e35582, https://doi.org/10.1016/j.heliyon.2024.e35582
Van Doom, J., Mende, M., Noble, S.M., Hulland, J., Ostrom, A.L., Grewal, D., & Petersen, J.A. (2022). Artificial intelligence in marketing interaction: Bridging the human-AI gap in affective and social customer experience. Journal of the Academy of Marketing Science, 50(1), 14-35, https://doi.org/10.1007/s11747-022-00892-5
Vitezic, V., & Peric, M. (2021). Artificial intelligence acceptance in services: connecting with generation z. Service Industries Journal, 41, 926-946.
Zhang, L., Pentina, I., & Fan, Y. (2021). Who do you chose? Comparing perception of human vs robo-advisor in the context of financial service. Journal of Service Marketing, 35(5), 634-646.
Zhou, Z. (2024). The social impact of the application of artificial intelligence in fintech: Consumer behavior and trust building. Business Administration and Management, 7(1), 1-15, https://doi.org/10.59429/bam.v7i1.9575
Zhu, D.H., & Chang, Y.P. (2020). Robot with humanoid hands cooks food better: effect of robotic chef anthropomorphism on food quality prediction. International Journal of Contemporary Hospitality Management, 32(3), 1367-1383.
Acikgoz, F., & Vega, R.P. (2022). The role of privacy cynicism in consumer habits with voice assitants: a technology acceptance model persective. International Journal of Human-Computer Interaction, 38(12), 1138-1152.
Alalwan, A.A., Dwivedi, Y.K., & Williams, M.D. (2017). Customer intention and adoption of telebanking in Jordan. Information System Management, 34(2), 85-100.
Alam, Y., Azizah, S.N., & Caroline, C. (2025). Digital transformation in banking management: Optimizing operational efficiency and enahncing customer experience. International Journal of Management Science and Information Technology, 5(1), 46-55.
Al-saedi, K., Al-Emran, M., Ramayah, T., & Dwivedi, Y.K. (2021). Towards understanding the determinants of employee adoption of AI-based system in the workplace. Information Technology & People, 35(4), 1603-1628.
Bagana, B.D., Irsad, M., & Santoso, I.H. (2021). Artificial intelligence as a human substitution? consumer’s perception of the conversational user interface in banking industry based on UTAUT concept. Review of Management and Entrepreneurship, 5(1), 33-44.
Belanche, D., Casalo, L.V., Flavian, C., & Schepers, J. (2022). Service robots or human staff? Understanding the impact of anthropomorphism and other drivers on customer acceptance of AI-based technologies in services. Journal of Service Management, 33(2), 317-336.
Berger, E.S., Von-Briel, F., Davidson, P., & Kuckertz, A. (2021). Digital or not- the future of entrepreneurship and innovation. Journal of Business Research, 125, 436-442.
Boustani, N.M. (2021). Artificial intelligence impact on banks clients and employee in an Asian developing country. Journal of Asia Business Studies, 16(2), 267-278.
Castelo, N., Bos, M.W., & Lehmann, D.R. (2019). Task-dependent algorithm aversion. Journal of Marketing Research, 56(5), 809-825.
Chatterjee, S., Riana, N.P., Tamilmani, K., & Sharma, A. (2021). The adoption of artificial intelligence in the banking sector: a thematic analysis and future research agenda. Journal of Enterprise Information Management, 34(6), 1649-1675.
Chi, O.H., Denton, G., Gursoy, D. (2020). Artificially intelligent device use in service delivery: a systematic review, synthesis, and research agenda. Journal of Hospitality Marketing and Management, 29(7), 757-786.
Cimpeanu, I.A., Dragomir, D.A., Zota, R.D. (2023). Banking chatbots: How artificial intelligence help the banks. Proceeding of the International Conference on Business Excellence, 17(1), 1716-1727.
Ding, S., Lin, J., & Zhang, Z. (2020). Influences of reference group on users’ purchase intention in network communities: from the Perspective of trial purchase and upgrade purchase. Sustainability, 12(24), 10619,
https://doi.org/10.3390/su122410619
El-Shyhy, D., Abdelraouf, M., Hegazy, M., & Hasan, N. (2024). The influence of AI chatbots in fintech services on customer loyalty within the banking industry. Future of Business Administration, 3(1), 16-28, https://doi.org/10.33422/fba.v3i1.644
Festinger, L. (1962). A theory of cognitive dissonance. Stanford University Press, Stanford, C.A.
Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50
Ghazwani, S., van Esch, P., Cui, Y., & Gala, P. (2022). Artificial intelligence, financial anxiety and cashier-less checkouts: a Saudi Arabian perspective. International Journal of Bank Marketing, 40(6), 1200-1216.
Goudey, A., & Bonnin, G. (2016). Must smart objects look human? Study of the impact of anthroporphism on the acceptance of companion robots. Recherche at Application en Marketing, 31(2), 2-20.
Gursoy, D., Chi, O.H., Lu, L., & Nunkoo, R. (2019). Consumer acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169.
Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2019). When to use and how to report the resut of PLS-SEM. European Business Review, 31(1), 2-24, https://doi.org/10.1108/EBR-11-2018-0203
Hair, J.F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V.G. (2014). Partial least square structural equation modeling (PLS-SEM): an emerging tool in business research. European Business Review, 26(2), 106-121, https://doi.org/10.1108/EBR-10-2013-0128
Hair, J.F., Hult, G.T.M., Ringle, C.M., & Sarstedt, M. (2022). A Primer on partial least square structural equation modeling (PLS-SEM), 3rd edition, SAGE Publication.
Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P., & Ray, S. (2021). Partial least square structural equation modeling (PLS-SEM) using R: a Workbook. Springer Internationa Publishing, https://doi.org/10.1007/978-3-030-80519-7
Hameed, S., & Nigam, A. (2022). Exploring India’s generation z perspective on enabled internet banking service. Foresight, 25(2), 287-302.
Hamzah, M.I., Maelah, R., & Ismail, N. (2022). Emotional engagement and the adoption of AI-based chatbots in Islamic banking. Journal of Islamic Marketing, 13(3), 637-659.
Hanlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: on the past, present and future of artificial intelligence. California Management Review, 61(4), 5-14.
Hermann, H., & Masawi, B. (2022). Three and a half decades of artificial intelligence in banking, financial service and insurance: a systematic evolutionary review. Strategic Change, 31(6), 549-569.
Huang, M.H., & Rust, R.T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
Jung, Y., Mende, M., Haubl, G. (2021). Conversational robo advisors as surrogates of trust: Onboarding experience, firm perception, and consumer financial decision making. Journal of the Academy of Marketing Science, 49, 659-676.
Kasula, V.K. (2023). AI driven banking: a Review on transforming the financial sector. World Journal of Advanced Research and Reviews, 20(2), 1461-1465.
Kelly, S., Kaye, S.A., Oviedo-Tespalacious, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925, 1-33.
Laukanen, T., & Kyriakos, M. (2023). Cross-cultural consumer trust in digital banking: a comparative analysis. International Journal of bank Marketing, 41(2), 233-251
Lazarus, R.S. (1991). Cognition and motivation in emotion. American Psychologist, 46(4), 352-367.
Liebana-Cabanillas, F., Molinillo, S., & Garcia, F.J. (2023). Exploring privacy and trust in AI-enabled banking platforms. Technological Forecasting and Social Change, 187, 122227.
Liu, X., Marchewka, J.T., Lu, J., & Yu, C.S. (2020). Understanding the influence of social norms and reference groups on innovation adoption: an empirical study of mobile payment users. International Journal of Innovation Management, 52, 102040, https://doi.org/10.1016/j.ijinfomgt.2020.102040
Lin, H., Chi, O.H., & Gursoy, D. (2020). Antecedents of customer acceptance of artificially intelligent robotic device use in hospitality services. Journal of Hospitality Marketing and Management, 29(5), 530-549.
Lu, L., Cai, R., & Gursoy, D. (2020). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 87, 102378, https://doi.org/10.1016/j.ijhm.2020.102378.
Marakarkandy, B., Yajnik, N., & Dasgupta, C. (2017). Enabling digital banking adoption: an empirical examination of Indian consumers. Technological Forecasting and Social Change, 123, 191-201.
Milojevic, N., & Redzepagic, S. (2021). Prospects of artificial intelligence and machine learning application in banking risk management. Journal of Central Banking Theory and Practice, 10(3), 41-57.
Nguyen, T.H., Ngo, L.V., & Northey, G. (2023). Digital transformation and generational differences in banking : is the gap closing? Journal of Retailing and Consumer Services, 71, 103151.
Northey, G., Hunter, V., Mulcahy, R., Choong, K., & Mehmet, M. (2022). Man vs machine: how artificial intelligence in banking influences consumer beliefs in financial advice. International Journal of Bank Marketing, 40(6), 1182-1199.
Oliveira T., Thomas, M., Baptista, G., Campos, F. (2016). Mobile payment: understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior,61, 404-414.
Ologun, V.O,, Olugbade, A., Azuikpe, P.F., Adegbite, M.A., Lawal, O.A., & John, S. (2025). Smart tech, scared users: a Behavioral analysis of AI powered solutions for cyber threat induced customer complaint in low income countries. iRASD Journal of Management, 7(1), 10-26.
Pande, S., & Gupta, K.P. (2022). Indian customers acceptance of service robots in restaurant service. Behavior and Information Technology, 42(12), 1946-1967.
Pedrosa, L. (2025). The role of artificial intelligence in mobile banking: Decoding portugese consumer perceptions and intentions to engage. Future Business Journal, 11, 125, https://doi.org/10.1186/s43093-025-00510-0
Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199-3226.
Pitardi, V., Marriot, H.R. (2021). Alexa, she’s not human but…unveiling the drivers of consumer trust in voice-based artificial intelligence. Psychology and Marketing, 38(4), 626-642.
Prebensen, N.K., & Rosengren, S. (2016). Experience value as a function of hedonic and utilitarian dominant services. International Journal of Contemporary Hospitality Management, 28(1), 113-135.
Prensky, M. (2015). Digital natives, digital imigrants: do they really exist? Educational Technology, 45(4), 1-8.
Rahi, S., Ghani, M.A., Alnaser, F.M., & Ngah, A.H. (2021). Adoption of digital banking: extending the role of
technology acceptance model (TAM) with e-customer service and customer satisfaction. Journal of Open Innovation : Technology Market and Complexity,7(1), 1-24.
Roy, P., Ramaprasad, B.S., Chakraborty, M., Prabhu, N., & Rao, S. (2020). Customer acceptance of use of artificial intelligence in hospitality services: an Indian hospitality sector perspective. Global Business Review, 25(3), 1-20.
Santoso, I.H., Nurcholis, L., & Kartika, E. (2020). Intention to use mobile banking application: gender based. Jurnal Penelitian Ekonomi dan Bisnis, 5(2), 203-211.
Setiawan, B., Phan, T.D., Medina, J., Wieriks, M., Nathan, R.J., & Fekete-Farkas, M. (2023). Quest for financial inclusion via digital financial services (fintech) during COVID 19 pandemic: Case study of women in Indonesia. Journal of Financial Service Marketing, 29, 459-473, https://doi.org/10.1057/s41264-023-00217-9
Setiawan, B. (2024). A multigroup analysis of gender in adopting fintech services in Indonesia. Enrichment: Journal of Management, 14(2), 238-248, https://doi.org/10.35335/enrichment.v14i2.1891
Shin, D.H., & Park, Y.J. (2017). Understanding the perceived privacy risk of using e-government service. Government Information Quarterly, 34(3), 389-399.
Sohn, K., & Kwon, O. (2020). Technology acceptance theories and factors influencing artificial intelligence-based intelligent product. Telematics and Informatics, 47, 101324, 1-14.
Tariq, M., Maryam, S.Z., & Shaheen, W.A. (2024). Cognitive factors and actual usage of fintech innovation: Exploring the UTAUT framework for digital banking. Heliyon, 10(4), e35582, https://doi.org/10.1016/j.heliyon.2024.e35582
Van Doom, J., Mende, M., Noble, S.M., Hulland, J., Ostrom, A.L., Grewal, D., & Petersen, J.A. (2022). Artificial intelligence in marketing interaction: Bridging the human-AI gap in affective and social customer experience. Journal of the Academy of Marketing Science, 50(1), 14-35, https://doi.org/10.1007/s11747-022-00892-5
Vitezic, V., & Peric, M. (2021). Artificial intelligence acceptance in services: connecting with generation z. Service Industries Journal, 41, 926-946.
Zhang, L., Pentina, I., & Fan, Y. (2021). Who do you chose? Comparing perception of human vs robo-advisor in the context of financial service. Journal of Service Marketing, 35(5), 634-646.
Zhou, Z. (2024). The social impact of the application of artificial intelligence in fintech: Consumer behavior and trust building. Business Administration and Management, 7(1), 1-15, https://doi.org/10.59429/bam.v7i1.9575
Zhu, D.H., & Chang, Y.P. (2020). Robot with humanoid hands cooks food better: effect of robotic chef anthropomorphism on food quality prediction. International Journal of Contemporary Hospitality Management, 32(3), 1367-1383.
Published
2025-11-05
How to Cite
Kartika, C., & Santoso, I. (2025). DO WE STILL NEED HUMAN IN DIGITAL BANKING? REDESIGN OF ARTIFICIALLY INTELLIGENT DEVICE USE ACCEPTANCE (AIDUA) MODEL MODERATED BY GENDER DIFFERENCES. Journal of Management : Small and Medium Enterprises (SMEs), 18(3), 1865-1881. https://doi.org/10.35508/jom.v18i3.22630
Section
Articles
