EVALUATING THE PERFORMANCE OF TECHNOLOGY TRANSFER OFFICES: A FUZZY COGNITIVE MAPS APPROACH
, F. Galati2
, G. Marolla2
, C. Verbano3
1University of Parma, Department of Industrial Engineering (ITALY)
2San Marino State University (RSM), Department of Economy and Technology (SAN MARINO)
3University of Padova (ITALY)
In today’s competitive market organizations recognize the need to acquire new technologies and knowledge from the external environment in order to compete and survive, as well as to exchange technologies, experience and knowledge they have developed in order to access new markets and revenue streams. In other words, companies recognize the importance of the “technology transfer” (henceforth, TT) process. As for a supply chain, where three main actors may be identified (i.e., a supplier, a manufacturer, and a customer), similarly for a TT process it is possible to identify the fundamental role of three “actors”: the role of the supplier is covered by a University, the source of knowledge and technologies or by a company with institutional R&D activity. In the first case to be effective, the knowledge and technologies developed by a University have to be transferred, by means of different potential channels, to the final customer, that in a TT process is represented by a firm. The central actor of the “TT supply chain” is represented by the technology transfer office (TTO), that is a formal mechanisms that, on the one hand, allows the transfer of knowledge and technology and, on the other hand, protects and licences the intellectual property.
Based on the assumption that technology transfer plays an important role for the growth of a company, of the industry it operates within, and for the economic development of a nation as a whole, the aim of our research is to assess the performance of a TTO. The research methodology followed was a combination of literature analysis, Delphi technique and case study-based research. Specifically, it was developed on four main steps: (i) as first, an in depth literature review, aiming at investigate the extant literature on the matter of TT and of TTOs’ performance in particular, was performed. Based on the results of this step, and specifically on the TTOs main characteristics and performance indicators identified, a panel of experts was set up to validate the indicators proposed, thus reaching a final model to assess a TTO performance. In the following step (iii) we adopted a case-study based research to test our model, and specifically we investigated in depth a TTO of an Italian University. (iv) Data gathered from the interviews have been than analysed in the final step by means of fuzzy cognitive maps.