| The social and organizational sciences do not have the variety of quantitative tools used in the physical sciences, and the shortage of these tools makes it difficult to model and predict the behavior of complex organizations. Despite the difficulties, the potential benefits of a computer-based model used for quantifying the study of complex entities such as organizations and evaluating related organizational theories are significant. Specifically, this research used cellular automata to model part of the organizational theory of Chester Barnard, to determine if a disciplined, rule-based model could be developed. Barnard's (1938) theories were selected because they provide a wide-ranging view of organizations, establish well-bounded rules, and lend themselves to automata.; Beyond the development of the resulting model, facts from two case studies, Apple Computer and Continental Airlines, were used as input to the model to determine if the model output would match the actual events in the case study. The comparison of the model outputs to actual results of the case studies was very encouraging. The model behaved as expected, predicting some of the already-known results from the case studies. These results demonstrate that this type of modeling may provide quantitative support to social science or organizational science researchers, educators, students, and corporate analysts.; The emerging social challenges in the twenty-first century---corporate meltdowns, out-of-control drug use, increasing poverty, unmanageable governmental spending, and the threat of terrorism, to name a few---all have one thing in common: they involve the conduct of many types of organizations. A rule-based model, which could predict with any accuracy the behavior of such complex entities as organizations, could possibly be very useful in a variety of important ways---from helping to analyze failing corporate entities to predicting the behavior of terrorist organizations. |
