Hélène Dernis

Triadic Patent Families Methodology

Patent indicators – within the science and technology (S&T) context – are used to measure inventive performance, diffusion of knowledge and internationalisation of innovative activities – across countries, firms, industries, technology areas, etc. A common approach is to calculate patent indicators based on information (filings, grants, etc.) from a particular patent office. While the richness and strength of those indicators are broadly recognised, they are affected by “home” advantage bias – where proportionate to their inventive activity, domestic applicants tend to file more patents in their home country compared to foreign applicants.Patents taken in various countries to protect inventions can be linked together to build triadic patent families: a set of patents taken at the European Patent Office (EPO), the Japanese Patent Office (JPO), and the US Patent and Trademark Office (USPTO) that share one or more priorities. Patent families are derived from priority application ... Methodologie relative aux familles triadiques de brevets Les indicateurs sur les brevets sont utilises, dans le cadre de la science et de la technologie (S-T), pour mesurer les performances de l’innovation, la diffusion du savoir et la mondialisation des activites innovantes dans les pays, les entreprises, les industries ou les domaines technologiques. Une technique frequemment utilisee pour leur comptage consiste a s’appuyer sur les informations (nombres de demandes, de delivrances, etc.) d’un office de brevets specifique. Si la richesse et l’importance de ces indicateurs sont largement reconnues, leur fiabilite n’en est pas moins soumise a des biais lies a l’avantage national : proportionnellement a leurs activites de decouverte, les demandeurs nationaux deposent generalement davantage de brevets dans leur pays d’origine que les demandeurs etrangers.Les brevets deposes dans divers pays pour proteger des inventions peuvent etre regroupes en familles triadiques de brevets : un groupe de brevets deposes aupres de l’Office europeen des ...

Nanotechnology: An Overview Based on Indicators and Statistics

Nanotechnology is commonly considered to offer considerable promise extending from business opportunities throughout various industries to broader socio-economic benefits, especially in the context of pressing global challenges such as those related to energy, health care, clean water and climate change. Governments around the world have invested heavily in R&D in this field and companies are also becoming increasingly engaged. Despite this promise, investments and company involvement in nanotechnology developments are still poorly monitored. The objective of this report is to provide a comprehensive overview of these developments through a systematic and critical analysis of available indicators and statistics, while acknowledging that there is a need for further work to both broaden the range of, and develop further, nanotechnology metrics. Panorama de la nanotechnologie : Indicateurs et statistiques On s’accorde generalement a reconnaitre que la nanotechnologie est extremement prometteuse en raison non seulement de ses possibles debouches commerciaux dans tout un eventail de branches mais aussi de ses retombees socio-economiques plus generales, face notamment a l’urgence des enjeux mondiaux concernant par exemple l’energie, les soins de sante, l’eau potable et le changement climatique. Des Gouvernements du monde entier ont fortement investi dans la R-D dans ce domaine, dans lequel les entreprises s’engagent egalement de plus en plus. Malgre ces promesses, les investissements et les participations des entreprises dans les developpements de la nanotechnologie sont encore mal mesures. L’objet de ce rapport est de brosser un panorama detaille de ces developpements a travers une analyse systematique et critique des indicateurs et statistiques disponibles, etant entendu que les travaux doivent etre poursuivis pour a la fois elargir et affiner le champ de l’appareil statistique sur la nanotechnologie.

Analysing European and International Patent Citations

This paper presents a preliminary set of European and international citation data tables designed to enable researchers to become familiar with the subject and undertake a range of analyses. It addresses analytical and statistical issues such as why citations from international searches and European searches should be combined; the calculation of citation lags; use of International Patent Classification (IPC) codes for grouping patents according to technology; treatment of references to Non-Patent Literature (NPL); and the notion that many publications, from different patenting authorities, covering the same invention can be cited. Differences between US and European citations are also discussed.

An Introduction to the Patstat Database with Example Queries

This paper provides an introduction to the Patstat patent database. It offers guided examples of ten popular queries that are relevant for research purposes and that cover the most important data tables. It is targeted at academic researchers and practitioners willing to learn the basics of the database.

Universities’ trademark patterns and possible determinants

Academic institutions may register trademarks (TMs) to protect and exploit key intangible assets (e.g. reputation), to better market current and prospective initiatives, and to better appropriate the output of innovative activities. TM registration by academic institutions – so far overlooked by the literature addressing the third function of universities – is investigated here. The analysis relies on a novel panel data set containing information about US universities, their main characteristics, and their TM and patent activities over the period 1997–2007. Our contribution is exploratory in nature and descriptive in aim and uncovers a number of relationships worth being investigated further, among them are the persistence of Intellectual Property Rights activities by academic institutions and the existence of positive and significant relationships between TM registration and universities’ characteristics such as being private institutions, the number of students enrolled and the share of graduate students, the share of federal funds received, and the presence of medical schools.