| dc.description.abstract | Technology Transfer (TT) can be defined as the business resulting from the interaction between actors who agree to exchange ownership, knowledge, and value, benefiting from this transaction. Such businesses are influenced by different factors, such as the knowledge available about a specific technology, the cost versus expected gain ratio in the operation, the type of mechanism employed, and the negotiated technology itself. The combination of these factors characterizes a dynamic and multivariate description and forecasting context to be considered in the decision to establish TT agreements. Consequently, characterizing and understanding the actors, their interactions, and the mechanisms involved in the decision-making dynamics of negotiating technology can contribute to the analysis of the possible results of TT at different scales. However, a structuring and characterization of what is a TT negotiation process, able of allowing the decision maker to delineate in a generalized way different examples of this dynamics, still appears in the literature as an open problem. Even with more than three decades of research on TT models, attempts to model the process of transferring a technology do not always converge, and do little to explore the importance of this formalization of knowledge about its elements and interaction dynamics to compose decision-making scenarios. Thus, this research proposes the construction of an artifact, in the form of an ontology, a formal vocabulary that consolidates the knowledge of TT, which abstracts the complexity involved in the interaction dynamics among actors in this transaction. Using the methodology of Design Science Research (DSR), the ontology has its foundation in the perception of TT as a game and in the concepts of complex adaptive systems and strategic alliances. In this way, it provides the necessary construction elements to model the structure and behavior of the interaction between actors in TT scenarios, including in silico, helping to identify decision criteria, and emerging patterns resulting from the possible choices of a decision-making process involves it. The results show that considering a representation that adds knowledge about TT, in an organized way to abstract the dynamic involved in an interaction between actors to constitute this alliance, provides more favorable conditions to compose and evaluate scenarios to decision makers, with high potential for learning and support decision in contexts of uncertainty. | en |
