Two probability theories and a garbage can

Abstract

Since its nascence, computational organization theory has predominantly relied on classical probability theory to model and simulate organizational properties. However, key assumptions of classical probability theory conflict with empirical observations of organizational behaviors and processes, thereby raising the question if an alternate theoretical basis for probabilistic modeling of organizations might improve the relevancy of computational organization research. In the context of the garbage can model of organizational decision-making, this paper provides two examples—order effects and system measurement—to illustrate the inadequacy of classical probability theory and to stimulate discussion on the merits of incorporating quantum probability theory in computational models. This paper recommends that future work explore the sensitivity of computational organization theory models to probability theories, the impacts associated theoretical assumptions might have on modeling and simulating dynamic organizational interdependencies, and the implications to community practices.