Suchergebnisse

This article undertakes a comprehensive study of worldwide literature gathered from the Web of Science database, using bibliometric analysis. The analysis covers all the years, and most publications are from 1988 to 2024. The primary focus of the inquiry centres on the development of public service concept, public services citizens' satisfaction, services' stakeholders, public services' quality and performance during this period. The assessment of public services quality by citizens has been a prominent subject of scholarly investigation for a considerable period of time. By conducting keyword co-occurrence analysis on pertinent literature, our objective was to uncover dominant themes and track trends over a period of time. Novel insights were obtained by generating density, network, and overlay maps using VOS Viewer software. The keyword co-occurrence analysis performed using VOS Viewer unveiled an intricate and interrelated network of study themes within the literature on stakeholders' perceptions of the quality and performance of public services. The study discovered four main clusters, each reflecting separate yet intersecting research topics. An in-depth analysis of these clusters provides significant insights into the emerging patterns and key areas of interest in this subject. This research provides essential insights for both academic and practical applications in public services, establishing a foundation for future investigations.

In the dynamic realm of public services, the integration of artificial intelligence (AI) has emerged as a transformative force, reshaping various sectors, including governance, urban development, healthcare, education, security infrastructure, decision-making processes, and responses to health crises. This article conducts an exploration spanning the years 1984 to 2023, employing bibliometric analysis to analyse global literature retrieved from the Scopus database. The central investigation revolves around the evolution of AI utilisation in public services during this period. Findings indicate a significant surge in AI-related publications, with notable global contributions from countries like China, India, and the United States, and a prevalence of computer science in AI research. Keyword clusters highlight seven prominent themes, ranging from digital governance to modelling health and social welfare in pandemics. Future research directions underscore ethical implications, AI adoption across government agencies, effectiveness in addressing urban challenges, machine learning applications in healthcare and education, security and privacy implications, application in diverse contexts, and AI's role in predicting and managing public health emergencies. This research contributes some necessary information for both academia and practical implementation in public services, laying the groundwork for future studies.