On decision processes in businesses, companies and organizations computed through a generative approach: The case of the agent-based modeling

In recent years, such organizations as businesses, companies and firms have improved their abilities to carry out their own research. Indeed, they have become able to improve their predictions thanks to new management techniques and to the development of technological instruments capable of capturing and analyzing large volumes of data. In a system where organizational variables are becoming more and more controlled but where the main actor – the human being – still remains the most important unknown factor, such business and social sciences as management, economics and psychology have tried to better identify how human habits and decision-making processes are connected. In fact, humans’ behavior has been studied through the development of decision science. In particular, two approaches have been used in order to study and model the way people make decisions. They are the Normative Approach and the Descriptive Approach. The Normative Approach is based on the analysis of decisions related to simple rules and norms used by a hypothetical human being that makes decisions. The Descriptive Approach examines individual decisions in the context of a set of needs, preferences, beliefs and values that an actual individual has. However, even a perfect knowledge of individual decision-making rules does not guarantee the possibility of predicting the macroscopic structure of human behavior. This possibility has been lately explored by starting from some solid scientific studies on individual behavior and by using advanced computing techniques capable of “growing up" phenomena at a macro level. This method, called Generative, has proven to be powerful. The generative method consists of generating and growing a phenomenon for explaining it. In recent years, computer simulations of social phenomena have produced a new scientific paradigm corresponding to the science that generates events that would be impossible to be recreated or to be observed. This approach has given excellent results in terms of simulations enabling the study of effects of decisions and helping to make good organizational decisions.