The presented article focusses on the analysis of perception of the university social responsibility through the eyes of Slovak university students. The aim is to compare how the values, efficiency of the organisation (university), and the educational process influence the perception of social responsibility among university students themselves. The research is based on the application of quantitative methodology towards the evaluation of differences and similarities in perceptions using two types of tests for statistical analysis, comparative (Mann-Whitney U test) and correlational (bivariate correlation matrix of Spearman’s rho).The results of the research provide a deeper understanding of how universities can shape students’ approach to social responsibility through their values and educational processes, which has important implications for the development of university policies and practices.
This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.
In recent years, information technology and social media has developed very rapidly and has had an impact on government services to the public. Social media technology is used hugely by several developing countries to provide services, information and promote information disclosure in its government to improve its performance. This study aims to build role of social media technology concept as a public service delivery facilitator to the public. Furthermore, it discusses the potential impact of social media use on government culture. To achieve the goal, this study combines two theories, namely government public value theory and green smart city with four variables, namely quality of public services, user orientation, openness, and greenness. These variables are used as the foundation for data collection through in-depth interviews and group discussion forums. In-depth interviews are utilized as data search and direct observation. The informants consist of several government elements, including heads of regional apparatus organizations, heads of public service malls and Palembang city government employees. The study revealed that the Palembang government has several social media-based public services that have quality of services, user-orientation, openness, and environmental friendliness.
This research paper aims to benchmark the characteristics of financial systems for 102 countries worldwide from the period of 2005 to 2017. The financial systems’ database encompasses four main dimensions, each consisting of several variables for every indicator: (a) financial depth, (b) financial efficiency, (c) financial access, and (d) financial stability. The objective is to closely analyse the different factors that contribute to the attractiveness of financial and economic systems globally. Furthermore, this paper employs a literature review and an empirical modelling and classification of financial systems worldwide to assess their attractiveness. The modelling process utilizes two statistical analysis methods: discriminant analysis (PCA) and neural analysis. By doing so, this research paper aims to identify the most appropriate measures to strengthen these systems and economies. The main conclusion of the research is to establish a ranking of the world’s best countries and also the validation of the hypothesis that macroeconomic conditions are the effective determinants of the classification dimensions of financial systems.
This empirical inquiry adopts the AutoRegressive Distributed Lag (ARDL) model to meticulously examine the multifaceted interconnections among innovation, globalization, and productivity across a diverse set of 76 nations, encompassing both developed and developing economies. The research employs rigorous econometric techniques within the ARDL framework to discern the short- and long-term effects of innovation and globalization on productivity levels. The findings underscore a robust and statistically significant association between innovation and productivity, as well as a constructive impact of globalization on enhancing productivity. The outcomes underscore the transformative potential of innovation and the facilitating role of globalization in fostering productivity growth. This empirical evidence contributes to the empirical literature by offering a refined understanding of the intricate relationships shaping productivity patterns on a global scale, emphasizing the joint influence of innovation and globalization in driving economic efficiency.
This paper analyzes the characteristics and influence mechanisms of financial support for China’s strategic emerging industries. Using a sample of 356 listed companies across nine major industries, we conduct an in-depth analysis of the efficiency of financial support and its influencing factors. In addition, this paper analyzes the influence mechanism of financial support for strategic emerging industries based on the relevant theory of financial support for industry development. It clarifies the internal and external influencing factors. Based on the theoretical analysis, a two-stage empirical investigation was conducted: The data of 356 listed companies in strategic emerging industries from 2010 to 2022 were selected as a sample, and the data envelopment analysis (DEA) method was applied to measure efficiency. The influencing factors were then analyzed using a Tobit regression and an intermediate effects test.
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