A Theory of Entrepreneurial Opportunity Discovery, Knowledge Creation, and Decision-Making

Abstract

The philosophy and methodology of Bayesian statistics bring with it a “style of reasoning” which may inform organizational researchers as they seek to conceptualize and model managerial decision-making processes. The style of reasoning of the Bayesian approach, in which posterior probabilities of the hypothesis are rigorously and continuously updated given new data, appears to closely model the researched observed decision behavior of a very important subset of managers: innovative entrepreneurs. That is, Bayesian reasoning may serve as a model of the cognitive processes undertaken by innovative entrepreneurs as they engage in knowledge creation through recombination of resources in response to new information from the environment (Schumpeter, 1934). Modeling disciplined intuitive implementation of Bayesian reasoning may assist researchers in building a cognitive theory of how and why innovative entrepreneurs are better at estimating the probabilities of success of newly recognized opportunities than the general public. Because innovative entrepreneurs are thought to play a very important role in the development of economic growth and productivity (Baumol, Sheshinski & Strom, 2007), a theory of their decision processes may assist organizational researchers devoted toward uncovering the here-to-fore poorly understood cognitive dynamics of the innovative entrepreneur, and may play a role in enhancing the efficacy of managerial decision behavior more generally.