Current theories and models of humor conceptualize humor at the individual, dyadic, and organizational level. These theories laid the foundation for research and empirical findings that have established humor’s impact in the workplace. Yet, because these theories are not integrated, they individually do not offer a comprehensive view of humor in the workplace across different levels, hindering the development of multilevel research designs. Additionally, the ambiguity of these narrative theories hampers empirical testing precision. This dissertation expands the literature by introducing a mathematical, multilevel model of humor and tests that theory using computational simulation methods. Synthetic environments reproduced observed correlations in the humor literature, showing generative sufficiency. Further, virtual explorations of follower impression management towards leader humor revealed that impression management tactics greatly impacted leader learning of follower humor preferences. Investigations into newcomer socialization in established humor climates showed that newcomer goals influenced group acceptance. Impacts of this dissertation include adding multilevel theory to the literature, making theory more communicable via mathematics, the novel explanation of the process of choosing to share humor, clarity for humor terms, and sharable computational modeling that offers precision for future investigations. Practical applications suggest leaders looking to use humor should build trusting relationships and that organizations hoping to dismantle hateful humor climates (e.g., racist or misogynistic joking) need to engage in active discourse. Together, the presented formal model of humor and computational simulation of that model propel the workplace humor literature forward
