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Extracting knowledge patterns with a social network analysis approach: an alternative methodology for assessing the impact of power inventors

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Abstract

This paper proposes a new, alternative analysis of patent data in order to extract knowledge patterns from inventors’ collaboration networks. Indeed, moving from a basic network analysis, we provide new developments to map and study co-inventorship. The goal of this research is to provide an overall understanding of the dynamics concerning knowledge flows in inventive activities. We show how the network of inventors is, on average, increasing in size: more and more inventors are contributing to technology innovations and they are more connected to each other. We also show to what extent inventors from different countries tend to cooperate with their local peers or internationally. Furthermore, an analysis of the clustering of inventors is carried out to show differences across countries in the structure of inventors’ communities, with a particular focus on the dynamics of collaboration for power inventors (i.e. star inventors).

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Notes

  1. See, for example, (Wasserman and Faust 1994; Barabási et al. 1999, 2002; Barabasi and Albert 1999; Albert and Barabási 2002; Clauset et al. 2004, 2009; Leicht et al. 2006; Newman and Leicht 2007).

  2. There are also two appendixes in the additional material: Appendix A includes formal definitions of several concepts introduced in the main text, whereas Appendix B presents statistical facts about patents and inventors’ collaboration in relation to technological sectors (which in our dataset are captured by IPC classes), not discussed in the main text due to space limitations.

  3. We thank an anonymous reviewer for pointing at this important reference.

  4. See, for example, Abbas et al. (2014), Lissoni and Miguelez (2014), Lubango (2015), Wagner and Leydesdorff (2005), Forti et al. (2013), Ejermo and Karlsson (2006), Sternitzke et al. (2008).

  5. See also the more recent contributions of Lissoni (2012), Landini et al. (2015), Miguélez and Moreno (2013) and Lubango (2015).

  6. We also have access to File Index (FI) concordance tables to convert IPC codes into more aggregated and manageable technological classes or Nomenclature of Units for Territorial Statistics (NUTS3).

  7. For more detailed information on inventors disambiguation and the Massacrator routine used in this research please see http://ideas.repec.org/p/grt/wpegrt/2012-29.html.

  8. See Appendix A, Sections A.1, A.2 and A.3, in the additional material.

  9. For all those countries whose distribution of \(M_{1}\) is totally different from a more or less disturbed power law the number of inventors and filed patents is so scarce to make any investigation about them unreliable and not really meaningful.

  10. See Appendix A, Section A.4. in the additional material.

  11. Recall that in SNA the density of a network is equal to the ratio of actual connections and all potential connections in the network.

  12. These results are in line with Landini et al. (2015), who observe how Egypt is one of the most active Northern African countries in terms of amount and variety of international collaborations and research output.

  13. Essentially, \(nbh_{i}\) is substituted by \(nbh_{i}^{F}\).

  14. This last case refers to countries that have a very low number of collaborations with foreign countries, which makes any analysis for them unreliable.

  15. Interestingly, \(M_{2}\) and \(M_{3}\) are equivalent to E-I index Hanneman and Riddle (2005).

  16. In the following, when X is not specified, we intend it to be equal to 5.

  17. Appendix A, Section A.7, in the additional material, includes a discussion on our notion of power inventor and the concept of star scientist.

  18. See Appendix A, Section A.4, in the additional material.

  19. See Appendix A, Section A.6, in the additional material.

References

  • Abbas, A., Zhang, L., & Khan, S. U. (2014). A literature review on the state-of-the-art in patent analysis. World Patent Information, 37, 3–13.

    Article  Google Scholar 

  • Agrawal, A., Cockburn, I., & McHale, J. (2006). Gone but not forgotten: Knowledge flows, labor mobility, and enduring social relationships. Journal of Economic Geography, 6(5), 571–591.

    Article  Google Scholar 

  • Albert, R., & Barabási, A.-L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74, 47–97.

    Article  MATH  MathSciNet  Google Scholar 

  • Alnuaimi, T., Singh, J., & George, G. (2012). Not with my own: Long-term effects of cross-country collaboration on subsidiary innovation in emerging economies versus advanced economies. Journal of Economic Geography, 12(5), 943–968.

    Article  Google Scholar 

  • Anderson, J. A. (1996). Communication theory: Epistemological foundations. New York: The Guilford Press.

    Google Scholar 

  • Azoulay, P., Ding, W., & Stuart, T. (2009). The impact of academic patenting on the rate, quality and direction of (public) research output. The Journal of Industrial Economics, 57, 637–676.

    Article  Google Scholar 

  • Balconi, M., Breschi, S., & Lissoni, F. (2002). Networks of inventors and the location of university research: An exploration of italian data. In Proceedings of the International Conference “Rethinking Science Policy”, Brighton, UK, SPRU.

  • Barabasi, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.

    Article  MATH  MathSciNet  Google Scholar 

  • Barabási, A.-L., Albert, R., & Jeong, H. (1999). Mean-field theory for scale-free random networks. Physica A: Statistical Mechanics and its Applications, 272(1), 173–187.

    Article  Google Scholar 

  • Barabási, A.-L., Jeong, H., Néda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and its Applications, 311(3), 590–614.

    Article  MATH  MathSciNet  Google Scholar 

  • Blumer, H. (1967a). Sociological analysis and the variable. In J. G. Manis & B. N. Meltzer (Eds.), Symbolic interaction. Boston: Allyn and Bacon.

    Google Scholar 

  • Blumer, H. (1967b). Threats from agency-determined research: The case of Camelot. In I. L. Horowitz (Ed.), The rise and fall of project Camelot. Cambridge: M.I.T. Press.

    Google Scholar 

  • Boissevain, J. (1979). Network analysis: A reappraisal. Current Anthropology, 20, 392–394.

    Article  Google Scholar 

  • Branstetter, L., Li, G., & Veloso, F. (2014). The rise of international coinvention. In A. B. Jaffe & B. F. Jones (Eds.), The changing frontier: Rethinking science and innovation policy (pp. 135–168). Chicago: University of Chicago Press.

    Google Scholar 

  • Breschi, S., & Lenzi, C. (2015). The role of external linkages and gatekeepers for the renewal and expansion of US cities’ knowledge base, 1990–2004. Regional Studies, 49(5), 782–797.

    Article  Google Scholar 

  • Breschi, S., & Lissoni, F. (2009). Mobility of skilled workers and co-invention networks: An anatomy of localized knowledge flows. Journal of Economic Geography, 9(4), 439–468.

    Article  Google Scholar 

  • Breschi, S., Lissoni, F., & Montobbio, F. (2008). University patenting and scienti c productivity: A quantitative study of Italian academic inventors. European Management Review, 5(2), 91–109.

    Article  Google Scholar 

  • Broadhead, R. S., & Rist, R. C. (1976). Gatekeepers and the social control of social research. Social Problems, 23(3), 325–336.

    Article  Google Scholar 

  • Cammarano, A., Caputo, M., Lamberti, E., & Michelino, F. (2017). R&D collaboration strategies for innovation: An empirical study through social network analysis. International Journal of Innovation and Technology Management, 14(01), 1740001.

    Article  Google Scholar 

  • Chen, Z., & Guan, J. (2016). The core-peripheral structure of international knowledge flows: Evidence from patent citation data. R&D Management, 46(1), 62–79.

    Article  MathSciNet  Google Scholar 

  • Chung, C. J., Barnett, G. A., Kim, K., & Lacka, D. (2013). An analysis on communication theory and discipline. Scientometrics, 95(3), 985–1005.

    Article  Google Scholar 

  • Clauset, A., Newman, M. E. J., & Moore, C. (2004). Finding community structure in very large networks. Physical Review E, 70, 066111.

    Article  Google Scholar 

  • Clauset, A., Shalizi, C. R., & Newman, M. E. J. (2009). Power-law distributions in empirical data. SIAM Review, 51(4), 661–703.

    Article  MATH  MathSciNet  Google Scholar 

  • Crane, D. (1965). Scientists at major and minor universities: A study of productivity and recognition. American Sociological Review, 30, 699–714.

    Article  Google Scholar 

  • Crawford, E. T., & Biderman, A. D. (1970). Paper money: Trends of research sponsorship in American sociology journals. Social Science Information, 9, 51–77.

    Article  Google Scholar 

  • Delgado, E., & Repiso, R. (2013). The impact of scientific journals of communication: Comparing google scholar metrics, web of science and scopus. Comunicar, 41, 45–52.

    Article  Google Scholar 

  • Ejermo, O., & Karlsson, C. (2006). Interregional inventor networks as studied by patent coinventorships. Research Policy, 35(3), 412–430.

    Article  Google Scholar 

  • Feeley, T. H., LaVail, K. H., & Barnett, G. A. (2011). Predicting faculty job centrality in communication. Scientometrics, 87, 303–314.

    Article  Google Scholar 

  • Fleming, L., King, C., & Juda, A. I. (2007). Small worlds and regional innovation. Organization Science, 18, 938–954.

    Article  Google Scholar 

  • Forti, E., Franzoni, C., & Sobrero, M. (2013). Bridges or isolates? investigating the social networks of academic inventors. Research Policy, 42(8), 1378–1388.

    Article  Google Scholar 

  • Freeman, L. C. (2004). The development of social network analysis: A study in the sociology of science. Vancouver: Empirical Press.

    Google Scholar 

  • Furman, J. L., Kyle, M. K., Cockburn, I. M., & Henderson, R. (2006). Public and private spillovers, location and the productivity of pharmaceutical research. Working paper 12509, National Bureau of Economic Research.

  • Furstenberg, F. F. (1971). Political intrusions and governmental confusion: The case of the National Institute of Law Enforcement and Criminal Justice. American Sociologist, 6, 59–62.

    Google Scholar 

  • Galliher, J. F., & McCartney, J. C. (1973). The influence of funding agencies on juvenile delinquency research. Social Problems, 21, 77–90.

    Article  Google Scholar 

  • Garcia, R., & Calantone, R. (2002). A critical look at technological innovation typology and innovativeness terminology: A literature review. Journal of Product Innovation Management, 19(2), 110–132.

    Article  Google Scholar 

  • Giuliani, E., & Bell, M. (2005). The micro-determinants of meso-level learning and innovation: Evidence from a Chilean wine cluster. Research Policy, 34(1), 47–68.

    Article  Google Scholar 

  • Giuliani, E., Martinelli, A., & Rabellotti, R. (2016). Is co-invention expediting technological catch up? a study of collaboration between emerging country firms and eu inventors. World Development, 77, 192–205.

    Article  Google Scholar 

  • Gould, R. V., & Fernandez, R. M. (1989). Structures of mediation: A formal approach to brokerage in transaction networks. Sociological Methodology, 19, 89–126.

    Article  Google Scholar 

  • Graf, H., & Kruger, J. J. (2011). The performance of gatekeepers in innovator networks. Industry and Innovation, 18(1), 69–88.

    Article  Google Scholar 

  • Grant, R. M. (1996). Prospering in dynamically-competitive environments: Organizational capability as knowledge integration. Organization Science, 7(4), 375–387.

    Article  Google Scholar 

  • Green, P. (1971). The obligations of American social scientists. The Annals, 394, 13–27.

    Google Scholar 

  • Griffin, D. J., Bolkan, S., Holmgren, J. L., & Tutzauer, F. (2016). Central journals and authors in communication using a publication network. Scientometrics, 106(1), 91–104.

    Article  Google Scholar 

  • Griliches, Z. (1990). Patent statistics as economic indicators: A survey. Journal of Economic Literature, 28(4), 1661–1707.

    Google Scholar 

  • Griliches, Z. (1992). Introduction to “output measurement in the service sectors”. In Z. Griliches (Ed.), Output measurement in the service sectors (pp. 1–22). Chicago: University of Chicago Press.

    Chapter  Google Scholar 

  • Guellec, D., & van Pottelsberghe de la Potterie, B. (2001). The internationalization of technology analyzed with patent data. Research Policy, 30(8), 1253–1266.

    Article  Google Scholar 

  • Hanneman, R. A. & Riddle, M. (2005). Introduction to social network methods. Published in digital form at http://faculty.ucr.edu/hanneman/, University of California, Riverside, CA.

  • Hingley, P., & Bas, S. (2009). Numbers and sizes of applicants at the European patent office. World Patent Information, 31(4), 285–298.

    Article  Google Scholar 

  • Horowitz, I. L. (1967). The rise and fall of project Camelot. In I. L. Horowitz (Ed.), The rise and fall of project Camelot. Cambridge: M.I.T. Press.

    Google Scholar 

  • Hsueh, C. C. & Wang, C. C. (2009). The use of SNA in knowledge diffusion research from patent data. In Proceedings of the International Conference on Advances in SNA and Mining (ASONAM), (pp. 393–398).

  • Kim, J., Lee, S. J., & Marschke, G. (2009). International knowledge flows: Evidence from an inventor-firm matched data set. In Science and engineering careers in the United States: An analysis of markets and employment, (pp. 321–348). National Bureau of Economic Research, Inc.

  • Kim, J. N., Park, S. C., Yoo, S. W., & Shen, H. (2010). Mapping health communication scholarship: Breadth, depth, and agenda of published research in health communication. Health Communication, 25, 487–503.

    Article  Google Scholar 

  • Landini, F., Malerba, F., & Mavilia, R. (2015). The structure and dynamics of networks of scientific collaborations in Northern Africa. Scientometrics, 105(3), 1787–1807.

    Article  Google Scholar 

  • Lee, S., Kim, J. H., & Rosen, D. (2009). A semantic network and categorical content analysis of Internet and online media. The Open Communication Journal, 3, 15–28.

    Article  Google Scholar 

  • Leicht, E. A., Holme, P., & Newman, M. E. J. (2006). Vertex similarity in networks. Physical Review E, 73, 026120.

    Article  Google Scholar 

  • Levinthal, D. A., & March, J. G. (1993). The myopia of learning. Strategic Management Journal, 14(S2), 95–112.

    Article  Google Scholar 

  • Leydesdor, L. (2007). Betweenness centrality as an indicator of the interdisciplinary of scientific journals. Journal of the American Society for Information Science, 58(9), 1303–1319.

    Article  Google Scholar 

  • Li, G. C., Lai, R., Damour, A., Doolin, D. M., Sun, Y., Torvik, V. I., et al. (2014). Disambiguation and co-authorship networks of the US patent inventor database. Research Policy, 43(6), 941–955.

    Article  Google Scholar 

  • Lissoni, F. (2012). Academic patenting in Europe: An overview of recent research and new perspectives. World Patent Information, 34(3), 197–205.

    Article  Google Scholar 

  • Lissoni, F. & Miguelez, E. (2014). Patents, innovation and economic geography. Technical Report 2014–16, Groupe de Recherche en Economie Théorique et Appliquée.

  • Lissoni, F., Coffano, M., Maurino, A., Pezzoni, M., & Tarasconi, G. (2010). APE-INV’s name game algorithm challenge: A guideline for benchmark data analysis and reporting. Mimeo.

  • Lissoni, F., Llerena, P., McKelvey, M., & Sanditov, B. (2008). Academic patenting in Europe: new evidence from the KEINS database. Research Evaluation, 17(2), 87–102.

    Article  Google Scholar 

  • Lissoni, F., Llerena, P., & Sanditov, B. (2006a). Networks of inventors and academics in France. Italy and Sweden: Evidence from the Keins Database.

  • Lissoni, F., Sanditov, B., & Tarasconi, G. (2006b). The Keins database on academic inventors: Methodology and contents. CESPRI working paper 181.

  • Lubango, L. M. (2015). The effect of co-inventors’reputation and network ties on the diffusion of scientific and technical knowledge from academia to industry in South Africa. World Patent Information, 43, 5–11.

    Article  Google Scholar 

  • Lusseau, D. (2003). The emergent properties of a dolphin social network. Proceedings of the Royal Society of London, Series B: Biological Sciences, 270, 186–188.

    Article  Google Scholar 

  • March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.

    Article  Google Scholar 

  • Marx, M., Strumsky, D., & Fleming, L. (2009). Mobility, skills, and the Michigan non-compete experiment. Management Science, 55(6), 875–889.

    Article  Google Scholar 

  • McCartney, J. L. (1971). The financing of sociological research: trends and consequences. In Edward A. Tiryakian (Ed.), The phenomenon of sociology. New York: Appleton-Century-Crofts.

    Google Scholar 

  • Menon, C. (2014). Spreading big ideas? The effect of top inventing companies on local inventors. Journal of Economic Geography, 15, 743–768.

    Article  Google Scholar 

  • Miguélez, E., & Moreno, R. (2013). Research networks and inventors’ mobility as drivers of innovation: Evidence from Europe. Regional Studies, 47(10), 1668–1685.

    Article  Google Scholar 

  • Montobbio, F., & Sterzi, V. (2011). Inventing together: Exploring the nature of international knowledge spillovers in Latin America. Journal of Evolutionary Economics, 21(1), 53–89.

    Article  Google Scholar 

  • Morrison, A. (2008). Gatekeepers of knowledge within industrial districts: Who they are how they interact. Regional Studies, 42(6), 817–835.

    Article  Google Scholar 

  • Nagaoka, S., Motohashi, K., & Goto, A. (2010). Patent statistics as an innovation indicator. Handbook of the Economics of Innovation, 2, 1083–1127.

    Article  Google Scholar 

  • Newman, M. E. J., & Leicht, E. A. (2007). Mixture models and exploratory analysis in networks. Proceedings of the National Academy of Sciences, 104, 9564–9569.

    Article  MATH  Google Scholar 

  • Nicholas, T. (2009). Spatial diversity in invention: Evidence from the early R&D labs. Journal of Economic Geography, 9(1), 1–31.

    Article  MathSciNet  Google Scholar 

  • Orlans, H. (1967). Ethical problems in the relations of research sponsors and investigators. In Gideon Sjoberg (Ed.), Ethics, politics, and social research. Cambridge: Schenkman.

    Google Scholar 

  • Otte, E., & Rousseau, R. (2002). Social network analysis: A powerful strategy, also for the information sciences. Journal of Information Science, 28, 441–453.

    Article  Google Scholar 

  • Park, H. W. (2010). Mapping the e-science landscape in South Korea using the webometrics method. Journal of Computer-Mediated Communication, 15, 211–229.

    Article  Google Scholar 

  • Pezzoni, M., Lissoni, F., & Tarasconi, G. (2014). How to kill inventors: Testing the Massacrator algorithm for inventor disambiguation. Scientometrics, 101, 477–504.

    Article  Google Scholar 

  • Platt, A. M. (1971). The politics of riot commissions. New York: Collier.

    Google Scholar 

  • Ponds, R., van Oort, F., & Frenken, K. (2010). Innovation, spillovers and university–industry collaboration: An extended knowledge production function approach. Journal of Economic Geography, 10(2), 231–255.

    Article  Google Scholar 

  • Raffo, J., & Lhuillery, S. (2009). How to play the name game: Patent retrieval comparing different heuristics. Research Policy, 38(10), 1617–1627.

    Article  Google Scholar 

  • Rist, R. C. (1973). Polity, politics, and social research: A study in the relationship of federal commissions and social science. Social Problems, 21, 113–128.

    Article  Google Scholar 

  • Rist, R. C. (1975). Ethnographic techniques and the study of an urban school. Urban Education, 10, 86–108.

    Article  Google Scholar 

  • Simpson, E. (1949). Measurement of diversity. Nature, 163, 688.

    Article  MATH  Google Scholar 

  • Singh, J. (2005). Collaborative networks as determinants of knowledge diffusion patterns. Management Science, 51(5), 756–770.

    Article  MATH  Google Scholar 

  • Singh, J. (2008). Distributed R&D, cross-regional knowledge integration and quality of innovative output. Research Policy, 37(1), 77–96.

    Article  Google Scholar 

  • Sternitzke, C., Bartkowski, A., & Schramm, R. (2008). Visualizing patent statistics by means of SNA tools. World Patent Information, 30(2), 115–131.

    Article  Google Scholar 

  • Thelwall, M. (2009). Introduction to webometrics. New York: Morgan and Claypool.

    Google Scholar 

  • Tseng, C. Y., Lin, S. C., Pai, D. C., & Tung, C. W. (2016). The relationship between innovation network and innovation capability: A social network perspective. Technology Analysis & Strategic Management, 28(9), 1029–1040.

    Article  Google Scholar 

  • Tsvetovat, M., & Kouznetsov, A. (2011). SNA for startups: Finding connections on the social web. Sebastopol: O’Reilly Media Inc.

    Google Scholar 

  • Wagner, C. S., & Leydesdorff, L. (2005). Network structure, self-organization, and the growth of international collaboration in science. Research Policy, 34(10), 1608–1618.

    Article  Google Scholar 

  • Wang, C., Rodan, S., Fruin, M., & Xu, X. (2014). Knowledge networks, collaboration networks, and exploratory innovation. Academy of Management Journal, 57(2), 484–514.

    Article  Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications (Vol. 8). Cambridge: Cambridge University Press.

    Book  MATH  Google Scholar 

  • Wellman, B., & Whitaker, M. (1974). Community, network, communication: An annotated bibliography. Toronto: Centre for urban and community studies, University of Toronto World Intellectual Property Organization (2009). Patent-Based Technology Analysis Report—Alternative Energy Technology.

  • WIPO. (2011). World intellectual property report: The changing face of Innovation. WIPO Press.

  • Zsindely, S., Schubert, A., & Braun, T. (1982a). Citation patterns of editorial gatekeepers in international chemistry journals. Scientometrics, 4(1), 69–76.

    Article  Google Scholar 

  • Zsindely, S., Schubert, A., & Braun, T. (1982b). Editorial gatekeeping patterns in international science journals. A new science indicator. Scientometrics, 4(1), 57–68.

    Article  Google Scholar 

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Acknowledgements

The authors wish to express their gratitude to the anonymous reviewers for their constructive comments and useful suggestions. This work has been partially funded by “Istituto di Ricerca per l’Innovazione e la Tecnologia nel Mediterraneo”, Reggio Calabria (Italy). The authors would like also to thank Pierluigi Decorato, Davide De Prosperis, Melissa Giorgio, Daniela Marra and Giorgio Tripodi for their excellent research assistantship. A special thanks to Davide Lanatà, Diego Fosso and Domenico Ursino for their support on data management. Any unreferenced errors, ambiguities, misconceptions will clearly be labelled as the fault of the authors by default.

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Authors and Affiliations

  1. DIGIEC, Mediterranean University of Reggio Calabria, Reggio Calabria, Italy

    Massimiliano Ferrara & Bruno Antonio Pansera

  2. ICRIOS, Bocconi University, Milan, Italy

    Massimiliano Ferrara & Roberto Mavilia

  3. MEDAlics, University for Foreigners “Dante Alighieri”, Reggio Calabria, Italy

    Roberto Mavilia

  4. DECISIONS_Lab, Mediterranean University of Reggio Calabria, Reggio Calabria, Italy

    Massimiliano Ferrara & Bruno Antonio Pansera

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Ferrara, M., Mavilia, R. & Pansera, B.A. Extracting knowledge patterns with a social network analysis approach: an alternative methodology for assessing the impact of power inventors. Scientometrics 113, 1593–1625 (2017). https://doi.org/10.1007/s11192-017-2536-2

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