Decision-Making Under Conditions of Multiple Values and Variation in Conditions of Risk and Uncertainty

Empirical research shows that humans face many kinds of uncertainties, responding in different ways to the variations in situational knowledge. The standard approach to risk, based largely on rational choice conceptualization, fails to sufficiently take into account the diverse social and psychological contexts of uncertainty and risk. The article addresses this challenge, drawing on sociological game theory (SGT) in describing and analyzing risk and uncertainty and relating the theory’s conceptualization of judgment and choice to a particular procedure of multi-criteria decision-making uncertainty, namely the TOPSIS approach. Part I of the article addresses complex risk decision-making, considering the universal features of an actor’s or decision-maker’s perspective: a model or belief structure, value complex, action repertoire, and judgment complex (with its algorithms for making judgments and choices). Although these features are universal, they are particularized in any given institutional or sociocultural context. This part of the article utilizes SGT to consider decision-making under conditions of risk and uncertainty, taking into account social and psychological contextual factors. Part II of the article takes up an established method, TOPSIS with Belief Structure (BS), for dealing with multi-criteria decision-making under conditions of uncertainty. One aim of this exercise is to identify correspondences between the SGT universal architecture and the operative components of the TOPSIS method. We expose, for instance, the different value components or diverse judgment algorithms in the TOPSIS procedure. One of the benefits of such an exercise is to suggest ways to link different decision methods and procedures in a comparative light. It deepens our empirical base and understanding of values, models, action repertoires, and judgment structures (and their algorithms). The effort here is, of course, a limited one.