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Patterns of scientific collaboration between Japan and France: Inter-sectoral analysis using Probabilistic Partnership Index (PPI)

Author

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  • Yasuhiro Yamashita

    (National Institute of Science and Technology Policy (NISTEP); Evaluation and Analysis Office, Yamagata University)

  • Yoshiko Okubo

    (Laboratoire Stratégie & Technologie, Ecole Centrale Paris; National Institute of Science and Technology Policy (NISTEP))

Abstract

Summary In this article we present an indicator - Probabilistic Partnership Index (PPI) - for use in measuring scientific linkages. This indicator is based on the Monte-Carlo simulation which provides a standard model to each network established in collaboration between two countries. Any relationship that occurs within a (whole) network can be projected to a standard model respectively and thus PPI is useful in examining individual networks within complex exchanges. We investigate inter-sectoral cooperation between France and Japan for the period of 1981-2004, by classifying every research unit appearing in the data set by its sector. We examine international collaborative patterns, domestic collaborative patterns and multilateral relationships established within the French-Japanese cooperation. We also compare PPI with the classic collaborative linkage indexes - Jaccard Index, Salton-Ochiai Index and Probabilistic Affinity Index - in order to describe the specificity of the new indicator. Our hope is that PPI will prove to be a useful and complementary tool for the analysis of international collaboration.

Suggested Citation

  • Yasuhiro Yamashita & Yoshiko Okubo, 2006. "Patterns of scientific collaboration between Japan and France: Inter-sectoral analysis using Probabilistic Partnership Index (PPI)," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(2), pages 303-324, August.
    • Handle: RePEc:spr:scient:v:68:y:2006:i:2:d:10.1007_s11192-006-0105-1
    DOI: 10.1007/s11192-006-0105-1
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    Cited by:

    1. Lili Wang & Xianwen Wang & Niels J. Philipsen, 2017. "Network structure of scientific collaborations between China and the EU member states," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 765-781, November.
    2. Han-Wen Chang & Mu-Hsuan Huang, 2014. "Cohesive subgroups in the international collaboration network in astronomy and astrophysics," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1587-1607, December.
    3. Sergey Shashnov & Maxim Kotsemir, 2018. "Research landscape of the BRICS countries: current trends in research output, thematic structures of publications, and the relative influence of partners," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 1115-1155, November.
    4. Gerson Pech & Catarina Delgado, 2020. "Percentile and stochastic-based approach to the comparison of the number of citations of articles indexed in different bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 223-252, April.
    5. Guijie Zhang & Luning Liu & Yuqiang Feng & Zhen Shao & Yongli Li, 2014. "Cext-N index: a network node centrality measure for collaborative relationship distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 291-307, October.
    6. Jyoti Dua & Vivek Kumar Singh & Hiran H. Lathabai, 2023. "Measuring and characterizing international collaboration patterns in Indian scientific research," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5081-5116, September.
    7. Zaida Chinchilla-Rodríguez & Yi Bu & Nicolás Robinson-García & Cassidy R. Sugimoto, 2021. "An empirical review of the different variants of the probabilistic affinity index as applied to scientific collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1775-1795, February.
    8. Nataliya Matveeva & Vladimir Batagelj & Anuška Ferligoj, 2023. "Scientific collaboration of post-Soviet countries: the effects of different network normalizations," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4219-4242, August.
    9. Jérôme Danguy, 2013. "Essays on the globalization of innovation using patent-based indicators," ULB Institutional Repository 2013/209409, ULB -- Universite Libre de Bruxelles.
    10. Zaida Chinchilla-Rodríguez & Yi Bu & Nicolás Robinson-García & Rodrigo Costas & Cassidy R. Sugimoto, 2018. "Travel bans and scientific mobility: utility of asymmetry and affinity indexes to inform science policy," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 569-590, July.
    11. Yoshiyuki Takeda & Shiho Mae & Yuya Kajikawa & Katsumori Matsushima, 2009. "Nanobiotechnology as an emerging research domain from nanotechnology: A bibliometric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 23-38, July.
    12. Jérôme Danguy, 2014. "Who collaborates with whom: the role of technological distance in international innovation," Working Papers TIMES² 2014-010, ULB -- Universite Libre de Bruxelles.
    13. Naveed, Nasir & Watanabe, Chihiro & Neittaanmäki, Pekka, 2020. "Co-evolutionary coupling leads a way to a novel concept of R&D - Lessons from digitalized bioeconomy," Technology in Society, Elsevier, vol. 60(C).
    14. Yukiko Murakami, 2014. "Influences of return migration on international collaborative research networks: cases of Japanese scientists returning from the US," The Journal of Technology Transfer, Springer, vol. 39(4), pages 616-634, August.

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