PERSEPSI MASYARAKAT PERKOTAAN TERHADAP LAYANAN SMART CITY: MODEL UTAUT2
Keywords:
smart city, technology readiness, UTAUT2, PLS-SEMAbstract
In this study, we look at technology readiness related to performance expectancy and effort expectancy from UTAUT2 to analyze urban community perceptions of smart city services. Data is collected using a survey questionnaire. We use Partial Least Square Structural Equation Modeling (PLS-SEM) analysis. The questionnaire consists of 16 items on the Technology Readiness Index 2.0 scale to measure technological readiness and the UTAUT2 scale which has 29 items. The research of the study shows that optimism has a positive effect on performance expectancy and effort expectancy in using smart services. This means that respondents believe and have a sense of optimism that smart city service technology will be understood and used. Effort expectancy, facilitation conditions, and hedonic motivation have a positive effect on the intention to use smart services. It can be said that although some users are anxious about the new technology, it will not have an impact on the usability and ease of use of smart service technology.Downloads
References
Smart Meter in Malaysia: The Effect of Electricity-Saving Knowledge and Environmental Awareness. IEEE Access, 8, 42794–42804. https://doi.org/10.1109/ACCESS.2020.2977060
Anggraini, A. T., & Iqbal, M. (2020). The Uttilization of Jogja Smart Service Application: an E-Readiness Approach. Journal of Governance and Public Policy, 7(2), 150–159. https://doi.org/10.18196/jgpp.72130
Arasteh, H., Hosseinnezhad, V., Loia, V., Tommasetti, A., Troisi, O., Shafie-khah, M., & Siano, P. (2016). Iot-based smart cities: A survey. 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), 1–6. https://doi.org/10.1109/EEEIC.2016.7555867
Armawi, A., Danugroho, A., Apriliyanti, K., & Asrofi, A. (2022). Smart Environment Program ’ s Traffic Management to Achieve Semarang City Resilience. Journal of Governance and Public Policy, 9(3), 171–184.
Arpaci, I. (2016). Understanding and predicting students’ intention to use mobile cloud storage services. Computers in Human Behavior, 58, 150–157. https://doi.org/10.1016/j.chb.2015.12.067
Asyraf, W. M., & Afthanorhan, B. W. (2013). A comparison of partial least square structural equation modeling (PLS-SEM) and covariance based structural equation modeling (CB-SEM) for confirmatory factor analysis. International Journal of Engineering Science and Innovative Technology (IJESIT), 2(5), 198–205.
Awang, Z., Afthanorhan, A., & Mamat, M. (2016). The Likert scale analysis using parametric based Structural Equation Modeling (SEM). Computational Methods in Social Sciences, 4(1), 13–21. https://doi.org/10.5281/zenodo.1299429
Turok, I., & McGranahan, G. (2013). Urbanization and economic growth: the arguments and evidence for Africa and Asia. Environment and Urbanization, 25(2), 465–482. https://doi.org/10.1177/0956247813490908
Venkatesh, Thong, & Xu. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157. https://doi.org/10.2307/41410412
Washburn, D., & Sindhu, U. (2009). Helping CIOs Understand “Smart City” Initiatives. Growth,
