Effectuation Under Risk and Uncertainty: A Simulation Model

Abstract

Effectuation was first proposed as an expert entrepreneur’s decision-making framework under uncertainty, but the condition of uncertainty has been questioned. Using an agent-based simulation model, this paper investigates the effectiveness of effectuation relative to causation in uncertain and risky contexts. The simulation overcomes some of the shortcomings of think aloud protocols typically used in effectuation research. The results suggest that effectuation outperforms causation in both risky and uncertain contexts up until the entrepreneur’s predictive ability nears omniscience. The implication is that effectuation should not be restricted to uncertain environments, but is an effective framework whenever predicting the future is challenging.