A METHOD FOR DECISION MAKING BASED ON PROBABILISTIC INFORMATION AND DISTANCE MEASURES

We develop a new method for decision making in strategic management. We focus on a decision making problem where a university is planning its strategy for the next year. For doing so, we use probabilistic information in order to assess the uncertain environment. We also use the ordered weighted averaging (OWA) operator because then, we can consider the attitudinal character of the decision maker in the decision problem. This model is based on the use of ideal alternatives that the decision maker believes that would be the best choice for him. Then, by comparing it with the available alternatives existing in the real world, he is able to obtain a result that shows which the best alternative is according to the particular interests of the decision maker. In order to develop this method, we introduce the probabilistic ordered weighted averaging distance (POWAD) operator. It is a new aggregation operator that uses a unified model between the probabilities and the OWA operator considering the degree of importance that each concept has in the particular problem considered. Moreover, it also uses distance measures in the aggregation process. In this paper, we consider the use of the Hamming distance but in future research we will also consider the use of more general formulations such as the use of the Minkowski distance or the quasi-arithmetic distance. We study some of the main properties of the POWAD operator and different particular cases such as the probabilistic maximum distance, the probabilistic minimum distance, the probabilistic Hamming distance, the POWA operator, the Hamming distance the classical probabilistic approach and the OWA operator. We also analyse the applicability of the new approach. We focus on a strategic decision making problem where a university is planning the general strategy for the next year. They analyze the possibility of increasing the prizes of the courses offered by the university. We see that depending on the particular type of POWAD operator used, the results may lead to different decisions.