Emotion Regulation as Risk Management: A Stochastic Control Model of Industrial Production Crises

Existing risk control systems seeking to evaluate and alleviate the negative outcomes of industrial production crises typically fail to consider the role of human factors, such as managers’ interpersonal emotion management. Yet, literature in applied psychology shows that leaders elicit very different reactions from others as a function of leaders’ abilities to regulate their emotions and those of people around them, particularly in times of crisis. Unfortunately, these two research communities tend to work in silos. Consequently, our research aims at developing a decision-making meta-model for addressing production crises that relies on both management science and applied psychology. We develop a practical production crisis decision model that couples the formalized decision making framework of a Markov Decision Process (MDP) with empirical data on interpersonal emotion management. This model is applied to cases of production crises or disruptions where managers use different levels of Interpersonal Emot...