Technology Adoption of Utility Mobile Applications across Generational Cohorts Using UTAUT: A PLS-SEM Approach
DOI:
https://doi.org/10.26877/asset.v8i1.2368Keywords:
Behavioral Intention, UTAUT, PLS-SEM, Mobile Utility Platform, Technology AdoptionAbstract
This study examines the determinants of users’ intention to adopt the PLN Mobile application among Generations X, Y, and Z in East Nusa Tenggara, Indonesia, by extending the Technology Acceptance Model (TAM) with additional constructs, including perceived value, perceived trust, perceived security, attractiveness of alternatives, and social influence, with generational cohort as a moderating variable. A quantitative causal design was applied, collecting data from 438 PLN customers using proportional stratified sampling across four regional offices. Data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results revealed that perceived ease of use (β = 0.322, p < 0.001), social influence (β = 0.268, p < 0.001), and perceived security (β = 0.194, p < 0.01) had significant positive effects on intention to use, while perceived value, perceived trust, and perceived usefulness were not significant predictors. Social influence also significantly influenced perceived trust (β = 0.531, p < 0.001). Moderation analysis indicated that Generation Y exhibited the strongest moderating effects across most relationships, whereas Generation Z had the least impact. These findings provide actionable insights for public digital service providers, emphasizing the need to enhance ease of use, strengthen security, and leverage peer influence to improve adoption across generational segments.
References
[1] I. N. M. Loda, A. E., & Yasa, “Determinants of Economic Growth and Poverty Levels of Districts/Cities in East Nusa Tenggara Province,” Int. Res. J. Econ. Manag. Stud., vol. 3, no. 8, Aug. 2024, doi: 10.56472/25835238/IRJEMS-V3I8P103.
[2] N. Qatawneh, M. Al-Okaily, R. Alkhasawneh, A. Althonayan, and A. Tarawneh, “The mediating role of e-trust and e-satisfaction in the relationship between e-service quality and e-loyalty toward e-government services,” Global Knowledge, Memory and Communication, 2024
[3] A. Miklosik, N. Evans, and A. M. A. Qureshi, “The use of chatbots in digital business transformation: A systematic literature review,” IEEE Access, vol. 9, pp. 106530–106539, 2021.
[4] S. Fosso Wamba, M. M. Queiroz, L. Wu, and U. Sivarajah, “Big data analytics-enabled sensing capability and organizational outcomes: assessing the mediating effects of business analytics culture,” Ann. Oper. Res., vol. 333, no. 2–3, pp. 559–578, Feb. 2024, doi: 10.1007/s10479-020-03812-4.
[5] M. T. Lee and I. Suh, “Understanding the effects of environment, social, and governance conduct on financial performance: Arguments for a process and integrated modelling approach,” Sustainable Technology and Entrepreneurship, vol. 1, no. 1, p. 100004, 2022.
[6] N. Nuryakin, N. L. P. Rakotoarizaka, and H. G. Musa, “The effect of perceived usefulness and perceived easy to use on student satisfaction: The mediating role of attitude to use online learning,” APMBA (Asia Pacific Management and Business Application), vol. 11, no. 3, pp. 323–336, 2023.
[7] K. Förster, “Extending the technology acceptance model and empirically testing the conceptualised consumer goods acceptance model,” Heliyon, vol. 10, no. 6, p. e27823, Mar. 2024, doi: 10.1016/j.heliyon.2024.e27823.
[8] F. Fachrizal, M. Apsari Sugiat, and I. Yunita, “Key of Customer’s Satisfaction and Loyalty: E-Service Quality, Price, and Trust,” J. Econ. Bus. UBS, vol. 12, no. 6, pp. 3920–3930, Dec. 2023, doi: 10.52644/joeb.v12i6.1281.
[9] V. D. Elwitrisnasafitri and M. Ariyanti, “The Influence Of Instagram Social Media Communication On Purchase Intention Through Brand Equity In Seblak Preanger Jember,” Enrich. J. Multidiscip. Res. Dev., vol. 2, no. 7, Oct. 2024, doi: 10.55324/enrichment.v2i7.159.
[10] F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, no. 3, p. 319, Sep. 1989, doi: 10.2307/249008.
[11] V. Venkatesh and F. D. Davis, “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Manage. Sci., vol. 46, no. 2, pp. 186–204, Feb. 2000, doi: 10.1287/mnsc.46.2.186.11926.
[12] M. Savari and B. Khaleghi, “Promoting safe and pro-environmental behaviors for sustainable forest management: Integrating technology acceptance model and the norm activation model,” Socioecon. Plann. Sci., vol. 98, p. 102158, Apr. 2025, doi: 10.1016/j.seps.2025.102158.
[13] L. Sharma, N. Kaushik, M. Maggon, and B. Sivathanu, “Cognitive and cultural factors in metaverse acceptance: A TAM-based meta-analysis,” Acta Psychol. (Amst)., vol. 254, p. 104855, Apr. 2025, doi: 10.1016/j.actpsy.2025.104855.
[14] Z. J. A. Belmonte, Y. T. Prasetyo, M. M. L. Cahigas, R. Nadlifatin, and M. J. J. Gumasing, “Factors influencing the intention to use e-wallet among generation Z and millennials in the Philippines: An extended technology acceptance model (TAM) approach,” Acta Psychol. (Amst)., vol. 250, p. 104526, Oct. 2024, doi: 10.1016/j.actpsy.2024.104526.
[15] Z. Niu, X. Hu, S. Qi, H. Yang, S. Wang, and S. An, “Determinants to parking mode alternatives: A model integrating technology acceptance model and satisfaction–loyalty model,” Transp. Res. Part A Policy Pract., vol. 152, pp. 216–234, Oct. 2021, doi: 10.1016/j.tra.2021.08.010.
[16] G. Lee and Y. Kim, “Effects of Resistance Barriers to Service Robots on Alternative Attractiveness and Intention to Use,” Sage Open, vol. 12, no. 2, Apr. 2022, doi: 10.1177/21582440221099293.
[17] B. C. Ezeudoka and M. Fan, “Determinants of behavioral intentions to use an E-Pharmacy service: Insights from TAM theory and the moderating influence of technological literacy,” Res. Soc. Adm. Pharm., vol. 20, no. 7, pp. 605–617, Jul. 2024, doi: 10.1016/j.sapharm.2024.03.007.
[18] D. Tenggino and T. Mauritsius, “Evaluation of factors affecting intention to use QRIS payment transaction,” ICIC Express Letters, vol. 16, no. 4, pp. 343–349, 2022.
[19] M. T. Alshurideh, B. Al Kurdi, R. E. Masa’deh, and S. A. Salloum, “The moderation effect of gender on accepting electronic payment technology: A study on United Arab Emirates consumers,” Review of International Business and Strategy, vol. 31, no. 3, pp. 375–396, 2021.
[20] Y. Wu and H. Huang, “Influence of Perceived Value on Consumers’ Continuous Purchase Intention in Live-Streaming E-Commerce—Mediated by Consumer Trust,” Sustainability, vol. 15, no. 5, p. 4432, Mar. 2023, doi: 10.3390/su15054432.
[21] K. Sae-tae and Q. Wang, “Satisfied but no payment: The impact of perceived value on continuance intention and purchase intention in music streaming services,” Telemat. Informatics Reports, vol. 16, p. 100179, Dec. 2024, doi: 10.1016/j.teler.2024.100179.
[22] I. A. Aditya et al., “Understanding service quality concerns from public discourse in Indonesia state electric company,” Heliyon, vol. 9, no. 8, p. e18768, Aug. 2023, doi: 10.1016/j.heliyon.2023.e18768.
[23] A. Van Looy, “A quantitative and qualitative study of the link between business process management and digital innovation,” Inf. Manag., vol. 58, no. 2, p. 103413, Mar. 2021, doi: 10.1016/j.im.2020.103413.
[24] J.-H. Cheah, F. Magno, and F. Cassia, “Reviewing the SmartPLS 4 software: the latest features and enhancements,” J. Mark. Anal., vol. 12, no. 1, pp. 97–107, Mar. 2024, doi: 10.1057/s41270-023-00266-y.
[25] A. England, “Quantitative and Qualitative Research Methods,” in Research for Medical Imaging and Radiation Sciences, Cham: Springer International Publishing, 2021, pp. 71–96. doi: 10.1007/978-3-030-79956-4_5.
[26] S. Rose, N. Spinks, and A. I. Canhoto, Management Research. London: Routledge, 2023. doi: 10.4324/9781003381006.
[27] M. Sarstedt, C. M. Ringle, and J. F. Hair, “Partial Least Squares Structural Equation Modeling,” in Handbook of Market Research, Cham: Springer International Publishing, 2022, pp. 587–632. doi: 10.1007/978-3-319-57413-4_15.
[28] F. L. Zulfiqar, T. Prasetia, and I. G. K. A. Ulupui, “Tax Incentives and Social Spending Amidst COVID-19: A VECM Analysis in a Subnational Government (case of Jakarta province, Indonesia),” J. Tax Reform, vol. 11, no. 1, pp. 243–260, 2025, doi: 10.15826/jtr.2025.11.1.200.
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