On the utility of the stochastic processes in modeling the nexus between entrepreneurship and innovation: a nonparametric application of Bayesian inference

The application of stochastic processes in modeling uncertain phenomena will benefit researchers in the fields of various sciences like management, engineering, chemistry, physics, and business. The present article tries to apply several stochastic processes to modeling the relationship between entrepreneurial innovation and entrepreneurship. The Chinese restaurant process (CRP) and the Blackwell-MacQueen scheme are the processes that will be utilized to explore a predictive model. By presenting illustrative evidence, the CRP and the Blackwell-MacQueen scheme have helped us to understand how the Schumpeterian approach goes true. The study on the proposed equation demonstrated that the considered model also may signify levels of the decision in interpreting the nexus between innovation and entrepreneurship. Hence, a new function, arbitrary called “decision function,” was discovered and introduced in this study. After having reviewed the properties of the decision function, the relationship between entrepreneurship and entrepreneurial innovation (and also economic growth in its wake) was studied and interpreted. Regardless of mathematical models resulted from applying stochastic processes in investigating the relationship between entrepreneurship and innovation factors, the present paper reveals the importance of statistical models and stochastic processes in understanding the unmeasurable networks formed out of various factors.