European knowledge transfer reflected by research collaboration and patent citations indicators

Knowledge transfer consists of activities that aim to capture and transmit
knowledge, skills and competence from those who generate them to those who will
transform them into socio-economic outcomes. In the context of the March 2000 Lisbon
strategy and its aim to make the European Union the “world's most dynamic and
competitive knowledge economy”, knowledge transfer is considered to play an important
role in helping to overcome obstacles such as a weak environment to stimulate high
quality research and exploit research results. The introduction of new funding schemes
and policies aimed at increasing knowledge flow between countries and sectors in Europe
has increased the demand for studies of the impact of such policies and funding
mechanisms and the development of relevant and accurate indicators related to them. The
aim of this thesis was to study the dynamics of knowledge transfer in Europe and to
examine how knowledge transfer can be measured and analysed through different
indicators. This was done by studying co-authorships and collaborations within Europe as
indicators of geographical knowledge transfer and patent citations as an indicator of
sectoral knowledge flow.
The results showed that researchers from smaller countries co-authored more with
other EU countries than those from bigger countries, while the co-authorship rate with
extra-EU partners was not dependent on a country’s size. Co-authorship patterns were also
found to depend on the scientific field. The analysis also indicated that multilateral
collaborations funded through the EU Framework Programmes are more exclusively
European in nature. In contrast, co-publication patterns in multilateral collaborations
suggested that European researchers tend to co-author more with global, rather than
exclusively European partners and that this global multilateral orientation in copublications
continues to rise.
When using co-publications as an indicator for geographical knowledge flow, the
results demonstrated that European research policy most likely has had an impact on
research collaboration patterns. However, the results also strongly suggested that any direct
impact was limited and did not over-ride self-selected collaboration patterns that continue
to drive a more global, rather than exclusively European, research collaboration orientation.
A more disaggregated scrutiny of publication patterns also underscored very clearly that
collaboration strategies show considerable diversity across scientific fields, as well as
countries. Further, the results suggest that some policies, to support innovation in regions
with a low absorptive capacity (weak innovation activities and a low tech profile) e.g.
supporting regional R&D through subsidies, may be less successful than the incorporation
of qualified personnel at firms or the increase of local university-industry links.
The thesis also made several contributions to the discussion of research
methods in this field by investigating the utility of some central indicators and approaches.
The results showed that the corresponding author is most likely to appear first and
thereafter most-likely to appear last in the byline. However, the analysis also indicated that
these results are dependent on the number of authors in a paper and that national
differences also exist, thus arguing for a fine-tuning of bibliometric tools, in order to more
effectively capture the relative importance of author contributions. Similarly, the analysis
examined the use of patent citations as an indicator for science-industry links and
geographical localization at a regional level. It found that there are reasons to question the
use of this indicator, specifically in a region with low absorptive capacity. The related
results also highlighted that there is a need to differentiate between applicant and examiner
citations when examining the knowledge base since examiners and applicants add different
types of knowledge