Objectives and competences
A student at this subject
1. develops the capacity to participate in the decision-making process
2. gains in-depth knowledge of decision-making systems and decision-support models
3. gains the ability to independently organize the decision-making process, with particular emphasis on group decision-making
Content (Syllabus outline)
1. Decision making process as a socio-technical process
2. Decision support systems and decision models
3. Multi-attribute decision making
4. Qualitative and quantitative modelling
5. Decision support methods and techniques
6. Using AI methods in the decision making
7. Data analytics
8. Deciding under risk / unknown conditions
9. Human in the decision-making process
10. Group decision making
11. Evaluating decisions
Learning and teaching methods
• Lectures
• Case studies
• Exercises
• Developing a decision support model for organizing a chosen decision support process
Intended learning outcomes - knowledge and understanding
Knowledge and understanding:
• to rationally link the elements of the decision process
• to argue the role of modern tools to support decision-making processes with an emphasis on group decision-making
• to develop a decision-making model to support a decision process
• to analyse the results of decision models
• to apply a decision model in a given process
• to choose suitable contemporary methods and techniques
Intended learning outcomes - transferable/key skills and other attributes
- ability to organize a decision making process as a cybernetic process
- ability to develop models for decision support by using modern methods and techniques
Readings
1. Rajkovič, V. (2019). Digitalizacija in odločanje. V Slovenija na poti digitalne preobrazbe (str. 182-207). Založba UL FRI. http://zalozba.fri.uni-lj.si/bavec2019.pdf
2. Rajkovič, U., & Werber, B. (2021). Sistemi za podporo odločanju: metodologija razvoja = Decision support systems. V Znanstveno-raziskovalni trendi na področju digitalne preobrazbe (str. 79–95). Univerzitetna založba. https://press.um.si/index.php/ump/catalog/book/605
3. Kljajić Borštnar, M., & Pucihar, A. (2022). Večkriterijski model za ocenjevanje digitalne zrelosti malih in srednje velikih podjetij = Multi-criteria model for digital maturity assessment of small and medium sized enterprises. V Znanstveno-raziskovalni izzivi na poti digitalne preobrazbe (str. 21–51). Univerzitetna založba. https://press.um.si/index.php/ump/catalog/book/712
4. Blatnik, S. (2024). Methodology development for open data maturity assessment in small and medium-sized enterprises – a literature review. 859–880. https://press.um.si/index.php/ump/catalog/view/880/1284/4184
Prerequisits
Prerequisites for enrolling:
knowledge of statistics and probability
basic knowledge of mathematics
basic knowledge of ICT
Exam admission requirement:
positive evaluation of a seminar work and its defence
Additional information on implementation and assessment Coursework (100%)
