Iskanje po katalogu digitalne knjižnice

Opis: Background/Purpose: ChatGPT’s rapid diffusion has transformed large-language-model (LLM) technology from a specialist tool into a mainstream companion for study and work. However, empirical evidence on what drives user satisfaction outside medical settings remains scarce. Focusing on future business and management professionals in Croatia, this study examines how perceived ease of use and perceived reliability shape satisfaction with ChatGPT and whether those effects differ between Generation Z (18–25 years) and Generation Y (26–35 years). Methodology: An online survey administered in August 2024 yielded 357 valid responses. The measurement model met rigorous reliability and validity criteria (CFI = 0.96, SRMR = 0.04). Results: Structural-equation modelling showed that, in the pooled sample, ease of use (β = 0.42) and reliability (β = 0.46) jointly explained 72 % of satisfaction. Multi-group analysis revealed a generational split: both predictors were significant for Gen Z. However, only reliability remained significant for Gen Y. Gaussian graphical models corroborated these findings, indicating a densely interconnected attitude network for younger users and a reliability-centred network for older users. Conclusion: The study extends technology-acceptance research to the management domain, underscores the moderating role of generation and illustrates the value of combining SEM with network analytics. Insights inform designers and educators aiming to foster informed, responsible and gratifying engagement with generative AI.
Ključne besede: artificial intelligence, large language models (LLM), marketing, user satisfaction, Croatia, ChatGPT
Objavljeno v DKUM: 04.09.2025; Ogledov: 0; Prenosov: 1
Celotno besedilo (1,06 MB)
Gradivo ima več datotek! Več...

Opis: Background and Purpose: To encourage petroleum industry development, a country needs to set up a regulatory framework that standardizes investment conditions. The objective of the research was to investigate the determinants of government effectiveness in the petroleum sector. Design/Methodology/Approach: Multiple regression analysis was conducted to investigate if government effectiveness in the petroleum sector is influenced by the country’s political stability, regulatory quality, the intensity of petroleum exploration and production activities, government take, and type of contract used. Artificial neural network analysis was additionally conducted to identify the importance of independent variables. Results: Political stability, regulatory quality, government take attractiveness, and the intensity of petroleum activities positively influence government effectiveness. A more attractive government take enhances effectiveness, while the type of contract for awarding petroleum rights did not significantly impact effectiveness. Artificial neural network analysis revealed that the most important variables were regulatory quality and political stability. Conclusion: The research concluded that political stability, regulatory quality, and the intensity of petroleum activities are key factors in enhancing government effectiveness in the petroleum sector. These findings have practical implications, as they emphasize the importance of stable and well-regulated environments for achieving higher government effectiveness in the petroleum industry. This equips policymakers and industry professionals with actionable insights for improving the sector’s performance.
Ključne besede: energy policy, petroleum sector, government effectiveness, industry development
Objavljeno v DKUM: 13.08.2025; Ogledov: 0; Prenosov: 3
Celotno besedilo (1,58 MB)
Gradivo ima več datotek! Več...

Opis: The goal of this research was to investigate the level of digital divide among selected European countries according to the big data usage among their enterprises. For that purpose, we apply the K-means clustering methodology on the Eurostat data about the big data usage in European enterprises. The results indicate that there is a significant difference between selected European countries according to the overall usage of big data in their enterprises. Moreover, the enterprises that use internal experts also used diverse big data sources. Since the usage of diverse big data sources allows enterprises to gather more relevant information about their customers and competitors, this indicates that enterprises with stronger internal big data expertise also have a better chance of building strong competitiveness based on big data utilization. Finally, the substantial differences among the industries were found according to the level of big data usage.
Ključne besede: big data, cluster analysis, digital divide, k-means, enterprise, industry, Europe, quality
Objavljeno v DKUM: 14.01.2025; Ogledov: 0; Prenosov: 7
Celotno besedilo (3,39 MB)
Gradivo ima več datotek! Več...

Opis: Business simulation games have become popular in higher education and business environments. The paper aims to identify the primary research trends and topics of business simulation games research using a systematic and automated literature review with the motivation of research (learning driven and domain driven). Based on these findings, the future development of business simulation games research projected papers that research business simulation games were extracted from Scopus. Second, the research timeline, main publication venues and citation trends have been analysed. Third, the most frequent words, phrases, and topics were extracted using text mining. Results indicate that the research on business simulation games has stagnated, with the most cited papers published in the 2000s. There is a balance between learning-driven and domain driven-research, while technology-driven research is scarce, indicating that the technology used for business simulation games is mature. We project that the research on business simulation games needs to be directed in the area of new technologies that could improve communication with and among the users (virtual reality, augmented reality, simulation games) and technologies that could improve the reasoning and decision-making complexity in business simulation games (artificial intelligence).
Ključne besede: simulation games, digital education, knowledge management, business games
Objavljeno v DKUM: 02.08.2023; Ogledov: 605; Prenosov: 69
Celotno besedilo (4,43 MB)
Gradivo ima več datotek! Več...

Opis: As a leader’s behavior can have a strong impact on different employee work- related outcomes, various approaches have been put forth in an effort to determine the most effective form of leadership and determinants of individuals’ choice of leadership style. This paper analyzed whether one’s choice of leadership style is due more to personal or organizational characteristics. We used survey data to investigate the determinants of leadership style among Montenegrin managers. Our analysis showed that, although demographic characteristics such as gender, age, and education do not influence the choice of leadership style, internal organizational characteristics such as hierarchical level, managerial orientation to tasks/people, and decision-making characteristics such as decision- making style and decision-making environment are positively associated with the choice of democratic leadership style. This contributes to recent research in leadership that shows how some personal characteristics are considered to be less important in developing certain styles and that the choice of style is more dependent and contingent on external influences and situations.
Ključne besede: decision-making characteristics, demographic characteristics, internal organizational characteristics, leadership style, Montenegro
Objavljeno v DKUM: 03.05.2018; Ogledov: 1233; Prenosov: 69
Celotno besedilo (1,66 MB)
Gradivo ima več datotek! Več...