1. Multicriteria risk evaluation model : utilizing fuzzy logic for improved transparency and quality of risk evaluation in healthcareRok Drnovšek, Marija Milavec Kapun, Simona Šteblaj, Uroš Rajkovič, 2025, izvirni znanstveni članek Opis: Introduction: Risk management is essential for quality assurance in modern healthcare organizations. Risk matrices are widely used
to evaluate risks in healthcare settings; however, this approach has noteworthy weaknesses and limitations. This paper introduces
a novel risk evaluation model that utilizes multicriteria decision-making and fuzzy logic, to enhance the transparency and quality of the
risk evaluation process in healthcare.
Methods: The Multicriteria Evaluation Model was developed using the Decision Expert method and expert knowledge integration.
Fuzzy logic was integrated within the model, using partial degrees of membership and probabilistic analysis, to address uncertainties
inherent to healthcare risk evaluation. The evaluation model was tested with healthcare professionals active in the field of risk
management in clinical practice and compared with the risk matrix.
Results: The designed evaluation model utilizes multicriteria decision-making while encompassing the risk matrix framework to
boost user understanding and enable meaningful comparison of results. Compared with the risk matrix, the model provided similar or
marginally higher risk-level evaluations. The use of degrees of membership enables evaluators to articulate a wide range of plausible
risk consequences, which are often overlooked or ambiguously addressed in the traditional risk matrix approach.
Discussion and Conclusions: The evaluation model demonstrates increased transparency of the decision-making process and
facilitates in-depth analysis of the evaluation results. The utilization of degrees of membership revealed distinct strategies for handling
uncertainty among participants, highlighting the weaknesses of using single value evaluation approach for the presented and similar
decision problems. The presented approach is not limited to healthcare-related risk evaluation, but has the capacity to improve risk
evaluation practices in diverse settings
Ključne besede: multi-criteria decision-making, risk management, fuzzy logic, decision support, patient care, DEX
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2. Navigating success : how decision–making transforms software performance into business performance in the logistics industry from an emerging countryBukra Doganer Duman, Gültekin Altuntaş, 2025, izvirni znanstveni članek Opis: Background/Purpose: This study investigates the mediating role of decision–making performance in the link between software performance and overall business performance in the logistics sector of an emerging economy. As logistics companies increasingly rely on digital infrastructures, understanding how advanced systems contribute to strategic outcomes is critical for sustaining competitiveness. Methods: A conceptual framework was developed integrating ERP systems, big data analytics, and IoT applications. In this model, software performance is positioned as the independent variable, decision–making performance as the mediator, and business performance as the dependent variable. Data were collected from medium- and large–scale logistics firms and analyzed using regression and bootstrapping methods through SPSS and the PROCESS Macro. Results: The findings reveal that software performance significantly improves decision–making performance (β = 0.552, p < 0.01), which in turn has a strong positive effect on business performance (β = 0.817, p < 0.01). The mediation analysis confirms that decision–making performance mediates the effect of software performance on business outcomes. Conclusion: The results highlight the strategic importance of aligning digital capabilities with organizational decision processes. By demonstrating the mediating role of decision–making, the study highlights that the effective use of advanced analytical tools is crucial for optimizing performance and achieving a sustainable competitive advantage in logistics.
Ključne besede: software performance, decision–making performance, business performance, TMS systems, logistics industry, emerging economy
Objavljeno v DKUM: 14.11.2025; Ogledov: 0; Prenosov: 8
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3. Understanding the impact of burnout on decision-making stylesMatea Cvjetković, Dinko Primorac, Katerina Fotova Čiković, 2025, izvirni znanstveni članek Opis: Background and purpose: This study aimed to fill a gap in the literature by identifying how employee burnout shapes decision-making styles in the post-COVID-19 business environment. The main goal was to examine the impact of three dimensions of burnout—exhaustion, cynicism, and professional efficacy—on four conflict-related decision-making styles: vigilance, buck-passing, procrastination, and hypervigilance.
Design/Methodology/Approach: A total of 567 employees from various companies in Croatia participated in the online survey conducted in March 2023. Multiple regression analysis examined the impact of exhaustion, cynicism, and professional efficacy on decision-making styles under conflict.
Results: The results of the multiple regression analysis revealed that professional efficacy leads to a vigilant decision-making style, while simultaneously diminishing procrastination, buck-passing, and hypervigilance. Cynicism, in contrast, was a positive predictor of procrastination, buck-passing, and hypervigilant decision-making. Finally, exhaustion was found to have a positive impact on hypervigilance.
Conclusion: The study is significant because it contributes to the body of knowledge on the impact of burnout dimensions on professional decision-making styles in organisational settings, and it also offers practical implications of considerable importance.
Ključne besede: employee burnout, decision-making style, work-related stress, Croatian companies, post-COVID-19 period
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4. The influence of emotional labor and emotional intelligence on cesarean section decision-making among midwives and obstetricians in Kosovo : a cross-sectional study using conjoint analysisBesarta Taganoviq, Pam Smith, Mateja Lorber, Ilir Hoxha, 2025, izvirni znanstveni članek Opis: Introduction: Cesarean section rates continue to increase worldwide. In 2021, one in every five deliveries was delivered by cesarean section. This is particularly alarming in resource-limited countries such as Kosovo, where the rates continue to increase and vary considerably between hospitals. Understanding the underlying factors that drive the increase and variation of cesarean section rates may help to change these trends. This study investigates how emotional intelligence and emotional labor impact cesarean section decision-making among midwives and obstetricians in Kosovo, along with clinical factors. Methods: We employed a conjoint analysis using a cross-sectional study design to assess preferences that drive decisions for cesarean section. We used the Dutch questionnaire on Emotional Labor, the Assessing Emotions Scale, and the Quality of Decision-making questionnaire, and designed a conjoint questionnaire with 28 hypothetical scenarios. We invited all midwives and obstetricians employed at the Gynecology and Obstetrics Clinic of the University Clinical Centre of Kosovo to participate in the study. The data were collected from January to the end of March 2023. Stata 18 BE was used for statistical computing and data visualization. Results: A gestational age of 42 weeks decreased CS likelihood among midwives (OR=0.75; 95% CI: 0.62–0.90, p=0.002). Previous cesarean sections (OR=1.42; 95% CI: 1.11–1.81, p=0.005) and hypertension (OR=1.23; 95% CI: 1.01–1.51, p=0.042) raised CS odds for midwives. A pelvic size of 8 cm significantly increased CS likelihood for midwives (OR=1.70; 95% CI: 1.37–2.09, p<0.001), while a size of 11 cm was protective for both groups (midwives: OR=0.73; 95% CI: 0.57–0.93, p=0.010; obstetricians: OR=0.70; 95% CI: 0.52–0.94, p=0.019). Maternal age of 40 years was significant only for obstetricians (OR=1.43; 95% CI: 1.00–2.06, p=0.052), and university education was significant for midwives (OR=1.19; 95% CI: 1.03–1.37, p=0.020). Non-clinical factors and emotional measures showed no significant or consistent trends in either group. Conclusions: Various clinical and non-clinical factors shape the decision to recommend a cesarean section, with obstetricians and midwives prioritizing these factors differently. These findings underscore the importance of implementing evidence-based practices to enhance maternal and newborn health outcomes in Kosovo and similar settings, while optimizing cesarean decision-making.
Ključne besede: cesarean section, emotional labor, emotional intelligence, midwives, obstetricians, decision-making
Objavljeno v DKUM: 13.11.2025; Ogledov: 0; Prenosov: 2
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5. Using data mining to improve decision-making : case study of a recommendation system developmentHyrmet Mydyti, Arbana Kadriu, Mirjana Pejić Bach, 2023, izvirni znanstveni članek Opis: Background and purpose: This study aims to provide a practical perspective on how data mining techniques are used in the home appliance after-sales services. Study investigates on how can a recommendation system help a customer service company that plans to use data mining to improve decision making during its digital transformation process. In addition, study provides a detailed outline on the process for developing and analyzing platforms to improve data analytics for such companies. Methodology: Case study approach is used for evaluating the usability of recommendation systems based on data mining approach in the context of home appliance after-sales services. We selected the latest platforms based on their relevance to the recommender system and their applicability to the functionality of the data mining system as trends in the system design. Results: Evaluation of the impact on decision making shows how the application of data mining techniques in organizations can increase efficiency. Evaluation of the time taken to resolve the complaint, as a key attribute of service quality that affects customer satisfaction, and the positive results achieved by the recommendation system are presented. Conclusion: This paper increases the understanding of the benefits of the data mining approach in the context of recommender systems. The benefits of data mining, an important component of advanced analytics, lead to an increase in business productivity through predictive analytics. For future research, other attributes or factors useful for the recommender systems can be considered to improve the quality of the results. Acknowledgement: The author Hyrmet Mydyti’s PhD thesis has been extended in this paper.
Ključne besede: digital transformation, data mining, decision tree algorithm, decision-making, home appliances after-sales services
Objavljeno v DKUM: 08.10.2025; Ogledov: 0; Prenosov: 2
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6. Health care decisions in social care settings : general regulation and interpretation in CPT’s jurisprudenceLaura Kadile, 2023, izvirni znanstveni članek Opis: The Committee for the Prevention of Torture and Inhuman Treatment is a body of the Council of Europe that organises visits to places of detention such as social care homes in order to assess how persons deprived of their liberty are treated. This means that in practice people are not free to leave the institution and are therefore de facto deprived of liberty. In such situations, people with disabilities are particularly vulnerable and have limited capacity to make decisions about medical treatment and care. As the number of such persons increases, and in order to ensure protection under international law, the results of the empirical study indicate the need to provide immediate assistance to residents in safeguarding their rights to self-determination or private autonomy and legal interests in making health care decisions in social care settings. For example, involving the resident in consenting to treatment or establishing a decision-making assessment procedure.
Ključne besede: decision making capacity, legal capacity, CPT, informed consent, people with disabilities
Objavljeno v DKUM: 28.08.2025; Ogledov: 0; Prenosov: 3
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7. Seasonal influenza vaccination uptake among health and medical college students : a discrete choice experimentMonika Lamot, Andrej Kirbiš, 2025, izvirni znanstveni članek Opis: Seasonal influenza is a highly contagious virus posing significant health risks, especially tochildren, pregnant women, and older adults. Despite its crucial role in prevention andreducing severity, vaccination rates among medical and health students, who frequentlyinteract with vulnerable groups, remain low. This study investigates attributes of influenzavaccines that predict vaccination decisions within this population, while also examininghow these preferences vary based on the health literacy levels of the respondents.Between May and June 2024, 239 Slovenian medical and health students completed anonline discrete choice experiment presenting vaccines varying in efficacy, side effects, andadministration site. Preferences were analyzed to identify key attributes. Results showedthat higher efficacy and fewer side effects drove vaccine choice across all disciplines.Medical students favored faculty-based vaccination, whereas nursing and other healthdiscipline students preferred GP offices and NIPH units. Health literacy did not alter theimportance of efficacy and safety, but those with sufficient literacy showed a strongerpreference for GP settings over faculty sites. Campaigns should emphasize vaccine efficacyand the low risk of severe side effects, reassuring that mild reactions are transient.Facilitating GP-based vaccination for nursing and other health discipline students mayfurther improve uptake.
Ključne besede: seasonal influenza, vaccination, decision-making, health behavior, students, discrete choice experiment
Objavljeno v DKUM: 25.08.2025; Ogledov: 0; Prenosov: 7
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8. Leveraging ChatGPT for enhanced logical analysis in the theory of constraints thinking processTomaž Aljaž, 2024, izvirni znanstveni članek Opis: Background/Purpose: Artificial intelligence (AI) has traditionally been used for quantitative analysis using explicit data. However, much of the information critical to decision making remains undocumented and is not stored in a structured way. This study explores the integration of AI, specifically ChatGPT, into Theory of Constraints (TOC) Thinking Process (TP) tools. Method: In this study, we applied ChatGPT to a real-world IT project management case using a variety of research methods, including international literature analysis, observation, and personal experience. The use of the TOC TP allowed us to understand the decision-making process of ChatGPT and to systematically explore its advantages and limitations in creating logical trees of TOC TP. Results: ChatGPT significantly enhanced efficiency and depth in TOC TP data collection and analysis, effectively addressing logical leaps for more coherent structures. It also promoted deeper analytical thinking and aided root cause identification. The integration of ChatGPT into the TOC TP process led to faster decision-making, reduced bias, and clearer analysis. Challenges of ChatGPT including the need for human oversight, specific TOC TP training, and ethical considerations were noted. Conclusion: This study provides an initial investigation into the use of ChatGPT in TOC TP tools. The results suggest that ChatGPT has the potential to be a valuable tool for organizations seeking to improve their decision making and performance. However, further research is needed to validate these findings and explore the full potential of AI in TOC TP.
Ključne besede: ChatGPT, artificial intelligence, Theory of Constraints, theory of constraints thinking process, logical analysis, decision making, structured analysis framework
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9. Sustainable transportation perspective: how our preferences for zero-emission vehicles change through time?Matevž Obrecht, Gözde Yanginlar, Dorota Klimecka-Tatar, Matjaž Knez, 2024, izvirni znanstveni članek Opis: The Slovenian automobile market has gained great momentum in the past decade. However, the demand contractions in the supply chain created a huge crisis in the automobile industry in Slovenia. The automotive industry's new competitive dynamics focus on green logistics, sustainability, and purchase decisions. The study aims to comparatively analyze the factors affecting consumers' automobile purchasing decisions from a sustainable transportation perspective. In the survey, we included 1502 participants to identify the most important parameters of consumer behaviour related to purchasing alternative fuel vehicles. In the regression analysis results in the first analysis, non-financial factors sub-dimensions such as the body shape and fuel type, vehicle size, and style/appearance/colour had a positive effect on purchasing decisions of zero-emission cars. The second analysis was performed 5 years after the first analysis. Moreover, the findings provide insights that non-financial factors sub-dimensions such as entertainment system, vehicle size, and vehicle capacity and financial factors sub-dimensions between the insurance group for the vehicle, finance deals, value for money, annual road tax had a positive effect on purchasing decisions of zero-emission vehicles in the second analysis. Results show that the most relevant factor for purchasing zero-emission vehicles is total vehicle price and that the segment of potential alternative fuel vehicle consumers is much higher than it has been anticipated. This study provides an overview of the current understanding of individuals' vehicle purchasing decisions.
Ključne besede: zero-emission vehicles, sustainable transportation, purchasing decision
Objavljeno v DKUM: 18.07.2025; Ogledov: 0; Prenosov: 2
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10. Geographical information system modeling for planning internal transportation in a manufacturing plant’s outdoor areaKlemen Prah, Brigita Gajšek, 2024, izvirni znanstveni članek Opis: A geographical information system (GIS) is an advanced tool for collecting, managing, and analyzing spatially-referenced data. The contribution of GIS use to process performance indicators can be improved by combining it with multi-criteria decision analysis (MCDA). Combining a GIS and MCDA is, in the scientific literature, rarely discussed for planning an internal transportation system in a manufacturing plant’s outdoor area. The purpose of this article is to clarify what mangers can expect from using a combined approach when deciding on a transport fleet and the operational routing of vehicles. Beside the simulation of MCDA, the computer software ArcGIS Pro 3.0.2 with the Network Analyst extension was used for modelling the transportation system in the form of a case study. The article demonstrates the feasibility and effectiveness of GIS and MCDA use and reveals the extent of the challenge of how decision makers could make the most of ArcGIS functionality. The final solution for an internal transportation system in a manufacturing plant’s outdoor area includes such a vehicle fleet and the set time windows of orders for transport services, so that there are no violations of time windows and the work is completed within the work shift while minimizing costs, time, and distance. Decision makers can use the program without advanced knowledge of optimization approaches, following a procedure that does not differ much from that of learning to use other business software tools. On the contrary, the listed disadvantages can be summarized as the rigidity of setting detailed boundary conditions for a specific simulation scenario.
Ključne besede: geographical information system, internal outdoor area transport, decision support system, vehicle fleet, planning
Objavljeno v DKUM: 18.07.2025; Ogledov: 0; Prenosov: 4
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