“Assumed as the universities third mission, the transfer of knowledge allowed to complete its functions, which already used to include teaching and research missions” (Ribeiro & Ruão, 2015, p. 43).

Knowledge transfer is a process through which the technical-scientific know-how is continuously transmitted to the stakeholders involved. That is, the transfer of knowledge is a special form of communication and interconnection in which the message conveyed is associated with a new technical or scientific knowledge.

This process is always initiated by a core activity for the entities in the primary sector of the transfer, usually universities, Technology Surveillance, or Intelligence. The Intelligence process has been increasingly implemented over the last decade in the world’s leading companies (Google, T-Mobile, Apple, Inditex, etc.) and it is a fundamental process for the creation of innovation and competitiveness. This situation is not currently implemented in the national business fabric in a wide scale, due to the fact that it is dominated by SMEs and their investments, which are centralized in material goods that are essentially productive.

The process of transferring scientific and technological knowledge, often carried out directly between technological centers and business entities, has presented, in recent years, some shortcomings both in its implementation and in its effectiveness.
A critical success factor in the knowledge transfer is the technical-scientific knowledge itself. The process of transferring scientific and technological knowledge, often carried out directly between technological centers and business entities, has presented, in recent years, some shortcomings both in its implementation and in its effectiveness. One of the differentiating aspects in the performance of knowledge transfer platforms, inserted in university contexts, is the introduction in the value chain of processes of scientific knowledge generation and valorization of scientific knowledge, that allow for the dissemination of greater know-how and the generation of higher value added products.

By introducing the innovation in the scientific knowledge generated within universities and responding with it through the transfer platforms to the opportunities identified, it will thus be possible to differentiate and optimize the process of transfer of scientific and technological knowledge, making it sustainable in a long-term. The introduction of scientific knowledge into the value chain of current knowledge transfer processes is not yet a reality and can be pointed out as one of the current gaps in this process. Thus, if on the one hand, the knowledge-generating entities, mainly universities, do not have a strong connection to the business environment, and on the other, the technological entities in the are do not have the skills to generate technical-scientific knowledge, the sustainability of the knowledge transfer process will be compromised.

The effectiveness of the role of a Knowledge Transfer Platform and its link with its stakeholdings is dependent on 5 distinguishing characteristics in its performance
The cooperative work in network, coordinated by a platform of transfer of scientific and technological knowledge, then appears as the most adequate alternative. The involvement of the entire value chain, and the creation of interactive networks among different sectors of activity fostered by cooperative network work, is also a differentiating factor.

The effectiveness of the role of a Knowledge Transfer Platform and its link with its stakeholdings is dependent on 5 distinguishing characteristics in its performance:

relative advantage
compatibility
complexity
testability
observability
Having a relative advantage is related to the fact that knowledge has a benefit when compared to other existing products. Within this attribute it is important to highlight the importance that the cost entails, as well as the design and engineering. As far as compatibility is concerned, the more distinct is the knowledge when compared to the already socially accepted and instituted, the more difficult and slow is its diffusion power. The complexity is associated with the idea that the less complex, i.e. the easier to understand, the faster is the diffusion as well as the fact of being testable, which allows conferring credibility to knowledge, thus contributing for a better diffusion. Finally, with regard to observability, it is preponderant that stakeholders can concretely verify the results of the innovation.