KABUPATEN CILACAP MENUJU SMARTCITY: PENERIMAAN GEN Z-MILLENIAL DALAM VISI CILACAP SMART REGENCY

Authors

  • Muhammad Alfarizi Universitas Bina Nusantara
  • Rafialdo Arifian Universitas Gadjah Mada

DOI:

https://doi.org/10.56655/jid.v2i2.122

Keywords:

millennials , smart city, cilacap smart regency, SEM PLS

Abstract

The development of Cilacap Smart City must consider the needs of its population, even though generally, districts and cities adopt similar Smart City systems. Cilacap is striving to develop Cilacap Smart City with a focus on achieving a balance between urban and rural areas. However, there has been no research on how rural communities, deeply rooted in cultural traditions and local wisdom, respond to this concept. This study aims to uncover the acceptance of the millennial and Gen Z generations in Cilacap towards Smart City, particularly the Cilacap Smart Regency program. In this research, the "Cilacap Smart Regency Millennial-Gen Z Adoption" model based on UTAUT2 theory is employed. The research methodology utilizes an online survey with 163 millennial and Gen Z respondents from Cilacap. Data is analyzed using PLS-SEM techniques and validated for reliability. The research findings indicate that perceptions of security and privacy influence trust in technology, although this trust does not affect the intention to use technology. Self-efficacy and effort expectations influence the intention to use Smart City technology. Trust in the government impacts the perceived value of technology, which in turn affects the intention to use Smart City technology. This study underscores the importance of involving the millennial and Gen Z generations in the development of Cilacap Smart Regency. Other critical factors include robust infrastructure, sustainability, sector collaboration, privacy protection, education, startup support, inclusivity, as well as community evaluation and feedback efforts to achieve success in the Smart City initiative in Cilacap Regency.

References

Alderete, M. V. (2021). Determinants of Smart City Commitment among Citizens from a Middle City in Argentina. Smart Cities, 4(3), 1113–1129. https://doi.org/10.3390/smartcities4030059

Allahar, H. (2020). What are the Challenges of Building a Smart City? Technology Innovation Management Review, 10(9), 38–48. https://doi.org/10.22215/timreview/1388

Alotaibi, L. S., & Alshamrani, S. S. (2021). Smart contract: Security and privacy. Computer Systems Science and Engineering, 38(1), 93–101. https://doi.org/10.32604/CSSE.2021.015547

Apanaviciene, R., Urbonas, R., & Fokaides, P. A. (2020). Smart building integration into a smart city: Comparative study of real estate development. Sustainability (Switzerland), 12(22), 1–22. https://doi.org/10.3390/su12229376

Becker, J.-M., Cheah, J.-H., Gholamzade, R., Ringle, C. M., & Sarstedt, M. (2023). PLS-SEM’s most wanted guidance. International Journal of Contemporary Hospitality Management, 35(1), 321–346. https://doi.org/10.1108/IJCHM-04-2022-0474

Fortuna, F., Rossi, L., Elmo, G. C., & Arcese, G. (2023). Italians and smart working: A technical study on the effects of smart working on the society. Technological Forecasting and Social Change, 187, 122220. https://doi.org/10.1016/j.techfore.2022.122220

Fromhold-Eisebith, M., & Eisebith, G. (2019). What can Smart City policies in emerging economies actually achieve? Conceptual considerations and empirical insights from India. World Development, 123, 104614. https://doi.org/10.1016/j.worlddev.2019.104614

Gansser, O. A., & Reich, C. S. (2021). A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology in Society, 65, 101535. https://doi.org/10.1016/j.techsoc.2021.101535

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2018). The Results of PLS-SEM Article information. European Business Review, 31(1), 2–24.

Hair Jr., J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107. https://doi.org/10.1504/ijmda.2017.10008574

Kociuba, D., Sagan, M., & Kociuba, W. (2023). Toward the Smart City Ecosystem Model. Energies, 16(6), 2795. https://doi.org/10.3390/en16062795

Kock, N. (2018). Should bootstrapping be used in pls-sem? Toward stable p-value calculation methods. Journal of Applied Structural Equation Modeling, 2(1), 1–12. https://doi.org/10.47263/JASEM.2(1)02

Lebrument, N., Zumbo-Lebrument, C., & Rochette, C. (2021). Acceptance of MaaS mobile applications: an application of UTAUT2 in the context of French smart cities. Systèmes d’information et Management, 26(04).

Leong, G. W., Ping, T. A., & Muthuveloo, R. (2017). Antecedents of Behavioural Intention to Adopt Internet of Things in the Context of Smart City in Malaysia. Global Business & Management Research, 9.

Lim, S. B., Malek, J. A., Yussoff, M. F. Y. M., & Yigitcanlar, T. (2021). Understanding and acceptance of smart city policies: Practitioners’ perspectives on the malaysian smart city framework. Sustainability (Switzerland), 13(17). https://doi.org/10.3390/su13179559

Lund, E. K., Nowostawski, M., Satybaldy, A., & Aeinehchi, N. (2019). Privacy-preserving tax-case processing. 2019 17th International Conference on Privacy, Security and Trust, PST 2019 - Proceedings. https://doi.org/10.1109/PST47121.2019.8949072

Palgunadi, S., Hanifah, R., & Wiranto, W. (2016). PEMBUATAN PETA SIMILARITAS KOTA DI PROVINSI JAWA TENGAH MENGGUNAKAN SELF-ORGANIZING MAPS (SOM). Prosiding Seminar Sains Nasional Dan Teknologi, 1(1).

Prabowo, A. S., & Bahroni, I. (2023). IMPLEMENTASI DAYA TARIK WISATA DI KABUPATEN CILACAP MENGGUNAKAN TEKNOLOGI AUGMENTED REALITY BERBASIS ANDROID DALAM RANGKA MEMBANGUN SMART CITY SYSTEM. Jurnal Informatika Upgris, 9(1). DOI: https://doi.org/10.26877/jiu.v9i1.15586

Prasetyo, Y. T., & Santiago, M. A. (2021). Factors Affecting the Well-being of People Working in Known Smart Cities: UTAUT2 Approach. 2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 1270–1274.

Rigdon, E. E., Sarstedt, M., & Ringle, C. M. (2017). On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations. Marketing ZFP, 39(3), 4–16. https://doi.org/10.15358/0344-1369-2017-3-4

Sarker, M. N. I., Khatun, M. N., Alam, G. M. M., & Islam, M. S. (2020). Big Data Driven Smart City: Way to Smart City Governance. 2020 International Conference on Computing and Information Technology, ICCIT 2020. https://doi.org/10.1109/ICCIT-144147971.2020.9213795

Sarstedt, M., Radomir, L., Moisescu, O. I., & Ringle, C. M. (2022). Latent class analysis in PLS-SEM: A review and recommendations for future applications. Journal of Business Research, 138, 398–407. https://doi.org/10.1016/j.jbusres.2021.08.051

Setiadi, T., Ratih, R., & Azhara, S. (2021). Pengembangan dan sosialisasi sistem informasi desa di Desa Panulisan Barat Kabupaten Cilacap Jawa Tengah. Prosiding Seminar Nasional Hasil Pengabdian Kepada Masyarakat Universitas Ahmad Dahlan, 3(1), 52–59.

Sharif, R. Al, & Pokharel, S. (2022). Smart City Dimensions and Associated Risks: Review of literature. Sustainable Cities and Society, 77, 103542. https://doi.org/10.1016/j.scs.2021.103542

Siokas, G., Tsakanikas, A., & Siokas, E. (2021). Implementing smart city strategies in Greece: Appetite for success. Cities, 108, 102938. https://doi.org/10.1016/j.cities.2020.102938

Streukens, S., & Leroi-Werelds, S. (2016). Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results. European Management Journal, 34(6), 618–632. https://doi.org/10.1016/j.emj.2016.06.003

Vidiasova, L., & Cronemberger, F. (2020). Discrepancies in perceptions of smart city initiatives in Saint Petersburg, Russia. Sustainable Cities and Society, 59, 102158. https://doi.org/10.1016/j.scs.2020.102158

Xavier, N., & Oliveira, T. (2016). Factors affecting behavioural intention to adopt e-participation: Extending the UTAUT 2 model. The European Conference on Information Systems Management, 322.

Xiao, J., Han, L., & Zhang, H. (2022). Exploring Driving Factors of Digital Transformation among Local Governments: Foundations for Smart City Construction in China. Sustainability, 14(22), 14980. https://doi.org/10.3390/su142214980

Yang, S., & Chong, Z. (2021). Smart city projects against COVID-19: Quantitative evidence from China. Sustainable Cities and Society, 70, 102897. https://doi.org/10.1016/j.scs.2021.102897

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Published

2023-12-15

How to Cite

Alfarizi, M., & Arifian, R. (2023). KABUPATEN CILACAP MENUJU SMARTCITY: PENERIMAAN GEN Z-MILLENIAL DALAM VISI CILACAP SMART REGENCY . Jurnal Inovasi Daerah, 2(2), 191–202. https://doi.org/10.56655/jid.v2i2.122