Trust is a crucial factor in multi-actor data-sharing initiatives, particularly in sensitive domains like healthcare, where patient privacy, regulatory requirements, and organizational collaboration intersect. However, achieving trust-by-design, creating trust through intentional design choices, is challenging. To address this challenge, this paper investigates how trust frameworks in healthcare data-sharing are designed and how they evolve over time. Central to this inquiry is the conceptualization of “trust anchors”– designable components that provide a foundation for creating trust. Drawing on Technological Innovative Systems theory, this research qualitatively examines two healthcare trust frameworks, each at different lifecycle stages. The case studies reveal how trust anchors contribute to both the development and active management of trust frameworks. The contribution includes a lifecycle approach for trust frameworks and a matrix for categorizing trust anchors, providing guidance for organizations aiming to implement and maintain multi-actor data-sharing frameworks. We find that enforceable trust anchors are more important in the mature phase of a trust frameworks, while in the growing phase, less designable and enforceable trust factors assume a greater role.

Using audit analytics influences all facets of internal audit activities. Audit analytics use is transforming internal audit processes, structures, and relationships with its counterparts. However, empirical research in AA literature often focuses on individual projects and technology adoption issues. This paper fills this void by presenting empirical accounts of how to embark on an AA implementation initiative at the organizational level. Furthermore, we confront our observation with the views and experiences of professionals in the broader internal audit community to translate the exhibited practices into broader contexts. The findings from the case suggest that AA implementation should be approached from the whole-of-organization perspective instead of a fragmented and project-based view, combining formal and informal approaches, and equipped with AA implementation indicators and guidelines. Further studies are fruitful for affirming or expanding this paper’s observations and suggestions and extending its generalizability.

Purpose – Although there is much research about Open Government Data (OGD), comprehensive evaluations of OGD policy impacts remain sparse. This study addresses this gap by empirically examining the alignment between OGD policy objectives and real-world outcomes across 337 Chinese municipalities. Design/methodology/approach – A typology of OGD policy objectives is developed and used to evaluate OGD policies and their impact in different geographical regions. Findings – The analysis revealed a hierarchy of outcomes where “technical support” goals yield higher impacts than “innovative value”, whereas the latter is often the goal of OGD initiatives. Regional disparities also emerge, with Eastern cities outperforming traditional industrial areas. Originality/value – These findings underscore that policy design does not guarantee expected outcomes, especially under varying regional contexts. Policy-makers should better address local characteristics and develop targeted policy strategies and effective resource allocation.

Design science research (DSR) has been advocated for combining relevance and rigor and is socio-technical by nature. Yet most articles in the digital government field focus on the resulting design artifacts, presenting only methodologies and evaluations, and generating limited actionable, generalizable design knowledge. This editorial analyzes multiple approaches to advancing the development of prescriptive design principles and policy statements. The generation and rationale of prescriptive knowledge are discussed, along with various forms of design knowledge evaluation, to facilitate its connection to specific contexts. Three foundational propositions are presented to identify orienting strategies for developing prescriptive knowledge, explain its underlying rationale, and evaluate design knowledge. An integrative framework for generating and grounding prescriptive knowledge in line with the classical DSR paradigm is developed. This framework provides the basis for researchers to make generalizable knowledge contributions to the field using DSR.

This is the 12th edition of the workshop series labeled "Web and the City - The Web and Smart Cities", which is the successor of the series of workshops that started in Florence in 2015 and has continued taking place every year in conjunction with the WWW conference series. Each year, the focus of the workshop is actualized, and this year, the workshop focuses on data-driven smart cities. In the era of IoT, AI, and agentic AI, integration, the citiverse (metaverse for people-centric cities), cities are being transformed into urban environments that use data as a foundational asset to improve decision-making, optimize services, and enhance citizen well-being. At the same time, data is processed using various techniques and methods, which influence the outcomes. This workshop aims to explore how the Web supports this transformation and how technologies can improve smart cities.

Organizations increasingly use Generative Artificial Intelligence (AI) to create strategic documents, legislation, and recommendations to support decision-making. Many current AI initiatives are technology-deterministic, whereas technology co-evolves with the social environment, resulting in new applications and situations. This paper presents a novel view of AI governance by organizations from the perspective of complex adaptive systems (CASs). AI is conceptualized as a socio-technological and adaptive system in which people, policies, systems, data, AI, processes, and other elements co-evolve. The CAS lens draws attention to focusing AI governance on the entire organization, taking an outward perspective and considering public values and societal concerns. Although there is no shortage of AI governance instruments, they differ in their effectiveness, and combinations of appropriate mechanisms should be selected to deal with AI's evolving nature and complexity. A major challenge is that no responsibility, and therefore accountability, is taken due to the lack of understanding of the full socio-technological CAS. As such, joint accountability is needed in which involved parties work together.

In response to unprecedented global urbanization, the smart city concept has emerged, leveraging ICT to enhance municipal efficiency and improve the quality of urban life. The concept of smart energy city (SEC) is closely related to smart cities, however, energy system development in a smart city context is often found eluding certain segments of society, which calls for more attention to inclusion in SEC development. In this paper, the research question is: How can inclusion be effectively integrated into a framework of SEC design? A framework is developed comprising three key principles - energy conservation, energy efficiency, and renewable energy. These principles are aligned with collaboration among stakeholders, smart energy solutions applications, and integration of these solutions. The framework is illustrated using two real-world cases of demonstration projects in the City of Amsterdam, the Netherlands. The paper concludes by presenting several strategies for fostering inclusion in SEC development. They pertain to including utilization of the framework as a guideline to promote inclusion, establishing a clear understanding of inclusion, and involving all relevant stakeholders, including citizens' rights from the project's inception, and fostering transparency regarding the objectives, interests, and individual stakeholders' value.

The metaverse is still in its early stages, and most prototype metaverse platforms fail to fulfill their potential and meet users’ demands. Numerous studies have focused on the success of metaverse applications. However, there has been limited research on the failure of the metaverse services. Based on digital service failure model (DSFM), uses and gratification theory (U&G), and organizational failure diagnosis model (OFDM), an integrated model to investigate the influences of different failure types on citizens’ satisfaction with meta-government services is developed. The model was tested using a survey of 402 responses in China, which were analyzed using a hybrid structural equation modeling artificial neural network (SEM-ANN) approach. The findings indicated that organizational failure exerts the most powerful effect on citizens’ satisfaction. Moreover, information, service, system, and psychological needs failure, negatively influence citizens’ satisfaction. In addition, technology anxiety can weaken the influences of information, system, psychological needs, and organizational failures on citizens’ satisfaction while enhancing the relationship between service failure and citizens’ satisfaction. This research contributes initial and original insights into the failure types of meta-government services and their impacts, addressing a significant gap in the literature.

Despite their pivotal role in promoting transparency, open data portals often struggle to engage citizens, functioning instead as static ‘data graveyards’. While external activities, such as hackathons, can raise awareness, they do not directly cultivate sustained engagement within the portals. One promising approach to leverage citizens’ engagement motivation is the integration of game elements to transform passive data access into interactive gamified experiences. However, despite its potential, there is limited research on gamified citizens’ motivation to engage with open data portals. This paper examines how static and dynamic game elements are implemented across 31 open data portals. Lastly, we use the Self-Concordance Model to discuss the alignment between motivation, personal values, and game elements. Our findings reveal that most portals incorporate ‘discovery’ elements into their dataset-searching features, subtly gamifying exploration. Additionally, portals emphasising external activities, such as hackathons and events, often lack integrated social features, suggesting a trade-off between external engagement and sustained in-portal interaction. These findings challenge the assumption that open data engagement relies primarily on external initiatives, emphasising in-portal gamification instead. This study provides recommendations for policymakers to engage with users within open data portals.