Entscheidungsfindung und Risikoverhalten im Controlling

Abstract

Problem: The controller is often seen as a safeguard of rationality in the company. To ensure this, however, he must always act rationally when making decisions. However, this is impossible for humans, because psychological factors always have an influence on decisions. If you are influenced by psychological factors, this often has an influence on how we assess risks. Therefore, if you do not heed them, it can happen that the controller underestimates risk too much or overestimates them. When this happens, decisions are often made that harm our companies or big opportunities are missed. Therefore, it should be of great interest in controlling to understand which factors influence us and what effects they have on decisions and risk behaviour. Structure and Methodology: The thesis refers to literature research. For the sake of simplicity, gender is omitted in the thesis. The thesis is structured as follows. First, there is a theoretical input. Definitions are clarified and the most important models and theories of psychological factors for decisionmaking are presented. Then, the influence of these on the decision-making process of controlling and on risk management are examined. In the last point of the thesis, suggestions are presented on how to increase the sensitivity to psychological factors and which controlling models in risk management can be adapted to consider psychological factors. Results: The results of this work show that psychological factors have a big influence on how we assess risks. In addition, people tend to take small shortcuts when making decisions. These successes subconsciously and we use irrational data that our brain believes will help us to make a good decision. The most important thing for the controller is that he knows about these factors and effects and can also assess what triggers them. This way, strategies can be developed, such as creating a checklist to check whether you have thought about all the factors, or you can adapt existing controlling models to take these factors into account.

Date of Award	2024
Original language	German (Austria)
Supervisor	Albert Mayr (Supervisor)