Accuracy and effort of decision making strategies with incomplete information

Decision makers are often required to make decisions with incomplete information. In order to design decision support systems (DSSs) to assist decision makers in these situations, it is essential to understand why and how decision makers select their strategies. This paper presents a simulation which examines the impact of incomplete information on the effort and accuracy of decision strategies. The current study evaluates two strategies: a normative-rational strategy (multi-attribute utility theory, MAUT) and a psychological heuristic (take-the-best, TTB). Under conditions of full (i.e., complete) information, the simulation is able to replicate previous studies showing that psychological heuristics perform as well as normative-rational methods with lower effort requirements. Under conditions of incomplete information, the simulation showed that psychological heuristics retain their high accuracy with low effort whereas the normative-rational strategies decrease in accuracy and still require high effort. Since decision makers´ strategy selection is known to be contingent upon many decision scenario contexts such as information availability, this simulation study provides direct links as to how decision making strategies are affected by different levels of information availability - supporting and expanding upon prior empirical and simulation studies.