We conducted a clustered randomized field experiment with 20 Brazilian distributorships of a multinational direct sales organization to examine whether controlling failure perceptions through formal communications increases performance. We used the organization's weekly sales meetings to deliver a video-based message from the regional head that either communicates workers should view failure as a natural part of learning rather than an indictment of their ability (treatment condition) or simply summarizes the organization's history (control condition). We find that those who were assigned to the treatment condition were more likely to sustain their effort in response to the economic adversity that coincided with our experiment. Additional analyses suggest that our treatment accomplished this by increasing job-specific confidence and by reinforcing social norms that encourage workers to persevere after failure. Overall, our findings highlight that formal communications from senior management are a viable control mechanism for sustaining effort in the face of failure.
We present a neural network model that aims to bridge the historical gap between dynamic and structural approaches to personality. The model integrates work on the structure of the trait lexicon, the neurobiology of personality, temperament, goal-based models of personality, and all evolutionary analysis of motives. It is organized in terms of two overarching motivational systems, an approach and an avoidance system, as well as a general disinhibition and constraint system. Each overarching motivational system influences more specific motives. Traits are modeled in terms of differences in the sensitivities of the motivational systems, the baseline activation of specific motives, and inhibitory strength. The result is a motive-based neural network model of personality based on research about the structure and neurobiology of human personality. The model provides an account of personality dynamics and person-situation interactions and suggests how dynamic processing approaches and dispositional, structural approaches can be integrated in a common framework.