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
This is a preview of subscription content, log in to check access.
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 was obtained from all individual participants included in the study.
Barabási A-L (2016) Network science. Cambridge University Press, CambridgeGoogle Scholar
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
Berliant M, Fujita M (2008) Knowledge creation as a square dance on the Hilbert cube. Int Econ Rev 49(4):1251–1295CrossRefGoogle Scholar
Bloom NN, Schankerman M, Van Reenen J (2013) Identifying technology spillovers and product market rivalry. Econometrica 81(4):1347–1393CrossRefGoogle Scholar
Fleming L, Mingo S, Chen D (2007a) Collaborative brokerage, generative creativity, and creative success. Admin Sci Q 52(3):443–475CrossRefGoogle Scholar
Fleming L, King C III, Juda AI (2007b) Small worlds and regional innovation. Org Sci 18(6):938–954CrossRefGoogle Scholar
Forti E, Franzoni C, Sobrero M (2013) Bridges or isolates? Investigating the social networks of academic inventors. Res Policy 42(8):1378–1388CrossRefGoogle Scholar
Fortunato S, Barthelemy M (2007) Resolution limit in community detection. Proc Natl Acad Sci 104(1):36–41CrossRefGoogle Scholar
Gautam A (2000) Collaboration networks, structural holes, and innovation: a longitudinal study. Admin Sci Q 45(3):425–455CrossRefGoogle Scholar
Gonzalez-Brambila CN, Veloso FM, Krackhardt D (2013) The impact of network embeddedness on research output. Res Policy 42(9):1555–1567CrossRefGoogle Scholar
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
Griliches Z (1998) R&D and productivity—the economic evidence. The University of Chicago Press, ChicagoCrossRefGoogle Scholar
Inoue H, Liu Y (2015) Revealing the intricate effect of collaboration on innovation. PLoS One 10(3):e0121973CrossRefGoogle Scholar
Inoue H, Nakajima K, Saito YU (2013) Localization of collaborations in knowledge creation. RIETI Discussion Paper Series, 13-E-070Google Scholar
Inoue H, Nakajima K, Saito YU (2015) Innovation and collaboration patterns between research establishments. RIETI Discussion Paper Series, 15-E-049Google Scholar
Jones BF (2005) The burden of knowledge and the ‘death of the renaissance man’: is innovation getting harder? NBER Working Paper SeriesGoogle Scholar
Kawamoto T, Rosvall M (2015) Estimating the resolution limit of the map equation in community detection. Phys Rev E 91(1):012809CrossRefGoogle Scholar
Lancichinetti A, Fortunato S (2009) Community detection algorithms: a comparative analysis. Phys Rev E 80(5):056117CrossRefGoogle Scholar
Merton RK (1979) The sociology of science: theoretical and empirical investigations. University of Chicago Press, ChicagoGoogle Scholar
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
Porter ME (1998) On competition. Harvard Business School Press, BrightonGoogle Scholar
Rosvall M, Bergstrom CT (2008) Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci 105(4):1118–1123CrossRefGoogle Scholar
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
Simonton DK (1988) Scientific genius: a psychology of science. Cambridge University Press, CambridgeGoogle Scholar
Trajtenberg M (1990) A penny for your quotes: patent citations and the value of innovations. Rand J Econ 21(1):172–187CrossRefGoogle Scholar
Weisberg RW (2006) Creativity: understanding innovation in problem solving, science, invention, and the arts. Wiley, New YorkGoogle Scholar
Wuchty S, Jones BF, Uzzi B (2007) The increasing dominance of teams in production of knowledge. Science 316(5827):1036–1039CrossRefGoogle Scholar