Performance Expectancy and Effort Expectancy as Determinantsof PLN Mobile Use Intention among PLN ULP Namlea Customers
DOI:
https://doi.org/10.37385/ceej.v7i4.12120Keywords:
Performance Expectancy, Effort Expectancy, Intention to Use, PLN Mobile, Technology AdoptionAbstract
This study examines the influence of performance expectancy and effort expectancy on customers’ intention to use the PLN Mobile application at PLN ULP Namlea. The study is motivated by the continuing development of digital electricity services while conventional service channels remain relevant among customers in the local service area. Previous studies have examined technology-adoption determinants in various digital-service contexts, but empirical evidence focusing specifically on performance expectancy and effort expectancy as direct determinants of PLN Mobile use intention in an island-area electricity service context remains limited. The novelty of this study lies in its focused application of these two core technology-acceptance constructs to PLN ULP Namlea customers. Data were obtained from PLN ULP Namlea customers who met the predetermined respondent criteria and were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS. The analysis evaluates the measurement model and the direct structural relationships between performance expectancy, effort expectancy, and intention to use PLN Mobile. The findings show that both performance expectancy and effort expectancy positively and significantly influence customers’ intention to use PLN Mobile. Customers are more likely to use the application when they perceive it as useful for supporting their electricity-related needs and easy to understand and operate. The results provide practical implications for improving the functional benefits and usability of PLN Mobile and contribute to research on digital-service adoption in geographically dispersed and island communities.
References
Al Ramdhani, T. D., Hurriyati, R., & Hendrayati, H. (2024). UTAUT model acceptance on consumers’ behavioral intention to use cellular digital application. In Proceedings of the International Conference on Economics, Business and Management (pp. 489–495). https://doi.org/10.2991/978-94-6463-234-7_49
Al-Saedi, K., Al-Emran, M., Ramayah, T., & Abusham, E. (2020). Developing a general extended UTAUT model for M-payment adoption. Technology in Society, 62, 101293. https://doi.org/10.1016/j.techsoc.2020.101293
Candra, S., Frederica, E., Putri, H. A., & Loang, O. K. (2024). The UTAUT approach to Indonesia’s behavioral intention to use mobile health apps. Journal of Science and Technology Policy Management, 16(5), 892–911. https://doi.org/10.1108/JSTPM-10-2022-0175
Farras, H., Ridha, Z., Indah, & Kusumasari, R. (2025). Peningkatan keterampilan digital masyarakat melalui pemberdayaan aplikasi PLN Mobile di PLN ULP Bojonegoro. Jurnal Sinabis. https://jsinabis.upnjatim.ac.id/index.php/jsinabis
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). 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
Indarti, S., Darmi, T., Adriadi, R., & Universitas Muhammadiyah Bengkulu. (2025). Implementasi program aplikasi PLN Mobile di PT PLN (Persero) ULP Curup. Sengkuni Journal, 6(1), 107–112. https://doi.org/10.37638/sengkuni.6.1.107-112
Jadil, Y., Rana, N. P., & Dwivedi, Y. K. (2021). A meta-analysis of the UTAUT model in the mobile banking literature: The moderating role of sample size and culture. Journal of Business Research, 132, 354–372. https://doi.org/10.1016/j.jbusres.2021.04.052
Lai, C. Y., Cheung, K. Y., & Pang, L. L. L. (2024). Examining the motivators affecting acceptance towards learning management systems for sustainable learning amid COVID-19 pandemic. Frontiers in Education, 9, 1365258. https://doi.org/10.3389/feduc.2024.1365258
Makarim, T. N., Hadi, H. K., Fachmi, M., & Kautsar, A. (2025). Pengaruh performance expectancy dan effort expectancy terhadap e-commerce adoption usage melalui behavioral intention. Indonesian Journal of Digital Business. https://ejournal.upi.edu/index.php/IJDB
Matheis, T. K., Lehnhart, E. dos R., Costa, A. C. C., Tontini, J., & Vieira, K. M. (2026). Analysis of the determinants of behavioral intention to use digital financial channels: User perspectives. Future Business Journal, 12(1), 59. https://doi.org/10.1186/s43093-026-00769-x
Mensah, I. K., & Khan, M. K. (2024). Unified Theory of Acceptance and Use of Technology (UTAUT) model: Factors influencing mobile banking services’ adoption in China. SAGE Open, 14(1), 1–18. https://doi.org/10.1177/21582440241234230
Ngusie, H. S., Kassie, S. Y., Zemariam, A. B., Walle, A. D., Enyew, E. B., Kasaye, M. D., Seboka, B. T., & Mengiste, S. A. (2024). Understanding the predictors of health professionals’ intention to use electronic health record system: Extend and apply UTAUT3 model. BMC Health Services Research, 24, 889. https://doi.org/10.1186/s12913-024-11378-1
Nurbaiti, S., Wihara, D. S., Amelia, R., & Hadi, H. K. (2026). Performance expectancy, effort expectancy, hedonic motivation and habit on behavioral intention of PLN Mobile usage among Generation Z in Solo Raya. Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA), 10(2), 2710–2727. https://doi.org/10.31955/mea.v10i2.7796
Paramita, E. D., & Cahyadi, E. R. (2024). The determinants of behavioral intention and use behavior of QRIS as digital payment method using extended UTAUT model. Indonesian Journal of Business and Entrepreneurship, 10(1), 132. https://doi.org/10.17358/ijbe.10.1.132
Praditya, L. I. H., Az-Zahra, H. M., & Arwani, I. (2021). Identify usability problems in the Halodoc mobile application using the usability testing method. Journal of Information Technology and Computer Science Development, 5(9), 78–87.
Priyastomo, P., Nimran, U., Prasetya, A., & Noerman, T. (2025). The effect of performance expectancy, effort expectancy, facilitating conditions on behavioral intention to use and their impact on usage behavior moderated by trust: A study on BRISPOT application users in the small and medium business segment of Bank BRI. Management, 3, 291. https://doi.org/10.62486/agma2025291
Purwanto, E., & Loisa, J. (2020). The intention and use behaviour of the mobile banking system in Indonesia: UTAUT model. https://www.researchgate.net/publication/343230847
Rachmad, Y. E., Bakri, A. A., Nuraini, R., Nurdiani, T. W., & Kushariyadi. (2024). Application of the Unified Theory of Acceptance and Use of Technology method to analyze factors influencing the use of digital wallets in Indonesia. Jurnal Informasi dan Teknologi, 6(1), 229–234. https://doi.org/10.60083/jidt.v6i1.504
Rizkalla, N., Tannady, H., & Bernando, R. (2023). Analysis of the influence of performance expectancy, effort expectancy, social influence, and attitude toward behavior on intention to adopt live.on. Multidisciplinary Reviews, 6(Special Issue). https://doi.org/10.31893/multirev.2023spe017
Shunmugasundaram, V., Srivastava, S., & Devi, P. (2025). A study on understanding QR-based m-payment adoption intention and satisfaction among consumers in India. European Journal of Management Studies, 1–22. https://doi.org/10.1108/EJMS-03-2025-0024
Siti Akromah, & Kusumasari, I. R. (2023). Penerapan aplikasi PLN Mobile dalam meningkatkan pelayanan pelanggan PLN ULP Bojonegoro Kota. Jurnal Masyarakat Mengabdi Nusantara, 2(2), 105–116. https://doi.org/10.58374/jmmn.v2i2.154
Timur, Y. P., Ratnasari, R. T., Pitchay, A. A., Sari, D. P., & Rifqi, M. (2024). Factors influencing behavioral intention to apply freemium services in Islamic lifestyle digital applications using Unified Theory of Acceptance and Use of Technology (UTAUT). Journal of Information Systems Engineering and Business Intelligence, 10(3), 340–354. https://doi.org/10.20473/jisebi.10.3.340-354
Tusyanah, T., Wahyudin, A., & Khafid, M. (2021). Analyzing factors affecting the behavioral intention to use e-wallet with the UTAUT model with experience as moderating variable. Journal of Economic Education, 10(2), 113–123. http://journal.unnes.ac.id/sju/index.php/jeec
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://aisel.aisnet.org/misq/vol27/iss3/5
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.
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