ISSN: 2222-6990
Open access
Leveraging mobile application features, the utility industry chooses such an advantageous platform to enhance customer value, customer satisfaction, and long-term engagement through continuance usage intention. Tenaga Nasional Berhad (TNB), as the main electricity utility company in Malaysia, considers customer satisfaction one of its main concerns as an electricity energy provider, which led it to explore and adopt digitalization in its business strategy. MyTNB mobile applications, categorized under smart retail technologies, have been commercialized as a medium to provide excellent customer experiences by providing superior, personalized retail services. Continuous improvement and exceeding customers’ expectations by providing mobile solutions lead to the necessity of this study, as it explores the status of the myTNB mobile applications and aligns with the company’s profit and sustainability strategy. In addition, business strategy and business performance could be supported by understanding the driving factors of customers’ mobile app use, including how they affect myTNB’s usage intention. Hence, investigates the relationships among theory of Technology Acceptance Model (TAM), consist of Perceived Ease of Use (PEOU), Perceived Usefulness (PU) and Technological Readiness (TR) theory with customers’ Attitude (ATT) and Intention to Use (ITU) myTNB mobile applications are the study focus. The data were collected from registered customers of TNB, and SmartPLS 4.0 was used for the analysis. PU and TR results positively influence the customer’s ATT, which in turn influences their ITU of the myTNB mobile application. PEOU affects the customer’s positive ATT. However, PEOU has no direct influence on the ITU of the myTNB mobile application.
Anwar, M. M. (2024). How does TAM affect impulsive buying of halal fashion products via shopping mobile apps? Journal of Islamic Marketing. https://doi.org/10.1108/JIMA-03-2023-0096
Baltaci, F., Ba?er, M. Y., & Çelik, M. (2024). Attitude towards service robots in tourism and hospitality services settings — The effect of multidimensional anthropomorphism and technology readiness. International Journal of Tourism Research, 26(4), 1–15. https://doi.org/10.1002/jtr.2685
Alhammadi, K., Marashdeh, H., & Hussain, M. (2023). Assessing the effect of innovation diffusion and technology readiness theories on attitude, behavioral intention and implementation of smart learning. Cross Cultural and Strategic Management, 30(4), 657–675. https://doi.org/10.1108/CCSM-12-2022-0213
Almajali, D. A., Majali, T., Masa’deh, R., Al-Bashayreh, M. G., & Altamimi, A. M. (2023). Antecedents of acceptance model for e-procurement in Jordanian public shareholding firms. Journal of Consumer Marketing, 40(6), 663–684. https://doi.org/10.1108/JCM-12-2021-5075
Cimbaljevi?, M., Demirovi? Bajrami, D., Kova?i?, S., Pavlukovi?, V., Stankov, U., & Vuji?i?, M. (2023). Employees’ technology adoption in the context of smart tourism development: the role of technological acceptance and technological readiness. European Journal of Innovation Management, 7739076. https://doi.org/10.1108/EJIM-09-2022-0516
Creswell, J.W. (2014), A Concise Introduction to Mixed Methods Research, SAGE Publications, Los Angeles.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155
Dash, A., & Mohanty, S. K. (2023). Technology readiness and the older citizen’s acceptance of m-health services in India. Digital Policy, Regulation and Governance, 25(2), 169–183. https://doi.org/10.1108/DPRG-11-2022-0126
Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13, pp. 319-340, doi: 10.2307/249008
Davis, F.D. (1993), “User acceptance of information technology: system characteristics, user perceptions and behavioral impacts”, International Journal of Man-Machine Studies, Vol. 38 No. 3, pp. 475-487, doi: 10.1006/ imms.1993.1022.
Davis, F.D., Bagozzi, R.P. and Warshaw, P.R. (1989), “User acceptance of computer technology: a comparison of two theoretical models”, Management Science, Vol. 35 No. 8, available at: www.mendeley.com/catalogue/03ec09b3-33ab- 3935-8826-43768b3147e6/
Fishbein, M. and Ajzen, I. (1975), Belief, Attitude, Intention and Behaviour: An Introduction to Theory and Research, AddisonWesley, Reading, Massachusetts, p. 480, available at: http://people. umass.edu/aizen/f&a1975.html.
ElSayad, G. (2024). Online customers’ attitudes and intentions towards e-payment usage in Egypt during the COVID-19 pandemic: the serial mediation roles of perceived usefulness, perceived trust, and attitude. Journal of Science and Technology Policy Management. https://doi.org/10.1108/JSTPM-02-2023-0024
Ferreira, A., Silva, G. M., & Dias, Á. L. (2023). Determinants of continuance intention to use mobile self-scanning applications in retail. International Journal of Quality and Reliability Management, 40(2), 455–477. https://doi.org/10.1108/IJQRM-02-2021-0032
Gopinathan, S. (2024). Role of Behavioral Intention in Implementation of Green Information Systems among Malaysians. 1–13.
Hasan, A. A.-T. (2022). Determinants of intentions to use foodpanda mobile applications in Bangladesh: the role of attitude and fear of COVID-19. South Asian Journal of Marketing, 4(1), 17–32. https://doi.org/10.1108/sajm-10-2021-0123
Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M., Danks, N.P. and Ray, S. (2017), Partial Least Squares Structural Equation Modeling (PLS-SEM), Evaluation of Reflective Measurement Models, pp. 75-90.
Hair, J. F., Howard, M. C., & Nitzl, C. (2020a). Assessing measurement model quality in PLS-SEM using con fi rmatory composite analysis. Journal of Business Research, 109(November 2019), 101–110. https://doi.org/10.1016/j.jbusres.2019.11.069
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Evaluation of Formative Measurement Models. https://doi.org/10.1007/978-3-030-80519-7_5
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3 ed.). Thousand Oaks, CA: Sage.
Herzallah, D., Muñoz-Leiva, F., & Liebana-Cabanillas, F. (2022). Drivers of purchase intention in Instagram Commerce. Spanish Journal of Marketing - ESIC, 26(2), 168–188. https://doi.org/10.1108/SJME-03-2022-0043
Jiang, Y., Wang, X., & Yuen, K. F. (2021). Augmented reality shopping application usage: The influence of attitude, value, and characteristics of innovation. Journal of Retailing and Consumer Services, 63(August), 102720. https://doi.org/10.1016/j.jretconser.2021.102720
Kampa, R. K. (2023). Combining technology readiness and acceptance model for investigating the acceptance of m-learning in higher education in India. Asian Association of Open Universities Journal, 18(2), 105–120. https://doi.org/10.1108/AAOUJ-10-2022-0149
Khashan, M. A., Alasker, T. H., Ghonim, M. A., & Elsotouhy, M. M. (2024). Understanding physicians’ adoption intentions to use Electronic Health Record (EHR) systems in developing countries: an extended TRAM approach. Marketing Intelligence and Planning. https://doi.org/10.1108/MIP-05-2023-0225
Kim, J. (Sunny), Hardin, A., & Lee, S. (2023). Factors influencing resistance to hospitality information system change. Journal of Hospitality and Tourism Insights, 6(5), 1926–1945. https://doi.org/10.1108/JHTI-04-2022-0129
Khor, X. Y., Teoh, A. P., Vafaei-Zadeh, A., & Md Hanifah, H. (2023). Predicting electronic personal health record (e-PHR) acceptance: evidence from emerging market. International Journal of Pharmaceutical and Healthcare Marketing, 17(4), 405–428. https://doi.org/10.1108/IJPHM-06-2021-0069
Liu, Y. (David), Chung, H. F. L., Zhang, Z. (Justin), & Wu, M. (2023). The dark side of mobile apps: when and how technical security matters for in-app purchases? Asia Pacific Journal of Marketing and Logistics, 35(12), 2965–2982. https://doi.org/10.1108/APJML-10-2022-0875
Malaysian Communication & Multimedia Commission, (2021) Malaysia’s Internet user Survey
Ofosu-Ampong, K., Asmah, A., Kani, J. A., & Bibi, D. (2023). Determinants of digital technologies adoption in government census data operations. Digital Transformation and Society, 2(3), 293–315. https://doi.org/10.1108/DTS-11-2022-0056
Omar, Q., Yap, C. S., Ho, P. L., & Keling, W. (2023). Can technology readiness predict farmers’ adoption intention of the e-AgriFinance app? Journal of Agribusiness in Developing and Emerging Economies, 13(1), 156–172. https://doi.org/10.1108/JADEE-04-2021-0090
Rahman, S. ur, Nguyen-Viet, B., Nguyen, Y. T. H., & Kamran, S. (2024). Promoting fintech: driving developing country consumers’ mobile wallet use through gamification and trust. International Journal of Bank Marketing, 42(5), 841–869. https://doi.org/10.1108/IJBM-01-2023-0033
Ringle, Christian M., Wende, Sven, & Becker, Jan-Michael. (2022). SmartPLS 4. Oststeinbek: SmartPLS. Retrieved from https://www.smartpls.com
Statista (2023) Number of mobile app downloads worldwide from 2016 to 2023
Shmueli, G., S. Ray, J.M. Velasquez Estrada, and S.B. Chatla. (2016). The elephant in the room: predictive performance of PLS models. Journal of Business Research, 69: 4552–4564.
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/EJM-02-2019-0189
Soodan, V., Jamwal, M., Rana, N. P., Sharma, D., & Chakraborty, S. (2023). Modelling the adoption of agro-advisory mobile applications: a theoretical extension and analysis using result demonstrability, trust, self-efficacy and mobile usage proficiency. Journal of Agribusiness in Developing and Emerging Economies. https://doi.org/10.1108/JADEE-05-
Tenaga Nasional Berhad. (2022). Integrated annual report 2021: Pathway to a sustainable future. tnb.com.my
Tenaga Nasional Berhad. (2023). Integrated annual report 2022: Accelerating responsible energy transition. https://www.tnb.com.my/assets/annual_report/TNB_IAR_2022.pdf
Hasim, H. K., & Osman, Z. (2026). Determinants of Customers’ Intention to Use the my TNB Mobile Application: Evidence from Malaysia’s Electricity Utility Sector. International Journal of Academic Research in Business and Social Sciences, 16(10), 656–672.
Copyright: © 2026 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode