Complex tasks, frustrated minds: Motivational predictors of performance in complex problem solving and dynamic decision making

Abstract

This study investigated the role of motivational factors in Complex Problem Solving (CPS) and Dynamic Decision Making (DDM). While previous research has focused primarily on cognitive predictors, we examined motivational variables including grit, competence satisfaction, competence frustration, and frustration tolerance. In Study 1 (N = 54), participants completed the complex and dynamic, software-based computer simulation ChocoFine, a business microworld that researchers can use to study CPS. Multiple regression analyses showed that competence frustration ( β = −.26) and low frustration tolerance ( β = −.27) were negatively associated with CPS performance (total monies). Motivational variables explained 16% of the variance, a level comparable to the influence of intelligence on CPS as reported in meta-analytic findings. In Study 2 (N = 72), frustration was experimentally induced by giving participants an unsolvable figure-tracing task and false normative feedback. Participants were then asked to work on the Cold-storage simulation, a task that requires decision making while the effects of performed actions are both delayed and imprecise. As expected, the frustrated group performed significantly worse than the control group ( p = .03, d = −.46). Together, the two studies provide converging evidence that motivational and emotional processes—especially competence-related dynamics—can influence performance in complex, non-transparent decision-making environments. These findings support PSI theory, which emphasizes the interplay between motivational, emotional, and cognitive processes.