Patent portfolio analysis of cities: statistics and maps of technological inventiveness

References

• Ahlgren, P., Jarneving, B., & Rousseau, R. (2003). Requirements for a cocitation similarity measure, with special reference to Pearson’s correlation coefficient. Journal of the American Society for Information Science and Technology, 54(6), 550–560. doi: 10.1002/asi.10242
   Web of Science ®Google Scholar
• Alkemade, F., Heimeriks, G., Schoen, A., Villard, L., & Laurens, P. (2015). Tracking the internationalization of multinational corporate inventive activity: National and sectoral characteristics. Research Policy, 44(9), 1763–1772. doi: 10.1016/j.respol.2015.01.007
   Web of Science ®Google Scholar
• Archibugi, D., & Pianta, M. (1996). Measuring technological change through patents and innovation surveys. Technovation, 16(9), 451–468. doi: 10.1016/0166-4972(96)00031-4
   Web of Science ®Google Scholar
• Arthur, B. (2007). The structure of invention. Research Policy, 36, 274–287. doi: 10.1016/j.respol.2006.11.005
   Web of Science ®Google Scholar
• Asheim, B., Isaksen, A., Moodysson, J., & Sotarauta, M. (2012). Knowledge bases, modes of innovation and regional innovation policy. In H. Bathelt, M. Feldman, & D. F. Kogler (Eds.), Beyond territory: Dynamic geographies of knowledge creation, diffusion, and innovation (pp. 227–249). London: Routledge.
   Google Scholar
• Bairoch, P. (1988). Cities and economic development: From the Dawn of history to the present. Chicago: University Press, Chicago.
   Google Scholar
• Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C., & West, G. B. (2007). Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences of the United States of America, 104(17), 7301–7306. doi: 10.1073/pnas.0610172104
   PubMed Web of Science ®Google Scholar
• Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). Ucinet for windows: Software for social network analysis. Harvard: Analytic Technologies.
   Google Scholar
• Boschma, R. (2017). Relatedness as driver of regional diversification: A research agenda. Regional Studies, 51(3), 351–364. doi: 10.1080/00343404.2016.1254767
   Web of Science ®Google Scholar
• Boschma, R., Balland, P.-A., & Kogler, D. F. (2015). Relatedness and technological change in cities: The rise and fall of technological knowledge in US metropolitan areas from 1981 to 2010. Industrial and Corporate Change, 24, 223–250. doi: 10.1093/icc/dtu012
   Web of Science ®Google Scholar
• Boschma, R., Heimeriks, G., & Balland, P.-A. (2014). Scientific knowledge dynamics and relatedness in biotech cities. Research Policy, 43(1), 107–114. doi: 10.1016/j.respol.2013.07.009
   Web of Science ®Google Scholar
• Boschma, R., & Martin, R. (2010). The aims and scope of evolutionary economic geography. In R. Boschma & R. Martin (Eds.), The handbook of evolutionary economic geography (pp. 3–39). Cheltenham: Edward Elgar.
   Google Scholar
• Braczyk, H.-J., Cooke, P., & Heidenreich, M. (Eds.). (1998). Regional innovation systems: The role of governances in a globalized world. London: UCL Press.
   Google Scholar
• Breschi, S., & Malerba, F. (2001). The geography of innovation and economic clustering: Some introductory notes. Industrial and Corporate Change, 10, 817–833. doi: 10.1093/icc/10.4.817
   Google Scholar
• Camagni, R. (1999). The city as a Milieu: Applying the Gremi approach to urban evolution. Révue d’Economie Régionale et Urbaine, 3, 591–606.
   Google Scholar
• Carlino, G. A., Chatterjee, S., & Hunt, R. M. (2007). Urban density and the rate of invention. Journal of Urban Economics, 61, 389–419. doi: 10.1016/j.jue.2006.08.003
   Web of Science ®Google Scholar
• Castaldi, C., Frenken, K., & Los, B. (2015). Related variety, unrelated variety and technological breakthroughs: An analysis of US state-level patenting. Regional Studies, 49(5), 767–781. doi: 10.1080/00343404.2014.940305
   Web of Science ®Google Scholar
• Cooke, P., & Leydesdorff, L. (2006). Regional development in the knowledge-based economy: The construction of advantage. The Journal of Technology Transfer, 31, 5–15. doi: 10.1007/s10961-005-5009-3
   Google Scholar
• David, P. A., & Foray, D. (2002). An introduction to the economy of the knowledge society. International Social Science Journal, 54(171), 9–23. doi: 10.1111/1468-2451.00355
   Google Scholar
• de Nooy, W., Mrvar, A., & Batagelj, V. (2011). Exploratory social network analysis with Pajek. Cambridge: Cambridge University Press.
   Google Scholar
• Feldman, M. P., & Kogler, D. F. (2010). Stylized facts in the geography of innovation. In B. Hall & N. Rosenberg (Eds.), Handbook of the economics of innovation (pp. 381–410). Oxford: Elsevier.
   Google Scholar
• Feldman, M. P., Kogler, D. F., & Rigby, D. L. (2015). Rknowledge: The spatial diffusion and adoption of rDNA methods. Regional Studies, 49(5), 798–817. doi: 10.1080/00343404.2014.980799
   Web of Science ®Google Scholar
• Fleming, L., & Sorenson, O. (2001). Technology as a complex adaptive system: Evidence from patent data. Research Policy, 30(7), 1019–1039. doi: 10.1016/S0048-7333(00)00135-9
   Web of Science ®Google Scholar
• Florida, R. (2002). The rise of the creative class. And how it’s transforming work, leisure and everyday life. New York: Basic Books.
   Google Scholar
• Florida, R. (2005). The world is spiky. The Atlantic monthly. Retrieved from https://www.theatlantic.com/past/docs/images/issues/200510/world-is-spiky.pdf
   Google Scholar
• Foray, D. (2015). Smart specialization: Opportunities and challenges for regional innovation policy. Abingdon: Routledge.
   Google Scholar
• Foray, D., David, P., & Hall, B. (2009, June). Smart specialization – the concept. Knowledge Economists Policy Brief Number 9, European Commission, Brussels: DG Research.
   Google Scholar
• Foray, D., David, P. A., & Hall, B. H. (2011). Smart specialization. From academic idea to political instrument, the surprising career of a concept and the difficulties involved in its implementation. MTEI Working Paper.
   Google Scholar
• Frenken, K., Hardeman, S., & Hoekman, J. (2009). Spatial scientometrics: Towards a cumulative research program. Journal of Informetrics, 3(3), 222–232. doi: 10.1016/j.joi.2009.03.005
   Web of Science ®Google Scholar
• Frenken, K., Van Oort, F., & Verburg, T. (2007). Related variety, unrelated variety and regional economic growth. Regional Studies, 41(5), 685–697. doi: 10.1080/00343400601120296
   Web of Science ®Google Scholar
• Fu, X., & Yang, Q. G. (2009). Exploring the cross-country gap in patenting: A stochastic frontier approach. Research Policy, 38, 1203–1213. doi: 10.1016/j.respol.2009.05.005
   Web of Science ®Google Scholar
• Glaeser, E. (2011). Cities: Engines of innovation. Scientific American, 305, 50–55. doi: 10.1038/scientificamerican0911-50
   PubMed Web of Science ®Google Scholar
• Greenhalgh, C., & Rogers, M. (2010). Innovation, intellectual property, and economic growth. Princeton, NJ: Princeton University Press.
   Google Scholar
• Griliches, Z. (1990). Patent statistics as economic indicators: A survey. Journal of Economic Literature, 28, 1661–1707.
   Web of Science ®Google Scholar
• Grossetti, M., Eckert, D., Gingras, Y., Jégou, L., Larivière, V., & Milard, B. (2014). Cities and the geographical deconcentration of scientific activity: A multilevel analysis of publications (1987–2007). Urban Studies, 51(10), 2219–2234. doi: 10.1177/0042098013506047
   Web of Science ®Google Scholar
• Hall, B. H., Jaffe, A. B., & Trajtenberg, M. (2001). The NBER patent citations data file: Lessons, insights and methodological tools (NBER Working Paper No. 8498), pp. 1–46.
   Google Scholar
• Hall, P. (1998). Cities in civilization: Culture, technology, and urban order. New York: Pantheon Books.
   Google Scholar
• Heimeriks, G., & Balland, P. A. (2016). How smart is specialisation? An analysis of specialisation patterns in knowledge production. Science and Public Policy, 43(4), 562–574. doi: 10.1093/scipol/scv061
   Web of Science ®Google Scholar
• Heimeriks, G., & Boschma, R. (2014). The path- and place-dependent nature of scientific knowledge production in biotech 1986-2008. Journal of Economic Geography, 14(2), 339–364. doi: 10.1093/jeg/lbs052
   Web of Science ®Google Scholar
• Heimeriks, G., & Vasileiadou, E. (2008). Changes or transition? Analysing the use of ICTs in the sciences. Social Science Information, 47(1), 5–29. doi: 10.1177/0539018407085747
   Web of Science ®Google Scholar
• Izsák, J., & Papp, L. (1995). Application of the quadratic entropy indices for diversity studies of drosophilid assemblages. Environmental and Ecological Statistics, 2(3), 213–224. doi: 10.1007/BF00456668
   Web of Science ®Google Scholar
• Jacobs, J. M. (1969). The economy of cities. New York: Random House.
   Google Scholar
• Jaffe, A. B. (1986). Technological opportunity and spillovers of R&D: Evidence from firm's patents, profits, and market value. American Economic Review, 76(5), 984–1001.
   Web of Science ®Google Scholar
• Jaffe, A. B. (1989). Characterizing the “technological position” of firms, with application to quantifying technological opportunity and research spillovers. Research Policy, 18(2), 87–97. doi: 10.1016/0048-7333(89)90007-3
   Web of Science ®Google Scholar
• Johansson, B., Lööf, H., & Savin, M. (2015). European R&D efficiency. Economics of Innovation and New Technology, 24(1–2), 140–158. doi: 10.1080/10438599.2014.897857
   Web of Science ®Google Scholar
• Kim, J., & Lee, S. (2015). Patent databases for innovation studies: A comparative analysis of USPTO, EPO, JPO and KIPO. Technological Forecasting and Social Change, 92, 332–345. doi: 10.1016/j.techfore.2015.01.009
   Web of Science ®Google Scholar
• Kogler, D. F. (2015). Editorial: Evolutionary economic geography – theoretical and empirical progress. Regional Studies, 49(5), 705–711. doi: 10.1080/00343404.2015.1033178
   Web of Science ®Google Scholar
• Kogler, D. F. (2016). Intellectual property and patents in manufacturing industries. In J. Bryson, J. Clark, & V. Vanchan (Eds.), The handbook of manufacturing industries in the world economy (pp. 163–188). Northampton: Edward Elgar.
   Google Scholar
• Kogler, D. F. (Ed.). (2017a). Evolutionary economic geography: Theoretical and empirical progress. London: Routledge.
   Google Scholar
• Kogler, D. F. (2017b). Relatedness as driver of regional diversification: A research agenda – A commentary. Regional Studies, 51(3), 365–369. doi: 10.1080/00343404.2016.1276282
   Web of Science ®Google Scholar
• Kogler, D. F., Essletzbichler, J., & Rigby, D. L. (2017). The evolution of specialization in the EU15 knowledge space. Journal of Economic Geography, 17(2), 345–373. doi: 10.1093/jeg/lbw024
   Web of Science ®Google Scholar
• Kogler, D. F., Rigby, D. L., & Tucker, I. (2013). Mapping knowledge space and technological relatedness in US cities. European Planning Studies, 21, 1374–1391. doi: 10.1080/09654313.2012.755832
   Web of Science ®Google Scholar
• Kogler, D. F., & Whittle, A. (2018). The geography of knowledge creation: Technological relatedness and regional smart specialization strategies. In A. Paasi, J. Harrison, & M. Jones (Eds.), Handbook on the geographies of regions and territories (pp. 153–168). Cheltenham: Edward Elgar. doi: 10.4337/9781785365805.00022
   Google Scholar
• Levin, R. C., Klevorick, A. K., Nelson, R. R., & Winter, S. G. (1987). Appropriating the returns from industrial research and development. Brookings Papers on Economic Activity, 1987, 783–820. doi: 10.2307/2534454
   Google Scholar
• Leydesdorff, L., & Bornmann, L. (2012). Mapping (USPTO) patent data using overlays to google maps. Journal of the American Society for Information Science and Technology, 63(7), 1442–1458. doi: 10.1002/asi.22666
   Web of Science ®Google Scholar
• Leydesdorff, L., Etzkowitz, H., & Kushnir, D. (2016). Globalization and growth of U.S. University patenting (2009–2014). Industry and Higher Education, 30(4), 257–266. doi: 10.1177/0950422216660253
   Web of Science ®Google Scholar
• Leydesdorff, L., Heimeriks, G., & Rotolo, D. (2016). Journal portfolio analysis for countries, cities, and organizations: Maps and comparisons. Journal of the Association for Information Science and Technology, 67(3), 741–748. doi: 10.1002/asi.23551
   Web of Science ®Google Scholar
• Leydesdorff, L., Kogler, D. F., & Yan, B. (2017). Mapping patent classifications: Portfolio and statistical analysis, and the comparison of strengths and weaknesses. Scientometrics, 112(3), 1573–1591. doi: 10.1007/s11192-017-2449-0
   PubMed Web of Science ®Google Scholar
• Leydesdorff, L., Kushnir, D., & Rafols, I. (2014). Interactive overlay maps for US patent (USPTO) data based on international patent classification (IPC). Scientometrics, 98(3), 1583–1599. doi: 10.1007/s11192-012-0923-2
   Web of Science ®Google Scholar
• Lundvall, B.-Å. (1988). Innovation as an interactive process: from user-producer interaction to the national system of innovation. In G. Dosi, C. Freeman, R. Nelson, G. Silverberg, & L. Soete (Eds.), Technical change and economic theory (pp. 349–369). London: Pinter.
   Google Scholar
• Maisonobe, M., Eckert, D., Grossetti, M., Jégou, L., & Milard, B. (2016). The world network of scientific collaborations between cities: Domestic or international dynamics? Journal of Informetrics, 10(4), 1025–1036. doi: 10.1016/j.joi.2016.06.002
   Web of Science ®Google Scholar
• Martin, R., & Sunley, P. (2006). Path dependence and regional economic evolution. Journal of Economic Geography, 6, 395–437. doi: 10.1093/jeg/lbl012
   Web of Science ®Google Scholar
• McCann, P., & Ortega-Argilés, R. (2015). Smart specialization, regional growth and applications to European Union cohesion policy. Regional Studies, 49(8), 1291–1302. doi: 10.1080/00343404.2013.799769
   Web of Science ®Google Scholar
• Mellander, C., & Florida, R. (2016). The city as innovation machine. Regional Studies, 51(1), 86–96.
   Web of Science ®Google Scholar
• Morgan, K. (1997). The learning region: Institutions, innovation and regional renewal. Regional Studies, 31(5), 491–503. doi: 10.1080/00343409750132289
   Web of Science ®Google Scholar
• Morgan, K. (2015). Smart specialisation: Opportunities and challenges for regional innovation policy. Regional Studies, 49(3), 480–482. doi: 10.1080/00343404.2015.1007572
   Web of Science ®Google Scholar
• Narin, F. (1976). Evaluative bibliometrics: The use of publication and citation analysis in the evaluation of scientific activity. Washington, DC: National Science Foundation.
   Google Scholar
• Nelson, R. (Ed.). (1993). National innovation systems: A comparative analysis. Oxford: Oxford University Press.
   Google Scholar
• Nelson, R., & Winter, S. G. (1982). An evolutionary theory of economic change. Cambridge, MA: The Belknap Press.
   Google Scholar
• Nomaler, Ö., Frenken, K., & Heimeriks, G. (2014). On scaling of scientific knowledge production in U.S. Metropolitan areas. PLoS ONE, 9(10), e110805. doi: 10.1371/journal.pone.0110805
   PubMed Web of Science ®Google Scholar
• OECD. (2009). OECD patent statistics manual. Report. Paris: OECD.
   Google Scholar
• Pavitt, K. (1985). Patent statistics as indicators of innovative activities: Possibilities and problems. Scientometrics, 7, 77–99. doi: 10.1007/BF02020142
   Web of Science ®Google Scholar
• Popp, D., Juhl, T., & Johnson, D. K. N. (2003). Determinants of the grant lag for U.S. Patent applications (NBER Working Paper No. 9518), pp. 1–50.
   Google Scholar
• Rafols, I., & Meyer, M. (2010). Diversity and network coherence as indicators of interdisciplinarity: Case studies in bionanoscience. Scientometrics, 82(2), 263–287. doi: 10.1007/s11192-009-0041-y
   Web of Science ®Google Scholar
• Rafols, I., Porter, A., & Leydesdorff, L. (2010). Science overlay maps: A new tool for research policy and library management. Journal of the American Society for Information Science and Technology, 61(9), 1871–1887. doi: 10.1002/asi.21368
   Web of Science ®Google Scholar
• Rao, C. R. (1982). Diversity: Its measurement, decomposition, apportionment and analysis. Sankhy: The Indian Journal of Statistics, Series A, 44(1), 1–22. doi: 10.1007/s13171-010-0002-9
   Google Scholar
• Ricotta, C., & Szeidl, L. (2006). Towards a unifying approach to diversity measures: Bridging the gap between the Shannon entropy and Rao’s quadratic index. Theoretical Population Biology, 70(3), 237–243. doi: 10.1016/j.tpb.2006.06.003
   PubMed Web of Science ®Google Scholar
• Rigby, D. (2015). Technological relatedness and knowledge space: Entry and exit of US cities from patent classes. Regional Studies, 49(11), 1922–1937. doi: 10.1080/00343404.2013.854878
   Web of Science ®Google Scholar
• Romer, P. M. (1994). The origins of endogenous growth. Journal of Economic Perspectives, 8(1), 3–22. doi: 10.1257/jep.8.1.3
   PubMed Web of Science ®Google Scholar
• Rotolo, D., Rafols, I., Hopkins, M. M., & Leydesdorff, L. (2017). Strategic intelligence on emerging technologies: Scientometric overlay mapping. Journal of the Association for Information Science and Technology, 68(1), 214–233. doi: 10.1002/asi.23631
   Web of Science ®Google Scholar
• Scherer, F. M. (1984). Innovation and growth: Schumpeterian perspectives. Cambridge, MA: MIT Press.
   Google Scholar
• Scheu, M., Veefkind, V., Verbandt, Y., Galan, E. M., Absalom, R., & Förster, W. (2006). Mapping nanotechnology patents: The EPO approach. World Patent Information, 28, 204–211. doi: 10.1016/j.wpi.2006.03.005
   Google Scholar
• Schumpeter, J. (1943). Socialism, capitalism and democracy. London: Allen & Unwin.
   Google Scholar
• Small, H., & Garfield, E. (1985). The geography of science: Disciplinary and national mappings. Journal of Information Science, 11(4), 147–159. doi: 10.1177/016555158501100402
   Web of Science ®Google Scholar
• Stirling, A. (2007). A general framework for analysing diversity in science, technology and society. Journal of the Royal Society Interface, 4(15), 707–719. doi: 10.1098/rsif.2007.0213
   PubMed Web of Science ®Google Scholar
• Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. doi: 10.1007/s11192-009-0146-3
   PubMed Web of Science ®Google Scholar
• Van Zeebroeck, N. (2011). The puzzle of patent value indicators. Economics of Innovation and New Technology, 20, 33–62. doi: 10.1080/10438590903038256
   Google Scholar
• Van Zeebroeck, N., & Van Pottelsberghe de la Potterie, B. (2011). The vulnerability of patent value determinants. Economics of Innovation and New Technology, 20, 283–308. doi: 10.1080/10438591003668638
   Google Scholar
• Veefkind, V., Hurtado-Albir, J., Angelucci, S., Karachalios, K., & Thumm, N. (2012). A new EPO classification scheme for climate change mitigation technologies. World Patent Information, 34(2), 106–111. doi: 10.1016/j.wpi.2011.12.004
   Google Scholar
• Wallace, M. L., & Rafols, I. (2015). Research portfolio analysis in science policy: Moving from financial returns to societal benefits. Minerva, 53(2), 89–115. doi: 10.1007/s11024-015-9271-8
   Web of Science ®Google Scholar
• Yan, B., & Luo, J. (2017). Measuring technological distance for patent mapping. Journal of the Association for Information Science and Technology, 68(2), 423–437. doi: 10.1002/asi.23664
   Web of Science ®Google Scholar
• Zhang, L., Rousseau, R., & Glänzel, W. (2011). Document-type country profiles. Journal of the American Society for Information Science and Technology, 62(7), 1403–1411. doi: 10.1002/asi.21537
   Web of Science ®Google Scholar
• Zhang, L., Rousseau, R., & Glänzel, W. (2016). Diversity of references as an indicator for interdisciplinarity of journals: Taking similarity between subject fields into account. Journal of the American Society for Information Science and Technology, 67(5), 1257–1265. doi: 10.1002/asi.23487
   Web of Science ®Google Scholar