Knowledge Diffusion Paths in a Research Chain

Abstract

Knowledge impacts all human actions and is responsible for survive and development of human race. Knowledge is both cause and solution for human’s changes in the environment and the technological development. It is transmitted by a nested complex net, with nested relations closely related to human knowledge generation. Analysis and solutions of how knowledge is generated and permeates into a research chain needs innovation, mainly in the context of comprehension of knowledge generation, knowledge diffusion and knowledge transferring processes. In this work we deal with the behavior of knowledge diffusion processes in a research chain, in the sense of the influence of preferential paths of knowledge diffusion among the chain net. A knowledge chain is adopted as the environment in which a research group deals and is affected by those phenomena. We present a model, developed from the continuum formulation, which established a partial difference system of equations that guide the problem, to the discrete formulation. This approach allows a numerical study, in finite elements, of knowledge generation and diffusion, together with the consideration of those paths inside the research chain. It is identified with the knowledge preferential connections and transfer like process as result of researches leaders’ efforts, result of human resources formation and knowledge transferring to the others researches of the chain. Accumulation and feedback of knowledge as also as the paths of knowledge transfer are considered. Some numeric experiments are given, related to scientific knowledge generation data, as also with the changes in diffusion coefficients, generation behavior, and knowledge inductance. The model considers a transient two dimension domain as the researches chain of knowledge. Results behavior denotes the influence of the connection and the preferential diffusion paths. We consider that this approach could be, also, a step to develop a computational model concerning to the evaluation of innovation impact in human society.