Transparency is an ever more important feature in local governments around the world. However, while a growing number of FOI laws have been approved, the extant literature signals the existence of a gap between the law de iure and its application de facto, between how the law is designed and how it is implemented. In this regard, the implementation of passive transparency has received comparatively less attention than active transparency. This presentation is based on 22.907 information requests made between 2019 and 2022 to 98 Catalan local councils of different provinces and population stretches. The results evidence that local councils provide heterogeneous responses to citizen information requests. The divergences in their responses not only relate to local councils’ characteristics (such as population size or province) but also to the requester’s characteristics and the request itself. These results point towards the existence of discretionality and biases, which menace the spirit of the law.

Abstract: [Purpose] Research on the efficient sharing and openness of government data is a cutting-edge topic in international e-government development. How to achieve efficient and secure sharing of government data is a fundamental aspect of global digital public governance. By examining two decades of research outcomes and thematic trends in both Chinese and English, this study aims to provide a theoretical foundation and innovative insights for activating international government data resources, optimizing the allocation of government computing power for addressing complex governance challenges in a digital society, innovating collaborative approaches for multi-agent, cross-departmental government data sharing, and enhancing the efficacy of digital government governance.

[Method] Utilizing DIKW8.2, COOC14.1, R 4.3.1, and Citespace6.16, we analyzed Chinese CSSCI core journals and Web of Science English core journals from 2004 to 2024. Visual knowledge mapping techniques were employed to display and comparatively analyze the dynamic evolution of topic trends and similarity in hot topic associations in Chinese and English e-government data sharing literature.

[Conclusion] The study reveals the coexistence of convergence and divergence within the current e-government data sharing research landscapes in Chinese and English. In terms of the thematic evolution from government information resource sharing to government data sharing, there remain some ambiguous conceptual boundaries in relevant research; Strategies for addressing persistent issues in data sharing rely heavily on prescribed paths, Longstanding underlying issues in research, such as insufficient exploration of how data might not run departments first in practice, have not been fully addressed.

This study aims to unpack challenges and barriers to coordination in collaborative platforms that deliver seamless digital services in the public sector. It also contributes to the conceptual clarification of collaborative platforms and related concepts. A governance perspective is applied to understand the complexity of structural and relational aspects of collaborative platforms co-creating seamless digital services. Using document analysis and interviews with coordinators of seven “life events” that are the most central initiatives for the implementation of seamless digital services in Norway, we identify the main challenges and barriers to coordination in collaborative platforms. Results reveal a number of interrelated structural barriers that then influence cultural barriers in collaboration platforms. Doing so, this article makes main contributions to the literature on collaborative governance in the digital age.

Keywords: coordination, collaborative platform, seamless digital services, collaborative governance, hybridity.

In the era of VUCA, governments face significant challenges in maintaining efficiency and responsiveness. While AI holds the potential to enhance bureaucracy, its adoption is influenced by various technical, organizational, social, and legislative factors. Existing research has primarily focused on the procedural and technical aspects of AI implementation in government, there is a limited understanding of perceptions of AI technologies within public sectors. This study aims to address this gap by investigating two key research questions: 1) How do politicians and civil servants view AI technologies differently, and how does this affect their acceptance of AI applications in government agencies? 2) How do the expectations of AI affect their real-world performance?

The research employs Q methodology, a qualitative-quantitative hybrid approach, to explore the subjective viewpoints of civil servants and politicians regarding AI adoption in government. 24 Q sample statements were carefully constructed based on six key categories: basic cognition, expectations differences, application scenarios differences, risks and challenges, facilitating and hindering factors, improvement and optimization. A total of 45 participants, including 30 civil servants and 15 politicians from Chinese public sectors, took part in the online survey. The survey data was supplemented with several in-depth offline interviews to enhance the understanding of the participants' viewpoints. The factor analysis revealed four distinct profiles among the participants: Technology Optimists, Risk Cautious, Change Promoters, and Resource Deficient.

Technology Optimists, mainly politicians, exhibit a strong belief in AI's potential to positively transform bureaucratic functions. They view AI as a powerful tool for enhancing efficiency, reducing costs, and improving decision-making processes. In contrast, Risk Cautious individuals, mostly civil servants, emphasize the need for careful regulation and consideration of potential downsides. They concerns about data privacy, job displacement, and the ethical implications of AI adoption. Change Promoters, found among both civil servants and politicians, actively advocate for the integration of AI in government agencies. They believe that AI can help streamline processes, reduce paperwork, and free up human resources for more complex tasks. However, Resource Deficient participants, predominantly civil servants, highlight the practical challenges related to funding, infrastructure, and technical expertise required for successful AI implementation.

The result also uncovers the relationship between AI adoption and the level of work personalization. In highly personalized work contexts, involving direct interaction with citizens or complex decision-making, AI is perceived as less applicable and potentially disruptive. Civil servants in these roles express concerns about the limitations of AI in handling nuanced and context-specific situations. Conversely, in depersonalized work environments, characterized by routine and repetitive tasks, AI is seen as more readily adoptable and beneficial for enhancing efficiency. Politicians who focus on policy-making, tend to view AI as a valuable tool for optimizing resource allocation and improving overall bureaucratic performance.

The findings are connected to bureaucracy theory, highlighting AI's potential to address inefficiencies while raising new challenges. A balanced approach, integrating optimistic and cautious perspectives, facilitating collaboration between civil servants and politicians is necessary to ensure AI implementation aligns with the needs and concerns of both groups.