Analysis of the Effectiveness of AI-Based Public Service Digitalization Policies in Improving Public Satisfaction
Keywords:
AI-Based Digitalization, Public Service Policy, Public Satisfaction, E-Government, Service QualityAbstract
Public service quality remains a critical issue in many countries, where traditional bureaucratic systems are often characterized by inefficiency, limited accessibility, and low levels of public satisfaction. In response, governments have increasingly adopted digitalization strategies, including the integration of Artificial Intelligence (AI), to improve service delivery. This study aims to analyze the effectiveness of AI-based public service digitalization policies in increasing public satisfaction. The research employs a quantitative approach using a survey method, with data collected through questionnaires distributed to users of digital public services. The data are analyzed using descriptive statistics and regression analysis to examine the relationship between AI-based digitalization and public satisfaction. The results indicate that AI implementation significantly improves service efficiency, accuracy, accessibility, and transparency, which in turn positively influences public satisfaction. Among these factors, service speed and ease of access are identified as the most dominant contributors. However, challenges such as digital literacy gaps and technical issues are also identified. In conclusion, AI-based public service digitalization policies are effective in enhancing public satisfaction, although their success depends on supporting factors such as infrastructure readiness, user capability, and system reliability.
References
Alawneh, A., Al-Refai, H., & Batiha, K. (2013). Measuring user satisfaction from e-Government services: Lessons from Jordan. Government Information Quarterly, 30(3), 277–288.
Chen, T., Guo, W., Gao, X., & Liang, Z. (2021). AI-based self-service technology in public service delivery: User experience and influencing factors. Government Information Quarterly, 38(4), 101520.
Cheng, Y., & Jiang, H. (2020). How do AI-driven chatbots impact user experience? Examining gratifications, perceived privacy risk, satisfaction, loyalty, and continued use. Journal of Broadcasting & Electronic Media, 64(4), 592–614.
Eller, R., Alford, P., Kallmünzer, A., & Peters, M. (2020). Antecedents, consequences, and challenges of small and medium-sized enterprise digitalization. Journal of Business Research, 112, 119–127.
Gesk, T. S., & Leyer, M. (2022). Artificial intelligence in public services: When and why citizens accept its usage. Government Information Quarterly, 39(3), 101704.
Ho, D. C. W., Lai, L. W. C., & Wang, A. (2021). The effects of ‘publicness’ and quality of publicly accessible open space upon user satisfaction. Environment and Planning B: Urban Analytics and City Science, 48(4), 861–879.
Humerick, M. (2017). Taking AI personally: how the EU must learn to balance the interests of personal data privacy & artificial intelligence. Santa Clara High Tech. LJ, 34, 393.
Kar, S., Kar, A. K., & Gupta, M. P. (2021). Modeling drivers and barriers of artificial intelligence adoption: Insights from a strategic management perspective. Intelligent Systems in Accounting, Finance and Management, 28(4), 217–238.
Lala, G. (2014). The emergence and development of the technology acceptance model (TAM). Marketing from Information to Decision, 7, 149–160.
Lanin, D., & Hermanto, N. (2019). The effect of service quality toward public satisfaction and public trust on local government in Indonesia. International Journal of Social Economics, 46(3), 377–392.
Milakovich, M. E. (2012). Digital governance: New technologies for improving public service and participation. Routledge.
Misuraca, G., Van Noordt, C., & Boukli, A. (2020). The use of AI in public services: Results from a preliminary mapping across the EU. Proceedings of the 13th International Conference on Theory and Practice of Electronic Governance, 90–99.
Mohajan, H. K. (2020). Quantitative research: A successful investigation in natural and social sciences. Journal of Economic Development, Environment and People, 9(4), 50–79.
Newman, J., Mintrom, M., & O’Neill, D. (2022). Digital technologies, artificial intelligence, and bureaucratic transformation. Futures, 136, 102886.
Nirala, K. K., Singh, N. K., & Purani, V. S. (2022). A survey on providing customer and public administration based services using AI: chatbot. Multimedia Tools and Applications, 81(16), 22215–22246.
Puchakayala, P. R. (2022). Responsible AI Ensuring Ethical, Transparent, and Accountable Artificial Intelligence Systems. Journal of Computational Analysis and Applications, 30(1), 208–221.
Sabeh, H. N., Husin, M. H., Kee, D. M. H., Baharudin, A. S., & Abdullah, R. (2021). A systematic review of the DeLone and McLean model of information systems success in an E-learning context (2010–2020). Ieee Access, 9, 81210–81235.
Safarov, N. (2021). Personal experiences of digital public services access and use: Older migrants’ digital choices. Technology in Society, 66, 101627.
Shneiderman, B. (2020). Human-centered artificial intelligence: Reliable, safe & trustworthy. International Journal of Human–Computer Interaction, 36(6), 495–504.
Spring, M., Faulconbridge, J., & Sarwar, A. (2022). How information technology automates and augments processes: Insights from Artificial‐Intelligence‐based systems in professional service operations. Journal of Operations Management, 68(6–7), 592–618.
Statistics, L. (2013). Descriptive and inferential statistics. Retrieved From.
Susar, D., & Aquaro, V. (2019). Artificial intelligence: Opportunities and challenges for the public sector. Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance, 418–426.
Vassilakis, C., Lepouras, G., Fraser, J., Haston, S., & Georgiadis, P. (2005). Barriers to electronic service development. E-Service, 4(1), 41–63.
시암술. (2021). A Research on The Factors That Influence The Adoption of AI-Based Public Services in The Indonesian Government. 서울대학교 대학원.
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