International and Comparative Digital Government Studies
Permanent URI for this collectionhttps://hdl.handle.net/10125/112463
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Item type: Item , Understanding the Perspective of Government Employees on Citizens’ Use of Open Government Data: A Case Study of Jakarta Province in Indonesia(2026-01-06) Sari, Dwi; Gasco-Hernandez, MilaAlthough the study of open government data (OGD) use is not new, research has predominantly focused on countries in the Global North. This study aims to understand the factors that hinder OGD use from the government employees’ perspective, as well as the strategies the government implements to enhance the use of OGD in a country from the Global South, and uses the case of Jakarta Province in Indonesia to do so. Our results indicate that the lack of data availability and discoverability, OGD awareness, data-related and technical skills, and necessity and interest hinder the use of OGD, which shows consistency across contexts. They also suggest that public outreach and organizing engagement events are two strategies often implemented to promote such use and provide evidence about their effectiveness from the point of view of government employees.Item type: Item , Responsible AI Adoption in the Public Sector: A Data-Centric Taxonomy of AI Adoption Challenges(2026-01-06) Nikiforova, Anastasija; Lnenicka, Martin; Melin, Ulf; Valle-Cruz, David; Gill, Asif; Casiano Flores, Cesar; Sirait, Emyana; Luterek, Mariusz; Dreyling, Richard Michael; Tesarova, BarboraDespite Artificial Intelligence (AI) transformative potential for public sector services, decision-making, and administrative efficiency, adoption remains uneven due to complex technical, organizational, and institutional challenges. Responsible AI frameworks emphasize fairness, accountability, and transparency, aligning with principles of trustworthy AI and fair AI, yet remain largely aspirational, overlooking technical and institutional realities, especially foundational data and governance. This study addresses this gap by developing a taxonomy of data-related challenges to responsible AI adoption in government. Based on a systematic review of 43 studies and 21 expert evaluations, the taxonomy identifies 13 key challenges across technological, organizational, and environmental dimensions, including poor data quality, limited AI-ready infrastructure, weak governance, misalignment in human-AI decision-making, economic and environmental sustainability concerns. Annotated with institutional pressures, the taxonomy serves as a diagnostic tool to surface “symptoms” of high-risk AI deployment and guides policymakers in building the institutional and data governance conditions necessary for responsible AI adoption.Item type: Item , Introduction to the Minitrack on International and Comparative Digital Government Studies(2026-01-06) Janowski, Tomasz; Estevez, Elsa; Noveck, Beth; Ojo, Adegboyega