Radovan Dragić

This paper presents the findings of a study aimed at exploring students activities during lectures and exercises. The research was conducted through basic population of students at the University “St. Kliment Ohridski” – Bitola, in academic years from 2015 to 2023. The data obtained from the continuous checking of the students’ knowledge, which refer to: attendance and activity in lectures and exercises, preparation of seminar papers, independent (home) work, completed or realized projects / programs, as well as from the colloquium grades, are the basis for the application of linear statistical models that will be realized through descriptive, correlation and regression analysis, factor analysis and statistical inference. In this way, information is obtained from a series of indicators that will serve the professors to take appropriate corrective actions, in order to improve and better create their teaching and educational process. As a result, it is expected to obtain better results that are of interest to students and higher education institutions, in terms of increasing the quality and efficiency of the teaching and learning process in higher education.

In this research, the impact of applications on improving urban logistics was examined using the example of the company EX, with an emphasis on the sustainability of its business. To conduct this research, expert decision-making was used. The model used ten criteria and eight applications. To incorporate uncertainty into this research, an intuitionistic fuzzy approach was used. Based on the obtained CC values, the criteria weights were determined using the SiWeC (Simple Weight Calculation) method, while the WASPAS (Weighted Aggregated Sum Product Assessment) method ranked the applications. The results showed that “Security and data protection” and “System reliability and stability” were the most important criteria, while Application 1 achieved the best results. These results were confirmed by the consistency analysis of the WASPAS method and the sensitivity analysis, which considered 30 scenarios.

The development of technology has influenced changes in agricultural production. Farmers are increasingly using modern devices and machinery that provide valuable information, and to manage this information effectively, it is necessary to use specialized applications. This research aims to evaluate various applications and determine which one is most suitable for small- and medium-sized farmers to adopt in precision agriculture. This research employed expert decision-making to determine the importance of criteria and evaluate applications using linguistic values. Due to the presence of uncertainty in decision-making, an interval type-2 fuzzy (IT2F) set was used, which addresses this problem through the support of a membership function. This approach allows for the display of uncertainty and imprecision using an interval rather than a single exact value. This enables a more flexible and realistic representation of ratings, leading to more confident decision-making. These membership functions are formed in such a way that there is symmetry around the central linguistic value. To use this approach, the SiWeC (simple weight calculation) and CORASO (compromise ranking from alternative solutions) methods were adapted. The results of the IT2F SiWeC method revealed that the most important criteria for experts are data accuracy, efficiency, and simplicity. The results of the IT2F CORASO method displayed that the A3 application delivers the best results, confirmed by additional analyses. This research has indicated that digital tools, in the form of applications, can be effectively used in small- and medium-scale precision agriculture production.

This study examines the influence of artificial inte ligence (AI), social unrest, and economic development as key antecedents in the selection of foreign tourist destinations. Specifica ly, it investigates the extent to which tourists utilize AI tools during the decision-making process and the role AI algorithms play in facilitating destination choice. Additiona ly, the research explores how social unrest, by disrupting stability and legal order, impacts tourists’ preferences, alongside the e fect of economic development on destination attractiveness. The empirical research was conducted in the Republic of Serbia in 2025 using the survey method, and the respondents' answers were analyzed using the statistical software SmartPLS 4. The total sample consisted of 310 respondents, and the findings indicate that a l variables exert a positive influence on the selection of foreign tourist destinations. By integrating technological, socio-political, legal and economic dimensions, this study offers valuable insights for tourism and hospitality service providers aiming to optimize their strategies and better cater to evolving tourist behaviors. The research contributes to the growing body of knowledge on how advanced technologies and contextual factors shape contemporary travel decisions, ultimately supporting more informed marketing and management practices in the global tourism industry.