Evolutionary and Institutional Economics Review

, Volume 15, Issue 2, pp 465–475 | Cite as

The community structure of business establishments and its properties: evidence from joint patent applications

  • Hiroyasu InoueEmail author


We investigate what properties are associated with knowledge-creating communities. Using unique Japanese patent data and a community-detection method, we separate Japanese business establishments into communities composed of connections through joint patent applications. By comparing actual and random communities, we reveal that communities are similar in the total patents applied for, the total citations, and geographic distance and that they are dissimilar in their knowledge distance. The findings can benefit those who develop collaboration strategies in firms and create government policies to nurture collaborations among business establishments.


Network Patent Business establishment Community Innovation 

JEL Classification

O31 O34 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal participants

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.


  1. Barabási A-L (2016) Network science. Cambridge University Press, CambridgeGoogle Scholar
  2. Benner M, Waldfogel J (2008) Close to you? Bias and precision in patent-based measures of technological proximity. Res Policy 37(9):1556–1567CrossRefGoogle Scholar
  3. Berliant M, Fujita M (2008) Knowledge creation as a square dance on the Hilbert cube. Int Econ Rev 49(4):1251–1295CrossRefGoogle Scholar
  4. Bloom NN, Schankerman M, Van Reenen J (2013) Identifying technology spillovers and product market rivalry. Econometrica 81(4):1347–1393CrossRefGoogle Scholar
  5. Fleming L, Mingo S, Chen D (2007a) Collaborative brokerage, generative creativity, and creative success. Admin Sci Q 52(3):443–475CrossRefGoogle Scholar
  6. Fleming L, King C III, Juda AI (2007b) Small worlds and regional innovation. Org Sci 18(6):938–954CrossRefGoogle Scholar
  7. Forti E, Franzoni C, Sobrero M (2013) Bridges or isolates? Investigating the social networks of academic inventors. Res Policy 42(8):1378–1388CrossRefGoogle Scholar
  8. Fortunato S, Barthelemy M (2007) Resolution limit in community detection. Proc Natl Acad Sci 104(1):36–41CrossRefGoogle Scholar
  9. Gautam A (2000) Collaboration networks, structural holes, and innovation: a longitudinal study. Admin Sci Q 45(3):425–455CrossRefGoogle Scholar
  10. Gonzalez-Brambila CN, Veloso FM, Krackhardt D (2013) The impact of network embeddedness on research output. Res Policy 42(9):1555–1567CrossRefGoogle Scholar
  11. Goto A, Motohashi K (2007) Construction of a Japanese patent database and a first look at Japanese patenting activities. Res Policy 36(9):1431–1442CrossRefGoogle Scholar
  12. Griliches Z (1998) R&D and productivity—the economic evidence. The University of Chicago Press, ChicagoCrossRefGoogle Scholar
  13. Inoue H, Liu Y (2015) Revealing the intricate effect of collaboration on innovation. PLoS One 10(3):e0121973CrossRefGoogle Scholar
  14. Inoue H, Nakajima K, Saito YU (2013) Localization of collaborations in knowledge creation. RIETI Discussion Paper Series, 13-E-070Google Scholar
  15. Inoue H, Nakajima K, Saito YU (2015) Innovation and collaboration patterns between research establishments. RIETI Discussion Paper Series, 15-E-049Google Scholar
  16. Jones BF (2005) The burden of knowledge and the ‘death of the renaissance man’: is innovation getting harder? NBER Working Paper SeriesGoogle Scholar
  17. Kawamoto T, Rosvall M (2015) Estimating the resolution limit of the map equation in community detection. Phys Rev E 91(1):012809CrossRefGoogle Scholar
  18. Lancichinetti A, Fortunato S (2009) Community detection algorithms: a comparative analysis. Phys Rev E 80(5):056117CrossRefGoogle Scholar
  19. Merton RK (1979) The sociology of science: theoretical and empirical investigations. University of Chicago Press, ChicagoGoogle Scholar
  20. Nagaoka S, Motohashi K, Goto A (2010) Patent statistics as an innovation indicator. In: Handbook of the economics of innovation, vol 2. Elsevier, pp 1083–1127Google Scholar
  21. Porter ME (1998) On competition. Harvard Business School Press, BrightonGoogle Scholar
  22. Rosvall M, Bergstrom CT (2008) Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci 105(4):1118–1123CrossRefGoogle Scholar
  23. Rosvall M, Bergstrom CT (2011) Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems. PLoS One 6(4):e18209CrossRefGoogle Scholar
  24. Simonton DK (1988) Scientific genius: a psychology of science. Cambridge University Press, CambridgeGoogle Scholar
  25. Trajtenberg M (1990) A penny for your quotes: patent citations and the value of innovations. Rand J Econ 21(1):172–187CrossRefGoogle Scholar
  26. Weisberg RW (2006) Creativity: understanding innovation in problem solving, science, invention, and the arts. Wiley, New YorkGoogle Scholar
  27. Wuchty S, Jones BF, Uzzi B (2007) The increasing dominance of teams in production of knowledge. Science 316(5827):1036–1039CrossRefGoogle Scholar

Copyright information

© Japan Association for Evolutionary Economics 2018

Authors and Affiliations

  1. 1.Graduate School of Simulation StudiesUniversity of HyogoKobeJapan

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