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Building an open data ecosystem is a long-term process during which it is necessary to collect feedback so that its development corresponds to the preferences and needs of users. The purpose of this paper is to provide findings and recommendations on how the intentions to use of Open Government Data (OGD) and OGD portals by Czech students evolved over the three years period from 2021 to 2023.

A mixed research approach was used to conduct the research study and to collect input data. A methodology followed the behavioural intention-based analysis using the model developed by Lnenicka et al. (2022) to analyse relationships between respective constructs and test the hypotheses. Each cycle of data collection using structured questionnaires was supplemented with semi-structured interviews to get students’ feedback on the findings.

The findings revealed that intentions to use of OGD and OGD portals by Czech students slightly decrease every year. Although students believe that using OGD is beneficial, can increase their performance and productivity, as well as they are influenced by other people to try to (re)use OGD, they miss concrete support above their daily activities in which they could use OGD. Therefore, we provided recommendations to improve their (re)use such as linking OGD with life events to show their usefulness for concrete life situations and activities.

The study provides insights into how intentions to use of OGD and OGD portals among Czech students evolved over the years and what should be the actions to consider improving the level of use. It provides governments on all administrative levels the recommendations for further improvements and actions to promote and stimulate the (re)use of OGD by students as well as other stakeholders.

Benchmarking e-government and digital society developments using relevant indicators provides crucial insights into what aspects to consider while building a resilient digital society in which digital public services are delivered effectively and sustainably. The purpose of this paper is to analyse selected indices and indicators over the years and provide findings and recommendations on what indicators contribute most to the development.

A mixed research approach was used to conduct the research and collect, analyse and interpret data. A qualitative analysis involving the search, decomposition and comparison approaches to identify e-government and digital society reports, indices, rankings and indicators was followed by a quantitative analysis comprising of regression and cluster analyses.

The findings revealed that changes in the mix of indicators used by e-government and digital society indices can be attributed to advances in ICT and channels through which people communicate and receive information. The authors found that digital and telecommunication infrastructures and the quality of their parameters such as broadband have the biggest influence on progress of the e-government and digital societies developments and contribute most to clustering of the EU member states into groups.

The paper provides insights into how the structures of related indices changed over the years and how different indicators contribute to benchmarking of e-government and digital society developments by means of their weights. It provides governments with recommendations on which indicators to focus most.

The study aims to understand the way metaverse might revolutionize the governance format – precisely the e-government concept – besides underlining the challenges leaving suggestive contours for further research in this realm.

An inductive research approach included the content analysis of relevant literature to identify patterns and generalize them into areas and approaches. Developing a conceptual framework seeks to systematically organize knowledge on metaverse government and provide an understanding of its contributions to enhancing the e-government maturity models.

The authors identified three general areas and approaches – content and data lifecycle management; platforms, tools and services; and infrastructure and computing resources – that shape how challenges of enterprise architecture layers should be resolved in a future research agenda. Integration of these government metaverse areas and approaches is linked with four enterprise architecture layers (technology, applications, data and business) that advance a new e-government meta stage of e-government maturity and the related challenges.

Hitherto, metaverse literature has hinged itself on the benefits and challenges of metaverse in the private sector. However, the exact dimensions have not been probed in the public sector and its e-government domain – the present study seeks to plug this gap.

As cities increasingly embrace smart technologies to enhance efficiency, sustainability and quality of life, integrating cybersecurity and data protection measures becomes paramount. This paper analyzes cybersecurity and data protection practices based on the existing strategies and projects in smart cities.

A research methodology involving searching for resources, content analysis and the Delphi method was developed to select the sample of smart cities, identify relevant resources, analyze and categorize their content, validate their relevance and transform them into a list of recommendations.

The findings include a validated list of 39 recommendations categorized into 6 categories for implementing robust cybersecurity and data protection measures in smart cities. We found that smart cities employ various measures to address cybersecurity and data protection, including technical solutions, organizational practices, policies and human resources initiatives. The smart economy and smart governance components are prioritized regarding data protection and cybersecurity measures, while smart living and smart environments receive less attention than others. There are regional differences in the implementation of cybersecurity measures, with Asia and Europe demonstrating higher levels of engagement.

The paper provides an approach to select sample smart cities and analyze their strategies and projects in different contexts to gather and validate best practices. The measures identified contribute to building sustainable and resilient cities regarding urban governance.

With the continuous development of the global COVID-19 epidemic, mobile learning has become one of the most significant learning approaches. The mobile learning resource is the basis of mobile learning; it may directly affect the effectiveness of mobile learning. However, the current learning resources cannot meet users' needs. This study aims to analyze the influencing factors of accepting open data as learning resources among users.

Based on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT), this study proposed a comprehensive theoretical research model. Data were obtained from 398 postgraduates from several universities in central China. Confirmatory factor analysis was used to determine the reliability and validity of the measurement model. Data has been analyzed using SPSS and AMOS software.

The results suggested that perceived usefulness, performance expectancy, social influence and facilitating conditions have a positive influence on accepting open data as learning resources. Perceived ease of use was not found significant. Moreover, it was further shown in the study that behavioural intention significantly influenced the acceptance of open data as learning resources.

There is a lack of research on open data as learning resources in developing countries, especially in China. This study addresses the gap and helps us understand the acceptance of open data as learning resources in higher education. This study also pays attention to postgraduates' choice of learning resources, which has been little noticed before. Additionally, this study offers opportunities for further studies on the continuous usage of open data in higher education.

This study investigates the individual and binary (i.e. combined) effects of institutional dimensions of open government data (which include instructional, structural and accessible rules) on scientific research innovation, as well as the mediating roles that researchers' perceived data usefulness and data capability play in between.

Based on a sample of 1,092 respondents, this study uses partial least squares structural equation modeling (PLS-SEM) and polynomial regression with response surface analysis to evaluate the direct and indirect effects of individual and binary institutional dimensions on scientific research innovation.

The findings demonstrate that instructional, structural and restricted access data have a positive effect on scientific research innovation in the individual effect. While the binary effect of institutional dimensions produces varying degrees of scientific research innovation. Furthermore, this study discovers that the perceived usefulness and data capability of researchers differ in the mediating effect of institutional dimensions on scientific research innovation.

Theoretically, this study contributes new knowledge on the causal links between data publication institutions and innovation. Practically, the research findings offer government data managers timely suggestions on how to build up institutions to foster greater data usage.

The Metaverse is rapidly reshaping the understanding of tourism, yet the public perception of this new domain remains largely uncharted empirically. This paper aims to build on the technology acceptance model (TAM) and diffusion of innovations theory (DIT) to fill this gap, offering crucial insights that could inform scholars and practitioners in both the tourism and technology sectors.

Using a big-data approach, the authors applied machine learning to scrape comments made by social media users on recent popular posts or videos related to tourism in the Metaverse from three prominent social media platforms. The cleaning process narrowed down 15,461 comments to 2,650, which were then analysed using thematic, emotion and sentiment analysis techniques.

The thematic analysis revealed that virtual tourism evokes a complex range of public beliefs. While many express awe and excitement toward its immersive capabilities, others remain sceptical about authenticity compared to physical travel. Additional themes show people draw comparisons to real-world tourism, discuss technology’s role and note educational value and novelty. However, some comments raise concerns about potential societal harms, exploitation and mental health impacts. Sentiment analysis found over half of the comments positive, though some were negative. Emotion analysis showed contentment, happiness and excitement as most frequent, though sadness, worry and loneliness also featured. Overall, perceptions of Metaverse tourism encompass enthusiasm yet substantial ambivalence.

To the best of the authors’ knowledge, this study is one of the first to comprehensively analyse public discussions on Metaverse tourism. It takes TAM and Rogers’s DIT a step further and provides fresh insights into how these theories can be employed in the emerging field of Metaverse tourism. The themes revealed new conceptual insights into multidimensional factors shaping public beliefs about Metaverse tourism and thus informing scholarly research on virtual interaction and technology acceptance regarding Metaverse tourism. In addition, the results can help tourism providers, platforms and marketers address salient public beliefs and sentiments/attitudes in developing marketing offerings, experiences and communications. Over time, this analysis methodology can be used to track the evolving public perceptions of Metaverse tourism.

This paper aims to further the understanding of Open Government Data (OGD) adoption by the government by invoking two quantum physics theories – percolation theory and expander graph theory.

Extant research on the barriers to adoption and rollout of OGD is reviewed to drive home the research question for the present study. Both the theories are summarized, and lessons are derived therefrom for answering the research question.

The percolation theory solves the riddle of why the OGD initiatives find it difficult to seep across the hierarchical and geographical levels of any administrative division. The expander graph theory builds the understanding of the need for having networking among and within the key government personnel for bolstering the motivation and capacity building of the operational personnel linked with the OGD initiative. The theoretical understanding also aids in the implementation and institutionalization of OGD in general.

Intersectionality of domains for conducting research on any theme is always a need. Given the fact that there are innumerable challenges regarding the adoption of OGD by the governments across the world, the application of the two theories of quantum physics might solve the quandary in a befitting way.

Protection of personal data is integral to the digital economy, ensuring trust and privacy as its foundational elements. The purpose of this study is to analyze data protection laws in Tanzania, Kenya, Uganda and Rwanda to understand their legal frameworks and identify challenges hindering their effective implementation.

This study uses a comparative exploratory case study approach, analyzing legal frameworks of four East African (EA) countries through examination of legal documents, official reports and academic articles. The dimensions of analysis include registration, supervisory authority, data subject rights and cross-border data transfer regulations.

While all four EA countries are in the process of enacting data protection acts, they differ in scope, provisions and enforcement; more needs to be done to ensure mature data protection in these countries. The commonalities and distinctions in the legal frameworks are underscored, providing a mapping of data protection regulations in the EA region. Moreover, this study reports implementation constraints and areas for improvement.

The findings of this study provide valuable insights for policymakers, highlighting areas where data protection regulations can be improved. The results of this study can guide harmonizing regional data protection laws, ensuring consistent and effective enforcement. This study offers a foundation for future policy development and regional cooperation on data protection issues.

The social implications of this research lie in its potential to shape public attitudes on data protection and privacy rights. By highlighting these concerns, this study may influence societal norms and values, encouraging a more informed and conscientious public discourse on inclusive policies that consider the diverse needs of different regional populations.

This study provides a pioneering comparative analysis of data protection regulations across four EA countries, offering unique insights into the regional variations and commonalities in legal frameworks. Its value lies in informing future policy development, enhancing regional cooperation and contributing to the harmonization of data protection practices in the selected EA countries, which remains an under-explored area in existing literature.