A primer on using Monte Carlo simulations to evaluate research methods in strategic management

Strategic management scholars increasingly rely on diverse research methodologies to investigate the field’s central questions. In this paper, we advance knowledge by demonstrating how Monte Carlo simulations (MCSs) can serve as an essential tool for evaluating and enhancing these techniques. To do so, we first overview strategy research that has employed MCSs to adjudicate statistical or econometric techniques. We then describe the intuition and main steps for specifying and employing MCSs, which involve defining the research question, designing a data generation (DGP) process, analyzing data, and summarizing/communicating results. To facilitate the implementation of MCSs, we developed a custom generative pre-trained transformer (GPT)that enables researchers to produce the code (R, Stata, and/or Excel) necessary to design and execute MCSs. We close with a research agenda for strategy scholars interested in using MCSs to advance their own methodological pursuits.