Digital, Volume 5, Issue 1 (March 2025) – 8 articles

Workplace safety training is the cornerstone of workplace safety and accident prevention. In the case of frequently rotating employees, such as in the laboratories of higher education institutions, where students are required to perform tasks as part of their education, a considerable amount of effort for workplace safety training is demanded from the supervising instructors. Accordingly, the use of self-guided workplace safety training may lead to significant savings in the workload for instructors. In this evaluation study, we investigated to what extent an augmented reality (AR) app is deemed suitable for workplace safety training. The prototypical augmented reality (AR) app is based on an AR platform that performs tracking based on visual Simultaneous Localization and Mapping (vSLAM, Google Tango). The workplace safety training was carried out for two common stations and two devices in a workshop of an environmental engineering laboratory at a higher education institution. A total of 12 participants took part in the mixed-method study. Standardized questionnaires were used to assess usability, cognitive load and the learner prerequisites of motivation and emotion. Qualitative results were collected through subsequent semi-structured interviews. The app was able to achieve good usability, and the values for cognitive load can be classified as conducive to learning, as can the values for the learning prerequisites of motivation and emotion. The interviews provided insights into strengths, but also into potential improvements to the app. The study proved that using vSLAM-based AR apps for workplace safety training is a viable approach. However, for further efforts to establish AR-app-based workplace safety training, these insights need to be ported to a new AR platform, as the platform used has since been discontinued. Full article

The success of digital transformation initiatives relies heavily on effective digital leadership, which requires a blend of human-centric traits and technical expertise. While digital technologies enable transformation, organizations must develop leaders with the skills to navigate the complexities of change, foster innovation, and align strategies with organizational goals. Despite the growing importance of digital leadership, there is a lack of standardized, validated tools to measure and assess digital leadership competencies systematically. This study introduces the Digital Leadership Scale (DLS), a validated self-assessment tool designed to measure a leader’s ability across seven human-centric dimensions essential for digital transformation: Positive Attitude, Ethical AI Use, Growth Mindset, Track Record, Transparent Agenda, Skills Acquisition, and Participative Style. The DLS serves as a practical tool for leaders to engage in self-reflection, identify strengths and development areas, and adopt personalized learning strategies. Organizations can leverage this scale to cultivate a digitally proficient workforce and foster leadership capabilities aligned with digital transformation success. Full article

This paper presents an application of the Ant Colony Optimization (ACO) algorithm combined with the Logistic Regression (LR) method in the lead acid battery charging process. The ACO algorithm is used to obtain the best current pattern in the battery charging system to produce a smart charging system with a fast and safe charging current for the battery. The best current pattern is conducted gradually and repeatedly to obtain termination in the form of the best current pattern according to the ACO algorithm. The results of the algorithm design produce a current pattern consisting of 10 A, 5 A, 3 A, 2 A, and 0 A. The charging system with this algorithm can charge all types of lead acid batteries. In this research, the capacity of battery 1’s State of Charge (SOC) is 56%, battery 2’s SOC is 62%, and battery 3’s SOC is 80%. When recharging the battery’s full condition to a SOC of 100%, the length of time for charging battery 1 for 12.73 min, battery 2 takes 15.73 min, and battery 3 takes 29.11 min. Smart charging with the ACO can charge the battery safely without current fluctuations compared to charging without an algorithm such that the amount of charging current used is not dangerous for the battery. In addition, data analysis is carried out to determine the value of accuracy in estimating SOC charging using supervised learning linear regression. The results of the data analysis with linear regression show that the battery’s SOC estimation has good accuracy, with an RMSE value of 0.32 and an MAE of 0.27. Full article

In South Korea, Generation Z’s influence on the growth of sports over-the-top (OTT) services is significant. For sustainable growth, OTT service providers need to focus on converting existing users into loyal customers. In this context, understanding Generation Z’s subjective perceptions of the constraints on the continued use of sports OTT services would be meaningful. Therefore, this study aims to identify and categorize the factors constraining Generation’s Z’s continued use of sports OTT services using the Q methodology. A total of 25 Q samples and 18 P samples were selected. The QUANL program was used to calculate the correlation coefficients for each respondent, and Q factor analysis was performed through principal component analysis and varimax rotation. As a result, three types were identified: ‘Demand for improvements in pricing plans and system quality’, ‘Dissatisfaction with subscription fees and demand for diverse content’, and ‘Demand for differentiated services’. The findings of this study suggest that, for Generation Z’s continued use of OTT services, it is essential to provide personalized experiences and benefits or satisfaction relative to subscription fees. On top of that, offering various pricing plans can provide flexibility in service choices and encourage continued use among Generation Z. As such, this study can provide insights into appreciating the consumption trends and factors influencing the continued use of OTT services by Generation Z and interpreting related research results in the future. Full article

This study investigates the integration, usability, and learning patterns associated with voice assistant technology among older adults, focusing on the “Amazon Echo Show 10, 3rd generation” as a case study. Conducted with 32 participants aged 55 and above in senior and complementary households, this research employs a mixed-method approach, incorporating qualitative interviews and quantitative voice command logging over a twelve-week period. Our findings reveal a high level of learnability and usability of the voice assistant, with 90% of participants finding the device easy to learn and use. The study further explores the patterns of voice assistant use, highlighting a preference for listening to music and seeking information, predominantly on weekends. Despite initial reservations, participants reported a high satisfaction level, with most not feeling monitored by the device. Key recommendations for manufacturers include prioritizing the design and user experience to cater to older adults’ needs, aiming to enhance their digital inclusion and participation. This study contributes to the human–computer interaction (HCI) field by providing insights into older adults’ interactions with voice assistant technology, emphasizing the importance of designing accessible and user-friendly digital solutions for the aging population. Full article

Cybercrime prevention is critical for the effective functioning of e-government services. Despite its importance, internal cybercrime mitigation processes within these services are underrepresented in the existing literature. This study addresses this gap by conducting a systematic review and bibliometric analysis of e-government research from January 2015 to January 2025. Using the Web of Science and Scopus databases, 3790 studies were identified; after removing duplicates, bibliometric analysis was performed using R Studio (Build 467). The analysis revealed that Government Information Quarterly was the leading journal, with China, the USA, and the UK contributing the most publications. Nineteen major themes emerged, with “adoption” identified as the dominant theme, followed by “governance” and “development”. Among 88 security-related studies, 19 specifically addressed cybersecurity in e-government services. Findings indicate a predominant focus on user-centric perspectives, such as service adoption and system vulnerabilities, while internal cybersecurity issues, including managerial practices and mitigation strategies, remain largely unexplored. Limited data availability may contribute to this gap. This study highlights the need for future research to adopt an integrated approach, emphasising management-level practices for cybercrime mitigation within e-government institutions from both developing and developed nations. Full article

Crowd panic emergencies can pose serious risks to public safety, and effective detection and mapping of such events are crucial for rapid response and mitigation. In this paper, we propose a real-time system for detecting and mapping crowd panic emergencies based on machine learning and georeferenced biometric data from wearable devices and smartphones. The system uses a Gaussian SVM machine learning classifier to predict whether a person is stressed or not and then performs real-time spatial analysis to monitor the movement of stressed individuals. To further enhance emergency detection and response, we introduce the concept of CLOT (Classifier Confidence Level Over Time) as a parameter that influences the system’s noise filtering and detection speed. Concurrently, we introduce a newly developed metric called DEI (Domino Effect Index). The DEI is designed to assess the severity of panic-induced crowd behavior by considering factors such as the rate of panic transmission, density of panicked people, and alignment with the road network. This metric offers immeasurable benefits by assessing the magnitude of the cascading impact, enabling emergency responders to quickly determine the severity of the event and take necessary actions to prevent its escalation. Based on individuals’ trajectories and adjacency, the system produces dynamic areas that represent the development of the phenomenon’s spatial extent in real time. The results show that the proposed system is effective in detecting and mapping crowd panic emergencies in real time. The system generates three types of dynamic areas: a dynamic Crowd Panic Area based on the initial stressed locations of the persons, a dynamic Crowd Panic Area based on the current stressed locations of the persons, and the dynamic geometric difference between these two. These areas provide emergency responders with a real-time understanding of the extent and development of the crowd panic emergency, allowing for a more targeted and effective response. By incorporating the CLOT and the DEI, emergency responders can better understand crowd behavior and develop more effective response strategies to mitigate the risks associated with panic-induced crowd movements. In conclusion, our proposed system, enhanced by the incorporation of these two new metrics, proves to be a dependable and efficient tool for detecting, mapping, and assessing the severity of crowd panic emergencies, leading to a more efficient response and ultimately safeguarding public safety. Full article

This study highlights the Digital Transformation issues in recent scientific topics, as well as the trends in the European Union’s Digital Economy dynamics. The aim is to identify key and promising research topics in the digital field and define priorities for adopting digital innovations in the EU in terms of bibliographical and statistical aspects. The study includes a bibliographic analysis using publication metrics statistics, word cloud diagrams, and network clustering. There is also a quantitative analysis of the leading Digital Economy trends in the EU using correlation and cluster analyses and visualizations of the selected economic and Digital Transformation metrics. The results identify critical keywords in digitalization publications related to other key research and multidisciplinary areas. A grouping is proposed of research paper topics and research issues related to Digital Transformation in the EU and worldwide based on the identified trends in recent research proposals. The study examines the correlation of some digital indices and trends in EU countries’ GDP dynamics, R&D investment, and digital inclusion. From the clustering based on the data of a single digital market that promotes e-commerce for individuals and businesses, groups of EU countries have been identified as having the potential to increase digital inclusion and convergence growth rate. The results provide a basis for future research on Digital Transformation and determine the need for further intensification of EU digitalization. Full article