The following four research projects were awarded funding in 2019.
The purpose of this project is to collect data on patents that were used as collateral in loan negotiations in four countries (Sweden, the Netherlands, Belgium and Luxembourg) where it is mandatory to report to the local patent authority if intellectual property rights have been pledged. In addition, it is proposed to conduct an economic analysis of pledged patents in order to shed some light on 1. how frequently are patents used as collateral, 2. which patents are used as collateral, 3. which type of firms pledge patents, 4. whether we can use pledged patents to estimate their value through firms’ debt levels, and 5. whether patent–pledging is effective in mitigating financing constraints of corresponding firms significantly.
Lead applicant |
University |
Thematic area |
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Dirk Czarnitzki |
KU Leuven, BE |
The role of patents in technology transfer, commercialisation, and/or investment decisions |
The aim of this project is to link patent to trademark data by mapping patent classes (IPC codes) to trademark classes (Nice codes and the keywords in the detailed goods and services descriptors). The main scientific objective of this project is threefold: 1. to develop a concordance map between patent and trademark classes, 2. to validate it extensively using complementary data sources and alternative techniques, and 3. to illustrate its use for cleantech patents. By focusing on classification systems, we aim at capturing the qualities of technological and market specialisation patterns. In this respect, the envisioned concordance map would allow to tackle three types of research questions.
Lead applicant |
University |
Thematic area |
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Carolina Castaldi |
Utrecht University, NL |
Advanced use of PATSTAT, patent searching, and analytics (e.g. classification, potential of IP linked open data |
The project’s primary goal is to assess and forecast the commercial value of SMEs’ patents measuring the proximity between their portfolio and their business model. With the use of artificial intelligence methodologies, the project aims to: 1. identify the closeness of firms’ business model developments from their technological footprint (patents) 2. predict the success likelihood of a specific business model applied to a given patent and 3. suggest alternative business models more in line with the patent portfolio characteristics. The project relies on original and relatively rare data regarding company business models disclosed directly by SMEs extracted from funding applications, submitted during the period 2014 to 2019, to the Horizon 2020 SME Instrument (SMEi) programme.
Lead applicant |
University |
Thematic area |
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Alberto Di Minin |
Sant'Anna School of Advanced Studies, IT |
The role of patents in technology transfer, commercialisation, and/or investment decisions |
The project aims to analyse international collaborations in science and inventive activity and investigate how the landscape of knowledge production in Europe has changed over the past 25 years. The aim is to analyse to what extent collaborations in science and collaborations in patents are related at regional level. These collaborations can be set up by researchers, universities and firms, and governments fund such collaborative initiatives (e.g., EU’s Framework Programmes). Thus, both academics and policymakers will benefit from knowing the impact of collaborations in research and patents. The project has four research questions: 1. do patent and research networks in Europe have similar dynamics?, 2. do patents have any impact on the formation and evolution of research networks?, 3. do the innovation performances of regions affect the formation and evolution of research networks?, and 4. do the innovation performances of regions affect the formation and evolution of patent networks?
Lead applicant |
University |
Thematic area |
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Semih Akçomak |
Middle East Technical University, TR |
Measuring the impact of patents on innovation |
The following four research projects were awarded funding in 2020.
The project will create a public database linking patents to scientific publications, using a high-performing text mining method to extract patent in-text references. As a result, it will make it possible for researchers to analyse the impact of scientific research on industry innovation.
Lead applicant |
University |
Thematic area |
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Jian Wang |
Leiden University, NL |
Advanced use of PATSTAT, patent searching, and analytics (e.g. classification, potential of IP linked open data |
Using a unique dataset of grant applications to the Research Council of Norway across all academic fields, the project will track patented innovation linked to the research grants, and derive implications on how the design of research funding can be improved to increase its impact on innovation.
Lead applicant |
University |
Thematic area |
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Marco Ottaviani |
Bocconi University, IT |
Role of IP in investment activities; Patents and the IP bundle; Advanced use of PATSTAT, patent searching, and analytics |
The project will combine the analysis of patent data, legal documents and case studies to shed light on how distributed manufacturing in the EPC area interacts with the patent system in practice, how patents might be optimised to enable distributed manufacturing, and how the distributed manufacturing sector may best make use of patenting options available to it.
Lead applicant |
University |
Thematic area |
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Angela Daly |
University of Strathclyde, UK |
Patents and disruptive technologies (AI, blockchain, 3D, etc.) |
Using a novel dataset linking declared-SEPs to different sources of government contribution, this project will assess the importance of government-sponsored research for SEPs and its impact on the development of technical standards.
Lead applicant |
University |
Thematic area |
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Emilio Raiteri |
Eindhoven University, NL |
Role of IP in technology transfer, commercialisation, and/or investment activities |