Public Perceptions of Perceived Value of "Smart Kampung" in Facilitating Public Participation in Banyuwangi

Priangga Eko Saputra; Titis Shinta Dhewi; Ita Prihatining Wilujeng; Naufal Dzakwana Muhammad

doi:10.55927/ajabm.v4i3.428

Authors

Priangga Eko Saputra Universitas Negeri Malang
Titis Shinta Dhewi Universitas Negeri Malang
Ita Prihatining Wilujeng Universitas Negeri Malang
Naufal Dzakwana Muhammad Universitas Negeri Malang

DOI:

https://doi.org/10.55927/ajabm.v4i3.428

Keywords:

Smart Village, Internet of Things, Theory Acceptance Model, public participation, Banyuwangi

Abstract

This study analyzes Banyuwangi residents' perceptions of the IoT-based Smart Kampung program's perceived value in facilitating public participation using the Technology Acceptance Model (TAM) framework. The research examines perceived usefulness, empowerment, information privacy, and information social support on value perceptions and continuous use intentions. The methodology employs quantitative explanatory research with 200 respondents. Analyzed using Structural Equation Modeling (SEM) based on Partial Least Squares (PLS). Results reveal empowerment as the dominant factor forming perceived value, followed by perceived usefulness, while information privacy and social support showed limited significance. Perceived value demonstrated strong correlation with continuous use intention. Multi-group analysis revealed gender differences in technology evaluation pathways, highlighting the importance of user empowerment in sustainable IoT adoption.

References

Acikgoz, F., Busalim, A., Gaskin, J., & Asadi, S. (2023). An Integrated Model for Information Adoption&Trust in Mobile Social Commerce. Journal of Computer Information Systems, 64, 797–819. https://doi.org/10.1080/08874417.2023.2251449

Ahmad., H., & Halim, H. (2017). Determining Sample Size for Research Activities. 2, 20–34. https://consensus.app/papers/determining-sample-size-for-research-activities-halim-ahmad/d0207ac9086b5f48afc4cb901cac1c89/

Burmeister, E., & Aitken, L. (2012). Sample size: how many is enough? Australian Critical Care : Official Journal of the Confederation of Australian Critical Care Nurses, 25 4, 271–274. https://doi.org/10.1016/j.aucc.2012.07.002

Chan, C., Burton, K., & Flower, R. (2024). Facilitators and barriers of technology adoption and social connectedness among rural older adults: a qualitative study. Health Psychology and Behavioral Medicine, 12. https://doi.org/10.1080/21642850.2024.2398167

Chatterjee, S. (2022). Antecedents of Behavioral Intention Impacting Human Behavior to Use IoT-Enabled Devices: An Empirical Investigation. Int. J. Technol. Hum. Interact., 18, 1–19. https://doi.org/10.4018/ijthi.300284

Chohan, S. R., Hu, G., Khan, A., Pasha, A. T., Saleem, F., & Sheikh, M. A. (2021). IoT as societal transformer: improving citizens’ continuous usage intention in digital society through perceived public value. Libr. Hi Tech, 41, 1214–1237. https://doi.org/10.1108/lht-05-2021-0156

Davis, C. (2000). Death in Abeyance. https://doi.org/10.1515/9780585445212

Davis, F. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Q., 13, 319–340. https://doi.org/10.2307/249008

Dong, H., Wang, H., & Han, J. (2022). Understanding Ecological Agricultural Technology Adoption in China Using an Integrated Technology Acceptance Model—Theory of Planned Behavior Model. 10. https://doi.org/10.3389/fenvs.2022.927668

Duan, Y. (2024). Can digital empowerment enhance the brand value of China’s enterprises? Technology Analysis & Strategic Management. https://doi.org/10.1080/09537325.2024.2358444

Dutta, A., Kovid, R., Drave, V., & Bhatia, M. S. (2023). Internet of Things adoption: unpacking the role of perceived brand credibility. Global Knowledge, Memory and Communication. https://doi.org/10.1108/gkmc-05-2023-0160

El-Haddadeh, R. (2019). Digital Innovation Dynamics Influence on Organisational Adoption: The Case of Cloud Computing Services. Information Systems Frontiers, 22, 985–999. https://doi.org/10.1007/s10796-019-09912-2

Fehrenbach, D., & Herrando, C. (2021). The effect of customer-perceived value when paying for a product with personal data: A real-life experimental study. Journal of Business Research, 137, 222–232. https://doi.org/10.1016/J.JBUSRES.2021.08.029

Granić, A., & Marangunic, N. (2019). Technology acceptance model in educational context: A systematic literature review. Br. J. Educ. Technol., 50, 2572–2593. https://doi.org/10.1111/BJET.12864

Handarkho, Y. D. (2024). Factors affecting user intention to use social commerce continuously from a habit perspective. Aslib Journal of Information Management. https://doi.org/10.1108/ajim-02-2024-0111

Hashim, H. S., & Al-Sulami, Z. A. (2020). A Model Of Factors Influencing Users’ Adoption Of Internet Of Things Services: A Case Study Of Iraqi Educational Institutions. IOP Conference Series: Materials Science and Engineering, 769. https://doi.org/10.1088/1757-899X/769/1/012006

Hsieh, S., Lee, C., & Tseng, T. (2021). Psychological empowerment and user satisfaction: Investigating the influences of online brand community participation. Inf. Manag., 59, 103570. https://doi.org/10.1016/j.im.2021.103570

Hsu, C.-L., & Lin, J. C.-C. (2018). Exploring Factors Affecting the Adoption of Internet of Things Services. Journal of Computer Information Systems, 58, 49–57. https://doi.org/10.1080/08874417.2016.1186524

Hsu, H., Liu, F., Tsou, H., & Chen, L.-J. (2019). Openness of technology adoption, top management support and service innovation: a social innovation perspective. Journal of Business & Industrial Marketing. https://doi.org/10.1108/JBIM-03-2017-0068

Hu, B., Liu, Y.-L., & Yan, W. (2023). Should I scan my face? The influence of perceived value and trust on Chinese users’ intention to use facial recognition payment. Telematics Informatics, 78, 101951. https://doi.org/10.2139/ssrn.4061630

Hu, G., Chohan, S. R., & Liu, J. (2020). Does IoT service orchestration in public services enrich the citizens’ perceived value of digital society? Asian Journal of Technology Innovation, 30, 217–243. https://doi.org/10.1080/19761597.2020.1865824

Joo, D., Woosnam, K., Strzelecka, M., & Boley, B. (2020). Knowledge, empowerment, and action: testing the empowerment theory in a tourism context. Journal of Sustainable Tourism, 28, 69–85. https://doi.org/10.1080/09669582.2019.1675673

Junglas, I., Goel, L., Rehm, S.-V., & Ives, B. (2022). On the benefits of consumer IT in the workplace - An IT empowerment perspective. Int. J. Inf. Manag., 64, 102478. https://doi.org/10.1016/j.ijinfomgt.2022.102478

Kervenoael, R., Hasan, R., Schwob, A., & LePaih, V. (2023). Consumers’ perceived value of Social IoT based online community: investigating social awareness processes surrounding smart kitchen robot appliances. Behaviour & Information Technology, 43, 3071–3090. https://doi.org/10.1080/0144929X.2023.2270713

Kowalczuk, P., & Hof, N. (2025). The customer’s perceived value-in-use of voice-assisted smart products and its impact on continuance intention: a trade-off between benefits and costs. Journal of Product & Brand Management. https://doi.org/10.1108/jpbm-08-2023-4670

Lakens, D. (2021). Sample Size Justification. Collabra: Psychology. https://doi.org/10.31234/osf.io/9d3yf

Li, L., Pongsakornrungsilp, S., Pongsakornrungsilp, P., & Jiang, Y. (2024). The Influence of Social Support on Customer Engagement in Live Streaming Commerce: The Mediating Role of Perceived Value. TEM Journal. https://doi.org/10.18421/tem134-21

Liu, D., Li, Q., & Han, S. (2022). Using Extended Technology Acceptance Model to Assess the Adopt Intention of a Proposed IoT-Based Health Management Tool. Sensors (Basel, Switzerland), 22. https://doi.org/10.3390/s22166092

Liu, S., Xiao, W., Fang, C., Zhang, X., & Lin, J. (2020). Social support, belongingness, and value co-creation behaviors in online health communities. Telematics Informatics, 50, 101398. https://doi.org/10.1016/j.tele.2020.101398

Mundfrom, D., Shaw, D., & Ke, T.-L. (2005). Minimum Sample Size Recommendations for Conducting Factor Analyses. International Journal of Testing, 5, 159–168. https://doi.org/10.1207/s15327574ijt0502_4

Nahida, S. (2024). Integration of TAM in IoT (Internet of Things) adoption: The Mediating Role of Service Quality. Bangladesh Journal of MIS. https://doi.org/10.61606/bjmis.v10n1.a1

Nguyen, T. (2021). Continuance Intention in Traffic-Related Social Media: A Privacy Calculus Perspective. Journal of Internet Commerce, 20, 215–245. https://doi.org/10.1080/15332861.2021.1875764

Oh, J., Kwon, S.-S., & Lee, H. (2023). Do IoT Users Trade off their Information Privacy? 4182–4190. https://doi.org/10.24251/hicss.2023.511

Pandharipande, A. (2021). Social Sensing in IoT Applications: A Review. IEEE Sensors Journal, 21, 12523–12530. https://doi.org/10.1109/JSEN.2021.3049714

Princi, E., & Krämer, N. (2020). Out of Control – Privacy Calculus and the Effect of Perceived Control and Moral Considerations on the Usage of IoT Healthcare Devices. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.582054

Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Comput. Educ., 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009

Sharef, B. (2022). The Usage of Internet of Things in Agriculture: The Role of Size and Perceived Value. Informatica (Slovenia), 46. https://doi.org/10.31449/inf.v46i7.4275

Siddiqui, K. (2013). Heuristics for Sample Size Determination in Multivariate Statistical Techniques. https://consensus.app/papers/heuristics-for-sample-size-determination-in-multivariate-siddiqui/5c60fd32d8695d82bb3c3b4dd06e1755/

Sun, Y., Zhong, Y., Jeyaraj, A., & Zhu, M. (2024). The impact of enterprise social media affordances on employees’ thriving at work: An empowerment theory perspective. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2023.122983

Tie, D. (2019). Purchase Intention towards IoT Smart Homes in Malaysia:A Value-Based Adoption Model. Journal of Contemporary Issues in Business and Government. https://doi.org/10.47750/cibg.2021.27.03.053

Usman, B., Sentosa, I., & Nurrahmi, F. (2021). Structural equation modeling of internet of things (IoT) adoption for Indonesian Village-Owned Enterprises (BUMDes). Informasi. https://doi.org/10.21831/informasi.v51i1.40170

Venkatesh, V., & Davis, F. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46, 186–204. https://doi.org/10.1287/MNSC.46.2.186.11926

Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User Acceptance of Information Technology: Toward a Unified View. Institutions & Transition Economics: Microeconomic Issues EJournal. https://doi.org/10.2307/30036540

Wiafe, I., Koranteng, F., Kastriku, F., & Gyamera, G. (2020). Assessing the impact of persuasive features on user’s intention to continuous use: the case of academic social networking sites. Behaviour & Information Technology, 41, 712–730. https://doi.org/10.1080/0144929X.2020.1832146

Xie, J., Ye, L., Huang, W., & Ye, M. (2021). Understanding FinTech Platform Adoption: Impacts of Perceived Value and Perceived Risk. J. Theor. Appl. Electron. Commer. Res., 16, 1893–1911. https://doi.org/10.3390/JTAER16050106