Prediction and control: An agent‐based simulation of search processes in the entrepreneurial problem space

Abstract

Research Summary: This study seeks to understand the boundary conditions and successful application of search processes in the entrepreneurial problem space. To this end, we employ an agent‐based simulation approach to formally investigate the influence of environmental isotropy, unpredictability, and goal ambiguity on two distinct search processes, one prediction‐based and one control‐based. Specifically, we investigate the performance of effectuation as an example of non‐predictive, control‐based search and causation as an example of prediction‐based search. Results enhance theory by revealing a more nuanced relationship between the environment and entrepreneurial search than previous conceptual and empirical work has suggested.Managerial Summary: Historically, entrepreneurship research has tended to view the external environment as given. The guidance for entrepreneurs given an immutable landscape sits on a continuum between “learn to plan better” and “learn to react faster.” These two approaches differ only in their suggestions about what entrepreneurs should do assuming the environment is given. A growing body of theoretical work questions this environment‐as‐given assumption and suggests an alternative entrepreneurial search process that seeks active control of environmental elements. To understand the successful applications as well as limitations of these entrepreneurial search processes, this study runs a simulation in which agents engage in different search processes. Practitioners receive more realistic guidance on how search for value needs a match between the idea, the context, and the search process.