Abstract Understanding how citizen satisfaction varies within a fragmented metropolis requires more than a single pooled index. This paper develops a transferable cross‐group MUlticriteria Satisfaction Analysis (MUSA) framework that fits comparable preference‐disaggregation models for municipalities and socio‐geographically grouped municipalities, enabling like‐for‐like comparison of importance and satisfaction on common scales. Its novelty lies in making such comparisons methodologically consistent and substantively interpretable across territorial units, with a policy contribution that is primarily diagnostic and comparative rather than prescriptive. Using an original trilingual survey in the Brussels‐Capital Region, we fit pooled, municipality‐level, and municipality‐group models across four dimensions: mobility and infrastructure, health and education, culture and community, and public safety and order. The pooled model indicates moderate overall satisfaction. Health and education emerges as the most influential and best‐performing dimension, whereas public safety and order combines high importance with the weakest satisfaction. Municipality‐level models reveal substantial spatial dispersion, but because single‐municipality samples are uneven, municipality‐group models provide the main comparative lens. At that level, the results show distinct priority structures: some groups exhibit one dominant high‐importance, low‐performance lever, whereas others require broader multi‐criteria improvement. The framework, therefore, helps identify priority domains within territorial units and benchmark municipalities and municipality groups on a common analytical basis, while making sample imbalance and model uncertainty explicit.

Citizen satisfaction with public services is a fundamental indicator of government effectiveness and democratic legitimacy in Latin America. However, there is little empirical evidence on regional gaps in countries with high territorial heterogeneity such as Peru. The objective of this study was to determine the differences in levels of citizen satisfaction with public services between the country’s coastal, mountain, and jungle regions. A secondary analysis was conducted of the 2024 National Household Survey, corresponding to the Governance, Democracy, and Transparency Module (n = 33,691), evaluating 21 public services using the Citizen Satisfaction Index. Student’s t-tests were applied for comparisons between urban and rural areas, one-factor ANOVA with Bonferroni post-hoc tests for comparisons between geographic domains, and principal component analysis to explore the dimensional structure. The results revealed statistically significant differences between the eight geographic domains (F = 89.57, p < .001, η² = .022); although this effect size is small, indicating that geographic domain accounts for 2.2% of the variance in satisfaction, the patterns are consistent and policy-relevant. The North Coast (M = 3.09) and Amazon (M = 3.13) showed the lowest satisfaction rates, while the Southern Highlands (M = 3.29) even surpassed Metropolitan Lima. Social programs (51.9%) and the Public Prosecutor’s Office (56.4%) obtained the lowest national satisfaction ratings, with the largest regional gaps. Rural areas reported higher satisfaction with public transportation (+7.0%) and public education (+3.5%) than urban areas. A four-dimensional factor structure was identified that explains 46.7% of the variance. It is concluded that territorial gaps are consistent with structural differences in regional institutional capacity, requiring territorially differentiated public policies to reduce inequalities in the provision of state services.

ABSTRACT Transparency, trust, and satisfaction are key components for government–citizen relations that support good governance. This study seeks to explore the “transparency-trust-satisfaction” nexus in the post-pandemic governance, focusing on public trust (mediator) and transformational leadership (moderator) in this relationship. Using survey data (n = 1154), the study conducts moderation and mediation analyses alongside structural equation modeling and sensitivity analysis to test transparency-trust-satisfaction hypotheses. Findings indicate that trust mediates the relationship between local government transparency and citizen satisfaction. Transformational leadership practices appear to enhance the transparency-satisfaction link. The findings support the importance of sustainable good governance in the post-pandemic and digital governance era.

This study analyzes the effectiveness, efficiency, and fairness of public services at the sub-district level in the context of fiscal constraints and institutional capacity. Using a descriptive qualitative research design combined with thematic and spatial analysis, this study assesses how governance innovations, institutional capacity, and basic infrastructure affect public service performance. Data were collected through multiactor interviews, observations, and document analysis involving 45 respondents from three administrative clusters. Results indicate that prioritizing basic needs such as road repairs, clean water access, and public lighting significantly improves public service accessibility and satisfaction, even under budget constraints. Data-driven governance innovations and digital technology increase service efficiency by approximately 35% and strengthen budget accountability. Program sustainability is strongly influenced by cross-period political commitment, staff training, and the existence of a transparent audit trail. Infrastructure quality is positively related to citizen satisfaction (r = 0.72), but maximum impact is achieved when supported by strong human resource capacity and information technology. The integration of public participation and transparency within the New Public Service framework has been shown to strengthen service fairness and responsiveness. This research provides empirical contributions to the development of a sustainable local governance model based on innovation and basic needs, and recommends further research on the integration of spatial and digital indicators in public policy evaluation in rural areas.

ABSTRACT This special issue of Public Management Review seeks to stimulate researchers working on citizen satisfaction with ideas and examples for improving on the currently dominant theory, the expectancy-disconfirmation model (EDM), as well as broadening the range of research designs used. We begin by identifying key areas where citizen satisfaction research is somewhat ‘stuck’. We then draw out key contributions by the articles in this special issue that provide a way forward. Finally, we offer specific suggestions for the next generation of citizen satisfaction research.

This study aims to critically analyze scholarly knowledge on citizen satisfaction with digital public services through a systematic bibliometric literature review, proposing an integrative tripartite framework that addresses technological-functional, psychological-perceptual, and social-contextual determinants while positioning digital inclusion as a cross-cutting moderator. A bibliometric systematic literature review was conducted. The methodology combined bibliometric mapping using Bibliometrix R package with AI-assisted full-text content analysis using GPT-4o to classify determinants and theoretical constructs across the tripartite framework. The analysis reveals a significant imbalance in research focus. The framework provides public managers with a structured lens to evaluate digital service performance beyond traditional metrics.

This article analyzes the strategic role and substantive challenges of public administration in implementing quality public services in the digital era. Based on a literature review, this study synthesizes findings on how digital transformation, e-government, and smart governance reshape the functions of public administration as a manager of public value, rather than merely an executor of bureaucratic procedures. The analysis shows that digitalization contributes to increased efficiency, accessibility, transparency, and citizen satisfaction, but its impact is highly determined by the quality of governance, institutional capacity, and human resource readiness. The main challenges identified include gaps in infrastructure and digital literacy, bureaucratic resistance to change, regulatory fragmentation, as well as cybersecurity risks and personal data protection. This article emphasizes that digital technology only becomes an enabler of service quality if integrated with institutional reform, strengthening of civil servants' digital competence, an adaptive regulatory framework, and inclusive citizen participation mechanisms. Artikel ini mengajukan rekomendasi kebijakan berupa penguatan visi digital government yang terintegrasi, systematic capacity building and digital literacy, strengthening cyber security governance and data protection, as well as developing a smart governance model that positions citizens as co-producers of public services

Purpose: Information Technology (IT) application within the public sector has brought some revolution to the delivery of public services in the world particularly with the emergence of e-government and digital government projects. In developing countries like Pakistan, IT is becoming a significant facilitator to improve efficiency, transparency, accessibility, and accountability in service delivery. This study examines how IT has helped in enhancing the service delivery in the public sector in Pakistan, by empirically evaluating the impact that IT has on the efficiency of the public sector, transparency, accessibility and citizen satisfaction. Methodology: This paper has used quantitative research design where the main data was gathered in a sample of 200; divided into employees of the public sector and active users of electronic government services (citizens). The questionnaire employed by the researchers had a 5-point Likert scale. The researchers test the hypotheses and evaluate the direct and indirect effects using Structural Equation Modeling (SEM) and Partial Least Squares (PLS-SEM) (Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., &amp; Ray, S. 2021). Findings: The findings of the study indicate that IT utilization has a positive effect on efficiency, transparency and accessibility of organizations in the public sector. This in its turn improves the services of the government and satisfaction by its citizens. However, the research also shows that there are still some challenges, including the absence of digital infrastructure, digital divide in urban and rural regions, and the problem of cybersecurity and privacy of data. Implications: This study contributes to the existing body of knowledge on digital governance and information systems, by providing empirical evidence based on a developing nation lens, in this case, Pakistan. It also carries practical implications to policymakers, in the sense that it recommends more investment on the digital infrastructure, capacity building and cybersecurity systems to facilitate the successful implementation of e-government systems.

Thispaperpresentsacomprehensiveand intelligent Smart city Grievance Management System aimed at transforming the traditional complainthandling process into an automated, efficient, and transparent workflow. The system integrates advanced technologies such as Natural language processing (NLP), Machine Learning -based classification, Cosine similarity-based duplicate detection, and service level Agreement (SLA) driven escalation mechanism. Citizens can register complaints related to civic issues including road damage, drainage blockage, water leakage, streetlight failures, and sanitation concerns. The proposed system automatically categorizes complaints, assign priorities, detects duplicates, and forwardthem to appropriate departments. Experiment evaluation demonstrates improved efficiency, reduced redundancy, and enhanced citizen satisfaction.

Municipal complaint management systems traditionally rely on manual processes that are inefficient, error-prone, and lack real-time transparency. This paper presents an NLP-Enhanced Intelligent Complaint Management System for Municipal Services that leverages Natural Language Processing (NLP) and machine learning techniques to automate the classification, prioritization, and routing of citizen complaints. The proposed system processes complaints submitted via web platforms and applies text preprocessing, feature extraction using TF-IDF and word embeddings, complaint classification, sentiment analysis, and automated routing to the appropriate departments. The system provides officers with a dashboard to track and update complaint statuses, while citizens receive real-time notifications. Experimental evaluation demonstrates that the proposed system significantly reduces manual processing time, improves classification accuracy, and enhances citizen satisfaction. The work draws inspiration from the Traffic Urgency Model (TUM) proposed for Indonesian traffic complaints and extends the concept to a broader municipal services domain using a robust NLP pipeline.

In the era of rapid urbanization, effective management of citizen grievances has become crucial for ensuring responsive governance and sustainable development, particularly in a developing country like India. Municipal authorities frequently encounter a growing number of complaints related to sanitation, water supply, damaged roads, and public infrastructure, while traditional complaint handling methods based on manual records and in-person visits often lead to inefficiencies, delays, and lack of transparency. To address these challenges, the proposed system, ReportBox – A Complaint Management System (CMS), offers a mobile-based digital solution that streamlines the entire grievance redressal process. Built using React Native for cross-platform accessibility and supported by a Node.js backend with MongoDB, the system enables citizens to securely register complaints with GPS-tagged locations and image evidence and track their status in real time. Field workers receive automated task assignments and update progress with proof of resolution, while administrators manage operations through a centralized dashboard for monitoring, analytics, and decision-making. By automating the complete complaint lifecycle, ReportBox enhances efficiency, transparency, and communication, ultimately improving service delivery, increasing citizen satisfaction, and strengthening public trust in governance.

Social media platforms have long acted as sensors for monitoring the city's pulse and citizen satisfaction. Our initial studies have shown that machine learning classifiers can identify citizen issues, but turning these algorithms into a working decision-support system requires a solid framework. This work outlines the complete lifecycle of a scalable web portal designed to collect, store, and analyze Twitter data from Türkiye's Aegean Region. We explain the high-performance computing setup, the linguistic analysis of Turkish social media posts, and the launch of a public interface for real-time visualization. This paper also examines the major changes in social media research following the shift from Twitter to X. We discuss the reliability of our findings in light of the end of the free Academic Research API, highlighting how these new financial pressures create significant challenges for similar future studies. The details of the system developed in our project using open-source tools have already been documented. This work not only provides a guide to technical setup but also highlights the growing value of archived regional datasets during a period of limited data access. The results show that, despite these changing challenges, using natural language processing (NLP) and big data architecture remains essential for local administrators.

ABSTRACT Substantive justice in policing focuses on the fairness of citizen-police encounter outcomes. Yet, much remains unknown about how substantive justice affects satisfaction with the police. This study provides the first quantitative examination of how substantive justice shapes public satisfaction with the police. The findings not only affirm the importance of substantive justice as the most influential factor in citizen satisfaction with the police but also uncover an additional dimension: substantive justice serves as a key mechanism underlying the differential levels of satisfaction with the police reported by Indigenous and non-Indigenous peoples. It is concluded that Indigenous people’s lower satisfaction reflects not only their marginalised social position but also persistent differential treatment by some police officers. This pattern of unequal treatment, resulting from what is termed the residual effect of “rotten apples,” warrants further investigation in other social and institutional contexts.

Community policing reforms have gained renewed attention as strategies aimed at improving police–community relations, enhancing legitimacy, and addressing crime through collaborative problem-solving. This study synthesizes evidence on what works in community policing, where reforms are most effective, and the unintended consequences that may arise during implementation. Drawing on empirical research across urban and rural settings, the analysis examines the theoretical foundations of community policing, including problem-oriented policing, community engagement, decentralization, and partnership-based governance. Evidence suggests that while community policing often improves public trust, citizen satisfaction, and perceptions of police legitimacy, its impact on crime reduction remains modest and context dependent. The effectiveness of these reforms varies according to geographic setting, socioeconomic conditions, governance capacity, and the level of sustained community involvement. Urban initiatives frequently demonstrate stronger outcomes due to greater opportunities for structured engagement, whereas rural settings face unique structural and resource constraints that influence reform implementation. The review also highlights the importance of contextual moderators such as neighborhood demographics, economic resources, and local institutional capacity. In addition, unintended consequences, including increased policing footprints, potential civil liberties concerns, and uneven distribution of policing resources, may undermine reform objectives if not carefully managed. Effective community policing, therefore, requires evidence-based policy design, rigorous evaluation methods, and strong accountability mechanisms. Overall, the findings emphasize that community policing should be implemented as a flexible, context-sensitive framework supported by continuous assessment, community participation, and ethical safeguards to ensure sustainable improvements in public safety and police legitimacy. Keywords: Community Policing, Police–Community Relations, Problem-Oriented Policing, Police Legitimacy and Trust, and Public Safety Governance

Procedural fairness has long been recognized as critical to citizen acceptance of urban renewal initiatives. However, research examining the underlying mechanisms of this relationship remains limited, hindering effective policy implementation. This study addresses this gap by investigating how relationship quality dimensions—specifically citizen satisfaction, citizen recognition, and citizen trust—mediate the link between procedural fairness and citizen acceptance. Drawing on survey data from 409 respondents across three communities in China that experienced urban renewal projects and employing structural equation modeling (SEM) and artificial neural network (ANN) analysis, our findings demonstrate that procedural fairness positively influences citizen acceptance, with citizen satisfaction and citizen recognition serving as partial mediators in this relationship, while citizen trust shows no significant mediating effect. These findings advance the literature by elucidating the distinct procedural fairness pathways through which citizens develop acceptance toward urban renewal policies, while also revealing the nuanced roles that different relational dimensions play in this process.

Purpose of the study: This study aims to analyze the effect of service effectiveness on taxpayer satisfaction at the Regional Revenue Agency of Maluku Province, specifically in Motor Vehicle Tax payment services at One-Stop Administration Services Office Waihaong Ambon. The research positions taxpayer satisfaction not only as an administrative performance indicator but also as a reflection of governance quality, institutional legitimacy, and the relational dynamics between government and citizens within a decentralized public administration framework. Methodology: This study employed a quantitative survey approach involving taxpayers who directly accessed Motor Vehicle Tax payment services. Respondents were selected using an incidental sampling technique based on their direct service experience. Data were collected through structured Likert-scale questionnaires measuring service effectiveness (service speed, procedural accuracy, clarity of information, accessibility, and officer professionalism) and taxpayer satisfaction. Instrument validity and reliability tests were conducted prior to analysis. Data were analyzed using descriptive statistics and simple linear regression with SPSS software, including hypothesis testing (t-test) and coefficient of determination (R²). Main Findings: The findings indicate that service effectiveness has a positive and statistically significant effect on taxpayer satisfaction. The regression results demonstrate that improvements in service speed, procedural clarity, accessibility, and officer professionalism directly increase satisfaction levels. The coefficient of determination shows that service effectiveness explains a substantial proportion of variance in taxpayer satisfaction. These results confirm that effective public service delivery not only enhances citizen satisfaction but also strengthens public trust, perceptions of administrative fairness, and institutional legitimacy in regional tax administration. Novelty/Originality of this study: This study contributes new empirical evidence from an archipelagic regional context in eastern Indonesia by integrating a quantitative service effectiveness model with a social governance perspective. Unlike prior studies that primarily emphasize technical service quality dimensions, this research conceptualizes taxpayer satisfaction as an indicator of institutional trust and governance legitimacy. The study enriches public administration literature by demonstrating how frontline service performance influences broader governance outcomes within decentralized regional tax systems.

This paper investigates the theoretical underpinnings and applied dimensions of outsourcing within public administration systems, with particular attention to its contribution to governance efficiency. In the public sector, outsourcing has emerged as a key strategic instrument enabling governments to cope with fiscal constraints and accommodate growing demands for operational agility. The conceptual framework integrates Transaction Cost Economics (TCE), Agency Theory, and Resource-Based Theory. Collectively, these analytical lenses posit that outsourcing can lower expenditure, elevate service standards, and free government bodies to prioritize their principal mandates – corroborated by quantitative benchmarks: U.S. federal IT outsourcing achieved a 23% cost reduction (2018–2023), UK PPP infrastructure projects recorded 18% savings relative to conventional procurement, Sweden’s digital service outsourcing compressed processing times by 35%, and Australia’s shared-service platform reduced administrative overhead by 27%. A structured comparison across the United States, United Kingdom, Sweden, Canada, and Australia reveals how national priorities shape model selection and control architecture. Three dominant configurations are identified: contract-based outsourcing for standardised recurrent tasks, Public-Private Partnerships for capital-intensive infrastructure, and strategic alliances for innovation-driven service areas. Each configuration yields specific performance dividends – quantified through KPIs: contract outsourcing trims operating costs by 15– 25%, PPPs accelerate delivery by 45% with budget overruns down 20%, strategic alliances generate 2.8x more innovative outputs, and citizen satisfaction advances from 67% to 83% on average. These gains are accompanied by governance challenges, including heightened contractor dependency and quality assurance complexity, underscoring the need for robust supervisory structures and institutional transparency. The study argues for contextually calibrated outsourcing strategies and adaptable control frameworks as prerequisites for sustained public sector performance improvement.

Despite increasing investments in digital transformation initiatives within public administration, there is limited empirical evidence on how these initiatives translate into higher beneficiary satisfaction. Prior studies have primarily emphasized technological adoption and infrastructure readiness, with less attention to the service-level mechanisms that operationalize digital investments into positive user experiences. To address this gap, this study aims to examine the direct and indirect effects of digital transformation initiatives (e-government services, mobile applications, and online portals) on beneficiaries’ satisfaction, with particular focus on the mediating roles of service accessibility and ease of use. Drawing on resource-based theory, the dynamic capabilities view, and the Technology–Organization–Environment framework, this study develops and tests a mediation model using Structural Equation Modeling (SEM). Data were collected from 400 beneficiaries of digital municipal services in Dhofar Municipality, Oman. Reliability and validity were assessed through measurement model evaluation, and mediation effects were tested using bootstrapping procedures. The results reveal that digital transformation initiatives significantly enhance service accessibility and ease of use. Both accessibility and ease of use positively influence beneficiaries’ satisfaction, with ease of use demonstrating a comparatively stronger effect. Mediation analysis indicates that digital transformation initiatives improve satisfaction both directly and indirectly through enhanced accessibility and usability, confirming partial mediation. The findings also highlight the importance of inclusive digital design, cybersecurity, and infrastructure reliability in maximizing satisfaction outcomes. This study contributes to digital governance literature by clarifying the service-level mechanisms through which digital transformation initiatives influence citizen satisfaction. Unlike prior research that has primarily focused on adoption rates, this study integrates service quality theory and digital transformation perspectives to explain how accessibility and ease of use operationalize digital investments into public value within a municipal context.

Extant literature in India has extensively examined the relationship between police effectiveness and public perceptions, however certain areas still lack enough research. The eastern part of the country particularly Assam, despite its demographic significance and socio-political sensitivities remains largely understudied in the context of community policing. In districts such as Sivasagar, where historical exposure to insurgency and ethnic complexities demands a nuanced policing model, the dynamics of community engagement and citizen-led initiatives remain underexplored. This study seeks to identify the extent to which perceived police effectiveness influences public trust and cooperation, mediated by citizen satisfaction, within the specific context of Sivasagar, Assam. Employing a quantitative, descriptive, and exploratory design, primary data were collected from 80 residents through structured surveys. The dataset was analysed using inferential statistical techniques to examine both direct and mediated relationships. The findings revealed both direct and indirect significant positive effects of perceived police effectiveness on public trust and cooperation, with citizen satisfaction serving as a key mediating factor. The study offers practical insights and actionable recommendations for police departments and policymakers. Additionally, it holds theoretical and practical implications for enhancing public perception and strengthening police–community relations in regions facing complex socio-political dynamics.

The study examined the moderating role of citizens' intent to use e-government services in the relationship between perceived service quality and citizen satisfaction in the Province of Cavite. As the Philippines transitioned toward a digitally powered public sector under the E-Governance Act of 2025, understanding the drivers of digital success was critical to maximizing public investment and ensuring long-term adoption. Using a descriptive-correlational design, the study surveyed 385 residents who had recently used the National Bureau of Investigation (NBI) Clearance Online Registration and Application Services. Results showed high perceived service quality (Mean=4.06) and citizen satisfaction (Mean=4.07), with perceived usefulness emerging as the strongest quality dimension. Regression analysis showed that service quality was a potent, statistically significant predictor of satisfaction, explaining 78.2% of the variance (Adjusted R² = 0.782, p &lt; .001). The data indicated that while service quality directly determined satisfaction, the moderation analysis showed that citizens' intent to use did not significantly alter this relationship; the positive effect of quality on satisfaction remained constant regardless of whether a user was highly motivated or reluctant. The implications of these findings suggested that tangible system performance, such as reliability, efficiency, and ease of use, superseded initial behavioral goals. Consequently, it was recommended that public administrators prioritize continuous technical improvements and security over broad behavioral campaigns. This research provided a localized, empirical framework for evaluating e-governance effectiveness in developing economies undergoing major digital reforms.