Completed research projects

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.

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.

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.

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?

The development of interoperability standards such as WiFi or 5G in information and communication technologies typically requires massive investments in R&D. It therefore generates large portfolios of related patents, part of which are standard-essential patents (SEPs) that are by definition infringed whenever the respective standard is implemented. This research project develops a novel method based on semantic data analysis to detect such standard essential patents. It provides valuable insights into the patent landscape around major ICT standard while enhancing transparency for the licensing of SEPs.

The project capitalises on Linked Open Data to build bridges between patent data and information on scientific knowledge, scientists and organisations. As main outputs the IP LodB project produced an intellectual property rights linked open data (LOD) map (IP LodB Map), tested the linkability of the EPO’s patent LOD database with Springer Nature, and constructed a new IPLOD database/dataset that has been made available for use by the research community.

Building upon the evolutionary concept of technological trajectories and computational tools to identify such trajectories, the project maps the entire contents of EPO patent citations in the PatStat database. The findings focus in particular on green technologies. They show that progress in such technologies is strongly intertwined with developments in non-green technologies and shall be understood as such by policy makers.

This project investigates how the emergence of 4IR-related technologies is modifying the positions of incumbents and new entrants in the automotive industry. For this purpose, it maps and analyses the evolution of the industry’s knowledge base by reconstructing the portfolio of patent families of the top 25 automotive manufacturers and the top 100 automotive suppliers over a 25-year period of analysis (1990-2014). 4IR technologies show a substantial patenting growth in the sector, especially after 2010. The 4IR knowledge base also differs from other established automotive technologies along several dimensions, including the way actors organise their 4IR knowledge sourcing and the patent filing strategies used to protect 4IR inventions.

This project studies the interplay between universities and firms located in the same European regions. A first line of research analyses the evolution of the technological trajectories of universities and co-localised firms. By linking evolution patterns to the overall innovation performance of the regions, it provides useful insights for smart specialisation policies in European regions. A second line of research analyses the impact of 3 697 scientific research grants awarded by the European Research Council (ERC) on the subsequent patents induced by the grant programs, thereby documenting the ability of the scheme to generate market-relevant inventions.

Innovation in one nation benefits others as it diffuses. While there is strong evidence linking the adoption of foreign innovations to international trade, there is as yet no evidence on how trade generates links to foreign innovations which promote new local innovations. To bridge this knowledge gap we used a proprietary dataset linking trade in products to technology classes, providing a state-of-the-art measure of the innovation content of trade. Furthermore, we examined how this knowledge content and thus the encouragement of new innovations are impacted by intellectual property rights driven trade policies such as the WTO's TRIPS agreement.

This research project establishes a link between financial constraints and corporate innovation in 15 European countries by analysing the impact of exogenous shocks on firms’ lending channels for their innovative activities. In order to infer causal relationships, the process of European financial integration in the early 2000s has been exploited as a quasi-natural experimental setup. The analysis used direct, quality-related measures of innovation based on patent information to assess the impact of financial constraints on innovative efficiency.

The scientific evidence for human induced climate change and environmental degradation is unequivocal. Accelerating the development of climate change mitigation technologies (CCMTs) is a key challenge to temper the costs associated with climate change and air pollution. This project investigated the impact of environmental policies on innovation activities in general, and CCMTs in particular. The methodology used original data at the regional level on environmental measures implemented to decrease air pollution in the European Union and data on patents relating to CCMT (and non-CCMT). A quasi diff-in-diff setting and an instrumental variable approach have been used to identify the influence of a stricter environmental policy on different patterns of innovation activity.

Patent attorneys have played an important role within the patent system for decades, but their role in sharing knowledge e.g. as they change jobs and interact with others has not previously been investigated in any detail. A comprehensive and current dataset about the activities and mobility of the patent attorneys has been missing. Based on preliminary work in the IP industry the project enabled the creation of a dataset of the career paths of all patent attorneys who have served as representatives before the EPO in the last ten years. This dataset, the EPAC, will be regularly updated and published as open data. It can be applied to identified career patterns of patent attorneys having a positive effect on the individual and firm success.

This project has used data science tools to build a database that tracks innovations into the marketplace. Specifically, new software has been developed to harvest data on products from the web, which could be directly traced to identifiable European patents. These data can be employed to advance our understanding of patent valuation and the patent prosecution process.

This research project aims at the large-scale categorisation of ‘technological fields’ to distinguish between process inventions and product inventions. Text searching methods have been applied to validate the resulting classifications, which will be made publicly available. The patent records have been coded to enable the identification and analysis of technological life-cycles following the introduction of product and process inventions. A second, analytical part of the project characterises different forms of spillovers related to products and processes and analyses their impacts on: i) innovation performance; ii) research or productivity; and iii) entry/exit in technological fields.