Government Information Quarterly最新文献

This paper examines the relationship between digital transparency and citizens' participation in government activity, specifically, online crowdsourcing. Many local governments have enhanced service transparency by disclosing and sharing information of government activities in digital format. These digital-driven transparency mechanisms often introduce interactive, tailor-made, and user-generating features to online government platforms. This paper explores the efficacy of digital transparency on citizens' participation in online crowdsourcing activities and its heterogeneous influences on various socioeconomic groups. Using the Propensity Score Matching and Difference-in-Differences (PSM-DID) method, this study analyzes the impact of digitized information disclosure to citizens' participation in Sacramento 311, an online crowdsourcing platform. It is found that enhancing digital transparency promotes citizens' participation in online crowdsourcing activities. Furthermore, results suggest that the influence of digital transparency on citizen participation is short termed and varies across communities of different socioeconomic conditions.

Interoperability is a key success factor for digital public services. Addressing the required interoperability principles in public service architectures is difficult, since a multitude of different layers of interoperability as well as of architecture development must be covered in complex real-world situations. Architecture development frameworks provide an instrument to systematically and holistically design and manage architectures of complex and interoperable digital public service contexts. Interoperable public service architectures resulting from the application of architecture development frameworks further need constant evaluation and modification to keep these architectures relevant and up-to-date. Different methodologies such as the “Design Science Research Methodology” (DSRM) or Enterprise Architecture Frameworks like “The Open Group Architecture Framework” (TOGAF) provide methodical foundations in the creation of interoperable public service solutions. However, these methodologies only target some of the needed aspects at a time. To address this challenge, the paper proposes an agile framework for the design, evaluation, and maintenance of interoperable public service architectures, based on DSRM, TOGAF, and other relevant approaches from literature. The “Framework for Interoperable Service Architecture Development” (FISAD) is designed following the DSRM. FISAD comprises seven phases, which integrate the four interoperability layers put forward in the European Interoperability Framework (EIF) and the architectural design phases (business, data, application and technology architecture) covered in the Architecture Development Method (ADM) of TOGAF in an incremental fashion along the DSRM. To demonstrate how it works, FISAD is applied to the use-case of harmonizing pre-qualification and Digital Purchasing Systems (DPS) processes in the pre-award phase of public procurement. The effectiveness of FISAD is verified on the use-case, providing further insights for the realization of interoperability along a systematic and holistic approach.

Citizens are oftentimes the central unit of analysis in e-government research and treated as one of the stakeholders receiving the most benefits from public sector digitalization. Still, they are mostly described in general terms, and it remains unclear what roles they can assume in relation to e-government. Different understandings of the citizens' role in e-government may impact research, because they entail different axioms mainly in relation to the technological frame for e-government but also for the citizens' relationship to public sector organizations in general. The aim of this article is to investigate and conceptualize the citizens' role in e-government based on public value positions. We depart from Rose et al.'s (2015) framework of value positions for managing e-government. After reviewing and analyzing extensive research on e-government, we use this framework to contribute a clarification of the citizens' role in each value position. Our analysis shows that the ideal citizen is conceptualized differently across the four value positions; ranging from an external entity that should service themselves using digital self-services, to an engaged agent that should be actively involved in policy making and service delivery. In addition to this new perspective on the citizens' role in e-government, we contribute with an extension of the public value positions framework. The extended framework presented in this article makes these differences visible and we discuss consequences of the citizens' role in e-government for other dimensions of the framework.

Recent advances in artificial intelligence (AI), especially in generative language modelling, hold the promise of transforming government. Given the advanced capabilities of new AI systems, it is critical that these are embedded using standard operational procedures, clear epistemic criteria, and behave in alignment with the normative expectations of society. Scholars in multiple domains have subsequently begun to conceptualize the different forms that AI applications may take, highlighting both their potential benefits and pitfalls. However, the literature remains fragmented, with researchers in social science disciplines like public administration and political science, and the fast-moving fields of AI, ML, and robotics, all developing concepts in relative isolation. Although there are calls to formalize the emerging study of AI in government, a balanced account that captures the full depth of theoretical perspectives needed to understand the consequences of embedding AI into a public sector context is lacking. Here, we unify efforts across social and technical disciplines by first conducting an integrative literature review to identify and cluster 69 key terms that frequently co-occur in the multidisciplinary study of AI. We then build on the results of this bibliometric analysis to propose three new multifaceted concepts for understanding and analysing AI-based systems for government (AI-GOV) in a more unified way: (1) operational fitness, (2) epistemic alignment, and (3) normative divergence. Finally, we put these concepts to work by using them as dimensions in a conceptual typology of AI-GOV and connecting each with emerging AI technical measurement standards to encourage operationalization, foster cross-disciplinary dialogue, and stimulate debate among those aiming to rethink government with AI.

This study seeks to establish a foundation for how FOI fees are received by public record requesters, and how fees influence behavior across demographics and requester types. A survey of 330 public records requesters in the United States revealed sharp disparities in how requesters perceive fees. Private citizens, journalists, academics, and nonprofit requesters were more likely to identify excessive fees as a serious impediment, whereas commercial requesters and lawyers did not. The study also found differences in how fees are experienced at the federal, state, and local levels. Findings suggest that fees are particularly problematic for certain requester types, notably average citizens and those seeking records in the public interest, and that fees may therefore obstruct the public's ability to become informed and better self-govern. Based on democratic theory, this U.S.-based study provides caution and insights for governments throughout the world against imposing barriers that might obstruct civic participation.

Agile is emerging as a promising approach in governments, with the potential to significantly enhance project management when implemented effectively. Despite its potential merits, it has not yet become a mainstream approach in government IT projects, primarily due to the incongruence between Agile practices and conventional methods of project funding, governance, and management. In order to contribute to our understanding of Agile in public sector practice, this study examines an extensive IT program in the UK defense sector which adopted Agile. We applied institutional logics as a theoretical lens to understand the complex dynamics within this environment, investigating the change mechanisms and the enduring tensions and conflicts. Our analysis of interview data revealed the key change mechanisms “mission collaborator” and “one team culture”. Unresolved tensions in our case setting encompass public value versus cost, project approval, policy, governance, and culture.

This research explores why and how members of the Information Sharing and Analysis Center (ISAC) share cybersecurity information to prevent cyber threats in Taiwan, and factors that encourage or discourage this behavior. The literature on information sharing has traditionally emphasized the motives for doing so and/or the structure of the sharing platform/network, leaving a gap in our understanding on how its formal and informal network rules shape, influence, and collide. By applying Ostrom's (2007) institutional analysis and development framework to Taiwanese Regional- and Sectoral-ISACs to qualitative data from 40 in-depth interviews across central/local governments, private companies, state-owned enterprises, and non-governmental organizations, this paper analyzes the institutional rules-in-use at the operational, collective, and constitutional levels. Our qualitative empirical study aims to induct the various institutional rules-in-use embedded in the ISAC networks, and its findings regarding inter-organizational crisis-management information sharing may have implications for cross-boundary participation in other nations.

Citizens' acceptance of artificial intelligence (AI) in public service delivery is important for its legitimate and effective use by government. Human involvement in AI systems has been suggested as a way to boost citizens' acceptance and perceptions of these systems' fairness. However, there is little empirical evidence to assess these claims. To address this gap, we conducted a pre-registered conjoint experiment in the UK regarding acceptance of AI in processing public permits: for immigration visas and parking permits. We hypothesise that greater human involvement boosts acceptance of AI in decision-making and associated perceptions of its fairness. We further hypothesise that greater human involvement mitigates the negative impact of certain AI features, such as inaccuracy, high cost, or data sharing. From our study, we find that more human involvement tends to increase acceptance, and that perceptions of fairness were less influenced. Yet, when substantial human discretion was introduced in parking permit scenarios, respondents preferred more limited human input. We found little evidence that human involvement moderates the impact of AI's unfavourable attributes. System-level factors such as high accuracy, the presence of an appeals system, increased transparency, reduced cost, non-sharing of data, and the absence of private company involvement all boost both acceptance and perceived procedural fairness. We find limited evidence that individual characteristics affect these results. The findings show how the design of AI systems can increase its acceptability to citizens for use in public services.

In this paper, we propose a conceptual framework composed of a number of e-government, implementation and evaluation-oriented variables, with which we jointly analyze chatbots presented in the research literature and chatbots deployed as public services in Spain at national, regional and local levels. As a result of our holistic analysis, we identify and discuss current trends and challenges in the development and evaluation of chatbots in the public administration sector, such as focusing the use of the conversational agents on the search for government information, documents and services –leaving citizen consultation and collaboration aside–, and conducting preliminary evaluations of prototypes in limited studies, lacking experiments on deployed systems, with metrics beyond effectiveness and usability –e.g., metrics related to the generation of public values. Addressing some of the identified challenges, we build and evaluate two novel chatbots that present advances in the access to open government data and citizen participation content. Moreover, we come up with additional, potential research lines that may be considered in the future for a new generation of e-government chatbots.

This research analyzes the possible underlying determinants of citizens' intent to use electronic services provided by e-government (e-gov). A total of 519 responses and a theoretical model based on Unified Model of Electronic Government Adoption (UMEGA) including the role of e-gov in the context of the COVID-19 pandemic, were used. A partial least squares structural equation model and the fs-QCA technique were used to analyze the data collected. The results showed how two factors studied, Attitude and Facilitating Conditions directly affected the decision to use e-gov services. Attitude means that governments must find effective ways to entice positive attitudes toward using e-services, and Facilitating Conditions implies that the resources and facilities provided to users improve their intention to use. However, the second most robust relationship was associated with the influence of Performance Expectancy on Attitude, suggesting that the trust placed in e-gov by the citizens, based on previous experiences, is a crucial determinant of their attitude toward it and their behavior when using it.