In the global science ecosystem, countries' academic outputs are a key determinant of their strategic development level. The aim of this study is to examine the development dynamics of higher education systems over a period of approximately thirty years using integrated decision analytics. The scientific dynamics of OECD countries between 1996 and 2024 were analyzed using integrated LODECI and RAWEC methods based on the SCIMAGO database. The study compares long-term trends with current data from 2024 from a comparative perspective. The criterion weighting analysis conducted with LODECI determined that the Citations criterion is the most important determinant of academic competitiveness. This finding shows that the positioning of higher education institutions at the national and international levels is shaped in the context of scientific impact and productivity, beyond mere quantity. Countries were ranked according to their performance by integrating the weights into the RAWEC method. This study, which synthesizes innovative MCDM methods with long-term data, offers a unique methodological framework for analyzing countries' scientific development.
This paper presents a comprehensive bibliometric analysis of the field of cybersecurity, with a specific focus on the application of artificial intelligence (AI) in attack detection. The study aims to provide insights into the trends, research areas, and key contributions in this rapidly evolving field, while also exploring the theoretical underpinnings of security and the challenges associated with the implementation of AI in attack detection. Theoretical frameworks in cybersecurity emphasize the importance of robust and adaptive defence mechanisms, which AI technologies strive to enhance. Despite these advancements, the dynamic nature of cyber threats necessitates continuous innovation and interdisciplinary collaboration. The findings of this bibliometric analysis provide valuable insights into the development and current state of research at the intersection of cybersecurity and AI. The study highlights the most influential works, prominent authors, and emerging trends in this critical area of study. This comprehensive analysis aims to serve as a valuable resource for researchers, practitioners, and policymakers, fostering a deeper understanding of how AI technologies can be effectively leveraged to enhance cybersecurity measures and address the complexities of modern cyber threats.
This paper examines the determinants of organizational change within the contemporary business environment, with a particular focus on innovation, leadership, business communication, and teamwork. The objective is to theoretically conceptualize and empirically determine the key factors that drive the dynamics and success of corporate transformational processes. The theoretical findings indicate that innovation serves as the primary vehicle for competitive advantage, leadership acts as the critical catalyst for change, business communication constitutes the foundational platform for information exchange, and teamwork facilitates the collective execution of strategic goals. The empirical results confirm the high predictive power of the model (R2=0.982), with the level of innovation exerting the most substantial impact (β=0.416), followed by leadership (β=0.217), business communication (β=0.206), and teamwork (β=0.152). The study concludes that organizational change emerges from a synergistic relationship among the analyzed determinants, with innovative processes playing a dominant role.
Digital transformation and digital platforms have led to significant changes in the way value is created, delivered, and captured in the economy and modern business. The aim of this paper is to analyze the structure of business models, monetization models, and the geographical scope of digital platforms awarded within the World Summit Awards (WSA) program in the period 2021-2025. The research is based on a mixed-method approach with a primary focus on qualitative analysis, applying content analysis and comparative analysis to a selected sample of 25 digital platforms. The results indicate the dominance of marketplace and fintech models, which account for more than two-thirds of the analyzed sample, while SaaS and AI platforms have a smaller but globally oriented presence. From a monetization perspective, transaction-based fees represent a significant revenue generation mechanism, while subscription models are primarily applied to standardized technological solutions. The findings reveal a clear correlation between the type of business model, monetization structure, and market expansion strategy. Interaction-based platforms tend to achieve regional growth, whereas standardized models demonstrate higher global adaptability. The contribution of this paper lies in the empirical analysis of platform development patterns across different environments, thereby enhancing the understanding of growth dynamics and internationalization of digital platforms, particularly in developing countries.
Smart contracts are one of the most prevalent and important blockchain-based technologies in the field of financial security, as the automatic execution of predefined rules provides additional efficiency, lowers costs and minimizes the involvement of intermediaries. This research will examine the use of smart contracts for process automation, risk reduction and organizational restructuring in the financial sector. In particular, the interaction between centralized and decentralized financial systems, the technology behind the implementation of blockchain and security issues associated with the use of smart contracts will be considered. At the same time, escrows will be presented as an example of the practical use of smart contracts for financial operations. The results of this analysis will show that smart contracts can be used as a means to increase the reliability of financial operations; however, their widespread use depends on proper regulation, security assessment and integration with the existing financial infrastructure.
