1. Jian Wang
Assistant Professor Science Based Business Program LIACS, Leiden University members/jian-wang Research Interests: Economics of science and innovation; strategic management; social networks; bibliometrics; patent analysis

2. Bachelor thesis topics
Translating science into innovation: An analysis of patent references to the scientific literature
Creativity, specialization, and diversification

3. Topic 1
Translating science into innovation: An analysis of patent references to the scientific literature

4. Translating science into innovation: Motivation
Science is an important source of societal and economic development, but we have limited understanding on the pathway from science to innovation.
Universities are expected to play a more active and direct role in stimulating industrial growth, but how?
One obstacle: lack of a large-scale database of knowledge flow from science to innovation.
Goal:
Develop a method to link publications to patents citing these publications.
Evaluate the validity of using this link to study knowledge flow from science to innovation.
Investigate features of science that is directly relevant for patented inventions.

5. Translating science into innovation: Available data
Georgia Institute of Technology Academic Scientists Survey (2010)
Sample: over 9000 US publications in the Web of Science database ( ), stratified by disciplines and citations
2327 completed responses (26% response rate)
Survey information on the project that produced the sampled publication
Technology transfer activities: patenting, licensing, start-up
Project characteristics
Team structure and member characteristics
Web of Science (WoS) bibliometric data
Impact: forward citations of the sampled publications
Novelty
Interdisciplinarity
Other basic publication features

6. Translating science into innovation: Additional data work
Develop a method to search the sampled publications in the US patent full text and check whether they are cited.
United States Patent and Trademark Office (USPTO) patent full texts are publically available at
Google patents
Reed Tech
A classification model
Features: matches in author name, paper title, journal title, volume/issue number, starting/ending page …

7. Translating science into innovation: Data analysis
Is patent citation to publications a good indicator of knowledge flow from science to innovation?
Compare patent citation data with survey information on technology transfer activities
What kinds of science is more likely to be cited by patents?
Explanatory variables:
Survey variables about project and team characteristics
Bibliometric variables such as publication impact, novelty, interdisciplinarity, etc.

8. Translating science into innovation: Expectations
Enthusiasm in technological innovation
Affinity with data mining
Develop method to link publications to patents
Basic statistical data analysis skills
Preferably some basic knowledge on applied economics and management science

9. Creativity, specialization, and diversification
Topic 2
Creativity, specialization, and diversification

10. Creativity, specialization, and diversification: Motivation
On the one hand, the stock of knowledge is growing at an ever faster rate. It is impossible for a researcher to be an expert on many subjects, and it is necessary to specialize in order to push forward the frontier of knowledge.
On the other hand, being a generalist is important for keeping a whole picture, and diversification is important for identifying missing connections and new perspectives.
Research question:
Which strategy is more beneficial for creativity: specialization or diversification?

11. Creativity, specialization, and diversification: Research question
Which strategy is more beneficial for creativity: specialization or diversification?
Furthermore:
Different levels of specialization/diversification:
A diverse team of specialists vs. a team of generalists
Different dimensions:
Methods, chemical, disease
Specialize in one disease but diversify in various chemicals is a better strategy than specialize in one disease and one chemical?

12. Creativity, specialization, and diversification: Available data
PubMed
Database of biomedical publications
Medical subject headings (MeSH)
Expert-controlled keywords of the publication
Author-ity
Disambiguated author names for PubMed
Web of Science
Linked to PubMed
Additional information
E.g., Citations across all scientific fields

13. Creativity, specialization, and diversification: Additional data work
Classify medical subject headings (MeSH)
Method
Chemical
Disease
Construct specialization/diversification variables based on MeSH terms
Different levels
Different dimensions

14. Creativity, specialization, and diversification: Data analysis
Publication level
Unit of analysis
publication
Explained variable
Forward citations …
Explanatory variable
Team specialization
Member specialization
Individual level
Unit of analysis
Individual scientist
Explained variable
Forward citations …
Explanatory variable
Individual specialization
Coauthor profile

15. Creativity, specialization, and diversification: Expectations
Enthusiasm in economics/organization of science, creativity, …
Affinity with data processing
Classify MeSH terms into different categories
Relational database
Basic statistical data analysis skills
Preferably some basic knowledge on applied economics, organization theory, social networks, …