Pub Date : 2025-08-14DOI: 10.1016/j.giq.2025.102063
Juliane Schmeling , Sami al Dakruni , Ines Mergel
Sovereign data infrastructures are a central building block of the European Data Strategy, yet little is known about how public administrations share and collaborate on both open and restricted data. This research addresses the gap by systematically analysing the existing literature on data collaboration within the field of digital government research. We thereby make a methodological contribution to digital government research through a rigorous literature review framework that includes Structural Topic Modelling to understand the different themes of the scientific discussion in the field of digital government. We propose an innovative data collaboration framework that includes the ecosystem, the organisational, and the individual levels, enhancing our understanding of the multidimensional nature of data collaboration. Our analysis reveals that while the emphasis is on innovation and participation, critical aspects like standardisation and data management have a declining topic prevalence, despite their importance in developing federated data ecosystems. This comprehensive analysis not only sheds light on the current landscape but also informs a structured research agenda in digital government, aiming to contribute to the advancement of the field.
{"title":"Data collaboration in digital government research: A literature review and research agenda","authors":"Juliane Schmeling , Sami al Dakruni , Ines Mergel","doi":"10.1016/j.giq.2025.102063","DOIUrl":"10.1016/j.giq.2025.102063","url":null,"abstract":"<div><div>Sovereign data infrastructures are a central building block of the European Data Strategy, yet little is known about how public administrations share and collaborate on both open and restricted data. This research addresses the gap by systematically analysing the existing literature on data collaboration within the field of digital government research. We thereby make a methodological contribution to digital government research through a rigorous literature review framework that includes Structural Topic Modelling to understand the different themes of the scientific discussion in the field of digital government. We propose an innovative data collaboration framework that includes the ecosystem, the organisational, and the individual levels, enhancing our understanding of the multidimensional nature of data collaboration. Our analysis reveals that while the emphasis is on innovation and participation, critical aspects like standardisation and data management have a declining topic prevalence, despite their importance in developing federated data ecosystems. This comprehensive analysis not only sheds light on the current landscape but also informs a structured research agenda in digital government, aiming to contribute to the advancement of the field.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102063"},"PeriodicalIF":10.0,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-13DOI: 10.1016/j.giq.2025.102062
Anastasija Nikiforova , Martin Lnenicka , Mariusz Luterek , Petar Milic , Manuel Pedro Bolívar Rodríguez
Public Data Ecosystems (PDEs) are increasingly viewed as dynamic socio-technical systems shaped by evolving interactions among actors, infrastructures, data types, and governance mechanisms. Yet, most existing research remains static or domain-specific, offering limited insight into the temporal and co-evolutionary dynamics of PDEs. To address this gap, this study adopts a theory-building approach to examine how PDEs evolve over time and to define a forward-looking research agenda. Drawing on empirical insights from five European countries, we investigate how key meta-characteristics and attributes of PDEs manifest, shift, and co-evolve in practice. Leveraging a recent multi-generational model as an analytical lens, we assess its alignment with real-world trajectories, identify overlooked and emerging features, and revise its structure accordingly. In doing so, we theorize PDE evolution as a multi-generational process shaped by institutional, technological, and contextual dynamics. This results in a refined model that better captures the complexity and diversity of PDE development, particularly considering emerging technologies such as artificial intelligence (AI), generative AI, and large language models (LLMs) shaping the forward-looking PDE generation. Building on these insights, we propose a future research agenda comprising 17 directions organized around revised meta-characteristics. This agenda supports the development of sustainable, resilient, and intelligent PDEs. The study contributes to the theorization of PDEs by offering an empirically grounded, temporally aware, and actionable roadmap for future research and policy design.
{"title":"Theorizing the evolution of public data ecosystems: An empirically grounded multi-generational model and future research agenda","authors":"Anastasija Nikiforova , Martin Lnenicka , Mariusz Luterek , Petar Milic , Manuel Pedro Bolívar Rodríguez","doi":"10.1016/j.giq.2025.102062","DOIUrl":"10.1016/j.giq.2025.102062","url":null,"abstract":"<div><div>Public Data Ecosystems (PDEs) are increasingly viewed as dynamic socio-technical systems shaped by evolving interactions among actors, infrastructures, data types, and governance mechanisms. Yet, most existing research remains static or domain-specific, offering limited insight into the temporal and co-evolutionary dynamics of PDEs. To address this gap, this study adopts a theory-building approach to examine how PDEs evolve over time and to define a forward-looking research agenda. Drawing on empirical insights from five European countries, we investigate how key meta-characteristics and attributes of PDEs manifest, shift, and co-evolve in practice. Leveraging a recent multi-generational model as an analytical lens, we assess its alignment with real-world trajectories, identify overlooked and emerging features, and revise its structure accordingly. In doing so, we theorize PDE evolution as a multi-generational process shaped by institutional, technological, and contextual dynamics. This results in a refined model that better captures the complexity and diversity of PDE development, particularly considering emerging technologies such as artificial intelligence (AI), generative AI, and large language models (LLMs) shaping the forward-looking PDE generation. Building on these insights, we propose a future research agenda comprising 17 directions organized around revised meta-characteristics. This agenda supports the development of sustainable, resilient, and intelligent PDEs. The study contributes to the theorization of PDEs by offering an empirically grounded, temporally aware, and actionable roadmap for future research and policy design.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102062"},"PeriodicalIF":10.0,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-31DOI: 10.1016/j.giq.2025.102058
Louise Jørring, Lise Justesen , Ursula Plesner
Digital technologies are increasingly being implemented in public sector organizations with the ambition to enhance efficiency by saving employees' time. Frontline workers, who are often described as lacking resources and working under constant time constraints, are continuously confronted with the introduction of new, supposedly time-saving technologies. However, the concept of time and how digital technologies impact frontline workers' use of time in practice are rarely examined explicitly in public administration research. This article foregrounds the concept of time, drawing on qualitative fieldwork in Denmark's public employment services to examine how frontline workers navigate time tensions introduced by supposedly time-saving technologies. The findings reveal that these technologies reinforce tight linear schedules, requiring frontline workers to balance both time delays and time gains. This dynamic necessitates flexible adjustments of work rhythms as employees speed up or slow down their tasks to adjust to the digitalized environment. To understand these temporal tensions—how they are created and handled—this article draws on insights from science and technology studies, applying the distinction between monochronic time—in which events are approached as unfolding sequentially with a focus on one event at a time—and polychronic time, in which events are unpredictable and may unfold simultaneously or in other non-linear ways. Based on our study, we argue for an explicit focus on temporality in public administration literature, offer a conceptual vocabulary to explore it further, and advocate for understanding how time-saving technologies unfold in everyday practice, while acknowledging the coexistence of monochronic and polychronic time orientations in organizations.
{"title":"Tensions in time-saving technologies: Adjusting work rhythms in the digitalized public sector frontline","authors":"Louise Jørring, Lise Justesen , Ursula Plesner","doi":"10.1016/j.giq.2025.102058","DOIUrl":"10.1016/j.giq.2025.102058","url":null,"abstract":"<div><div>Digital technologies are increasingly being implemented in public sector organizations with the ambition to enhance efficiency by saving employees' time. Frontline workers, who are often described as lacking resources and working under constant time constraints, are continuously confronted with the introduction of new, supposedly time-saving technologies. However, the concept of time and how digital technologies impact frontline workers' use of time in practice are rarely examined explicitly in public administration research. This article foregrounds the concept of time, drawing on qualitative fieldwork in Denmark's public employment services to examine how frontline workers navigate time tensions introduced by supposedly time-saving technologies. The findings reveal that these technologies reinforce tight linear schedules, requiring frontline workers to balance both time delays and time gains. This dynamic necessitates flexible adjustments of work rhythms as employees speed up or slow down their tasks to adjust to the digitalized environment. To understand these temporal tensions—how they are created and handled—this article draws on insights from science and technology studies, applying the distinction between <em>monochronic time</em>—in which events are approached as unfolding sequentially with a focus on one event at a time—and <em>polychronic time</em>, in which events are unpredictable and may unfold simultaneously or in other non-linear ways. Based on our study, we argue for an explicit focus on temporality in public administration literature, offer a conceptual vocabulary to explore it further, and advocate for understanding how time-saving technologies unfold in everyday practice, while acknowledging the coexistence of monochronic and polychronic time orientations in organizations.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102058"},"PeriodicalIF":10.0,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144748718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-23DOI: 10.1016/j.giq.2025.102061
Aya Rizk , Ida Lindgren
Implementing Automated Decision-Making (ADM) systems in public administrations raises several tensions: between efficiency and ensuring fair decisions, between public transparency and individual privacy, and between standardization and discretion. To develop legitimate ADM systems that balance these tensions, we need to better understand the phenomenon on the societal, organizational and individual levels. To this end, we conduct a multidisciplinary literature review with the analysis utilizing Coleman's macro-micro model of social action, in which individual attitudes and actions relevant to ADM are related to ADM social structures and outcomes. We develop an ADM framework that captures and conceptualizes these macro-micro relationships and use this framework to identify gaps in research and motivate a research agenda. Our results also reveal a changing decision space between public officials and citizens that, if well investigated, may facilitate the development of citizen-centric ADM solutions and effective human-machine hybrids. We illustrate how the framework and ADM decision space can contribute to research, practice and policy.
{"title":"Automated decision-making in public administration: Changing the decision space between public officials and citizens","authors":"Aya Rizk , Ida Lindgren","doi":"10.1016/j.giq.2025.102061","DOIUrl":"10.1016/j.giq.2025.102061","url":null,"abstract":"<div><div>Implementing Automated Decision-Making (ADM) systems in public administrations raises several tensions: between efficiency and ensuring fair decisions, between public transparency and individual privacy, and between standardization and discretion. To develop legitimate ADM systems that balance these tensions, we need to better understand the phenomenon on the societal, organizational and individual levels. To this end, we conduct a multidisciplinary literature review with the analysis utilizing Coleman's macro-micro model of social action, in which individual attitudes and actions relevant to ADM are related to ADM social structures and outcomes. We develop an ADM framework that captures and conceptualizes these macro-micro relationships and use this framework to identify gaps in research and motivate a research agenda. Our results also reveal a changing decision space between public officials and citizens that, if well investigated, may facilitate the development of citizen-centric ADM solutions and effective human-machine hybrids. We illustrate how the framework and ADM decision space can contribute to research, practice and policy.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102061"},"PeriodicalIF":7.8,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-22DOI: 10.1016/j.giq.2025.102060
Jae Woo Lee , Keeheon Lee
Artificial Intelligence (AI) permeates various technologies, including information and communication technology, significantly reshaping societal practices and individual routines. While this offers benefits, it also prompts concerns about the negative changes of AI, requiring careful governance. This paper focuses on mitigating these risks by offering recommendations for establishing coherent legal frameworks to safeguard innocent individuals from AI-related threats or potential harm, whether intentional or unintentional. We propose a framework that utilizes a large language model to assess the alignment between AI ethical guidelines and bills. A case study is conducted to analyze the Korean regulatory landscape, since Korea's AI legal frameworks particularly lag behind amid its rapid advancement of technology. This study employs a range of methods - descriptive, correlation, cluster, and semantic analyses - to offer a comprehensive comparison of Korea's legislative documents. Our findings reveal continuity in certain aspects but discontinuity in others between these two governance tools. Consequently, we suggest measures to enhance the consistency between these two realms for AI regulation, contributing to more robust and effective AI governance practices.
{"title":"Building a consensus: Harmonizing AI ethical guidelines and legal frameworks in Korea for enhanced governance","authors":"Jae Woo Lee , Keeheon Lee","doi":"10.1016/j.giq.2025.102060","DOIUrl":"10.1016/j.giq.2025.102060","url":null,"abstract":"<div><div>Artificial Intelligence (AI) permeates various technologies, including information and communication technology, significantly reshaping societal practices and individual routines. While this offers benefits, it also prompts concerns about the negative changes of AI, requiring careful governance. This paper focuses on mitigating these risks by offering recommendations for establishing coherent legal frameworks to safeguard innocent individuals from AI-related threats or potential harm, whether intentional or unintentional. We propose a framework that utilizes a large language model to assess the alignment between AI ethical guidelines and bills. A case study is conducted to analyze the Korean regulatory landscape, since Korea's AI legal frameworks particularly lag behind amid its rapid advancement of technology. This study employs a range of methods - descriptive, correlation, cluster, and semantic analyses - to offer a comprehensive comparison of Korea's legislative documents. Our findings reveal continuity in certain aspects but discontinuity in others between these two governance tools. Consequently, we suggest measures to enhance the consistency between these two realms for AI regulation, contributing to more robust and effective AI governance practices.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102060"},"PeriodicalIF":7.8,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-08DOI: 10.1016/j.giq.2025.102057
Beatrice I. Johannessen
As governments increasingly try to develop their own technological solutions to handle growing demands, a key response has been to move away from traditional “waterfall” methods and towards modern “agile” principles for innovation. While agile principles are advocated as crucial to handling the complexity of the public sector, they have also been found to be difficult to implement in practice. To advance our understanding of these difficulties, this article aims to unpack the challenges facing software development teams when trying to use agile methods in the public sector. The article draws on ethnographic data from a study of software development teams in the Norwegian Labor and Welfare administration (NAV). By analyzing these data through the theoretical lens of institutional theory – particularly emphasizing institutional complexity due to conflicting institutional logics – the article uncovers three critical tensions facing the development teams: between bottom-up methods vs. top-down delegation, flexibility vs. pre-planned mandates, and “fast” teams vs. a “slow” context. These tensions indicate a “decoupling” between proclaimed agility and practiced methodologies, with the practical reality of the teams' working environment being characterized as a mixture of elements from both waterfall and agile methods. By uncovering these tensions and contradictions, the article explores the institutional complexity of public sector innovation, in which workers struggle to navigate an institutional context characterized by conflicting demands.
{"title":"An agile bureaucracy? Lessons from an ethnographic study of agile teams in the Norwegian public sector","authors":"Beatrice I. Johannessen","doi":"10.1016/j.giq.2025.102057","DOIUrl":"10.1016/j.giq.2025.102057","url":null,"abstract":"<div><div>As governments increasingly try to develop their own technological solutions to handle growing demands, a key response has been to move away from traditional “waterfall” methods and towards modern “agile” principles for innovation. While agile principles are advocated as crucial to handling the complexity of the public sector, they have also been found to be difficult to implement in practice. To advance our understanding of these difficulties, this article aims to unpack the challenges facing software development teams when trying to use agile methods in the public sector. The article draws on ethnographic data from a study of software development teams in the Norwegian Labor and Welfare administration (NAV). By analyzing these data through the theoretical lens of institutional theory – particularly emphasizing institutional complexity due to conflicting institutional logics – the article uncovers three critical tensions facing the development teams: between bottom-up methods vs. top-down delegation, flexibility vs. pre-planned mandates, and “fast” teams vs. a “slow” context. These tensions indicate a “decoupling” between proclaimed agility and practiced methodologies, with the practical reality of the teams' working environment being characterized as a <em>mixture</em> of elements from both waterfall and agile methods. By uncovering these tensions and contradictions, the article explores the institutional complexity of public sector innovation, in which workers struggle to navigate an institutional context characterized by conflicting demands.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102057"},"PeriodicalIF":7.8,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This case study explores how co-production of digital services contributes to a re-framed institutional structure for collaborative governance to respond effectively to collective threats. This study explores the role of collaborative governance and digital technologies in ensuring public service delivery amidst the ongoing war in Ukraine. Focusing on the Diia platform and co-production of services between local government and civil society organizations, the research highlights how digital tools have enabled adaptive governance under extreme crisis posed by the war. By analyzing institutional dynamics in collaborative practices of co-production of public services enabled by digital technologies, this study sheds light on joint capacity for adaptive governance in societies under extreme crisis conditions. Using the Dnipropetrovsk region as an empirical case, this research applies Ostrom's Institutional Analysis and Development (IAD) framework to examine how government and civil society collaborations to deliver public services have fostered institutional changes and adaptation. The findings contribute to broader discussions on governance in on-going extreme crises, offering valuable insight into conflict-affected areas and emphasizing the importance of flexible, digitally enabled institutional arrangements for sustaining public service delivery.
{"title":"Adaptive governance amidst the war: Overcoming challenges and strengthening collaborative digital service provision in Ukraine","authors":"Mariana Gustafsson , Olga Matveieva , Elin Wihlborg , Yevgeniy Borodin , Tetiana Mamatova , Sergiy Kvitka","doi":"10.1016/j.giq.2025.102056","DOIUrl":"10.1016/j.giq.2025.102056","url":null,"abstract":"<div><div>This case study explores how co-production of digital services contributes to a re-framed institutional structure for collaborative governance to respond effectively to collective threats. This study explores the role of collaborative governance and digital technologies in ensuring public service delivery amidst the ongoing war in Ukraine. Focusing on the Diia platform and co-production of services between local government and civil society organizations, the research highlights how digital tools have enabled adaptive governance under extreme crisis posed by the war. By analyzing institutional dynamics in collaborative practices of co-production of public services enabled by digital technologies, this study sheds light on joint capacity for adaptive governance in societies under extreme crisis conditions. Using the Dnipropetrovsk region as an empirical case, this research applies Ostrom's Institutional Analysis and Development (IAD) framework to examine how government and civil society collaborations to deliver public services have fostered institutional changes and adaptation. The findings contribute to broader discussions on governance in on-going extreme crises, offering valuable insight into conflict-affected areas and emphasizing the importance of flexible, digitally enabled institutional arrangements for sustaining public service delivery.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102056"},"PeriodicalIF":7.8,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144569823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-27DOI: 10.1016/j.giq.2025.102055
Luca Tangi , A. Paula Rodriguez Müller , Marijn Janssen
Implementing artificial intelligence (AI) in public settings requires a fundamental transformation of various social and technical aspects within public administration. However, the transformative efforts required for AI integration and use in government remain underexplored. This study introduces the concept of 'AI-augmented government transformation,' building on sociomateriality and sociotechnical theory, and develops a theoretical framework to explore this phenomenon. By applying this framework and drawing insights from expert interviews, we identify the strategic shifts and socio-technical adaptations essential for integrating AI into public administrations. Our analysis highlights the importance of opening the 'black box' of AI to gain a deep understanding of its underlying technologies and their materialities.
The findings reveal complex interdependencies between AI materiality and the social and technical systems that public administrations must navigate. Specifically, AI, as a novel materiality, introduces new organizational dynamics, enhances employee capabilities, and alters operational routines and practices. These changes complement technical ones, such as upgrades and advancements in data collection and processing. By investigating the complexities of AI-augmented government transformation, this research offers novel and practical insights for policymakers and practitioners navigating the challenges and opportunities of AI integration.
{"title":"AI-augmented government transformation: Organisational transformation and the sociotechnical implications of artificial intelligence in public administrations","authors":"Luca Tangi , A. Paula Rodriguez Müller , Marijn Janssen","doi":"10.1016/j.giq.2025.102055","DOIUrl":"10.1016/j.giq.2025.102055","url":null,"abstract":"<div><div>Implementing artificial intelligence (AI) in public settings requires a fundamental transformation of various social and technical aspects within public administration. However, the transformative efforts required for AI integration and use in government remain underexplored. This study introduces the concept of 'AI-augmented government transformation,' building on sociomateriality and sociotechnical theory, and develops a theoretical framework to explore this phenomenon. By applying this framework and drawing insights from expert interviews, we identify the strategic shifts and socio-technical adaptations essential for integrating AI into public administrations. Our analysis highlights the importance of opening the 'black box' of AI to gain a deep understanding of its underlying technologies and their materialities.</div><div>The findings reveal complex interdependencies between AI materiality and the social and technical systems that public administrations must navigate. Specifically, AI, as a novel materiality, introduces new organizational dynamics, enhances employee capabilities, and alters operational routines and practices. These changes complement technical ones, such as upgrades and advancements in data collection and processing. By investigating the complexities of AI-augmented government transformation, this research offers novel and practical insights for policymakers and practitioners navigating the challenges and opportunities of AI integration.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102055"},"PeriodicalIF":7.8,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-24DOI: 10.1016/j.giq.2025.102054
Anne David , Tan Yigitcanlar , Kevin Desouza , Karen Mossberger , Pauline Hope Cheong , Juan Corchado , Prithvi Bhat Beeramoole , Alexander Paz
The rise of Artificial Intelligence (AI) has significant implications for local government service delivery, offering considerable advantages alongside inherent risks that warrant careful management. While responsible AI has become a focal point in academic and policy discussions, public perceptions remain marginal in these debates. This paper explores how behavioural factors along with perceived risk, local government AI policy awareness and policy expectations influence public intentions to support local government responsible AI practices. Using the Theory of Planned Behaviour, this study examines a multi-factor survey through Confirmatory Factor Analysis, followed by Structural Equation Modelling to assess relationships between key factors. A survey questionnaire, conducted with participants from Australia, the United States, and Spain via the Prolific platform, reveals key insights: (a) perceived risk exhibit a stronger influence than other factors; (b) policy awareness plays a critical role in shaping public intention towards support for responsible practices; (c) greater AI policy awareness correlates with more realistic expectations of local government AI policies; (d) social influence lacks a notable impact in this context. These findings provide valuable guidance for urban policymakers in crafting AI strategies that promote responsible AI implementation within local government services.
{"title":"Public perceptions of responsible AI in local government: A multi-country study using the theory of planned behaviour","authors":"Anne David , Tan Yigitcanlar , Kevin Desouza , Karen Mossberger , Pauline Hope Cheong , Juan Corchado , Prithvi Bhat Beeramoole , Alexander Paz","doi":"10.1016/j.giq.2025.102054","DOIUrl":"10.1016/j.giq.2025.102054","url":null,"abstract":"<div><div>The rise of Artificial Intelligence (AI) has significant implications for local government service delivery, offering considerable advantages alongside inherent risks that warrant careful management. While responsible AI has become a focal point in academic and policy discussions, public perceptions remain marginal in these debates. This paper explores how behavioural factors along with perceived risk, local government AI policy awareness and policy expectations influence public intentions to support local government responsible AI practices. Using the Theory of Planned Behaviour, this study examines a multi-factor survey through Confirmatory Factor Analysis, followed by Structural Equation Modelling to assess relationships between key factors. A survey questionnaire, conducted with participants from Australia, the United States, and Spain via the Prolific platform, reveals key insights: (a) perceived risk exhibit a stronger influence than other factors; (b) policy awareness plays a critical role in shaping public intention towards support for responsible practices; (c) greater AI policy awareness correlates with more realistic expectations of local government AI policies; (d) social influence lacks a notable impact in this context. These findings provide valuable guidance for urban policymakers in crafting AI strategies that promote responsible AI implementation within local government services.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102054"},"PeriodicalIF":7.8,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Public sector institutions are under increasing pressure to deliver greater public value through disruptive technologies, despite ongoing pressures. In response to evolving technological change and an abundance of information, many public sector organisations have adopted Artificial Intelligence (AI) to improve decision-making and generate social value. While AI's role in public administration is gaining attention, little is known about how its use alters internal power dynamics. This research uses a qualitative case study approach, drawing on 30 semi-structured interviews with operational managers and various analysts in a large public institution to explore how AI influences power relations. Findings reveal that AI use creates tensions among operational managers, organisation-wide analysts and the increasingly influential hybrid/in-house analysts who possess both technical and institutional expertise. The study presents and empirically validates the AI Power Enactment Framework and introduces the AI Power Matrix, providing policymakers with a structured tool to evaluate AI projects. These insights can inform targeted funding strategies and capacity building, helping to lessen dependence on hybrid analysts and enhance the success of AI implementation in the public sector.
{"title":"Navigating power dynamics in the public sector through AI-driven algorithmic decision-making","authors":"Kamran Mahroof , Vishanth Weerakkody , Zahid Hussain , Uthayasankar Sivarajah","doi":"10.1016/j.giq.2025.102053","DOIUrl":"10.1016/j.giq.2025.102053","url":null,"abstract":"<div><div>Public sector institutions are under increasing pressure to deliver greater public value through disruptive technologies, despite ongoing pressures. In response to evolving technological change and an abundance of information, many public sector organisations have adopted Artificial Intelligence (AI) to improve decision-making and generate social value. While AI's role in public administration is gaining attention, little is known about how its use alters internal power dynamics. This research uses a qualitative case study approach, drawing on 30 semi-structured interviews with operational managers and various analysts in a large public institution to explore how AI influences power relations. Findings reveal that AI use creates tensions among operational managers, organisation-wide analysts and the increasingly influential hybrid/in-house analysts who possess both technical and institutional expertise. The study presents and empirically validates the AI Power Enactment Framework and introduces the AI Power Matrix, providing policymakers with a structured tool to evaluate AI projects. These insights can inform targeted funding strategies and capacity building, helping to lessen dependence on hybrid analysts and enhance the success of AI implementation in the public sector.</div></div>","PeriodicalId":48258,"journal":{"name":"Government Information Quarterly","volume":"42 3","pages":"Article 102053"},"PeriodicalIF":7.8,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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