1. Sustainable development of ethno-villages in Bosnia and Herzegovina : a multi criteria assessmentBoris Prevolšek, Aleksandar Maksimović, Adis Puška, Karmen Pažek, Maja Borlinič Gačnik, Črtomir Rozman, 2020, izvirni znanstveni članek Opis: This paper explores ethno-villages in Bosnia and Herzegovina as an important element of rural and cultural tourism. The attractiveness of natural and cultural heritage is very important for sustainable rural tourism development. In order to improve the process of decision making to enable the sustainable development of ethno-villages, a multi-criteria assessment model has been developed. The methodology is based on qualitative modeling using a multi-criteria analysis via the DEXi software. The model is based on hierarchical relations consisting of three main criteria that are the basis of sustainable tourism development: economic, social, and environmental criteria. The ultimate goal of the model in this study was to evaluate ethno-villages, namely six ethno-villages in Bosnia and Herzegovina. The results of the study show how ethno-villages contribute to sustainable development. Ključne besede: sustainable development, tourism, ethno-villages, DEXi, decision support, multi-criteria model, assessment Objavljeno v DKUM: 07.02.2025; Ogledov: 0; Prenosov: 2
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2. Transformation of the RESPO decision support system to higher education for monitoring sustainability-related competenciesAndreja 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: 346; Prenosov: 20
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3. Decision support concept for improvement of sustainability-related competencesAndreja 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: 469; Prenosov: 65
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4. Landslide assessment of the Strača basin (Croatia) using machine learning algorithmsMiloš 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: 1268; Prenosov: 66
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5. A statistical model for shutdowns due to air quality control for a copper production decision support systemKhalid Aboura, 2015, izvirni znanstveni članek Opis: Background: In the mid-1990s, a decision support system for copper production was developed for one of the largest mining companies in Australia. The research was conducted by scientists from the largest Australian research center and involved the use of simulation to analyze options to increase production of a copper production facility.
Objectives: We describe a statistical model for shutdowns due to air quality control and some of the data analysis conducted during the simulation project. We point to the fact that the simulation was a sophisticated exercise that consisted of many modules and the statistical model for shutdowns was essential for valid simulation runs.
Method: The statistical model made use of a full year of data on daily downtimes and used a combination of techniques to generate replications of the data.
Results: The study was conducted with a high level of cooperation between the scientists and the mining company. This contributed to the development of accurate estimates for input into a support system with an EXCEL based interface.
Conclusion: The environmental conditions affected greatly the operations of the production facility. A good statistical model was essential for the successful simulation and the high budget expansion decision that ensued. Ključne besede: decision support system, simulation, statistical modelling Objavljeno v DKUM: 28.11.2017; Ogledov: 1317; Prenosov: 340
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6. Organizational learning supported by machine learning models coupled with general explanation methods : a case of B2B sales forecastingMarko Bohanec, Marko Robnik Šikonja, Mirjana Kljajić Borštnar, 2017, izvirni znanstveni članek Opis: Background and Purpose: The process of business to business (B2B) sales forecasting is a complex decision-making process. There are many approaches to support this process, but mainly it is still based on the subjective judgment of a decision-maker. The problem of B2B sales forecasting can be modeled as a classification problem. However, top performing machine learning (ML) models are black boxes and do not support transparent reasoning. The purpose of this research is to develop an organizational model using ML model coupled with general explanation methods. The goal is to support the decision-maker in the process of B2B sales forecasting.
Design/Methodology/Approach: Participatory approach of action design research was used to promote acceptance of the model among users. ML model was built following CRISP-DM methodology and utilizes R software environment.
Results: ML model was developed in several design cycles involving users. It was evaluated in the company for several months. Results suggest that based on the explanations of the ML model predictions the users’ forecasts improved. Furthermore, when the users embrace the proposed ML model and its explanations, they change their initial beliefs, make more accurate B2B sales predictions and detect other features of the process, not included in the ML model.
Conclusions: The proposed model promotes understanding, foster debate and validation of existing beliefs, and thus contributes to single and double-loop learning. Active participation of the users in the process of development, validation, and implementation has shown to be beneficial in creating trust and promotes acceptance in practice. Ključne besede: decision support, organizational learning, machine learning, explanations Objavljeno v DKUM: 01.09.2017; Ogledov: 1751; Prenosov: 338
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7. Decision making under conditions of uncertainty in agriculture : a case study of oil cropsKarmen Pažek, Črtomir Rozman, 2009, pregledni znanstveni članek Opis: In decision under uncertainty individual decision makers (farmers) have to choose one of a set number of alternatives with complete information about their outcomes but in the absence of any information or data about the probabilities of the various state of nature. This paper examines a decision making under uncertainty in agriculture. The classical approaches of Wald’s, Hurwicz’s, Maximax, Savage’s and Laplace’s are discussed and compared in case study of oil pumpkin production and selling of pumpkin oil. The computational complexity and usefulness of the criterion are further presented. The article is concluded with aggregate the results of all observed criteria and business alternatives in the conditions of uncertainty, where the business alternative 1 is suggested. Ključne besede: uncertainty, Wald’s, Hurwicz’s, Maximax, Savage’s and Laplace’s criterion, decision support system, agriculture, oil crops Objavljeno v DKUM: 20.07.2017; Ogledov: 1261; Prenosov: 138
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8. Application of analytical hierarchy process in agricultureKarmen Pažek, Črtomir Rozman, 2005, izvirni znanstveni članek Opis: Hierarchical decision models are a general decision support methodology aimed at the classification or evaluation of options that accur in desion-making processes. Decision models are typically developed through the decomposition of complex decision problems into smaller and less comple subproblems. This paper presents an approach to the development and implementation of multicriteria decision model based on Analytical Hierarchy Process - AHP (Expert Choice, EC). Likewise, the AHP is used as a potential multicriteria decision making method for application in agriculture. In order to show the implementation of explained MCDA methods in real situation in agriculture, theapplication of AHP on a sample model farm is presented in the second part of the article. Ključne besede: multicriteria decision analysis, MCDA, analytical hierarchy process, AHP, decision support system, DSS, agriculture Objavljeno v DKUM: 20.07.2017; Ogledov: 1759; Prenosov: 210
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10. Comparative analysis of collaborative and simulation based learning in the management environmentMirjana Kljajić Borštnar, 2012, izvirni znanstveni članek Opis: Purpose of the study is to compare two different approaches to the collaborative problem solving one in a highly controlled laboratory experiment: Optimisation of business politics using business simulator at different experimental condition which reflect different feedback information structure and one in a collaborative environment of the social media, characterised by non-structured, rule-free and even chaotic feedback information. Comparative analyses of participant’s opinion who participate in experiments have been considered in order to find common characteristics relevant for group/collaborative problem solving. Based on these findings a general explanatory causal loop model of collaborative learning during problem solving was built. Ključne besede: group decision support, information structure, collaborative learning, simulation model Objavljeno v DKUM: 10.07.2015; Ogledov: 1557; Prenosov: 385
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