Bangladeshi University Students’ Behavioral Intention to Adopt Mobile Payment for Academic Fees The Impact of Perceived Usefulness, Hedonic Motivation, and Government Support

Main Article Content

Sakib Talukder
Md. Zaber Hossain
Md. Muntasim Rafi
Most. Karima Ali

Abstract

The global financial transaction system is dramatically changing because of the rapid adoption of mobile payment (m-payment), instigating an investigation into the drivers of acceptance of m-payment for academic fees by Bangladeshi University students. This research investigation aims to explore Bangladeshi university students’ intention to adopt mobile payment (m-payment) for their academic fees. A convenience sampling was utilized, and a total of 124 University Students were used to analyze the data. The investigation formulates PLS-SEM modelling for analyzing the measurement and structural model. Three independent variables, Perceived Usefulness, Hedonic Motivation, and Government Support, were used to examine behavioral intention to adopt mobile payment for academic fees among Bangladeshi university students. The findings of this existing research investigation show that the three variables positively and significantly affect behavioral intention to adopt m-payment among Bangladeshi University Students.  The research suggests the need to use mobile payment systems in universities’ financial operations to enhance service efficiency. M-payment service providers can meet the specific needs of university students by enhancing user experience. The government support motivates m-payment service providers to take effective organizational decisions.

Article Details

Section

Articles

References

Abdennebi, H. B. (2023). M-banking adoption from the developing countries perspective: A mediated model. Digital Business, 3(2), 100065. https://doi.org/10.1016/j.digbus.2023.100065

Academic fees Definition | Law Insider. (n.d.). Law Insider. https://www.lawinsider.com/dictionary/academic-fees

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Al-Azawei, A., & Alowayr, A. (2020). Predicting the intention to use and hedonic motivation for mobile learning: A comparative study in two Middle Eastern countries. Technology in Society, 62, 101325. https://doi.org/10.1016/j.techsoc.2020.101325

Al-Rahmi, A. M., Al-Rahmi, W. M., Alturki, U., Aldraiweesh, A., Almutairy, S., & Al-Adwan, A. S. (2022). Acceptance of mobile technologies and M-learning by university students: An empirical investigation in higher education. Education and Information Technologies, 27(6), 7805–7826. https://doi.org/10.1007/s10639-022-10934-8

Alwi, S. (2021). Fintech as financial inclusion: Factors affecting behavioral intention to accept mobile e-wallet during Covid-19 outbreak. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(7), 2130–2141.

Awal, M. R., & Haque, M. E. (2024). Revisiting university students’ intention to accept AI-Powered chatbot with an integration between TAM and SCT: a south Asian perspective. Journal of Applied Research in Higher Education. https://doi.org/10.1108/jarhe-11-2023-0514

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/bf02723327

Baicu, C. G., Gârdan, I. P., Gârdan, D. A., & Epuran, G. (2020). The impact of COVID-19 on consumer behavior in retail banking. Evidence from Romania. Management & Marketing, 15(s1), 534–556. https://doi.org/10.2478/mmcks-2020-0031

Bala, T., Jahan, I., Amin, M. A., Tanin, M. H., Islam, M. F., Rahman, M. M., & Khatun, T. (2021). Service Quality and Customer Satisfaction of Mobile Banking during COVID-19 Lockdown; Evidence from Rural Area of Bangladesh. Open Journal of Business and Management, 09(05), 2329–2357. https://doi.org/10.4236/ojbm.2021.95126

Bhuiyan, M. R. I., Akter, M. S., & Islam, S. (2024). How does digital payment transform society as a cashless society? An empirical study in the developing economy. Journal of Science and Technology Policy Management. https://doi.org/10.1108/jstpm-10-2023-0170

Biswas, B., Roy, S. K., & Roy, F. (2020). Students Perception of Mobile Learning during COVID-19 in Bangladesh: University Student Perspective. Aquademia, 4(2), ep20023. https://doi.org/10.29333/aquademia/8443

Cao, T. (2021). The Study of Factors on the Small and medium Enterprises’ adoption of Mobile Payment: Implications for the COVID-19 Era. Frontiers in Public Health, 9, 646592. https://doi.org/10.3389/fpubh.2021.646592

Chawla, D. and Joshi, H. (2019), “Consumer attitude and intention to adopt mobile wallet in India– an empirical study”, International Journal of Bank Marketing, Vol. 37 No. 7, pp. 1590-1618, doi: 10. 1108/IJBM-09-2018-0256.

Chen, W., Chen, C., & Chen, W. (2019). Drivers of mobile payment acceptance in China: an empirical investigation. Information, 10(12), 384. https://doi.org/10.3390/info10120384

Cheng, N. T. Y., Fong, L. H. N., & Law, R. (2021). Mobile payment technology in hospitality and tourism: a critical review through the lens of demand, supply and policy. International Journal of Contemporary Hospitality Management, 33(10), 3636–3660. https://doi.org/10.1108/ijchm-02-2021-0261

Cheong, H. S., Kwon, K. T., Hwang, S., Kim, S., Chang, H., Park, S. Y., Kim, B., Lee, S., Park, J., Heo, S. T., Oh, W. S., Kim, Y., Park, K., Kang, C. K., Oh, N., Lim, S. J., Yun, S., & Son, J. W. (2022b). Workload of healthcare workers during the COVID-19 outbreak in Korea: a nationwide survey. Journal of Korean Medical Science, 37(6). https://doi.org/10.3346/jkms.2022.37.e49

Colquitt, J.A. and Zapata-Phelan, C.P. (2007), “Trends in theory building and theory testing: a five decade study of the academy of management journal”, Academy of Management Journal, Vol. 50 No. 6, pp. 1281-1303

Dahlberg, T., Mallat, N., Ondrus, J., & Zmijewska, A. (2007). Past, present and future of mobile payments research: A literature review. Electronic Commerce Research and Applications, 7(2), 165–181. https://doi.org/10.1016/j.elerap.2007.02.001

Dalim, S. H. (2024, November 17). Mobile financial service accounts increase by nearly 20 million in one year. bdnews24.com. https://bdnews24.com/business/6fb10d263321

Das, A. C. (2024). Understanding the Dynamics of digital payment adoption among public university students of Bangladesh: A Quantitative study. Research Square (Research Square). https://doi.org/10.21203/rs.3.rs-4138836/v1

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Dhaka Tribune. (2022, July 23). bKash app’s ‘Education Fee’ icon revamped with more user-friendly features.https://www.dhakatribune.com/business/274711/bkash-app%E2%80%99s-%E2%80%98education-fee%E2%80%99-icon-revamped-with

Di Pietro, L., Mugion, R.G., Mattia, G., Renzi, M.F. and Toni, M. (2015), “The integrated model on mobile payment acceptance (IMMPA): an empirical application to public transport”, Transportation Research Part C: Emerging Technologies, Vol. 56, pp. 463-479, doi: 10.1016/j. trc.2015.05.001

F, H. J. J., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. London; Prentice Hall; 7 Ed; 2010. 785 P. | SES-SP | SESSP-ISACERVO. https://pesquisa.bvsalud.org/portal/resource/pt/biblio-1074274

Farah, M. F., Hasni, M. J. S., & Abbas, A. K. (2018). Mobile-banking adoption: empirical evidence from the banking sector in Pakistan. International Journal of Bank Marketing, 36(7), 1386–1413. https://doi.org/10.1108/IJBM-10-2017-0215

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

Geetha, V. (2024). Students’ behavioural intention towards mobile technology for online shopping. International Journal of Electronic Marketing and Retailing, 16(1), 67–78. https://doi.org/10.1504/ijemr.2025.142894

Gupta, K., & Arora, N. (2019). Investigating consumer intention to accept mobile payment systems through unified theory of acceptance model. South Asian Journal of Business Studies, 9(1), 88–114. https://doi.org/10.1108/sajbs-03-2019-0037

Hai, L. C., & Kazmi, S. H. A. (2015). Dynamic support of government in online shopping. Asian Social Science, 11(22). https://doi.org/10.5539/ass.v11n22p

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate Data Analysis: A Global Perspective (7th ed.). Upper Saddle River, NJ: Prentice Hall.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2021). Multivariate data analysis (8th ed.). Cengage Learning.

Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2011). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433. https://doi.org/10.1007/s11747-011-0261-6

Hair, J. F., Wolfinbarger, M., Money, A. H., Samouel, P., & Page, M. J. (2017). Essentials of business research methods (3rd ed.). Routledge.

Hair, J.F., Risher, J.J., Sarstedt, M. and Ringle, C.M. (2019) When to Use and How to Report the Results of PLS-SEM. European Business Review, 31, 2-24. https://doi.org/10.1108/EBR-11-2018-0203

Han, H., & Hyun, S. S. (2017). Impact of hotel-restaurant image and quality of physical-environment, service, and food on satisfaction and intention. International Journal of Hospitality Management, 63, 82–92. https://doi.org/10.1016/j.ijhm.2017.03.006

Hasibuan, A. Q. R. (2023). Effect of Tuition Fee, Promotion on Number of Students: Trust as Mediation Variable. UPI YPTK Journal of Business and Economics, 8(1), 8–16. https://doi.org/10.35134/jbe.v8i1.220

Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

Ho, J. C., Wu, C., Lee, C., & Pham, T. T. (2020). Factors affecting the behavioral intention to adopt mobile banking: An international comparison. Technology in Society, 63, 101360. https://doi.org/10.1016/j.techsoc.2020.101360

Hossain, M. M., Ibrahim, Y., & Uddin, M. M. (2020). Finance, financial literacy and small firm financial growth in Bangladesh: the effectiveness of government support. Journal of Small Business & Entrepreneurship, 35(3), 336–361. https://doi.org/10.1080/08276331.2020.1793097

Jayarathne, P. A., Chathuranga, B., Dewasiri, N., & Rana, S. (2022). Motives of mobile payment adoption during COVID-19 pandemic in Sri Lanka: a holistic approach of both customers’ and retailers’ perspectives. South Asian Journal of Marketing. https://doi.org/10.1108/sajm-03-2022-0013

Jöreskog, K. G. (1971). Statistical analysis of sets of conGeneric tests. Psychometrika, 36(2), 109–133. https://doi.org/10.1007/bf02291393

Kelly, A. E. (2024a). The sustainability and contribution of Generation Z influenced by hedonic and utilitarian values to use mobile money services for fee payment. Telematics and Informatics Reports, 14, 100145. https://doi.org/10.1016/j.teler.2024.100145

Kim, C., Mirusmonov, M., & Lee, I. (2009). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322. https://doi.org/10.1016/j.chb.2009.10.013

Leong, C., Tan, K., Puah, C., & Chong, S. (2020). Predicting mobile network operators users m-payment intention. European Business Review, 33(1). https://doi.org/10.1108/ebr-10-2019-0263

Ling, P., Lim, X., Wong, L., & Lee, K. Y. M. (2024). Thank you, government! Your support facilitated my intention to use mobile payment in the new normal era. Spanish Journal of Marketing - ESIC, 29(1), 3–21. https://doi.org/10.1108/sjme-08-2022-0186

Long, S., Mamun, A. A., Yang, Q., Gao, J., Hussain, W. M. H. W., & Shami, S. S. a. A. (2023). Modelling the mass adoption of mobile payment for e-hailing services using SEM-MGA. PLoS ONE, 18(10), e0287300. https://doi.org/10.1371/journal.pone.0287300

Mailizar, M., Almanthari, A., & Maulina, S. (2021). Examining teachers’ behavioral intention to use e-learning in teaching of mathematics: an Extended TAM model. Contemporary Educational Technology, 13(2), ep298. https://doi.org/10.30935/cedtech/9709

Moorthy, K., Tsen, T. Y., Loh, C. T., & Vikniswari, V. K. (2019). Habit and hedonic motivation are the strongest influences in mobile learning behaviours among higher education students in Malaysia. Australasian Journal of Educational Technology, 35(4), 174-191. https://doi.org/10.14742/ajet.4432

Murphy, J. (2021). Mobile payment system usage among tertiary students. A case study of Kumasi Metropolitan. http://41.74.91.244:8080/handle/123456789/1218

Mwale, M., & Phiri, J. (2024). Secure mobile Payment gateway for higher institutions of learning. In Lecture notes in networks and systems (pp. 367–381). https://doi.org/10.1007/978-981-97-3302-6_30

Natasia, S. R., Wiranti, Y. T., & Parastika, A. (2022). Acceptance analysis of NUADU as e-learning platform using the Technology Acceptance Model (TAM) approach. Procedia Computer Science, 197, 512–520. https://doi.org/10.1016/j.procs.2021.12.168

Nguyen, V. A., & Nguyen, T. P. T. (2020). An integrated model of CSR perception and TAM on intention to adopt M-banking. The Journal of Asian Finance, Economics and Business, 7(12), 1073–1087. https://doi.org/10.13106/jafeb.2020.vol7.no12.1073

Nguyen, V. A., & Nguyen, T. P. T. (2020). An integrated model of CSR perception and TAM on intention to adopt M-banking. The Journal of Asian Finance, Economics and Business, 7(12), 1073–1087. https://doi.org/10.13106/jafeb.2020.vol7.no12.1073

O'Brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41(5), 673–690.

Pawar, P. (2025, April 23). Digital Banking Statistics by Market, Demographics and Country (2025). Sci-Tech Today. https://www.sci-tech-today.com/stats/digital-banking-statistics-updated/

Prasetyo, Y. T., Susanto, K. C., Chuang, K., Yin, R., Chen, J., Zhang, Y., Benito, O. P., Belmonte, Z. J. A., Cahigas, M. M. L., Nadlifatin, R., & Gumasing, M. J. J. (2025). Factors influencing the perceived usability of line pay: An extended technology acceptance model approach. Acta Psychologica, 255, 104924. https://doi.org/10.1016/j.actpsy.2025.104924

Rabiah, A. S., Setiawan, M., Rohman, F., & Mugiono, N. (2024). Assess the impact of hedonic motivation, social influence, gamification, and education level on behavioral intention to adopt mobile shopping in Jakarta, Indonesia. Revista De Gestão Social E Ambiental, 18(7), e05024. https://doi.org/10.24857/rgsa.v18n7-008

Riggins, F., & Dewan, S. (2005). The Digital Divide: Current and future research directions. Journal of the Association for Information Systems, 6(12), 298–337. https://doi.org/10.17705/1jais.00074

Silviana, A., & Pudjiarti, E. S. (2024). THE CRITICAL ROLE OF TECHNOLOGY ADOPTION AND COMPETENCY THROUGH IMPROVING TEAMWORK AND KNOWLEDGE TRANSFORMATION IN THE FURNITURE BUSINESS IN JEPARA. Fokus Ekonomi Jurnal Ilmiah Ekonomi, 19(1), 71–84. https://doi.org/10.34152/fe.19.1.71-84

Świecka, B., Terefenko, P., & Paprotny, D. (2021). Transaction factors’ influence on the choice of payment by Polish consumers. Journal of Retailing and Consumer Services, 58, 102264. https://doi.org/10.1016/j.jretconser.2020.102264

Toraman, Y., & Geçi̇T, B. B. (2023). User Acceptance of Metaverse: An analysis for e-Commerce in the framework of Technology Acceptance Model (TAM). Sosyoekonomi, 31(55), 85–104. https://doi.org/10.17233/sosyoekonomi.2023.01.05

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://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, 36(1), 157–178. https://doi.org/10.2307/41410412.

Wang, K., Van Hemmen, S. F., & Criado, J. R. (2022). The behavioural intention to use MOOCs by undergraduate students: incorporating TAM with TPB. International Journal of Educational Management, 36(7), 1321–1342. https://doi.org/10.1108/ijem-11-2021-0446

Wu, M., Liu, Y., Chung, H. F., & Guo, S. (2021). When and how mobile payment platform complementors matter in cross-border B2B e-commerce ecosystems? An integration of process and modularization analysis. Journal of Business Research, 139, 843–854. https://doi.org/10.1016/j.jbusres.2021.10.019

Yan, L.-Y., Tan, G.W.-H., Loh, X.-M., Hew, J.-J. and Ooi, K.-B. (2021), “QR code and mobile payment: the disruptive forces in retail”, Journal of Retailing and Consumer Services, Vol. 58, p. 102300.

Zhao, H., & Khaliq, N. (2024b). In quest of perceived risk determinants affecting intention to use fintech: Moderating effects of situational factors. Technological Forecasting and Social Change, 207, 123599. https://doi.org/10.1016/j.techfore.2024.123599