Conceptualizing Organizational Change Through the Lens of Complexity Science

Organizational scholars interested in organizational change and learning have been inspired by the mathematics, concepts, models, and metaphors of complexity science since the 1990s. Time is a fundamental variable in all complexity science models, so descriptions of change follow naturally. Complexity science builds upon systems theory to provide a more nuanced and thick causal narrative of change. Researchers in the organizational sciences have used four different types of complexity science based models to conceptualize organizational change: agent-based, computational, dynamical, and far-from-equilibrium. These different approaches hold the common assumptions that change is both continuous and discontinuous, and nonlinear dynamics arising from complex interactions can make organizational change difficult to predict or control. Studies of organizational change using complexity science models may be deductive or inductive and may engage quantitative or qualitative data. This chapter reviews these models and their application to the study of organizational change and assesses what influence complexity science has had on organizational studies since its own emergence.