A Comparative Analysis of UTAUT and UTAUT 2 in M-Commerce and M-Banking

Tri Wulandari  Ginting; Joy Nasten Sinaga

doi:10.29407/intensif.v9i2.24179

Authors

Tri Wulandari Ginting Universitas Mikroskil https://orcid.org/0009-0009-2222-8210
Joy Nasten Sinaga Universitas Mikroskil https://orcid.org/0009-0006-4581-8190

DOI:

https://doi.org/10.29407/intensif.v9i2.24179

Keywords:

UTAUT, M-Banking, M-Commerce

Abstract

Background: The debate over the superiority between UTAUT and UTAUT 2 has driven the development of UTAUT 3. However, this latest model is still not the best solution, as several variables remain less influential. Objective: This study aims to determine which UTAUT model is superior in technology acceptance, particularly for m-commerce and m-banking. Methods: Multiple linear regression was used to determine the direction and magnitude of the influence of independent variables on the dependent variable, analyzing key factors affecting the adoption of mobile banking and m-commerce by comparing UTAUT and UTAUT 2. Results: In m-commerce, UTAUT highlights behavioral intention and facilitating conditions, while UTAUT 2 adds habit and price value as key influencing factors. Conclusion: For m-banking, both models are equally effective, but UTAUT 2 is superior due to the strong influence of habit. In m-commerce, UTAUT 2 is also preferable, as price value significantly affects behavioral intention.

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Author Biographies

Tri Wulandari Ginting, Universitas Mikroskil

Sistem Informasi, Universitas Mikroskil
Joy Nasten Sinaga, Universitas Mikroskil

Sistem Informasi, Universitas Mikroskil

References

[1] S. Zahra, Shaker A.; Liu, Wan; Si, “How digital technology promotes entrepreneurship in ecosystems,” Technovation, vol. 119, 2023, doi: https://doi.org/10.1016/j.technovation.2022.102457.

[2] E. O. Bereczki and A. Kárpáti, “Technology-enhanced creativity: A multiple case study of digital technology-integration expert teachers’ beliefs and practices,” Think. Ski. Creat., vol. 39, no. January, 2021, doi: 10.1016/j.tsc.2021.100791.

[3] A. Q. Salimon, Maruf Gbadebo; kareem, Olanrewaju; Mokhtar, Sany Sanuri Mohd; Aliyu Olayemi Abdullateef; Bamgbade, Jibril Adewale; Adeleke, “Malaysian SMEs m-commerce adoption: TAM 3, UTAUT 2 and TOE approach,” J. Sci. Technol. Policy Manag., vol. 14, no. 1, pp. 98–126, 2021, doi: https://doi.org/10.1108/JSTPM-06-2019-0060.

[4] J.-H. Omar, Suha; Mohsen, Kholoud; Tsimonis Georgios; Oozeerally Adam; Hsu, “M-commerce: The nexus between mobile shopping service quality and loyalty,” J. Retail. Consum. Serv., vol. 60, 2021, doi: https://doi.org/10.1016/j.jretconser.2021.102468.

[5] F. I. Purnomo, Agung; Susanti, Triana; Anisah, Hastin Umi; sari, Anita Kartika; Maulana, “Value of M-Commerce Research: A Bibliometric Perspective,” in International Conference on Information Management and Technology (ICIMTech), 2021, doi: 10.1109/ICIMTech53080.2021.9534928.

[6] J. Ciunova-Shuleska, Anita; Palamidovska-Sterjadovska, Nikolina; Prodanova, “What drives m-banking clients to continue using m-banking services?,” J. Bus. Res., vol. 139, pp. 731–739, 2022, doi: https://doi.org/10.1016/j.jbusres.2021.10.024.

[7] H. N. B. Mulia, Dipa; Usma, “The role of customer intimacy in increasing Islamic bank customer loyalty in using e-banking and m-banking,” J. Islam. Mark., vol. 12, no. 6, pp. 1097–1123, 2021, doi: https://doi.org/10.1108/JIMA-09-2019-0190.

[8] U. Shadid, Shadma; Islam, Jamid Ul; Malik, Shehla; Hasan, “Examining consumer experience in using m-banking apps: A study of its antecedents and outcomes,” J. Retail. Consum. Serv., vol. 65, 2022, doi: https://doi.org/10.1016/j.jretconser.2021.102870.

[9] R. G. Firmansyah, Irfan Achmad; Yasirandi, Rahmat; Utomo, “The influence of efficacy, credibility, and normative pressure to M-banking adoption level in Indonesia,” Procedia Comput. Sci., vol. 197, pp. 51–60, 2022, doi: https://doi.org/10.1016/j.procs.2021.12.117.

[10] D. B. Lucas, Gabriel Almeida; Lunardi, Guilherme Lerch; Dolci, “From e-commerce to m-commerce: An analysis of the user’s experience with different access platforms,” Electron. Commer. Res. Appl., vol. 58, 2023, doi: https://doi.org/10.1016/j.elerap.2023.101240.

[11] Henry Fransisko Paniroi, Erika Hardiyanti Kusuma Dewi, and Muhammad Irsad K, “M-banking: Salah Satu Layanan Jasa Bank Yang Menjadi Faktor Penting Dalam Mendapatkan Kepuasan Nasabah,” Pajak dan Manaj. Keuang., vol. 1, no. 3, pp. 63–70, 2024, doi: 10.61132/pajamkeu.v1i3.182.

[12] I. C. Iuga and D. Wainberg, Factors That Influence the Implementation of M-Commerce by Romanian SMEs During the COVID-19 Pandemic, vol. 15, no. 1. Springer US, 2024.

[13] M. B. Ali, R. Tuhin, M. A. Alim, M. Rokonuzzaman, S. M. Rahman, and M. Nuruzzaman, “Acceptance and use of ICT in tourism: the modified UTAUT model,” J. Tour. Futur., vol. 10, no. 2, pp. 334–349, 2024, doi: 10.1108/JTF-06-2021-0137.

[14] C. W. Yu, C. M. Chao, C. F. Chang, R. J. Chen, P. C. Chen, and Y. X. Liu, “Exploring Behavioral Intention to Use a Mobile Health Education Website: An Extension of the UTAUT 2 Model,” SAGE Open, vol. 11, no. 4, 2021, doi: 10.1177/21582440211055721.

[15] S. Tirtayasa, “The Effect Of Product Quality, Price, And Innovation On Marketing Performance Moderated Consumer Purchasing Power In UMKM Of Boba Drinks In Deli Serdang,” Int. J. Sci. Technol. Manag., vol. 3, no. 6, pp. 1731–1742, 2022, doi: 10.46729/ijstm.v3i6.642.

[16] D. Prasetya et al., “Technology Acceptance Analysis Using UTAUT: A Study of QRIS Acceptance during the Pandemic,” INTENSIF J. Ilm. Penelit. dan Penerapan Teknol. Sist. Inf., vol. 8, no. 2, pp. 181–199, 2024, doi: 10.29407/intensif.v8i2.21982.

[17] M. Blut, A. Y. L. Yee, L. Chong, Z. Tsigna, and V. Venkatesh, “Meta-analysis of the unified theory of acceptance and use of technology,” J. Assoc. Inf. Syst. Forthcom., vol. 23, no. 1, pp. 13–95, 2021, [Online]. Available: https://aisel.aisnet.org/jais/vol23/iss1/10.

[18] M. Rouidi, A. E. Elouadi, A. Hamdoune, K. Choujtani, and A. Chati, “TAM-UTAUT and the acceptance of remote healthcare technologies by healthcare professionals: A systematic review,” Informatics Med. Unlocked, vol. 32, no. June, p. 101008, 2022, doi: 10.1016/j.imu.2022.101008.

[19] F. D. Venkatesh, Viswanath; Morris, Michael G.; Davis, Gordon B.;Davis, “User Acceptance of Information Technology: Toward a Unified View,” MIS Q., vol. 27, no. 3, pp. 425–478, 2003, doi: https://doi.org/10.2307/30036540.

[20] B. G. Acosta-Enriquez et al., “Acceptance of artificial intelligence in university contexts: A conceptual analysis based on UTAUT2 theory,” Heliyon, vol. 10, no. 19, 2024, doi: 10.1016/j.heliyon.2024.e38315.

[21] X. Venkatesh, Viswanath; Thong, James Y.L.; Xu, “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology,” MIS Q., vol. 36, no. 1, pp. 157–178, 2012, doi: https://doi.org/10.2307/41410412.

[22] A. Chopdar, Prasanta Kr ; Lytras, Miltiadis D.; Visvizi, “Exploring factors influencing bicycle-sharing adoption in India: a UTAUT 2 based mixed-method approach,” Int. J. Emerg. Mark., vol. 18, no. 11, pp. 5109–5134, 2023, doi: https://doi.org/10.1108/IJOEM-06-2021-0862.

[23] N. S. Azman Ong, Mohd Hanafi; Yusri, Muhammad Yassar; Ibrahim, “Use and behavioural intention using digital payment systems among rural residents: Extending the UTAUT-2 model,” Technol. Soc., vol. 74, 2023, doi: https://doi.org/10.1016/j.techsoc.2023.102305.

[24] H. V. Osei, K. O. Kwateng, and K. A. Boateng, “Integration of personality trait, motivation and UTAUT 2 to understand e-learning adoption in the era of COVID-19 pandemic,” Educ. Inf. Technol., vol. 27, no. 8, pp. 10705–10730, 2022, doi: 10.1007/s10639-022-11047-y.

[25] K. Tamilmani, N. P. Rana, and Y. K. Dwivedi, “Consumer Acceptance and Use of Information Technology: A Meta-Analytic Evaluation of UTAUT2,” Inf. Syst. Front., vol. 23, no. 4, pp. 987–1005, 2021, doi: 10.1007/s10796-020-10007-6.

[26] H. S. Lee, Yvonne; Lim, Weilee; Eng, “A systematic review of UTAUT2 constructs’ analysis among MSMEs in non-OECD countries,” J. Sci. Technol. Policy Manag., vol. 15, no. 4, pp. 765–793, 2023, doi: https://doi.org/10.1108/JSTPM-08-2022-0140.

[27] C. M. Sarstedt, Marko ; Radomir, Lăcrămioara; Moisescu, Ovidiu Ioan; Ringle, “Latent class analysis in PLS-SEM: A review and recommendations for future applications,” J. Bus. Res., vol. 138, pp. 398–407, 2022, doi: https://doi.org/10.1016/j.jbusres.2021.08.051.

[28] C. B. ; Hair, Joseph F. ;Astrachan, L. ; Moisescu, Ovidiu I. ; Radomir, and C. M. Sarstedt, Marko ; Vaithilingam, Santha; Ringle, “Executing and interpreting applications of PLS-SEM: Updates for family business researchers,” J. Fam. Bus. Strateg., vol. 12, no. 3, 2021, doi: https://doi.org/10.1016/j.jfbs.2020.100392.

[29] G. Dash and J. Paul, “CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting,” Technol. Forecast. Soc. Change, vol. 173, no. June, p. 121092, 2021, doi: 10.1016/j.techfore.2021.121092.

[30] J. H. Cheah, S. Amaro, and J. L. Roldán, “Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations,” J. Bus. Res., vol. 156, no. April 2022, 2023, doi: 10.1016/j.jbusres.2022.113539.

[31] M. Alshurideh, B. Al Kurdi, S. A. Salloum, I. Arpaci, and M. Al-Emran, “Predicting the actual use of m-learning systems: a comparative approach using PLS-SEM and machine learning algorithms,” Interact. Learn. Environ., vol. 31, no. 3, pp. 1214–1228, 2023, doi: 10.1080/10494820.2020.1826982.

[32] S. A. Rehman Khan and Z. Yu, “Assessing the eco-environmental performance: an PLS-SEM approach with practice-based view,” Int. J. Logist. Res. Appl., vol. 24, no. 3, pp. 303–321, 2021, doi: 10.1080/13675567.2020.1754773.

[33] M. Ghasemy, V. Teeroovengadum, J. M. Becker, and C. M. Ringle, “This fast car can move faster: a review of PLS-SEM application in higher education research,” High. Educ., vol. 80, no. 6, pp. 1121–1152, 2020, doi: 10.1007/s10734-020-00534-1.

[34] A. Alharbi and O. Sohaib, “Technology Readiness and Cryptocurrency Adoption: PLS-SEM and Deep Learning Neural Network Analysis,” IEEE Access, vol. 9, pp. 21388–21394, 2021, doi: 10.1109/ACCESS.2021.3055785.

[35] T. Nainggolan and T. W. Ginting, “Analisis Persepsi Penggunaan Terhadap Aplikasi Lichess Dengan Model UTAUT-3,” vol. 25, no. 2, pp. 107–124, 2024.

[36] B. K. AlNuaimi, M. Khan, and M. M. Ajmal, “The role of big data analytics capabilities in greening e-procurement: A higher order PLS-SEM analysis,” Technol. Forecast. Soc. Change, vol. 169, no. May, p. 120808, 2021, doi: 10.1016/j.techfore.2021.120808.

[37] C. H. Huang, “Using pls-sem model to explore the influencing factors of learning satisfaction in blended learning,” Educ. Sci., vol. 11, no. 5, 2021, doi: 10.3390/educsci11050249.

[38] T. W. Ginting, E. S. Panjaitan, and R. Yunis, “Peran Variabel Keakraban Dalam Penggunaan E-Commerce Pada Model UTAUT,” J. Tek. Inform. dan Sist. Inf., vol. 10, no. 2, pp. 105–116, 2023.

[39] N. Surjanovic, R. A. Lockhart, and T. M. Loughin, “A generalized Hosmer–Lemeshow goodness-of-fit test for a family of generalized linear models,” Test, vol. 33, no. 2, pp. 589–608, 2024, doi: 10.1007/s11749-023-00912-8.

[40] I. A. Nurcahyani, “Hubungan Teknologi dan Organisasi dengan Kepuasaan Pengguna dalam Penerapan Sistem Informasi Manajemen Rumah Sakit (SIMRS) di Rumah Sakit Umum Daerah Ajibarang,” J. Manaj. Inf. Kesehat. …, vol. 12, no. 1, pp. 90–95, 2024, [Online]. Available: https://jmiki.aptirmik.or.id/jmiki/article/view/653.

[41] R. Hasjim, Darmawansyah, A. Arifin, Balqis, Suriah, and Wahiduddin, “The Influence of Patient Satisfaction on the Loyalty of Inpatient Patients at Dr. Tadjuddin Chalid Hospital Makassar City Year 2023,” Pharmacogn. J. , vol. 16, no. 2, pp. 436–441, 2024, doi: 10.5530/pj.2024.16.69.

[42] S. Surianto and F. D. Khang, “The Influence of Host Attractiveness and TV Programs on Interest in Watching Net.Tv (Case Study of Desta in the Main Hakim Sendiri),” J. Syntax Admiration, vol. 5, no. 6, pp. 2250–2260, 2024, doi: 10.46799/jsa.v5i6.1198.