Patricia Laurens

Delineation of the genomics field by hybrid citation-lexical methods: interaction with experts and validation process

In advanced methods of delineation and mapping of scientific fields, hybrid methods open a promising path to the capitalisation of advantages of approaches based on words and citations. One way to validate the hybrid approaches is to work in cooperation with experts of the fields under scrutiny. We report here an experiment in the field of genomics, where a corpus of documents has been built by a hybrid citation-lexical method, and then clustered into research themes. Experts of the field were associated in the various stages of the process: lexical queries for building the initial set of documents, the seed; citation-based extension aiming at reducing silence; final clustering to identify noise and allow discussion on border areas. The analysis of experts’ advices show a high level of validation of the process, which combines a high-precision and low-recall seed, obtained by journal and lexical queries, and a citation-based extension enhancing the recall. This findings on the genomics field suggest that hybrid methods can efficiently retrieve a corpus of relevant literature, even in complex and emerging fields.

Analysing knowledge capture mechanisms: Methods and a stylised bioventure case

Knowledge transfer between science and technology has been studied at micro- and macro-levels of analysis. This has contributed to the understanding of the mechanisms and drivers, but actual transfer mechanism and process, be they through codified or tacit sources, have very rarely been mapped and measured to completeness and remain, to a large extent, a black box. We develop a novel method for mapping science–technology flows and introduce ‘concept clusters’ as an instrument to do so. Using patent and publication data, we quantitatively and visually demonstrate the flows of knowledge between academia and industry. We examine the roles of exogenous and endogenous knowledge sources, and of co-inventors and co-authors in the application of university-generated knowledge. When applied to a stylised case, we show that the method is able to trace the linkages between base knowledge and skill sets and their application to a technology, which in some instances span over twenty-five years.

The determinants of cleaner energy innovations of the world’s largest firms: the impact of firm learning and knowledge capital*

ABSTRACT In this paper, we address the determinants of clean energy inventions by 946 large firms. We use a new set of large firms’ patent portfolios and we broaden and deepen existing literature on this issue in two main ways: first, we conduct our study directly at the firm level and not at the industry or national levels and second, we do not focus on a single industry but encompass all industrial sectors. Drawing on firm (internal and external) knowledge and knowledge accumulation, we show there is a robust positive association between the (past) knowledge accumulated capital related to clean technologies and the number of inventions produced in that field, even after controlling for industry and nation fixed effects and other factors. The same relation works for (past) knowledge-accumulated capital in other (non-clean) technologies. However, the relation’s impact on the number of clean inventions produced is much lower. The magnitudes of our coefficient are in line with that obtained previously on firms in the auto-industry or at the sectoral level.

The artificial patents in the PATSTAT database: How much do they matter when computing indicators of internationalisation based on worldwide priority patents?

This paper proposes to broaden by more than 10%—compared with the current practice—the set of applications for priority patents, which is used to compute worldwide patent indicators. This extension is made possible thanks to the inclusion in the corpus of documents used for the calculation of indicators of the first filing patent applications that are designated as “artificial priority patents” in the PATSTAT database and currently discarded for the production of indicators. This research aims to show how adding these “artificial” patent applications can modify the value of the worldwide patent indicators. Artificial patent applications have never been used before because they contain very scarce information in their original state. We present a methodology we have developed to, first, replenish the artificial patents with information retrieved from close patents belonging to the same INPADOC family. Then, we study in details a range of indicators characterising the trends in the internationalisation of corporate R&D inventive activities. We provide evidence that the internationalisation pattern can be modified when including replenished artificial corporate patents in the indicator calculation. At the world level, incorporating artificial priority patents does not affect the trends over time, nor introduce any significant changes in the values of the indicators. However, analyses performed at a smaller scale, such as the firms’ continent level or the firms’ sector, show significant changes of the level of the intercontinental internationalisation in particular for the US firms.