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An Event-Centric Knowledge Graph Approach for Public Administration as an Enabler for Data Analytics
No full textIn a continuously evolving environment, organizations, including public administrations, need to quickly adapt to change and make decisions in real-time. This requires having a real-time understanding of their context that can be achieved by adopting an event-native mindset in data management which focuses on the dynamics of change compared to the state-based traditional approaches. In this context, this paper proposes the adoption of an event-centric knowledge graph approach for the holistic data management of all data repositories in public administration. Towards this direction, the paper proposes an event-centric knowledge graph model for the domain of public administration that captures these dynamics considering events as first-class entities for knowledge representation. The development of the model is based on a state-of-the-art analysis of existing event-centric knowledge graph models that led to the identification of core concepts related to event representation, on a state-of-the-art analysis of existing public administration models that identified the core entities of the domain, and on a theoretical analysis of concepts related to events, public services, and effective public administration in order to outline the context and identify the domain-specific needs for event modeling. Further, the paper applies the model in the context of Greek public administration in order to validate it and showcase the possibilities that arise. The results show that the adoption of event-centric knowledge graph approaches for data management in public administration can facilitate data analytics, continuous integration, and the provision of a 360-degree-view of end-users. We anticipate that the proposed approach will also facilitate real-time decision-making, continuous intelligence, and ubiquitous AI.1311
Regulatory profiling and endogenous benchmarking
No full textBanks' responses to regulatory requirements have a direct effect on their balance sheet mix and their business models. The paper introduces the concept of regulatory profiling, which establishes a nexus between banks' operations and their regulatory choices. Regulatory profiling is a process that identifies an optimal number of regulatory peers sharing similar operational characteristics for a bank. We also introduce a novel methodology for identifying the optimal direction of improvement in bank operations through Principal Components Pursuit, thereby overcoming restrictive shortcomings of competing approaches. This methodology identifies the core operations within each regulatory profile, which are effectively projections of the actual operations, and uses the projected points as optimal directions of improvement. Using data from US commercial banks following the Dodd-Frank Act's relaxation, we find empirical evidence of convergence in operations while controlling for banks' regulatory responses. Core banking operations shift towards a safer mode of operations, arguably to improve capital adequacy. Our findings are validated for banks' risk and profitability while carry important policy implications, since regulatory profiling seems to matter the most for smaller banks.96Part A10357
The impact of culture on the acceptance of Industry 4.0 technologies in Greek organisations: An empirical investigation of a lean digital transformation
No full textPurpose- In the digital era, studying how employees interact with technology and what the role of management can be to foster this interaction are of the utmost strategic importance. In this sense, the purpose of this study is to measure the impact of a lean and digital form of organisational culture on the intention to use Industry 4.0 technologies. Design/methodology/approach- This research draws on the socio-technical systems and the technology acceptance theories to analyse and measure people's attitudes on the road to digital transformation supported by lean principles. A comprehensive review of the literature led to the composition of a research model that highlights the intention to use digital technologies as a composite construct of effort expectancy, performance expectancy, and social influence moderated by user resistance and anxiety. An empirical survey was launched in Greek organisations over a three-month period. 452 usable responses were collected by employees of different positions and ranks. The validity of the integrated measurement model was then confirmed using partial least squares structural equation modelling (PLS-SEM). Findings - Research limitations/implications- The results show a positive and significant relationship between lean-digital organisational culture and the intention to use Industry 4.0 technologies. Future research could test the model in other locations to increase generalisability. Practical implications- From a practical viewpoint, the validated model can aid decision-makers by providing a foundation for developing targeted action plans to facilitate technology adoption. Originality/value- This study is pioneering in bringing together the technology adoption intention and a particular organisational culture that merges lean management and digital transformation, offering novel insights to managers and researchers.383408Proceedings of the 6th International Conference on Quality Engineering and Management, ICQEM 202
Impact of Artificial Intelligence on Learning Management Systems: A Bibliometric Review
No full textThe field of artificial intelligence is drastically advancing. This study aims to provide an overview of the integration of artificial intelligence into learning management systems. This study followed a bibliometric review approach. Specifically, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, 256 documents from the Scopus and Web of Science (WoS) databases over the period of 2004–2023 were identified and examined. Besides an analysis of the documents within the existing literature, emerging themes and topics were identified, and directions and recommendations for future research are provided. Based on the outcomes, the use of artificial intelligence within learning management systems offers adaptive and personalized learning experiences, promotes active learning, and supports self-regulated learning in face-to-face, hybrid, and online learning environments. Additionally, learning management systems enriched with artificial intelligence can improve students’ learning outcomes, engagement, and motivation. Their ability to increase accessibility and ensure equal access to education by supporting open educational resources was evident. However, the need to develop effective design approaches, evaluation methods, and methodologies to successfully integrate them within classrooms emerged as an issue to be solved. Finally, the need to further explore education stakeholders’ artificial intelligence literacy also arose.897
TD Classifier: Automatic Identification of Java Classes with High Technical Debt
No full textTo date, the identification and quantification of Technical Debt (TD) rely heavily on a few sophisticated tools that check for violations of certain predefined rules, usually through static analysis. Different tools result in divergent TD estimates calling into question the reliability of findings derived by a single tool. To alleviate this issue, we present a tool that employs machine learning on a dataset built upon the convergence of three widely-adopted TD Assessment tools to automatically assess the class-level TD for any arbitrary Java project. The proposed tool is able to classify software classes as high-TD or not, by synthesizing source code and repository ac-tivity information retrieved by employing four popular open source analyzers. The classification results are combined with proper vi-sualization techniques, to enable the identification of classes that are more likely to be problematic. To demonstrate the proposed tool and evaluate its usefulness, a case study is conducted based on a real-world open-source software project. The proposed tool is expected to facilitate TD management activities and enable fur-ther experimentation through its use in an academic or industrial setting. Video: https://youtu.be/umgXU8u7lIA Running Instance: http://160.40.52.130:3000/tdclassifier Source Code: https://gitlab.seis.iti.gr/root/td-classifier.git7680Proceedings of the International Conference on Technical Deb
Trust in E-Government and Successful Information Management in the Public Sector During a Pandemic: Proposing an Extended Framework
No full textThe COVID-19 pandemic invaded the lives of people all over the world in early 2020 and created a new way of life for everyone. In order for the Greek government to be able to cope with the difficult situation, it suddenly found itself in, and, for development to continue in all sectors, it was deemed imperative that the government cooperate with the various state mechanisms and take the appropriate measures to solve the existing technical problems that arose due to the imposition of lockdowns and social distancing measures. The main – and most significant – of all the measures that needed to be taken in this respect was the creation of a digital state and the possibility of internet access for all the citizens of the country, so that everyone could continue to work, communicate, be educated, and be facilitated by the various state services with as little exposure to the deadly virus as possible. The purpose of this chapter is to propose an extension of the well-known DeLone and McLean Information System success model by incorporating the factor of trust in e-government, which arguably can contribute by improving the effectiveness of government.649657Computational and Strategic Business Modellin
Attitudes and Self-efficacy of Swimming Coaches towards the Inclusion of Swimmers with Autism Spectrum Disorder
No full textΠρόκειται για περιοδικό/δημοσίευση Open Access.The purpose of this study was to investigate the attitudes and self-efficacy of swimming coaches regarding the inclusion of swimmers with autism spectrum disorder (ASD). The sample consisted of 150 Greek swimming coaches with an average age of 29.58 years. Each participant completed the Swimming Coaches Attitudes towards Inclusion Questionnaire for perceptions assessment and the Biddle and Goudas (1997) self-efficacy questionnaire. The statistical analysis used SPSS 27 to calculate Cronbach’s alpha, Pearson product-moment correlations, independent t-tests, and ANOVA. The findings of the study showed that the swimming coaches expressed positive attitudes and a high percentage of perceived self-efficacy towards the inclusion of athletes with ASD in the general swimming team. Attitudes were not associated with self-efficacy. Training in adapted physical education and the geographical distribution seemed to influence attitudes whereas gender and coaching experience influenced self-efficacy. Overall, swimming coaches expressed positive attitudes towards the inclusion of swimmers with ASD in their general team and considered their teaching effective.143
Evaluating Factors Affecting Users’ Intention to Use and Satisfaction in the Digital Justice Sector
No full textICT use in e-government, especially in the justice sector, opens up new possibilities and improves user and citizen services. Studies looking at the acceptance and satisfaction of users of the electronic justice system are scarce, despite the fact that this scientific field has drawn the interest of many academics and professionals in the justice sector and that money has been spent on enhancing the performance of justice staff and the outcomes of the courts. Thus, in the context of Greek e-justice services, this paper evaluates level of IS employees’ satisfaction in the justice sector. Data was collected by 121 internal users in Greece. Employees appears that they are more concerned with obtaining a positive overall impression of the system and making sure that the application has quality dimensions that will enable it to be helpful for their everyday work activities.14907 LNCS210221Disruptive Innovation in a Digitally Connected Healthy Worl
Evaluating the Efficacy of AI Techniques in Textual Anonymization: A Comparative Study
No full textIn the digital era, with escalating privacy concerns, it's imperative to devise robust strategies that protect private data while maintaining the intrinsic value of textual information. This research embarks on a comprehensive examination of text anonymisation methods, focusing on Conditional Random Fields (CRF), Long Short-Term Memory (LSTM), Embeddings from Language Models (ELMo), and the transformative capabilities of the Transformers architecture. Each model presents unique strengths since LSTM is modeling long-term dependencies, CRF captures dependencies among word sequences, ELMo delivers contextual word representations using deep bidirectional language models and Transformers introduce self-attention mechanisms that provide enhanced scalability. Our study is positioned as a comparative analysis of these models, emphasising their synergistic potential in addressing text anonymisation challenges. Preliminary results indicate that CRF, LSTM, and ELMo individually outperform traditional methods. The inclusion of Transformers, when compared alongside with the other models, offers a broader perspective on achieving optimal text anonymisation in contemporary settings.2422462024 7th International Balkan Conference on Communications and Networking (BalkanCom
Enhanced Inclusion through Advanced Immersion in Cultural Heritage: A Holistic Framework in Virtual Museology
No full textIn recent years, the digitization of cultural heritage has been favored by significant advancements in specific technologies, such as photogrammetry and three-dimensional scanning. The digital representations of artifacts, paintings, books, and collections, as well as buildings or archaeological sites, has led to the transfer of cultural organizations to the digital space. On the other hand, the rapid development of immersive technologies and the Internet of Things is expected to decisively shape virtual cultural heritage in the coming years. However, this digital transition should expand its impact on most of the population. This article aims to cover the lack of structured methodology in the design and development of inclusive virtual spaces in cultural heritage. This research introduces a holistic framework that is mainly based on the disciplines of virtual museology. The proposed methodology takes into account the advancements in extended reality and the creative industry of computer games. The multisensory approach would lead to advanced immersive experiences, while the multilayered approach of cultural heritage content would enhance accessibility in inclusive virtual spaces. Moreover, this holistic framework could provide evidence from the virtual worlds that could be applied to real cultural heritage organizations.137139