Multiple-stage Decision-making: the Effect of Planning Horizon Length on Dynamic Consistency

Many decisions involve multiple stages of choices and events, and these decisions can be represented graphically as decision trees. Optimal decision strategies for decision trees are commonly determined by a backward induction analysis that demands adherence to three fundamental consistency principles: dynamic, consequential, and strategic. Previous research (Busemeyer et al. 2000, J. Exp. Psychol. Gen. 129, 530) found that decision-makers tend to exhibit violations of dynamic and strategic consistency at rates significantly higher than choice inconsistency across various levels of potential reward. The current research extends these findings under new conditions; specifically, it explores the extent to which these principles are violated as a function of the planning horizon length of the decision tree. Results from two experiments suggest that dynamic inconsistency increases as tree length increases; these results are explained within a dynamic approach–avoidance framework.