A compensation index for multiattribute decision strategies

In multiattribute decision problems, the subject has to evaluate a number of alternatives with given values on a number of attributes, in order to arrive at some conclusion about the attractiveness or utility of these alternatives. The information processing procedure leading to a conclusion is called adecision strategy, and one of the main research topics in multiattribute decision research has been the extent to which these strategies follow compensatory principles. Judges are said to follow compensatory strategies when low values on some attributes are compensated for by high values on other attributes. In process tracing studies using the information board technique, descriptions of decision strategies are usually based on three indices of the information search process:variability of search,search pattern (Payne, 1976), anddepth of search. Variability of search, defined as the standard deviation of the proportion of information searched per alternative, is considered to give an indication of the degree of compensation of a decision strategy, compensation being smaller as variability increases. In this article, we propose an alternative way for establishing the degree of compensation of decision strategies in information board studies. We argue that the degree of compensation depends on both variability of searchand depth of search (the proportion of information searched), and that a valid compensation index has to be a multiplicative function of these two indices.