Factors Influencing University Student Decision to Utilize Mobile Banking in Cambodia: An Extension of UTAUT-2 with SERVQUAL and DIT

Authors

DOI:

https://doi.org/10.26905/ap.v10i2.15055

Keywords:

Diffusion of Innovation Theory (DIT), Generation Z, Mobile banking, Service Quality Model (SERVQUAL), unified theory of acceptance and use of technology (UTAUT-2)

Abstract

Even though mobile banking has become popular in Cambodia, its adoption among university students is still a question. Hence, this study aims to investigate the factors influencing mobile banking adoption among university students in Cambodia. The study extends the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) by integrating Service Quality (SERVQUAL) model, and Diffusion of Innovation (DIT) theory to examine factors driving mobile banking adoption. The study uses a questionnaire to collect data from 520 university students. By using structural equation modeling, the study found that compatibility and observability affect intention through performance expectancy and effort expectancy. The study also found that performance expectancy, effort expectancy, hedonic motivation, price value, and habit all had a significant positive effect on the intention to adopt mobile banking. However, social influence and facilitating condition do not have an impact on intention. At the final path, the study found that performance expectancy, responsiveness, tangible, and intention have a positive impact on the students' behavior to use mobile banking.

References

ACLEDABank. (n.d.). Bank Profile: Performances. Retrieved from https://www.acledabank.com.kh/kh/eng/bp_performance.

AdvancedBankofAsiaLimited. (2023). ABA Annual Report 2023. Retrieved from https://www.ababank.com/about-us/annual-reports/.

Al-Jabri, I. M., & Sohail, M. S. (2012). Mobile banking adoption: Application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), 379-391. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2523623

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99-110. https://doi.org/doi.org/10.1016/j.ijinfomgt.2017.01.002

Ali, S., Simboh, B., & Rahmawati, U. (2023). Determining factors of peer-to-peer (P2P) lending avoidance: Empirical evidence from Indonesia. Gadjah Mada International Journal of Business, 25(1), 1-27. https://doi.org/10.22146/gamaijb.68805

Almaiah, M. A., Al-Rahmi, A. M., Alturise, F., Alrawad, M., Alkhalaf, S., Lutfi, A., Al-Rahmi, W. M., & Awad, A. B. (2022). Factors influencing the adoption of internet banking: An integration of ISSM and UTAUT with price value and perceived risk. Frontiers in Psychology, 13, 919198. https://doi.org/doi.org/10.3389/fpsyg.2022.919198

Angelia, A., Panjaitan, E. S., & Yunis, R. (2021). Effect of attitude on mobile banking acceptance using extended UTAUT model. Jurnal Mantik, 5(2), 1006-1013. https://doi.org/https://doi.org/10.35335/jurnalmantik.Vol5.2021.1440.pp1006-1013

Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418-430. https://doi.org/doi.org/10.1016/j.chb.2015.04.024

Batucan, G. B., Gonzales, G. G., Balbuena, M. G., Pasaol, K. R. B., Seno, D. N., & Gonzales, R. R. (2022). An extended UTAUT model to explain factors affecting online learning system amidst COVID-19 pandemic: The case of a developing economy. Frontiers in Artificial Intelligence, 5, 768831. https://doi.org/doi.org/10.3389/frai.2022.768831

Bhasin, H. (2023). The Servqual Model – Definition, Dimensions, Gaps and Advantages Service. Retrieved from https://www.marketing91.com/servqual/.

Chao, C.-M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10, 1652. https://doi.org/doi.org/10.3389/fpsyg.2019.01652

Choe, M.-J., & Noh, G.-Y. (2018). Combined Model of Technology Acceptance and Innovation Diffusion Theory for Adoption of Smartwatch. International Journal of contents, 14(3). https://doi.org/doi.org/10.5392/IJoC.2018.14.3.032

Dai Thich, P. (2021). A study on behavior intention to adopt mobile banking apps. International Journal of E-Services and Mobile Applications (IJESMA), 13(2), 60-72. https://doi.org/doi.org/10.4018/ijesma.2021040104

Dhingra, S., & Gupta, S. (2020). Behavioural intention to use mobile banking: An extension of UTAUT2 model. International Journal of Mobile Human Computer Interaction (IJMHCI), 12(3), 1-20. https://doi.org/doi.org/10.4018/ijmhci.2020070101

Dwiputranti, I., Oktora, A., Okdinawati, L., & Fauzan, M. (2019). Acceptance and use of information technology: Understanding information systems for Indonesia's humanitarian relief operations. Gadjah Mada International Journal of Business, 21(3), 242-262. https://doi.org/DOI: 10.22146/gamaijb.39199

Farzin, M., Sadeghi, M., Yahyayi Kharkeshi, F., Ruholahpur, H., & Fattahi, M. (2021). Extending UTAUT2 in M-banking adoption and actual use behavior: does WOM communication matter? Asian Journal of Economics and Banking, 5(2), 136-157. https://doi.org/doi.org/10.1108/AJEB-10-2020-0085

Gefen, D., & Keil, M. (1998). The impact of developer responsiveness on perceptions of usefulness and ease of use: An extension of the technology acceptance model. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 29(2), 35-49. https://doi.org/doi.org/10.1145/298752.298757

Gharaibeh, M. K., Arshad, M. R. M., & Gharaibh, N. K. (2018). Using the UTAUT2 model to determine factors affecting adoption of mobile banking services: A qualitative approach. International Journal of Interactive Mobile Technologies, 12(4). https://doi.org/doi.org/10.3991/ijim.v12i4.8525

Goodwin, T. D. S. R. (2010). Factors Influencing Citizen Adoption of SMS‑Based e‑Government Services. Electronic journal of e-government, 8(1), pp55-70.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis (6th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Hubert, M., Blut, M., Brock, C., Zhang, R. W., Koch, V., & Riedl, R. (2019). The influence of acceptance and adoption drivers on smart home usage. European Journal of Marketing, 53(6), 1073-1098. https://doi.org/doi.org/10.1108/EJM-12-2016-0794

Iskandar, M., Hartoyo, H., & Hermadi, I. (2020). Analysis of Factors Affecting Behavioral Intention and Use of Behavioral of Mobile Banking Using Unified Theory of Acceptance and Use of Technology 2 Model Approach. International Review of Management and Marketing, 10(2), 41-41. https://doi.org/doi.org/10.32479/irmm.929

Ivanova, A., & Kim, J. Y. (2022). Acceptance and use of mobile banking in Central Asia: Evidence from modified UTAUT model. The Journal of Asian Finance, Economics and Business, 9(2), 217-227. https://doi.org/doi.org/10.13106/jafeb.2022.vol9.no2.0217

NBC. (2023). NBC Annual Report 2023. Retrieved from https://www.nbc.gov.kh/download_files/publication/annual_rep_eng/NBC%20Annual%20Report%202023%20Eng.pdf.

Ngam, P., & Norng, S. (2022). Factors Hindering University Students to Adopt ACLEDA Mobile. AIB Research Series, II, 159-171.

Norng, S. (2022). Factors Influencing Mobile Banking Adoption in Cambodia: The Structuring of TAM, DIT, and Trust with TPB. Asian Journal of Business Research Volume, 12(3). https://doi.org/doi.org/10.14707/ajbr.220133

Nunnally, J. C. (1994). Psychometric theory 3E. Tata McGraw-hill education.

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. https://doi.org/doi.org/10.1016/j.chb.2016.03.030

Parasuraman, A., Zeithaml, V. A., & Berry, L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40.

Parker, K., & Igielnik, R. (2020). On the Cusp of Adulthood and Facing an Uncertain Future: What We Know About Gen Z So Far. Retrieved from https://www.pewresearch.org/social-trends/2020/05/14/on-the-cusp-of-adulthood-and-facing-an-uncertain-future-what-we-know-about-gen-z-so-far/.

Phan, C., & Nham, P. (2015). Impact of service quality on customer satisfaction of automated teller machine service: case study of a private commercial joint stock bank in Vietnam. Business: Theory and Practice, 16, 280-280.

Phou, S., Norng, S., & Hann, O. (2024). Investigating Factors Influencing Consumers’ Purchase Intention and Decisions towards Bubble Tea in Phnom Penh, Cambodia. Cambodia Journal for Business and Professional Practice, I, 1-30.

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-879. https://doi.org/doi.org/10.1037/0021-9010.88.5.879

Rasoolimanesh, S. M. (2022). Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach. Data Analysis Perspectives Journal, 3(2), 1-8.

Rogers, E. M. (2003). Diffusion of Innovations, Fifth Edition. Free Press: New York. Free Press.

Santos, J. (2002). From intangibility to tangibility on service quality perceptions: a comparison study between consumers and service providers in four service industries. Managing Service Quality: An International Journal, 12(5), 292-302. https://doi.org/doi.org/10.1108/09604520210442083

Savić, J., & Pešterac, A. (2019). Antecedents of mobile banking: UTAUT model. The European journal of applied economics, 16(1). https://doi.org/doi.org/10.5937/EJAE15-19381

Schermelleh-Engel, K., Moosbrugger, H., Müller, H., & others. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.

Schindler, P. (2019). Business Research Methods. 13th Ed. New York, USA: McGraw- Hill Higher Education.

Sekaran, U., & Bougie, R. (2016). Research Methods for Business: A Skill-Building Approach (7th ed.). John Wiley & Sons Ltd.

Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review. Telematics and Informatics, 32(1), 129-142. https://doi.org/doi.org/10.1016/j.tele.2014.05.003

Sharma, G. (2017). What is Digital Banking?. Retrieved from https://www.ventureskies.com/blog/digital-banking. In.

Solihat, I., Hamundu, F. M., & Wahyu, M. (2023). DETERMINANTS OF BEHAVIOR INTENTION TO ADOPT PEER-TO-PEER LENDING SERVICES AMONG INDONESIA MSMES. International Journal of Business & Society, 24(1). https://doi.org/doi.org/10.33736/ijbs.5633.2023

Tamilmani, K., Rana, N. P., & Dwivedi, Y. K. (2019, 2019). Use of ‘habit’is not a habit in understanding individual technology adoption: a review of UTAUT2 based empirical studies.

Tamilmani, K., Rana, N. P., Wamba, S. F., & Dwivedi, R. (2021). The extended Unified Theory of Acceptance and Use of Technology (UTAUT2): A systematic literature review and theory evaluation. International Journal of Information Management, 57, 102269. https://doi.org/doi.org/10.1016/j.ijinfomgt.2020.102269

Usman, O., Alianti, M., & Fadillah, F. N. (2024). Factors affecting the intention to use QRIS on MSME customers. International Journal of Applied Economics, Finance and Accounting, 18(1), 77-87. https://doi.org/doi.org/10.33094/ijaefa.v18i1.1323

Utomo, P., Kurniasari, F., & Purnamaningsih, P. (2021). The effects of performance expectancy, effort expectancy, facilitating condition, and habit on behavior intention in using mobile healthcare application. International Journal of Community Service & Engagement, 2(4), 183-197.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178. https://doi.org/doi.org/10.2307/41410412

Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44, 119-134.

Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013). Sample size requirements for structural equation models: An evaluation of power, bias, and solution propriety. Educational and Psychological Measurement, 73(6), 913-934.

Yu, C.-S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 104.

Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767. https://doi.org/doi.org/10.1016/j.chb.2010.01.013

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2024-09-30

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