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Commercialization of research projects at the university, in particular, its efficiency and performance, have attracted little attention in the empirical literature to date. This despite the fact that commercialization of university knowledge is increasingly seen as a third task of universities and understanding of what enhances and what blocks the processes involved, is virtually lacking, particularly on the project level. The purpose of this chapter is therefore to identify factors that influence the performance of university-driven knowledge projects, including efficiency, in the context of commercialization of knowledge at universities. In this context, the study employs Data Envelop Analysis combined with Rough-Set Analysis on a sample of 42 projects in the Netherlands. The major factors influencing overall performance in commercialization turn out to be years of collaboration with large firms and efficiency in use of resources in the projects, but the affinity of the project managers at university with the market also plays a role. The best overall results in commercialization (introduction to market in a relatively short time) are gained with a longer period of collaboration with large firms (5–10 years) and a medium level of efficiency. There are also some contradictory trends. The chapter concludes with implications of the results, as well as some future research paths.

Over the years, the above advantages have gained wide recognition in such a way that fostering spin-offs has become part of most universities’ and research centers’ policy. Among the many ways of accelerating the growth of USOs, perhaps the most captivating one is establishing incubator organizations. The networks of incubators have been built gradually in industrialized regions such as the United States and in Western Europe over the past two decades and now have reached maturity (Lalkaka, 2003). The first generation of incubators in the 1980s essentially only offered affordable office facilities to potential new ventures, including shared services, and soft loans. As time progressed, it was realized that the needs of spin-offs included more than just physical and financial support. This situation has challenged some incubators to change into providers of “added-value support,” such as business skills training and connecting the entrepreneurs to various networks.

The commercialization of research produced by universities constitutes a core facet of academic entrepreneurship (AE). Academic literature reveals the need to shed light on entrepreneurial processes in higher education institutions (HEIs). This study intends to fill this gap by researching the mechanisms for facilitating AE and the variables that can moderate the relationship between such mechanisms and AE in Portuguese HEIs.

Our research model aims to assess the mechanisms of academic entrepreneurship (AE) within a sample of 125 Portuguese public higher education institutions (HEIs). To test our research hypotheses, we employed a structural equation model (SEM) using the partial least squares (PLS) method. Additionally, our evaluation examines the potential moderating effects of incubator programs, support initiatives, and proof-of-concept programs (PoCs). Our research model seeks to evaluate the mechanisms for facilitating AE and explore the effects of including incubator programs, support initiatives, and PoCs as moderators. The seven variables (Research mobilization, Unconventionality, Industry collaboration, University policies, Incubator programs and support initiatives, Proof-of-concept programs, and academic entrepreneurship) were measured using a 7-point Likert scale.

The results revealed that different drivers of AE influence the creation and development of entrepreneurial activities. Our findings also show the moderating effects of incubator programs, support initiatives, and proof-of-concept programs on AE. We find that incubator programs, other support initiatives, and PoCs maintain a moderating effect on AE and benefit their respective HEIs.

The study examines only the Portuguese HEI context. Therefore, generalizing these results necessitates reservations. However, the responses came from various actors in HEIs, from different academic backgrounds and research interests. This makes the results more generalizable. Limitations are evident in external validity, given that we gathered the data over a relatively short period.

Observed factors are explored to gain a deeper understanding of their influence on the mechanisms of AE. The implications arise from the new perspective presented and the methodology used to identify mechanisms capable of fostering AE. We hope this research will encourage other researchers to study this topic further.

the engagement of universities at the global level should be emphasised in future policy. While universities in innovation systems often have a local focus, their engagement in innovation ecosystems transcends the boundaries of geographic locations.

PoCs had a significant positive moderating effect on the impact of research mobilization and university policies on AE. Thus, we find interactions between universities and industry boost AE. This study demonstrates how AE benefits HEIs by extending orientation towards mobilizing research, unconventional approaches, cooperation with industry, and university policy implementation. We thus advocate a new approach, demonstrating the influence that the mobility of research, unconventionality, industry collaboration, and university policies hold over AE.

This paper aims to analyse the key trends in oil delivery and production and evaluate the capacities of crude oil transportation systems in the Western European region.

To meet these goals, qualitative data analysis was used to assess the contribution of countries in the region to the total crude oil production and delivery, the changes in concentration of crude oil deliveries and refineries’ capacities, the capabilities of the regional crude oil transportation system and the trends in crude oil supplies and processing from 2005 to 2015.

The study established that from 2013 to 2015 oil supply to the region’s refineries increased and generated additional stress on the transportation and refining infrastructure.

This study examined the aggregate values of crude oil production, crude oil deliveries and refining capacities. In practice, different refineries are set to process certain types of crude oil. It is possible to use the described approach with a certain crude oil grade.

When developing the programmes for crude oil supply to refineries, it is vital to take into account the capacities of refineries and the capabilities of the crude oil transportation systems.

The study suggests that the region’s infrastructure has the necessary reserves to operate for the next few years without additional investments.