Conscientiousness and General Mental Ability Predict Deviation from Optimal Resource Allocation

Abstract

This research speaks to developments in the conscientiousness literature regarding the consequences of being overly conscientious. Specifically, research has found that excessively conscientious individuals exhibit worse task performance than individuals with moderate levels of conscientiousness. The purpose of our study is to understand why and for whom high levels of conscientiousness may be detrimental. To this end, we incorporated resource allocation and general mental ability (GMA) to answer these questions. We conducted a laboratory study in which we manipulated the optimal level of resource allocation across multiple trials of a work simulation. Participants could maximize performance by matching actual resource allocation to the optimal level of resource allocation. This design allowed us to directly observe participants’ resource allocation decisions and vary the optimal level of resource allocation from low to high. We found that individuals with high conscientiousness and low GMA deviated most from the optimal level of resource allocation. Specifically, individuals with high conscientiousness and low GMA had a tendency to over-allocate resources. Downstream, the greater the deviation from the optimal level of resource allocation the worse performance was. Although conscientiousness may be beneficial in some circumstances, more is not always better. We demonstrated that high levels of conscientiousness can be detrimental to performance. This reduction in performance occurs when individuals are willing to invest a great deal of resources (high conscientiousness) but unable to recognize the optimal level of resource allocation (low GMA). Past research has provided limited insight into why highly conscientious individuals have been found to perform worse than individuals with moderate levels of conscientiousness. Our study extends this research by using an experimental design to demonstrate that conscientiousness and GMA interact to indirectly predict performance via resource allocation.