Institutional Repository of Academic Research University of Macedonia
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A Virtual Reality Museum to Reinforce the Interpretation of Contemporary Art and Increase the Educational Value of User Experience
No full textThe cultural heritage sector increasingly integrates augmented and virtual reality (VR) solutions to meet dissemination and interpretation needs for its collections. As research in the field grows, the required entertainment and learning impacts of such applications are rising. This study presents a VR museum that aims to facilitate an understanding of cultural heritage. More specifically, an exhibition was designed, curated and developed in a VR environment based on a framework that encourages the public’s interaction with the artworks and experiential learning through activities that utilize VR functionalities in a meaningful way. This framework was applied in a contemporary art museum where the description of artistic concepts is not always obvious to the general public due to the abstract forms of the artworks or the particularities of different artistic movements. This paper focuses on the application development and three user experience evaluations (museum experts, technical experts and general audience). The results were positive regarding the perceived sense of control, usability and the feelings of the user, including their sense of entertainment. Additionally, the participants valued the educational value of the developed activity types and their usefulness. Moreover, the users were interested in exploring the cultural heritage content available in the exhibition, and they would suggest the application to colleagues or friends.654134417
Examining the effects of creativity, collaboration, creative diversity and autonomy on team creative performance
No full textThe present study investigated the multidimensional relationships among some of the factors which affect the creative performance of teams, including creativity, collaboration, diversity, and autonomy in educational settings. Two hundred and thirty one (231) university students of Informatics worked in teams for a whole semester, and their projects were evaluated for creativity with the Consensual Assessment Technique. Structural equation modeling and path analysis with bootstrapping were used to analyze the collected data and examine relationships. According to the results, the creative diversity of teams had a significant positive relationship with their creative performance, whereas the aggregated individual creativity of members did not have a significant effect. Collaboration among team members had a positive impact on the teams’ creative outputs and also partially mediated the relationship between creative diversity and creative performance. Autonomy of members correlated significantly with their creativity, however, at the team level, there was not a significant relationship between autonomy and creative performance. Theoretical and practical implications are discussed and future research directions are proposed.5010141
Macroeconomic Uncertainty Indices for European Countries
No full textThe present article seeks to develop a macroeconomic uncertainty index for the EU Member States based on Google Trends for a period of fifteen years (from January 2008 to December 2022). Monthly data were collected for the 12 countries for four different word-terms, as well as for unemployment rate, inflation and the 10-year Government Bond yield. For simplifying the research the keywords searched were in English and were not translated into the countries’ own languages. Our findings were then compared to existing uncertainty indices. Lastly, we employed Impulse Response Functions (IRFs) with the existing economic indicators to highlight the effect that one standard deviation shock on the uncertainty index has on all three indicators and its ability to accurately depict the future precariousness of the country.Keywords: Uncertainty; Google trends; European uncertainty index.20235775
Revisiting the Mankiw et al. (1992) growth regressions
No full textWe revisit the famous Mankiw et al 1992 (MRW) paper by updating the data for the periods 1960-2015, 1970-2015 and 1990-2015. We present results for the Solow, the augmented Solow model and the conditional convergence on saving rates, population growth and human capital. The augmented model fits the data better. Human capital remains significant and higher than the MRW estimates for both the augmented model and the conditional convergence. The updated dataset highlights that the importance of human capital for growth is higher than MRW have demonstrated to be. The datasets for reproduction are also provided.12324124
A novel modeling framework for quantifying spatial spillovers on total factor productivity growth and its components
No full textThis article presents a novel modeling framework that quantifies spatial spillovers on firm total factor productivity (TFP) growth and its components in a single-stage setting. A random parameters frontier model is specified to measure firm efficiency and calculate TFP growth and its components while allowing for the random parameters and the inefficiency term to be functions of individuals' and neighbors' characteristics. In this manner, the dependence of TFP growth and its components on these characteristics is built into the model, and the corresponding marginal effects are calculated. The empirical application concerns specialized Dutch dairy farms observed over the 2009–2016 period. Apart from the conventional input–output quantities, information on farms' latitudes and longitudes is available, thus allowing the identification of neighboring producers and testing for the existence of spatial spillovers. The empirical findings suggest that farms surrounded by more intensive neighbors experience faster technical progress and TFP growth, which highlights the existence of positive spatial spillovers in Dutch dairy farming.10541221124
An Aggregation-Based Algebraic Multigrid Method with Deflation Techniques and Modified Generic Factored Approximate Sparse Inverses
No full textIn this paper, we examine deflation-based algebraic multigrid methods for solving large systems of linear equations. Aggregation of the unknown terms is applied for coarsening, while deflation techniques are proposed for improving the rate of convergence. More specifically, the V-cycle strategy is adopted, in which, at each iteration, the solution is computed by initially decomposing it utilizing two complementary subspaces. The approximate solution is formed by combining the solution obtained using multigrids and deflation. In order to improve performance and convergence behavior, the proposed scheme was coupled with the Modified Generic Factored Approximate Sparse Inverse preconditioner. Furthermore, a parallel version of the multigrid scheme is proposed for multicore parallel systems, improving the performance of the techniques. Finally, characteristic model problems are solved to demonstrate the applicability of the proposed schemes, while numerical results are given.11364
Business Process Management Analysis with Cost Information in Public Organizations: A Case Study at an Academic Library
No full textPublic organizations must provide high-quality services at a lower cost. In order to accomplish this goal, they need to apply well accepted cost methods and evaluate the efficiency of their processes using Business Process Management (BPM). However, only a few studies have evaluated the addition of cost information to a process model in a public organization. The aim of the research is to evaluate the combination of cost data to process modeling in an academic library. Our research suggests a new and easy to implement process analysis in three phases. We have combined qualitative (i.e., interviews with the library staff) and quantitative research methods (i.e., estimation of time and cost for each activity and process) to model two important processes of the academic library of the University of Macedonia (UoM). We have modeled the lending and return processes using Business Process Model and Notation (BPMN) in an easy-to-understand format. We have evaluated the costs of each process and sub process with the use of Time-Driven Activity-Based Costing (TDABC) method. The library’s managers found our methodology and results very helpful. Our analysis confirmed that the combination of workflow and cost analysis may significantly improve the decision-making procedure and the efficiency of an organization’s processes. However, we need to further research and evaluate the appropriateness of the combination of various cost and BPM methods in other public organizations.4225126
The ISO/IEC 27001 Information Security Management Standard: How to Extract Value from Data in the IT Sector
No full textIn order to handle their regulatory and legal responsibilities and to retain trustworthy strategic partnerships, enterprises need to be dedicated to guaranteeing the privacy, accessibility, and authenticity of the data at their disposal. Companies can become more resilient in the face of information security threats and cyberattacks by effectively integrating security strategies. The goal of this article is to describe a plan that a corporation has implemented in the information technology industry in order to ensure compliance with International Organization for Standardization (ISO) 27001. This research demonstrates an examination of the reasons that force enterprises to make a investment in ISO 27001 in addition to the incentives that might be acquired from having undergone this process. In addition, the research examines the reasons that push firms to make an investment in ISO 27001. More particularly, the research investigates an international IT consulting services institution that is responsible for the implementation of large-scale business assistance insertion and projects. It demonstrates the risk management framework and the administrative structure of the appropriate situations so that its procedures are adequate and also in line with the guidelines founded by ISO 27001. In conclusion, it discusses the problems and difficulties that were experienced.157582
Dynamic Capabilities and Digital Transformation in the COVID-19 Era: Implications from Driving Schools
No full textBackground: The COVID-19 pandemic is a worldwide threat that has positioned micro-enterprises under enormous tension to persevere. As a result, these businesses are obligated to respond to the epidemic in an efficacious manner. In order to weather this economic storm, micro-enterprises have implemented a variety of digital technologies. Methods: The research investigates the connection between the communications technology of driving schools and the public crisis responses of those driving schools using a data set obtained from a survey administered to those schools. Results: The quantitative findings demonstrate that digitalization has made it possible for driving schools to efficiently and successfully respond to the public dilemma by utilizing their resilient functionality. In addition, digitalization can greatly enhance driving schools’ performance. Conclusions: This paper provides drawings for digitalization and crisis responses for driving schools.748
Probabilistic Community Detection in Social Networks
No full textThe detection of community structures is a very crucial research area. The problem of community detection has received considerable attention from a large portion of the scientific community. More importantly, these articles are spread across a large number of different disciplines, from computer science, to statistics, and social sciences. The analysis of modern social networks becomes rather cumbersome, as their size and number keeps growing larger and larger. Moreover, in the modern communities, users participate in large number of groups. From the network perspective, efficient methods should be developed to automatically identify overlapping communities, that is, communities with overlapping nodes. In this work, we use a probabilistic network model to characterize and identify linked communities with common nodes. The innovative idea in this work is that the communities are represented as Markovian networks with continuously changing states. Each state represents the number of users within a cluster, that have specific characteristic classes. Based on the current state, we introduce a fast, linear on the number of newly added users, approach to estimate the probability of each cluster to be homogeneous in terms of sets of user characteristics and to determine how well the new user fit within a community. Because of the linear computations involved, our proposed probabilistic model can detect communities and overlaps with low execution time and high accuracy, as shown in our experimental results. The experimental results have shown that our probabilistic scheme executes faster and provides more robust communities compared to competitive schemes.11256292564