A DECISION MAKING METHOD WITH COMPLEX ATTITUDINAL CHARACTERS FOR EDUCATIONAL MANAGEMENT

We develop a new method for decision making based on situations where the decision maker may have complex attitudinal characters and we apply it in educational management. We focus on the selection of advanced studies from the perspective of an academic institution where they are looking for the optimal courses to be included in their programs. We try to develop this approach showing the benefits of establishing an ideal course that we compare with the available alternatives. For doing this, we use different concepts found in decision theory such as the Minkowski distance, the ordered weighted averaging (OWA) operator, induced aggregation operators and the interval numbers. By using the Minkowski distance we are able to make comparisons between the ideal plan and the available ones in the market. The OWA operator is an aggregation operator that provides a parameterized family of aggregation operators that includes among others the maximum, the minimum and the average criteria. In this paper, we use a more complex form of the OWA operator called the induced OWA (IOWA) operator that it is able to deal with complex attitudinal characters such as the decisions taken with a group of experts. And the interval numbers are a very useful technique for representing the information when the environment is very complex because it gives all the possible results from the minimum to the maximum. Therefore, it includes all the possible results that could happen in the future. For doing so, we introduce a new aggregation operator called the uncertain induced generalized ordered weighted averaging distance (UIGOWAD) operator. It is a distance aggregation operator that uses the main characteristics of the Minkowski distance, the IOWA operator and the interval numbers. We develop an illustrative example where we can see the usefulness of the UIGOWAD operator for selecting courses in an advanced studies plan in educational management. The main reason for using the UIGOWAD is that it provides a wide range of distance aggregation operators in the decision problem. Thus, the decision maker gets a more complete view of the selection process and he is able to select the alternative that better fits his interests.