Vesna Čančer

The rapid digitalization of higher education has transformed how students learn, collaborate, and engage with emerging technologies such as artificial intelligence (AI). While earlier research emphasized generational or academic-level differences in digital behavior, recent evidence suggests convergence in technology use. This study explores whether undergraduate and postgraduate students at the Faculty of Economics and Business, University of Maribor, display distinct technology engagement patterns across five constructs: excessive technology use, online collaboration, the use of digital learning tools (E-boards), the use of AI in education, and perceived academic success. A survey among 285 students was analyzed using the non-parametric Mann–Whitney U test due to a non-normal data distribution. The findings showed that postgraduate students did not report higher levels of E-Board use, online collaboration, or perceived academic success. Undergraduate students scored higher on one item related to excessive technology use, but not across the full construct. However, significant differences emerged in AI use, where postgraduate students showed greater confidence and willingness to integrate AI tools. The findings suggest that digital competence and the quality of technology integration, rather than study level, shape students’ learning experiences. Higher education institutions should promote balanced and ethical technology use, strengthen AI literacy, and foster self-regulated learning skills.

To provide a more holistic understanding of how digital tools shape the educational environment, this paper includes a comprehensive analysis that explores several dimensions of technology use in higher education: use of artificial intelligence in education, online collaboration, use of an E-Board for learning, and excessive use of technology. With the aim of measuring students’ use of digital technology to support their studies, this research meets the goals of developing the measurement process, building a multi-criteria model, and applying it to a real-life example of determining the degree of students’ use of digital technology in relation to the demonstrated quality of academic performance. The analysis is based on a survey conducted among students at the University of Maribor’s Faculty of Economics and Business. Using factor analysis and multi-criteria evaluation, the findings reveal that students who demonstrate very-high-quality achievements also report the highest level of technology use to support their studies. They are followed by students with outstanding achievements, who excel in using an E-Board for learning and in demonstrating responsibility regarding excessive technology use. Students who achieve acceptable-quality results with certain defects stand out in online collaboration and the use of AI in the study process. The lowest level of technology use was reported by students demonstrating moderate-quality achievements. Theoretically, this research contributes to a better understanding of the multidimensional use of digital technology in higher education, while, practically, it provides useful guidelines for optimizing digital learning tools and enhancing the overall quality of the academic process.

Background: When pairwise comparisons are used to express preferences for alternatives or judgments on criteria's importance, several methods can be used to derive priorities in multi-criteria decision-making. In the case of inconsistency, different methods give different results. Objectives: The main goal of this paper is to present the procedure of measuring the accuracy of the selected approximation methods based on pairwise comparisons compared to the priorities obtained by the eigenvalue method. It also aims to illustrate the procedure on the numerical example characterised by acceptable inconsistency. Methods/Approach: The presented procedure is based on a prescriptive approach, the fixed ratio scale, reciprocal pairwise comparison matrices, and consistency ratio. Mean absolute deviation and mean absolute percentage deviation are used to measure accuracy. Results: The first result is the theoretical statement of the priorities’ accuracy measurement procedure. The results of the numerical example characterised by the preferences of strength slight to strong plus show that, on average, the most accurate approximation method is the geometric mean method. Conclusions: The research contributes to the literature on prescriptive approaches to decision-making. The results can show potential users which approximation method to use and lecturers which of them to include in the curriculum portfolio.

Background: This article delves into an in-depth analysis of the statistically significant differences in AI support levels for project management between SMEs and large enterprises. The research was conducted based on a comprehensive survey encompassing a sample of 473 SMEs and large Slovenian enterprises. Methods: To validate the observed differences, statistical analysis, specifically the Mann–Whitney U test, was employed. Results: The results confirm the presence of statistically significant differences between SMEs and large enterprises across multiple dimensions of AI support in project management. Large enterprises exhibit on average a higher level of AI adoption across all five AI utilization dimensions. Specifically, large enterprises scored significantly higher (p < 0.05) in AI adopting strategies and in adopting AI technologies for project tasks and team creation. This study’s findings also underscored the significant differences (p < 0.05) between SMEs and large enterprises in their adoption and utilization of AI technologies for project management purposes. While large enterprises scored above 4 for several dimensions, with the highest average score assessed (mean value 4.46 on 1 to 5 scale) for the usage of predictive Analytics Tools to improve the work on the project, SMEs’ average levels, on the other hand, were all below 4. SMEs in particular may lag in incorporating AI into various project activities due to several factors such as resource constraints, limited access to AI expertise, or risk aversion. Conclusions: The results underscore the need for targeted strategies to enhance AI adoption in SMEs and leverage its benefits for successful project implementation and strengthen the company’s competitiveness.

This paper aims to measure the level of artificial intelligence (AI) support to project management (PM) in selected service sector activities. The exploratory factor analysis based on the extensive survey on AI in Slovenian companies along with the multi-criteria measurement with an emphasis on value functions and pairwise comparisons in the analytic hierarchy process, was employed. The synthesis and performance sensitivity analysis results show that in the service sector concerning all criteria, PM is with the level 0.276 best supported with AI in services of professional, scientific, and technical activities, which also stand out concerning the first-level goals, in using AI solutions in a project with the value 0.284, and in successful project implementation using AI with the value 0.301. Although the lowest level of AI support to PM, which is 0.220, is in services of wholesale and retail trade, and repair of motor vehicles and motorcycles, these services excel in adopting AI technologies in a project with a value of 0.277. Services of financial and insurance activities, with the level 0.257 second-ranked concerning all criteria have the highest value of 0.269 concerning the first-level goal of improving the work of project leaders using AI. The paper therefore contributes to the comparisons of AI support to PM in service sector activities. The results obtained can help AI development policy makers, which activities need to be supported and which ones should be set as an example. The presented methodological frame can serve to perform measurements and benchmarking in various research fields.

Research Question (RQ): Are there statistically significant differences in work motivation, satisfaction and engagement among older employees before the COVID-19 pandemic and during the COVID-19 pandemic? Purpose: The aim of the paper is to examine if there are statistically significant differences in work motivation, satisfaction and engagement among older employees before the COVID-19 pandemic and during the COVID-19 pandemic. The aim of the paper is also to identify which factors contribute to increasing work motivation, satisfaction and engagement during the COVID-19 pandemic. Method: The differences in work motivation, satisfaction and engagement among older employees before the COVID-19 pandemic and during the COVID-19 pandemic were tested with the nonparametric test for two related samples. To analyze the differences between individual statements, we used the non-parametric Wilcoxon signed-rank test. Results: The results show that there are statistically significant differences in work motivation, satisfaction and engagement among older employees before the COVID-19 pandemic as compared to the during COVID-19 pandemic. Organisation: The results have a significant impact on a more detailed review of the creation of new working conditions for employees during the Covid-19 pandemic and especially in the period after the Covid-19 pandemic. Society: During the COVID-19 pandemic, companies and society can focus on how to constructively manage the new challenges that the COVID-19 pandemic brings to companies and what they can learn from it. For companies and leaders or HRM in particular, the pandemic can be used as a starting point for positive and future-oriented developments. Originality: With our findings we contribute to the discussion on a constructive and future oriented approach to the COVID-19 pandemic, both for practices around the management of employees as well as for future research. Also, our research highlights which factors increase work motivation, work satisfaction and work engagement during COVID-19 and how to create appropriate working conditions during the COVID-19 and after the COVID-19 pandemic to keep employees motivated, satisfied and engaged. Limitations/further research: Our sample was limited to Slovenian companies and older employees. Also, in our research we limited on work motivation, work satisfaction and work engagement. Therefore, for further research we propose the examination of differences in others constructs before the COVID-19 pandemic and employees during the COVID-19 pandemic in Slovenian companies and also, the examination of differences in constructs between Slovenia and other countries. Raziskovalno vprašanje (RV): Ali obstajajo statistično značilne razlike v delovni motivaciji, zadovoljstvu in zavzetosti med starejšimi zaposlenimi pred COVID-19 pandemijo in med COVID-19 pandemijo? Namen: Namen prispevka je preveriti, ali obstajajo statistično značilne razlike v delovni motivaciji, zadovoljstvu in zavzetosti med starejšimi zaposlenimi pred COVID-19 pandemijo in med COVID-19 pandemijo. Cilj prispevka je tudi ugotoviti, kateri dejavniki prispevajo k povečanju delovne motivacije, zadovoljstva in zavzetosti v času pandemije COVID-19. Metoda: Razlike v delovni motivaciji, zadovoljstvu in zavzetosti med starejšimi zaposlenimi pred COVID-19 pandemijo in med COVID-19 pandemijo smo testirali z neparametričnim testom za dva odvisna vzorca. Za analizo razlik med posameznimi trditvami smo uporabili neparametrični Wilcoxonov signed-rank test. Rezultati: Rezultati kažejo, da obstajajo statistično značilne razlike v delovni motivaciji, zadovoljstvu in zavzetosti med starejšimi zaposlenimi pred COVID-19 pandemijo v primerjavi s časom med COVID-19 pandemijo. Organizacija: Rezultati pomembno vplivajo na podrobnejši pregled ustvarjanja novih delovnih pogojev za zaposlene v času pandemije COVID-19 in še posebej v obdobju po pandemiji COVID-19. Družba: Med COVID-19 se lahko podjetja in družba osredotočijo na to, kako konstruktivno obvladati nove izzive, ki jih podjetjem prinaša COVID-19 pandemija. Za podjetja in vodje oziroma zlasti za managerje se lahko pandemija uporabi kot izhodišče za pozitiven in v prihodnost usmerjen razvoj. Originalnost: Z našimi ugotovitvami prispevamo k razpravi o konstruktivnem in v prihodnost usmerjenem pristopu k pandemiji COVID-19, tako za prakse v zvezi z upravljanjem zaposlenih kot tudi za prihodnje raziskave. Naša raziskava prav tako poudarja, kateri dejavniki povečujejo delovno motivacijo, zadovoljstvo pri delu in delovno zavzetost med COVID-19 in kako ustvariti ustrezne delovne pogoje med COVID-19 in po pandemiji COVID-19, da ostanejo zaposleni motivirani, zadovoljni in zavzeti. Omejitve/nadaljnje raziskovanje: Omejili smo se na slovenska podjetja in starejše zaposlene. Prav tako smo se v naši raziskavi omejili na delovno motivacijo, zadovoljstvo in zavzetost. Zato za nadaljnje raziskave predlagamo preučitev razlik v drugih konstruktih pred pandemijo COVID-19 in zaposlenih v času pandemije COVID-19 v slovenskih podjetjih oz. tudi preučitev razlik v konstruktih med Slovenijo in drugimi državami.

Purpose: The main aim of the paper is to establish the effects of appropriately organized work as well as the effects of the employees' concerns related to work during the COVID-19 pandemic on work efficiency and work satisfaction among employees working from home during this period. The empirical research includes 619 employees in Slovenia, who participated in the survey during the COVID-19 pandemic.Design/methodology/approach: Structural equation modeling was used in exploring the effects between constructs.Findings: Based on the results, the authors found that appropriately organized work during the COVID-19 pandemic has a positive effect not only on the work efficiency of employees who work from home during the COVID-19 pandemic in Slovenia but also on their work satisfaction. Also, based on the results, the authors found that the employees' concerns related to work during the COVID-19 pandemic have a negative effect on the work efficiency and on the work satisfaction of employees who work from home during this period in Slovenia.Originality/value: The COVID-19 pandemic dramatically changed the way we live and work; therefore, this paper contributes to the creation of new working conditions and employee management during and also after the COVID-19 pandemic.

Background: The increase in population life expectancy in developed economies is also reflected in the aging of the workforce; therefore, enterprises should create an appropriate work environment for all employees, emphasizing the older ones. Objectives: The major objectives of this paper are to establish the impact of appropriate working conditions and training programs for older employees on their work motivation, as well as to establish the latter’s impact on the older employees’ work engagement in Slovenian medium-sized and large enterprises. Methods/Approach: Structural equation modeling explored the links between four constructs – appropriate working conditions, training programs, work motivation, and work engagement. Results: In Slovenian enterprises, appropriate working conditions and training programs for older employees positively impact their work motivation. Moreover, the work motivation of older employees positively impacts their work engagement. Conclusions: These findings can be useful for employers or managers for developing targeted employee motivation and employee engagement programs to leverage the talents and dedication of older employees.

Future economic growth and competitiveness will increasingly depend on how effectively employers can utilise their ageing workforces. To manage the inevitable changes in demographics, employers need to start preparing for an ageing workforce and developing strategies to manage and retain older employees. The main objective of this paper is to determine the impact of leadership and employee relations on work satisfaction of older employees, as well as to determine the impact of work satisfaction on the work engagement of older employees in financial service companies in Slovenia. To test the hypotheses, the authors used structural equation modelling. The results show that the effects of leadership and employee relations on work satisfaction in the case of older employees in financial service companies in Slovenia are positive, and the effect of work satisfaction on the work engagement of older employees is positive, too.