735318 Decision support systems

Type
Seminar
Semester hours
2
Lecturer (assistant)
Meixner, Oliver
Organisation
Offered in
Wintersemester 2024/25
Languages of instruction
Englisch
Content

"Decision support for the solution of complex multicriteria problems"

"Decision Support Systems (DSS)" is a lecture that explores the application of computer-based systems that aid in decision-making processes. The course covers key concepts such as data research, data analysis, modeling, including artificial intelligence to enhance decision quality in complex environments. Students learn how to integrate tools like databases, expert systems, and machine learning algorithms to provide effective support for both structured and unstructured decisions in various organizational contexts.

After a general introduction to decision theory, the lecturer will give a brief overview over decision support systems for solving complex, unstructured decision situations in organizations. The students work out solutions for a specific question which is poorly structured and complex.
"Decision support for the solution of complex multicriteria problems"

"Decision Support Systems (DSS)" is a lecture that explores the application of computer-based systems that aid in decision-making processes. The course covers key concepts such as data research, data analysis, modeling, including artificial intelligence to enhance decision quality in complex environments. Students learn how to integrate tools like databases, expert systems, and machine learning algorithms to provide effective support for both structured and unstructured decisions in various organizational contexts.

After a general introduction to decision theory, the lecturer will give a brief overview over decision support systems for solving complex, unstructured decision situations in organizations. The students work out solutions for a specific question which is poorly structured and complex.

After an introduction into decision theory and application of DSS, the workload of students comprises the workout of an essay including a comprehensive literature review, research in adequate data bases, development of an appropriate decision model, analysis and presentation and discussion of results. The students select a case study (provided by lecturer) which forms the basis for the elaboration of the essay.
Previous knowledge expected


Objective (expected results of study and acquired competences)

Students will be able to answer amongst others the following questions:

Why is decision making one of the most important tasks in our society?
How can decision making in organizations be improved?
Which methods may be applied, what are their advantages and disadvantages?
What are important fields of application of decision support systems?
How can a specific decision support system be applied to a (more or less) strategic decision problem in an organizational context?
How can artificial intelligence support decision making in an organizational context?

Students will be able to

* understand and support the management of decision making in organizations
* solve poorly structured, complex decision problems (of strategic nature) using a convenient decision support system
* understand and apply multi criteria decision making (MCDM)
* understand the state of the art / theories in decision making
* apply decision making tools
* develop and apply new approaches in decision making based on a specific real-life case study
* name examples of decision making such as strategic management decisions, investment decisions, project selection, relocation decision, mergers & acquisition, evaluation/selection of future corporate strategies, etc.

After the course the students will be able to analyze and solve unstructured, complex decision problems in an organizational context confirming the state of the art decision making theory.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.