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1.
Transformation of the RESPO decision support system to higher education for monitoring sustainability-related competencies
Andreja Abina, Bojan Cestnik, Rebeka Kovačič Lukman, Sara Zavernik, Matevž Ogrinc, Aleksander Zidanšek, 2023, izvirni znanstveni članek

Opis: A result-oriented engagement system for performance optimisation (RESPO) has been developed to systematically monitor and improve the competencies of individuals in business, lifelong learning and secondary schools. The RESPO expert system was transferred for use in higher education institutions (HEIs) based on successful practical application trials. The architecture and functionality of the original RESPO expert system have been transformed into a new format that will collect information on the required competencies and the available educational programmes to help students effectively develop competencies through formal and non-formal education. First, the initial version of the RESPO system and its functionality were tested on a selected group of students and higher education staff to validate and improve its effectiveness for the needs of HEIs. This paper summarises the key findings and recommendations of the validators for transforming the RESPO application into an application for HEIs. In addition, the selection of competencies in the RESPO application database has been adapted to align with selected study programmes and the need to develop sustainability-related competencies. These findings can support professionals working in higher education institutions in developing students’ future competencies and fostering the targeted use of learning analytics tools.
Ključne besede: higher education, competencies development, decision support, STEM education, sustainability
Objavljeno v DKUM: 02.08.2023; Ogledov: 251; Prenosov: 16
.pdf Celotno besedilo (1,83 MB)
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2.
Decision support concept for improvement of sustainability-related competences
Andreja Abina, Tanja Batkovič, Bojan Cestnik, Adem Kikaj, Rebeka Kovačič Lukman, Maja Kurbus, Aleksander Zidanšek, 2022, izvirni znanstveni članek

Opis: In this paper, we derived competences from previously developed competence models, ensuring the effective use of advanced technologies in future factories to improve the sustainability of their business models and strategies. Based on the analysis of the Hogan competence model and competence models for sustainability and leadership, we compiled a selection of competences for digitalisation, automation, robotics, artificial intelligence, and soft competences such as emotional intelligence and cultural literacy. We also included competences required for sustainability, corporate social responsibility, and circular economy. The selected competences formed the core for the conceptual development of a decision support tool for the individualised selection of training for employees. The concept was tested in customised training to improve employees’ skills and motivation for lifelong learning at the selected industrial partner. The developed assessment algorithm was used to monitor the progress of individual employees’ skills development before and after their training participation. The results of the assessment help human resource departments make decisions for selecting the most effective and optimal training for employees to improve their sustainability-related competences. Such a systematic approach can improve and evaluate competences that companies need to transition to a circular economy.
Ključne besede: circular economy, sustainability, competence development, employee training plan, decision support
Objavljeno v DKUM: 26.07.2023; Ogledov: 353; Prenosov: 35
.pdf Celotno besedilo (3,61 MB)
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3.
Perspectives of artificial intelligence in judiciary: application in selected parts of civil proceedings : application in selected parts of civil proceedings
Mariia Sokolova, 2021, magistrsko delo

Opis: The master’s thesis is devoted to the issue of Artificial Intelligence (AI) perspectives in the judiciary, in particular, its application to selected parts of civil proceedings. AI affects virtually the future of every industry and every human being. The application of AI technologies in the legal industry is an issue of growing interest. In particular, attention is drawn to the judicial system due to the fact that, apart from its position of guarantor of justice in society enabling its members to enjoy their rights and freedoms granted by law, it is a service of its nature. Almost all leading jurisdictions apply AI systems in attempts to enhance the efficiency of the court proceedings. Without any doubts, AI already and successfully can imitate activities traditionally performed by humans in the courts: from vision, recognising and extracting information, whether from the document, picture or natural speech, to analysing of information received and predicting the outcomes or decision-making. However, it is hard to say that AI-era in the judiciary has already begun. There is no jurisdiction in the world in which AI is fully given ‘green light’- they are all at the beginning of the AI-journey. That is mostly due to the fact that the same technical specifications, which power achievements, accuracy and flexibility of AI, place serious limitations for the wide application thereof. First of all, AI systems rely on data, which can be biased or spoiled in another way initially or easily manipulated later. Secondly, AI systems are not transparent (black-box-problem) and, as a result, are incomprehensible. These two shortcomings place an obstacle for the correct realisation of some fundamental rights in civil proceedings in their traditional understanding, and consequently, for the wide deployment of AI systems therein. It is concluded that the application of AI in the judiciary, in general, and in the civil proceedings, in particular, is subject of sufficient limitations mostly due to incompliance of AI systems with the traditional understanding of fundamental rights and principles the civil proceedings stand on. In the pursuit of the effectiveness of judiciary by means of AI application, fundamental guarantees can appear at stake, and vice versa, in the pursuit of respect of fundamental rights, the judiciary may be left out of the modern world in the stage of complete inadequacy to the needs of the society, therefore, the issue is required extensive research in order to find a fair and right balance.
Ključne besede: artificial intelligence, judiciary, civil proceedings, AI-judge, efficiency of the judiciary, automatic decision-making
Objavljeno v DKUM: 24.09.2021; Ogledov: 843; Prenosov: 117
.pdf Celotno besedilo (1,13 MB)

4.
Systems methodology for strategic decision-making in complex healthcare system
Tadeja Jere Lazanski, 2017, izvirni znanstveni članek

Opis: Systems methodology as a support for strategic decision- making will be discussed in the paper. A society will be presented as a complex system, which is comprised of many smaller, complex systems as its component parts. The healthcare system is one of them. The support to the strategic decision-making in a healthcare system will be shown through systems thinking and systems modelling. We will develop models of a healthcare system in frame of a systems dynamics; a qualitative causal loop diagram (CLD), which helps us to discuss the challenges categorically and a quantitative model, which is a simulation model. Both models illustrate the discussed methodology.
Ključne besede: systems methodology, healthcare system, strategic decision-making, systems thinking, modelling
Objavljeno v DKUM: 09.10.2018; Ogledov: 1448; Prenosov: 70
.pdf Celotno besedilo (783,10 KB)
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5.
Landslide assessment of the Strača basin (Croatia) using machine learning algorithms
Miloš Marjanović, Miloš Kovačević, Branislav Bajat, Snježana Mihalić Arbanas, Biljana Abolmasov, 2011, izvirni znanstveni članek

Opis: In this research, machine learning algorithms were compared in a landslide-susceptibility assessment. Given the input set of GIS layers for the Starča Basin, which included geological, hydrogeological, morphometric, and environmental data, a classification task was performed to classify the grid cells to: (i) landslide and non-landslide cases, (ii) different landslide types (dormant and abandoned, stabilized and suspended, reactivated). After finding the optimal parameters, C4.5 decision trees and Support Vector Machines were compared using kappa statistics. The obtained results showed that classifiers were able to distinguish between the different landslide types better than between the landslide and non-landslide instances. In addition, the Support Vector Machines classifier performed slightly better than the C4.5 in all the experiments. Promising results were achieved when classifying the grid cells into different landslide types using 20% of all the available landslide data for the model creation, reaching kappa values of about 0.65 for both algorithms.
Ključne besede: landslides, support vector machines, decision trees classifier, Starča Basin
Objavljeno v DKUM: 13.06.2018; Ogledov: 1162; Prenosov: 59
.pdf Celotno besedilo (382,76 KB)
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6.
Thinking in options – finding and evaluating alternatives
Edeltraud Günther, Daria Meyr, 2016, samostojni znanstveni sestavek ali poglavje v monografski publikaciji

Opis: After this general observation of decision processes we want to have a look at two decision making situations, that necessitate these processes, more detailed: Investment decisions are on the agenda for small and medium-sized companies, while acquisition decisions are more relevant in larger companies.
Ključne besede: decision-making, investment decisions, acquisition decisions, monetary assessment, effects, economic-ecological net effect
Objavljeno v DKUM: 11.05.2018; Ogledov: 1109; Prenosov: 58
.pdf Celotno besedilo (537,94 KB)
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7.
Dimensions of decision-making process quality and company performance : a study of top managers in Slovenia
Damjan Grušovnik, Alenka Kavkler, Duško Uršič, 2017, izvirni znanstveni članek

Opis: This paper investigates the relationship between the dimensions of the decision-making process quality and company performance of top managers’ in Slovenia. We found out that companies whose managers exhibit an above-average dimension of openness of spirit in the quality of the decision making process, on average, have a higher stance on foreign markets as companies in which managers show a below-average open spirit. For the managers who work in companies that are present in foreign markets, we could confirm that there is a low/weak correlation between the dimension of effort of the decision-making process quality and the number of employees in a company.
Ključne besede: quality of the decision-making process, rationality, motivation, participation, exhaustivity of the information, managers effort, creativity and innovativeness, company stakeholders, company performance
Objavljeno v DKUM: 03.05.2018; Ogledov: 1514; Prenosov: 192
.pdf Celotno besedilo (1,27 MB)
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8.
Examining determinants of leadership style among Montenegrin managers
Anđelko Lojpur, Ana Aleksić, Sanja Vlahović, Mirjana Pejić Bach, Sanja Peković, 2015, izvirni znanstveni članek

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: 1137; Prenosov: 57
.pdf Celotno besedilo (1,66 MB)
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9.
Representation of Boolean functions with ROBDDs
Aleš Časar, Robert Meolic, samostojni znanstveni sestavek ali poglavje v monografski publikaciji

Opis: This paper describes data structures and algorithms for representation of Boolean functions with reduced ordered binary decision diagrams (ROBDDs). A hash table is used for quick search. Additional information about variables and functions is stored in binary trees. Manipulations on functions are based on a recursive algorithm of ITE operation. The primary goal of this article is describe programming technics needed to realize the idea. For the first time here recursive algorithms for composing functions and garbage collection with a formulae counter are presented. This is better than garbage collection in other known implementations. The results of the tests show that the described representation is very efficient in applications which operate with Boolean functions.
Ključne besede: Reduced Ordered Binary Decision Diagram, Boolean function, logic functions, logic design verification, hash table
Objavljeno v DKUM: 02.02.2018; Ogledov: 2379; Prenosov: 53
.pdf Celotno besedilo (323,32 KB)

10.
Understanding the structural complexity of induced travel demand in decision-making : a system dynamics approach
Juan Angarita-Zapata, Jorge Parra-Valencia, Hugo Andrade-Sosa, 2016, izvirni znanstveni članek

Opis: Background and purpose: Induced travel demand (ITD) is a phenomenon where road construction increases vehicles’ kilometers traveled. It has been approached with econometric models that use elasticities as measure to estimate how much travel demand can be induced by new roads. However, there is a lack of “white-box” models with causal hypotheses that explain the structural complexity underlying this phenomenon. We propose a system dynamics model based on a feedback mechanism to explain structurally ITD. Methodology: A system dynamics methodology was selected to model and simulate ITD. First, a causal loop diagram is proposed to describe the ITD structure in terms of feedback loops. Then a stock-flows diagram is formulated to allow computer simulation. Finally, simulations are run to show the quantitative temporal evolution of the model built. Results: The simulation results show how new roads in the short term induce more kilometers traveled by vehicles already in use; meanwhile, in the medium-term, new traffic is generated. These new car drivers appear when better flow conditions coming from new roads increase attractiveness of car use. More cars added to vehicles already in use produce new traffic congestion, and high travel speeds provided by roads built are absorbed by ITD effects. Conclusion: We concluded that approaching ITD with a systemic perspective allows for identifying leverage points that contribute to design comprehensive policies aimed to cope with ITD. In this sense, the model supports decision- making processes in urban contexts wherein it is still necessary for road construction to guarantee connectivity, such as the case of developing countries.
Ključne besede: induced travel demand, system dynamics, decision-making, dynamic modeling
Objavljeno v DKUM: 23.01.2018; Ogledov: 1402; Prenosov: 159
.pdf Celotno besedilo (1,96 MB)
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