A Method Using Two Dimensions of the Patent Classification for Measuring the Technological Proximity. An Application in Identifying a Potential R&D Partner in Biotechnology

Katia Angué (), Cécile Ayerbe () and Liliana Mitkova ()
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Katia Angué: CEMOI - Centre d'Économie et de Management de l'Océan Indien - UR - Université de La Réunion
Cécile Ayerbe: GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique
Liliana Mitkova: IRG - Institut de Recherche en Gestion - UPEM - Université Paris-Est Marne-la-Vallée - UPEC UP12 - Université Paris-Est Créteil Val-de-Marne - Paris 12

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Abstract: This paper aims to show how the information contained in patent documents can be used to identify basic and specific technological proximities between firms and therefore a potential research and development (R&D) partner. More generally, it looks at patents as a strategic tool that can be used for concluding cooperative R&D agreements (CRDA). The approach begins by looking at the state of the art on the role of technological proximity in CRDAs. This review clearly raises the problem of measuring technological proximity, which needs to be gauged at a two-fold level: general and specific. Then a dual method based on patent portfolios for analyzing the profiles of different potential partners is described along with an example of its application. Concretely, the exploratory study proposed here is based on an analysis of the patent portfolios of 14 French listed biotechnology companies and those of their main R&D partners. The analysis of 5,603 patents filed by the focal firms and their partners shows how the approach can be used to identify compatible partners that are more or less technologically matched.

Keywords: Strategy; Cooperation; outsourcing; Technological proximity; International Patent Classification (IPC); new organizational design; Proximity; R&D Collaborations; Patents; Choice of partner (search for similar items in EconPapers)
Date: 2014-10-01
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Citations: View citations in EconPapers (6)

Published in Journal of Technology Transfer, 2014, 39 (5), pp.716-747. ⟨10.1007/s10961-013-9325-8⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01133957

DOI: 10.1007/s10961-013-9325-8

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