Decision Making Based on Ill-Known Decision Trees

conference paper

English

IB (Insolvency and Bankruptcy) tasks are ill-known processes. Real life decision making related to IB is based on common sense reasoning only. To formalise such vague, sparse, partially inconsistent and subjective tasks as IB classical decision making trees can be used. However, traditional evaluation of these trees requires a complete set of relevant numerical values. These values are often either prohibitively inaccurate or they are unknown as they are unique. Moreover, decision economists dealing with IBs are usually not willing to invest too much time into study of complex mathematical theories. IB problem is transferred into a decision making tree which indicates all sub-decisions and random lotteries. Random lotteries quantifies such sub-IBs events which are not certain. Such decision trees are evaluated using well known methods. However, the required data sets are often incomplete. The problem of missing data items is solved by introducing a simple and generally applicable heuristic – a longer sequence of events is less probable. A company has legislatively supported several options how to deal with bankruptcy situation. Each of the option can be solved in three different ways by using decision–making tree as tool for probability determination, using already known probabilities from previous case.

Insolvency, restructuring, decision–making tree, probabilities, reconciliation, creditors claim, water probability.

POLÁČEK, T.; DOUBRAVSKÝ, K.; DOHNAL, M.

19. 9. 2018

Banja Luka

978-99938-46-80-2

6th REDETE Conference RESEARCHING ECONOMIC DEVELOPMENT AND ENTREPRENEURSHIP IN TRANSITION ECONOMIES

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