1. Comparative analysis of nonlinear models developed using machine learning algorithmsMaja Rožman, Alen Kišić, Dijana Oreški, 2024, original scientific article Abstract: Machine learning algorithms are increasingly used in a vast spectrum of domains where statistical approaches were previously used. Algorithms such as artificial neural networks, classification, regression trees, or support vector machines provide various advantages over traditional linear regression or discriminant analysis. Advantages such as flexibility, scalability, and improved accuracy in dealing with diverse data types, nonlinear problems, and dimensionality reduction, compared to traditional statistical methods are empirically demonstrated in many previous research papers. In this paper, two machine learning algorithms are compared with one statistical method on highly nonlinear data. Results indicate a high level of effectiveness for machine learning algorithms when dealing with nonlinearity.
Keywords: machine learning, decision tree algorithm, artificial neural network, predictive models, data characteristics, nonlinear data, artificial intelligence
Published in DKUM: 02.07.2025; Views: 0; Downloads: 1
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2. Exploring differences in green innovation among countries with individualistic and collectivist cultural orientationsAlona Sova, Maja Rožman, Romana Korez-Vide, 2024, original scientific article Abstract: In this paper, we explore the extent to which individualistic and collectivist national cultural orientations are essential for green innovation. In this context, we also examine the extent of green innovation in countries at different levels of socioeconomic development. All data were collected for the latest available year (2020). This research was carried out on a sample of 60 selected countries, using parametric tests to identify statistically significant differences between variables and descriptive statistics to examine statistically significant differences in-depth. The results show that, on average, countries with prevailing individualistic cultural orientations and high levels of socioeconomic development perform better in green innovation than countries with prevailing collectivist cultural orientations. On average, countries with a prevailing individualistic cultural orientation scored moderate on green innovation, while countries with a prevailing collectivist orientation scored low. However, the level of socioeconomic development, including designing and implementing green policies, was recognized as essential to green innovation in both national cultures with prevailing individualistic orientations and national cultures with prevailing collectivist orientations.
Keywords: green innovation, national culture, individualism, collectivism, parametric statistics, descriptive statistics
Published in DKUM: 02.07.2025; Views: 0; Downloads: 1
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3. Evaluating progress in achieving the UN's sustainable development goals : ǂa ǂcomparative analysisKatja Crnogaj, Maja Rožman, 2024, original scientific article Abstract: This study aims to explore the percei-ved progress in fulfilling the United Nations Sustaina-ble Development Goals (SDGs) at the national level. Using the data from 2022 and 2023 for 43 countri-es, sourced from the contributions of 3,690 national experts, we assess the perceived progress in areas critical to sustainable development, including social contribution, social responsibility, investor interests, economic opportunities for minority groups, envi-ronmentally conscious practices, energy efficiency, national cultural values towards sustainability, SDG-aligned business activities and government support for sustainability-focused businesses. The assessment covers twelve key aspects to determine the extent to which new and growing companies and the broader business and policy environment are aligned with the SDGs. The main objective is to identify trends, achi-evements and areas for improvement in integrating the SDGs into business operations and policy fra-meworks. Research methods include a quantitative analysis of the GEM database (Global Entrepreneur-ship Monitor, the world's foremost study of entrepre-neurship), comparative statistical analysis and trend evaluation to provide a comprehensive overview of the progress made between 2022 and 2023. This re-search is crucial to understanding the effectiveness of current strategies and identifying the need for further action to achieve the SDGs.
Keywords: sustainable development goals, entrepreneurship, environmental sustainability, government support, global entrepreneurship monitor, comparative analysis
Published in DKUM: 02.07.2025; Views: 0; Downloads: 0
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4. Psychological factors impacting academic performance among business studies’ studentsMaja Rožman, Igor Vrečko, Polona Tominc, 2025, original scientific article Abstract: This study explores the significant psychological factors that impact academic success among students. The sample included 287 undergraduate and postgraduate students of business studies. Structural Equation Modeling was used to analyze the data, investigating the impact of students’ motivation, mental and physical health, work-life balance, and anxiety on both perceived academic success as well as quantitative indicators of academic success. The findings reveal that students’ motivation is significant for enhancing academic success. Additionally, while mental and physical health are significant contributors to academic success, balancing academic work with personal life is essential for fostering a positive perception of academic success. Conversely, anxiety, particularly exam-related, negatively affects students’ perceived academic success, highlighting the need for comprehensive support systems. These findings offer crucial insights for educators and policymakers, paving the way for innovative strategies that enhance academic success and empower students to thrive holistically, both academically and personally. By addressing the full spectrum of challenges students face, we can foster a more resilient, motivated, and successful generation of students.
Keywords: psychological factors, students, education, academic success
Published in DKUM: 02.07.2025; Views: 0; Downloads: 0
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5. Navigating gender nuances : assessing the impact of AI on employee engagement in Slovenian entrepreneurshipMaja Rožman, Polona Tominc, 2024, original scientific article Abstract: Background: Our research delved into exploring various selected facets of AI-driven
employee engagement, from the gender perspective, among Slovenian entrepreneurs. Methods:
This research is based on a random sample of 326 large enterprises and SMEs in Slovenia, with an
entrepreneur completing a questionnaire in each enterprise. Results: Findings suggest that there
are no significant differences between male and female entrepreneurs in Slovenia regarding various
aspects of AI-supported entrepreneurial management practice including the following: AI-supported
entrepreneurial culture, AI-enhanced leadership, adopting AI to reduce employee workload, and
incorporating AI tools into work processes. The widespread integration of AI into entrepreneurship
marks a transition to a business landscape that values inclusivity and equity, measuring success
through creativity, strategic technology deployment, and leadership qualities, rather than relying on
gender-based advantages or limitations. Our research also focused on the identification of gender
differences in path coefficients regarding the impact of the four previously mentioned aspects of
AI on employee engagement. While both genders see the value in using AI to alleviate employee
workload, the path coefficients indicate that female entrepreneurs report higher effectiveness in
this area, suggesting differences in the implementation of AI-integrated strategies or tool selection.
Male entrepreneurs, on the other hand, appear to integrate AI tools into their work processes more
extensively, particularly in areas requiring predictive analytics and project scheduling. This suggests
a more technical application of AI in their enterprises. Conclusions: These findings contribute
to understanding gender-specific approaches to AI in enterprises and their subsequent effects on
employee engagement.
Keywords: entrepreneurship, artificial intelligence, AI-supported entrepreneurial culture, AI-enhanced leadership, adopting AI to reduce employee workload, incorporating AI tools into work processes, employee engagement
Published in DKUM: 01.07.2025; Views: 0; Downloads: 1
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6. Agility and artificial intelligence adoption : small vs. large enterprisesMaja Rožman, Dijana Oreški, Katja Crnogaj, Polona Tominc, 2023, original scientific article Abstract: This article presents the findings of a survey conducted in Slovenia, encompassing
a random sample of 275 enterprises, to analyze the factors influencing
the transition to an agile approach, the AI-supported organizational
culture, AI-enabled workload reduction, and AI-enabled performance enhancement
in small and large enterprises. The study investigates whether
there are statistically significant differences between small and large
enterprises in Slovenia regarding these aspects. These findings provide
valuable insights into the distinct perspectives and priorities of small and
large enterprises in Slovenia regarding agility and the adoption of AI technologies.
The results highlight areas where small businesses may need
additional support or targeted strategies to fully leverage the benefits of
agility and AI. Policymakers and industry leaders can utilize these findings
to promote tailored approaches that enhance agility and facilitate effective
AI integration in both small and large enterprises, ultimately contributing
to the growth and competitiveness of the Slovenian business landscape.
Keywords: firm performance, IT management, agility, artificial intelligence, Slovenia
Published in DKUM: 28.05.2025; Views: 0; Downloads: 3
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7. Vpliv stresa na tiho odhajanje zaposlenih v organizaciji xRobert Šket, 2025, master's thesis Abstract: V magistrski nalogi preučujemo problematiko stresa na delovnem mestu in ugotavljamo njegovo povezavo s pojavom tihega odhajanja zaposlenih. Stres je eden največjih in najpomembnejših izzivov sodobnega delovnega okolja. Stres vpliva tako na posameznike, kot na organizacije. Izvori stresa so tako izven delovnega okolja, kakor v njem. Dejavniki v delovnem okolju, ki zaposlenim povzročajo stres vplivajo na motivacijo zaposlenih, poveča se tveganje za različne zdravstvene težave, izgorelost itd. V organizaciji se lahko pojavi tudi tiho odhajanje zaposlenih. Negativne posledice stresa se kažejo tudi na upadu produktivnosti in uspešnosti organizacije. Glavni cilj naše raziskave je bil ugotoviti, ali stres vpliva na tiho odhajanje zaposlenih v izbrani organizaciji.
V teoretičnem delu magistrske naloge predstavljamo koncept stresa, različne vrste stresa, simptome stresa in njegove posledice. Stres povzročajo različni dejavniki, ki jih glede na mesto izvora delimo na stresorje v delovnem okolju (neugodne delovne razmere, slabi odnosi s sodelavci in nadrejenimi, odgovornost za druge zaposlene, časovni pritiski in preobremenjenost idr.) in stresorje izven delovnega okolja. Poznamo številne simptome stresa, tako čustvene, kot fizične, vedenjske in psihološke. Stres povzroča številne negativne posledice za zaposlene in organizacijo, kot so zmanjšana produktivnost, slabše duševno in fizično zdravje zaposlenih, višja fluktuacija in zmanjšanje uspešnosti organizacije. Da bi preprečili te negativne posledice stresa je pomembno, da posamezniki in organizacije izvajajo ukrepe za premagovanje in obvladovanje stresa. Gre za ukrepe, povezane z zdravim življenjskim slogom zaposlenih (zdrava prehrana, telesna dejavnost, joga, meditacija, odsotnost kajenja in psihoaktivnih snovi idr.), kakor tudi za ukrepe, ki se neposredno nanašajo na oblikovanje delovnih mest (preoblikovanje dela, uvedba fleksibilnega delovnega časa, kroženje itd.). Nadalje smo predstavili koncept tihega odhajanja zaposlenih (ang. quiet quitting), ki postaja v organizacijah vse pogostejše. Gre za vedenje, ko zaposleni opravljajo le nujne delovne naloge, da obdržijo zaposlitev. Vzroki za tiho odhajanje so različni: prenizke plače, slabe možnosti za razvoj kariere in napredovanje, nepravično ocenjevanje, slabo delovno okolje idr.. Tiho odhajanje prinaša višjo fluktuacijo zaposlenih, zmanjšano pripadnost zaposlenih organizaciji, znižuje produktivnost in uspešnost organizacije.
V empiričnem delu smo preučevali zaznavanje stresa, izvore in posledice stresa, ukrepe za premagovanje stresa ter prisotnost tihega odhajanja med zaposlenimi v organizaciji X. Rezultati raziskave so pokazali, da zaposleni v izbrani organizaciji doživljajo stres zaradi dela, ki ga opravljajo. Ob tem kot najpogostejše stresorje navajajo preobremenjenost, časovne pritiske in težke delovne razmere. Zaposleni kot najpogostejše posledice, ki jih občutijo navajajo čustvenost, občutek utrujenosti, izčrpanosti in izgorelosti ter živčnost in napetost. Za premagovanje stresa zaposleni največkrat določijo prioriteto delovnih nalog, poiščejo pomoč sodelavca ter si vzamejo kratek odmor. Po drugi strani pa kot ukrepe, ki jih najpogosteje izvaja organizacija navajajo spodbujanje sodelovanja med zaposlenimi, spodbujanje zdravega načina življenja ter omogočanje sodelovanja pri izboljšavah delovnega okolja in organizacije dela. Prav tako smo ugotovili, da je tiho odhajanje zaposlenih v izbrani organizaciji prisotno in da stres vpliva na pojav tihega odhajanja zaposlenih. Za zmanjšanje obeh negativnih dejavnikov bi bilo smiselno izvesti razbremenitev zaposlenih s preoblikovanjem delovnih mest in zaposlitvijo dodatnega kadra.
Keywords: stres, stresorji, posledice stresa, tiho odhajanje, javne organizacije
Published in DKUM: 14.05.2025; Views: 0; Downloads: 36
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8. Statistically significant differences in AI support levels for project management between SMEs and large enterprisesPolona Tominc, Dijana Oreški, Vesna Čančer, Maja Rožman, 2024, original scientific article Abstract: 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.
Keywords: enterprises, project management, leadership, artificial intelligence
Published in DKUM: 04.04.2025; Views: 0; Downloads: 6
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9. Upravljanje talentov v digitalni dobiMarija Jovičić, 2025, master's thesis Abstract: Raziskava obravnava digitalizacijo v kontekstu upravljanja talentov in organizacijskega razvoja v digitalni dobi. V današnjem hitrem in dinamičnem poslovnem okolju digitalizacija oblikuje vse vidike poslovanja organizacij, vključno z menedžmentom človeških virov. V tem kontekstu postaja upravljanje talentov vse pomembnejši proces za dosego in ohranjanje konkurenčne prednosti organizacij. Digitalna orodja, kot so umetna inteligenca in sistemi za podporo odločanju, izboljšujejo preglednosti in omogočajo etično usmerjene odločitve, kar pripomore k večji natančnosti in preglednosti v organizacijskih procesih. Hkrati digitalizacija prinaša izzive, kot so povečana konkurenca pri pridobivanju talentov ter izzivi pri usklajevanju poklicnega in zasebnega življenja, kar zahteva uvedbo politik, kot je pravica do odklopa, da bi preprečili izgorelost zaposlenih. Poleg tega digitalna orodja pozitivno vplivajo na razvoj kompetenc, karierni napredek in izboljšanje zadrževanja talentov. Vendar digitalizacija prinaša tudi izzive, kot so manjša osebna interakcija in večja fluktuacija zaposlenih. Digitalizacija torej preoblikuje prakse upravljanja talentov, vendar zahteva premišljeno strategijo za obvladovanje negativnih vplivov, kot so izgorelost in težave pri usklajevanju osebnega in poklicnega življenja. Uspešna implementacija digitalnih orodij v organizacijah je mogoča le, če se upoštevajo izzivi ter oblikujejo ustrezne strategije, ki omogočajo polno izkoriščanje prednosti digitalne preobrazbe. Tako lahko organizacije v celoti izkoristijo potencial digitalnih orodij za razvoj in upravljanje talentov v dinamičnem poslovnem okolju.
Keywords: digitalizacija, upravljanje talentov, osebna blagovna znamka, nenehno učenje, etika v HR, ravnovesje med poklicnim in zasebnim življenjem.
Published in DKUM: 25.03.2025; Views: 0; Downloads: 75
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10. A comparative study using two SEM techniques on different samples sizes for determining factors of older employeeʹs motivation and satisfactionMaja Rožman, Polona Tominc, Borut Milfelner, 2020, original scientific article Abstract: The purpose of this article is to present the relationships among older employee stress, motivation, satisfaction, and relationships in the workplace using two different approaches and different sample sizes. Research was implemented on an initial sample of 1013 older employees. In the next step, six smaller samples were calculated using the random selection of cases, namely samples with 25, 50, 100, 250, 400, and 500 older employees. This way the possible impact of sample size on relationships between latent variables using the covariance-based structural equation modeling (CB-SEM) and the partial least squares structural equation modeling (PLS-SEM) methods was assessed. The results on the larger samples have proved to be quite robust since they were confirmed with both approaches. They indicate that stress has a strong and negative impact on employee relationships and also a negative impact on employee satisfaction. Furthermore, employee relationships have a strong and positive impact on satisfaction and a positive impact on employee motivation. In addition, satisfaction has a strong and positive impact on employee motivation. The present paper helps readers to better understand the difference between the CB-SEM and the PLS-SEM methods. Researchers should be encouraged to use both techniques, even though CB-SEM methods have had a long tradition in management and marketing research since both fields heavily rely on psychometric measurement. From the organizational point of view, conclusions highlight the importance of the impact the variables of older employee stress, motivation, satisfaction and employee relations have on each other in the workplace.
Keywords: stress, employee motivation, employee satisfaction, employee relations
Published in DKUM: 10.03.2025; Views: 0; Downloads: 9
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