This chapter analyzes the efforts and policies implemented in Brazil to support innovation and facilitate interaction among universities, researchers, research organizations, and companies based on a review of literature and legislation on university–industry relations in Brazil; data on IP and related indicators in official Brazilian government reports; information gathered through questionnaires sent to eighteen Brazilian universities and research institutes; and in-depth interviews with four selected Brazilian knowledge transfer offices. The chapter reviews the key literature on knowledge transfer in Brazil and provides an overview of the role of public research organizations in the Brazilian innovation system as well as the new policies introduced to reinforce its scientific and innovative capacity. It also analyzes the institutional practices as well as the main channels for knowledge transfer in Brazil. The chapter concludes that while the major universities and research institutes in Brazil now have a knowledge transfer office to support knowledge transfer to the business sector and the Brazilian legislation has improved its management of intellectual property rights, excessive bureaucracy, limited patent licensing to companies, and lack of competition among Brazilian companies are a few reasons why university–industry interaction is not stronger in Brazil.

This chapter looks at successful knowledge transfer of products or processes from public research organizations to private sector firms for commercialization. Through six national case studies (Germany, the Republic of Korea, and the UK for high-income countries, and Brazil, China, and South Africa for middle-income countries), contextual conditions that influence success are discussed. Over time, the conceptual model behind policies to support knowledge transfer has shifted from a mode 1 linear pipeline model to a mode 3 model. In the linear model, basic research conducted by universities is followed by applied research, either by public research organizations or firms. In a mode 3 model, multiple actors – such as different types of public research organization, knowledge intermediaries such as knowledge transfer offices, and private businesses – are involved in an innovation system; there is a reverse knowledge flow whereby firms provide public research scientists with information on their needs, which influences the research projects of public research scientists. Best practice includes policy support for research and development and other innovation-related activities and incentives for firms to work closely with public sector researchers for problem solving and commercialization.

This chapter analyzes the structures and processes in place for knowledge transfer from publicly financed research in Germany. The chapter discusses the common channels of knowledge transfer from universities and public research institutes in Germany and the policies implemented to enhance the transfer. The chapter also discusses changes in the German knowledge transfer system and their impact, such as the abolition of professor’s privilege, the introduction of patent valorization agencies, and other major funding schemes. The chapter reviews scholarly literature relating to knowledge transfer in Germany and research findings from interviews with selected university knowledge transfer offices and policymakers. The chapter also presents results from a survey sent to all knowledge transfer offices at German universities. It concludes that while efforts have been made to foster systematic knowledge transfer from science to industry in the past decade in Germany, universities and public research institutes need to deepen the understanding of intellectual property and business-relevant research and applications within their institutes and to further improve knowledge transfer between their researchers and industry.

The main aim of this research is to explore the progress of the knowledge transfer system in the Republic of Korea and assess how much of this generated knowledge had been successfully commercialized. The chapter reviews policy changes since 2000 that were implemented to improve knowledge transfer from public research institutes. It identifies the important knowledge transfer channels in the Republic of Korea and reviews the challenges that government policy and public research institutes face in achieving successful knowledge transfer. The chapter concludes that for the national innovation system in the Republic of Korea to change from the old catch-up mode characterized by the twin dominance of big businesses and the government, the Korean system would need to support demand-oriented research, provide monetary incentives for researchers in terms of license income, place more weight on knowledge transfer performance in performance evaluation of researchers, and recruit high-quality personnel for knowledge transfer offices.

Commercialization of public research to support economic growth involves the transfer of knowledge produced by public research organizations to private sector businesses or government agencies. This chapter describes the diverse range of national and institutional policies and practices implemented across countries to encourage knowledge transfer between public research organizations and firms. The chapter largely focuses on the IP licensing model, highlighting its advantages and disadvantages, and discusses how the costs of IP-mediated knowledge transfer can be minimized. It outlines the main reasons for collecting knowledge transfer metrics for licensing – for benchmarking, for identifying factors that support or hinder knowledge transfer, and for informing policy. The chapter also identifies the most commonly used methods for collecting knowledge transfer metrics, and discusses basic metrics that all countries should collect on the IP licensing model, plus supplementary metrics of relevance to specific policy issues.

Several policies and practices are involved in the successful transfer of knowledge from public research organizations to private sector firms for commercialization. To evaluate the effectiveness of these policies, metrics are used for benchmarking changes in performance over time. Most of the existing metrics focus on IP-mediated knowledge transfer, such as the number of patents produced by universities and the amount of license income earned. Thus, non-IP-mediated knowledge transfer gets viewed as unimportant and of low value. This chapter identifies data for measuring non-IP-mediated methods and recommends collecting metrics for other formal (collaboration, contracts, consultancy, etc.) and informal (from surveys of academics and firms) channels of knowledge transfer.