Empirical modeling (EM) has been a useful approach for the analysis of different problems across a number of areas/fields of knowledge. As is known, this type of modeling is particularly helpful when parametric models due to a number of reasons cannot be constructed. Based on different methodologies and approaches (e.g., Least Squares Method, LSM), EM allows the analyst to obtain an initial understanding of the relationships that exists among the different variables that belong to a particular system or a process.
Part of the book: Empirical Modeling and Its Applications
Very few papers in the operations management (OM) field have taken the themes of universal-deterministic (UD) and probabilistic hypotheses as their main topics of investigation and discussion. Our investigation continues a recent line of research that focuses on a better understanding of these critical issues. Specifically, we attempt to respond to some pointed criticisms that experts in the field have made when the topic UD and probabilistic hypotheses have emerged in academic settings/discussions. A detailed analysis of those criticisms shows that they lack merit, thereby reinforcing our argument that it is most important to distinguish between the two types of scientific hypotheses in order to advance in the rigor of OM theoretical and empirical research. Ideas for future research are outlined.
Part of the book: Operations Management and Management Science