The selection of an appropriate operating system (OS) in educational environments is a critical decision that impacts the functionality, user experience, and overall efficiency. Financial factors, along with the availability and functionality of tools used on these systems, play a crucial role in this selection. Furthermore, the OS affects the user experience, security, and adaptability to learning. Previous research in this area is scarce, and this paper contributes to a better understanding of the OS selection process in education. This paper proposes a novel multi-criteria decision-making approach to evaluate and select the most suitable OS for educational institutions. The methodology integrates the PIPRECIA method for assessing weighted criteria, alongside utility analysis (NWA), enabling a balanced decision-making process between institutional management and IT experts. The evaluation considered the following criteria: performance, cost, security, usability, implementation, support, and documentation. The study compared three popular operating systems: Microsoft Windows 11, GNU Linux Ubuntu 22.04 LTS, and Apple macOS 12 using the proposed approach. The results, based on the integrated evaluation of all criteria, indicate that GNU Linux Ubuntu 22.04 LTS (0.562) ranked highest, followed by Microsoft Windows 11 (0.553) and Apple macOS 12 (0.543). This paper emphasizes the importance of objective, group-based decision-making in selecting an OS for education, providing practical insights and guidelines for effective technology integration in academic settings.

As e-commerce continues to grow, businesses are realizing the significance of having a strong online presence through well-designed websites. This study aims to establish a comprehensive understanding of the key factors that contribute to website quality and their importance from the consumer's perspective. The main objectives of this research are to identify and prioritize these factors. To achieve this, a questionnaire was distributed among a younger demographic, and participants were asked to rate the importance of 11 parameters related to website quality. The data collected from the survey were analyzed using various statistical tests, including descriptive statistics, Chi-square independence test, and factor analysis. These tests were employed to rank the parameters, examine the influence of gender on respondents' answers, identify areas of disagreement among participants, and determine if certain parameters could be grouped together. The quality of a Web page is greatly influenced by various features, including its layout, visual complexity, colorfulness, user-friendliness, speed of processing visitor requests, and reliability. To analyze these features, a feature vector was created. Conducted as exploratory descriptive research, this study utilized a survey to gather data from 117 participants across different social networks. The research encompasses both qualitative and quantitative stages. The qualitative phase aims to identify variables that impact consumer engagement in social commerce, while the quantitative phase involves data collection, validation, and analysis.

The increasing demand for energy-efficient and interconnected smart buildings, particularly in the tourism sector, has driven the adoption of advanced wireless technologies. IoT technologies are crucial in this evolution, improving modern buildings’ functionality and operational efficiency. This study investigates the utilization of various wireless technologies within Wireless Personal Area Networks (WPANs), including Bluetooth BLE 4.2, Bluetooth BLE 5.0, ZigBee, and Z-Wave, in smart buildings. A multiple-criteria decision-making (MCDM) approach, specifically the PIPRECIA-S model, was applied to evaluate these technologies based on criteria such as device connectivity, mobility, low energy consumption, scalability, flexibility, and interoperability. Simulations using the PIPRECIA-S model were conducted to assess technology performance across various real-world scenarios. The results indicate that ZigBee (0.2942) and Bluetooth BLE 5.0 (0.2602) provide superior performance in terms of energy efficiency and scalability, followed by Z-Wave (0.2550) and Bluetooth BLE 4.2 (0.1906). These findings provide decision-makers with data-driven recommendations for selecting the most suitable wireless technologies for smart buildings.

Despite the intensive development of research in the field of cyber security, existing approaches still dominantly view security culture through the prism of formal policies, training and technical controls, ignoring the deeper organizational determinants of employee behavior. This paper proposes an original integrative framework - the Four Path Model (FPM) - that operationalizes causal paths from organizational culture to cybersecurity behavior for the first time. The model identifies cybersecurity culture as an emergent property of the broader organizational culture and specifies measurable indicators for each level of culture, addressing the practical challenge of assessing implementation. Unlike previous descriptive models, FPM offers operationalized pathways through which organizations achieve greater compliance, reduce human factor risk, and increase resilience to cyber incidents.

The rise of advanced digital technologies (ADT) within Industry 4.0 has transformed modern industrial operations, with select industry leaders emerging as pioneers in the integration of these technologies. This has positioned them as benchmarks for companies with limited digital capabilities. The vulnerabilities of Industry 4.0 to external disruptions, including natural disasters such as the earthquakes in Japan and Turkey, the COVID-19 pandemic, and especially the ongoing energy crises, exemplified by the war in Ukraine and sanctions on the Russian Federation, have necessitated a shift in business continuity management (BCM) strategies. Traditionally focused on safeguarding information technologies, BCM now places greater emphasis on ensuring energy independence and reducing reliance on state-controlled critical infrastructure. In response to these risks, enterprises are increasingly adopting resilient production models designed to restore functionality after cyberattacks, solar flares, extended power outages, and internet disruptions. The journey toward energy independence spans from initial recognition of the need for action to the implementation of robust solutions, such as Faraday cages for server protection and off-grid energy systems. While rare a decade ago, energy-independent enterprises are becoming more common, as illustrated by the copper smelter in Sevojno, a pioneering example. The acceleration of energy independence among companies has been driven by a series of crises, prompting significant BCM advancements. Early responses to these threats primarily focused on information technology (IT) disaster management methodologies, but Industry 4.0 discussions have evolved toward risk-resilient production systems. This study explores theoretical approaches to enhancing enterprise resilience to modern energy challenges, offering insight into emerging strategies aimed at safeguarding continuity in an increasingly volatile global landscape.