Qualitative knowledge acquisition using fuzzy logic and system dynamics

Business models based on knowledge have increased the demand for tools to acquire and represent this intangible asset of organizations in computer-based systems. Qualitative knowledge is the knowledge contained in mental models, in the "back of our heads". The problem is how to acquire it when many of the times the owner is not even aware of it. The issue becomes challenging when the knowledge is about dynamics of complex systems, that is, how our social, fmancial, technological and ecological systems evolve through time. This research proposes a method to carry out qualitative knowledge acquisition of dynamics of continuos complex systems using Fuzzy Logic and System Dynamics. The method holds a different approach over existing methods by (1) joining both techniques and (2) using Fuzzy Logic as mapping function that transforms information into action, instead of a function for managing parameter valué uncertainty. The focus is toward the modeling of mental models of decision-makers and policy makers in a context of business administration. The technical issue is the knowledge acquisition when scarce or non-numerical data are available and only individual or collective mental models are the information sources. The method proposes the construction of a model comprised by two subsystems: a virtual decision-maker and a business process. The method is applied in a context of a hotel administration with the participation of a collaborative team of three persons. Simulation results are analyzed and discussed under principies of feedback dynamic systems to valídate the method.