An explanatory coherence model of decision making in ill-structured problems

Classical models of decision making deal fairly well with uncertainty, where settings are well-structured in terms of goals, alternatives, and consequences. Conversely, the typical ill-structured nature of strategy choices remains a challenge for extant models. Such cases can hardly build on the past, and their novelty makes the prediction of consequences a very difficult and poorly robust task. The weakness of the classical expected utility model in representing such problems has not been adequately solved by recent extensions. In this paper we offer an explanatory coherence model for decision making in ill-structured problems. We model alternatives as sets of concurrent causal explanations of reality that act as justifications for action. According to these premises, choice is based on an evaluation of the internal coherence and the consistency of competing explanations of the available evidence. This model is psychologically grounded on causal inference and builds on the connectionist tradition of explanatory coherence. To illustrate the model, we consider the decision of investing in a new technology and we discuss how changes in the structure of alternatives may impact on the solution. We show how the final choice depends on collecting the relevant evidence, making the suitable hypotheses, and drawing the consistent causal explanations linking the two. © 2014, Springer-Verlag Berlin Heidelberg.