Commercializing academic research: a social network approach exploring the role of regions and distance

  • André SpithovenEmail author
  • Jef Vlegels
  • Walter Ysebaert


Relationships between firms and universities have been centre stage for some time. However, empirical studies on firms contracting research to universities remains limited. The likelihood of engaging in contract research depends on the characteristics of the firm and the university. Because existing literature further suggests that location is a key facilitator for knowledge transfer activities, the paper investigates the role played by regions and geographical distance between firms and universities when engaging in contract research. Hence, the analysis combines characteristics from both organisations and adds relationship-specific features with respect to the distance between them and the region they are located in. It also looks at the role played by cognitive distance. The paper contributes to the understanding of how academic research, commissioned by firms, is influenced by locational features: the ability to engage in contract research and the regional context, the regional embeddedness of research contract partners, and the geographical distance between these partners. It builds on an original dataset with information on contract research at firm. Based on a panel of three consecutive waves of R&D surveys in Belgium conducted in 2006, 2008 and 2010, the linkages of universities with R&D active firms are examined by linking a database on universities with one on firm R&D investments. Using the most recent insights in the social network approach, highlights the variables that impact the likelihood of firms engaging in research contracted to a university. Descriptive measurements are calculated from social network analysis to capture the basic structure of the firm-university network and construct an Exponential Random Graph model to predict firm-university relationships based on network characteristics and node attributes. Four main conclusions are drawn. First, more innovative regions do not show a higher likelihood of firms to engage in contract research with universities. Second, the likelihood for contract research is higher, if firms and universities are located in the same region. Third, geographical distance shows a negative relation to the likelihood of contract research suggesting cluster formation. Fourth, in the case of contract research cognitive distance complements geographic distance.


Firm-university relationships Contract research Geographical distance Cognitive distance Regional embeddedness Social network analysis 

JEL Classifications

I23 L24 O32 O33 R12 



  1. Agneessens, F., Roose, H., & Waege, H. (2004). Choices of theatre events: p* models for affiliation networks with attributes. Metodoloski Zvezki, 1(2), 419–439.Google Scholar
  2. Arundel, A., & Geuna, A. (2004). Proximity and the use of public science by innovative European firms. Economics of Innovation and New Technology, 13, 559–580.CrossRefGoogle Scholar
  3. Asheim, B. T., & Isaksen, A. (2002). Regional innovation systems: The integration of local ‘sticky’ and global ‘ubiquitous’ knowledge. Journal of Technology Transfer, 27(1), 77–86.CrossRefGoogle Scholar
  4. Audretsch, D. B., & Lehmann, E. E. (2005). Does the knowledge spillover theory of entrepreneurship hold for regions? Research Policy, 34, 1191–1202.CrossRefGoogle Scholar
  5. Azagra-Caro, J. M., Archontakis, F., Gutiérrez-Gracia, A., & Fernández-de-Lucio, I. (2006). Faculty support for the objectives of university–industry relations versus degree of R&D cooperation: The importance of regional absorptive capacity. Research Policy, 35(1), 37–55.CrossRefGoogle Scholar
  6. Balconi, M., Breschi, S., & Lissoni, F. (2004). Networks of inventors and the role of academia: An exploration of Italian patent data. Research Policy, 33(1), 127–145.CrossRefGoogle Scholar
  7. Balland, P.-A., & Rigby, D. (2017). The geography of complex knowledge. Economic Geography, 93(1), 1–23.CrossRefGoogle Scholar
  8. Bathelt, H., Malmberg, A., & Maskell, P. (2004). Clusters and knowledge: Local buzz, global pipelines and the process of knowledge creation. Progress in Human Geography, 28, 31–56.CrossRefGoogle Scholar
  9. Bekkers, R., & Bodas Freitas, I. M. (2008). Analysing knowledge transfer channels between universities and industry: To what degree do sectors also matter? Research Policy, 37(10), 1837–1853.CrossRefGoogle Scholar
  10. Belgian Science Policy Office. (2016). Last Accessed October 8, 2016.
  11. Bodas Freitas, I. M., & Verspagen, B. (2017). The motivations, institutions and organization of university-industry collaborations in the Netherlands. Journal of Evolutionary Economics, 27, 379–412.CrossRefGoogle Scholar
  12. Borgatti, S. P., & Cross, R. (2003). A relational view in social networks. Management Science, 49, 432–445.CrossRefGoogle Scholar
  13. Breschi, S., & Lissoni, F. (2001). Knowledge spillovers and local innovation systems: A critical survey. Industrial and Corporate Change, 10, 975–1005.CrossRefGoogle Scholar
  14. Broekel, T., & Boschma, R. (2012). Knowledge networks in the Dutch aviation industry: The proximity paradox. Journal of Economic Geography, 12(2), 409–433.CrossRefGoogle Scholar
  15. Broström, A. (2010). Working with distant researchers—Distance and content in university-industry interaction. Research Policy, 39(10), 131–1320.CrossRefGoogle Scholar
  16. Bruneel, J., Spithoven, A., & Clarysse, B. (2017). Interorganizational trust and technology complexity: Evidence for new technology-based firms. Journal of Small Business Management, 55(S1), 256–274.CrossRefGoogle Scholar
  17. Cairncross, F. (2001). The death of distance 2.0. London: Texere Publishing Limited.Google Scholar
  18. Caniëls, M. C. J., Kronenberg, K., & Werker, C. (2014). Conceptualizing proximity in research collaborations. In R. Rutten, P. Benneworth, D. Irawati, & F. Boekema (Eds.), The social dynamics of innovation networks (pp. 221–238). London: Routledge.Google Scholar
  19. Caniëls, M. C. J., & van den Bosch, H. (2011). The role of higher education institutions in building regional innovation systems. Papers in Regional Science, 90(2), 271–286.CrossRefGoogle Scholar
  20. Cantner, U., & Graf, H. (2006). The network of innovators in Jena: An application of social network analysis. Research Policy, 35(4), 463–480.CrossRefGoogle Scholar
  21. Capello, R., & Caragliu, A. (2018). Proximities and the intensity of scientific relations: Synergies and nonlinearities. International Regional Science Review, 41(1), 7–44.CrossRefGoogle Scholar
  22. Casper, S. (2013). The spill-over theory reversed: The impact of regional economies on the commercialization of university science. Research Policy, 42, 1313–1324.CrossRefGoogle Scholar
  23. Charles, D. (2006). Universities as key knowledge infrastructures in regional innovation systems. Innovation: The European Journal of Social Science Research, 19(1), 117–130.Google Scholar
  24. Cohen, W. M., Nelson, R. R., & Walsh, J. P. (2002). Links and impacts: The influence of public research on industrial R&D. Management Science, 48(1), 1–23.CrossRefGoogle Scholar
  25. Cooke, P., Uranga, M. G., & Etxebarria, G. (1997). Regional innovation systems: Institutional and organisational dimensions. Research Policy, 26(4–5), 475–492.CrossRefGoogle Scholar
  26. Cowan, R., David, P. A., & Foray, D. (2000). The explicit economics of knowledge codification and tacitness. Industrial and Corporate Change, 9(2), 211–253.CrossRefGoogle Scholar
  27. Cumbers, A., MacKinnon, D., & Chapman, K. (2003). Innovation, collaboration, and learning in regional clusters: A study of SMEs in the Aberdeen oil complex. Environment and Planning A, 35, 1689–1709.CrossRefGoogle Scholar
  28. Czarnitzki, D., & Delanote, J. (2013). Young Innovative Companies: The new high-growth firms? Industrial and Corporate Change, 22(5), 1315–1340.CrossRefGoogle Scholar
  29. D’Este, P., & Patel, P. (2007). University-industry linkages in the UK: What are the factors underlying the variety of interactions with industry? Research Policy, 36(9), 1295–1313.CrossRefGoogle Scholar
  30. D’Este, P., & Perkmann, M. (2011). Why do academics engage with industry? The entrepreneurial university and individual motivations. Journal of Technology Transfer, 36(3), 316–339.CrossRefGoogle Scholar
  31. Dahl, M. S., & Sorenson, O. (2012). Home sweet home: Entrepreneurs’ location choices and the performance of their ventures. Management Studies, 58(6), 1059–1071.Google Scholar
  32. Davids, M., & Frenken, K. (2018). Proximity, knowledge base and the innovation process: Towards an integrated framework. Regional Studies, 52(1), 23–34.CrossRefGoogle Scholar
  33. De Fuentes, C., & Dutrénit, G. (2016). Geographic proximity and university–industry interaction: The case of Mexico. The Journal of Technology Transfer, 41(2), 329–348.CrossRefGoogle Scholar
  34. Doloreux, D., & Parto, S. (2005). Regional innovation systems: Current discourse and unresolved issues. Technology in Society, 27(2), 133–153.CrossRefGoogle Scholar
  35. Döring, T., & Schnellenbach, J. (2006). What do we know about geographical knowledge spillovers and regional growth? A survey of the literature. Regional Studies, 40(3), 375–395.CrossRefGoogle Scholar
  36. Etzkowitz, H. (1998). The norms of entrepreneurial science: Cognitive effects of the new university–industry linkages. Research Policy, 27(8), 823–833.CrossRefGoogle Scholar
  37. European Commission. (2017). Regional innovation scoreboard. Luxembourg, European Commission.
  38. Fontana, R., Geuna, A., & Matt, M. (2006). Factors affecting university-industry R&D projects: The importance of searching, screening and signalling. Research Policy, 35(2), 309–323.CrossRefGoogle Scholar
  39. Frank, O., & Strauss, D. (1986). Markov graphs. Journal of the American Statistical Association, 81, 832–842.CrossRefGoogle Scholar
  40. Fritsch, M., & Stephan, A. (2005). Regionalization of innovation policy—Introduction to the special issue. Research Policy, 34(8), 1123–1127.CrossRefGoogle Scholar
  41. Garcia, R., Araújo, V., Mascarini, S., Santos, E. G. D., & Costa, A. R. (2018). An analysis of the relation between geographical and cognitive proximity in university-industry linkages. Proceedings of the 44th Brazilian Economics Meeting, no. 132.Google Scholar
  42. Gertler, M. S. (1995). “Being there”: Proximity, organization, and culture in the development and adoption of advanced manufacturing technologies. Economic Geography, 71(1), 1–26.CrossRefGoogle Scholar
  43. Godin, B., & Gingras, Y. (2000). The place of universities in the system of knowledge production. Research Policy, 29, 273–278.CrossRefGoogle Scholar
  44. Goodreau, S. M., Handcock, M. S., Hunter, D. R., Butts, C. T., & Morris, M. (2008). A statnet tutorial. Journal of Statistical Software, 24(9), 1–27.CrossRefGoogle Scholar
  45. Greunz, L. (2005). Intra- and inter-regional knowledge spillovers: Evidence from European regions. European Planning Studies, 13(3), 449–473.CrossRefGoogle Scholar
  46. Grillitsch, M., & Trippl, M. (2014). Combining knowledge from different sources, channels and geographical scales. European Planning Studies, 22(1), 2305–2325.CrossRefGoogle Scholar
  47. Hagedoorn, J., & Zobel, A. K. (2015). The role of contracts and intellectual property rights in open innovation. Technology Analysis & Strategic Management, 27(9), 1050–1067.CrossRefGoogle Scholar
  48. Handcock, M. S., Hunter, D. R., Butts, C. T., Goodreau, S. M., & Morris, M. (2003). Statnet: Software tools for the statistical modeling of network data.
  49. Hansen, T. (2015). Substitution or overlap? The relations between geographical and non-spatial proximity dimensions in collaborative innovation projects. Regional Studies, 49(10), 1672–1684.CrossRefGoogle Scholar
  50. Holcomb, T. R., & Hitt, M. A. (2007). Toward a model of strategic outsourcing. Journal of Operations Management, 25(2), 464–481.CrossRefGoogle Scholar
  51. Huber, F. (2012). On the role and interrelationship of spatial, social and cognitive proximity: Personal knowledge relationships of R&D workers in the Cambridge information technology cluster. Regional Studies, 46(9), 1169–1182.CrossRefGoogle Scholar
  52. Hunter, D. R. (2007). Curved exponential family models for social networks. Social Networks, 29, 216–230.CrossRefGoogle Scholar
  53. Isaksen, A. (2008). The innovation dynamics of global competitive regional clusters: The case of Norwegian centres of expertise. Regional Studies, 43(9), 1155–1166.CrossRefGoogle Scholar
  54. Isaksen, A., & Karlsen, J. (2013). Can small regions construct regional advantages? The case of four Norwegian regions. European Urban and Regional Studies, 20(2), 243–257.CrossRefGoogle Scholar
  55. Jensen, P. H., Palangkaraya, A., & Webster, E. (2015). Trust and the market for technology. Research Policy, 44, 340–356.CrossRefGoogle Scholar
  56. Keeble, D., Lawson, C., Moore, B., & Wilkinson, F. (1999). Collective learning processes, networking and ‘institutional thickness’ in the Cambridge region. Regional Studies, 33(4), 319–332.CrossRefGoogle Scholar
  57. Klein Woolthuis, R., Hillebrand, B., & Nooteboom, B. (2005). Trust, contract, and relationship development. Organization Studies, 26(6), 813–840.CrossRefGoogle Scholar
  58. Knoben, J., & Oerlemans, L. A. G. (2006). Proximity and inter-organizational collaboration: A literature review. International Journal of Management Reviews, 8(2), 71–89.CrossRefGoogle Scholar
  59. Kramer, J.-P., & Revilla-Diez, J. (2012). Catching the local buzz by embedding? Empirical insights on the regional embeddedness of multinational enterprises in Germany and the UK. Regional Studies, 46(10), 1303–1317.CrossRefGoogle Scholar
  60. Laursen, K., Reichstein, T., & Salter, A. (2011). Exploring the effect of geographical proximity and university quality on university-industry collaboration in the United Kingdom. Regional Studies, 45(4), 507–523.CrossRefGoogle Scholar
  61. Lerner, J., & Malmendier, U. (2010). Contractibility and the design of research agreements. American Economic Review, 100(1), 214–246.CrossRefGoogle Scholar
  62. Lusher, D., Koskinen, J., & Robins, G. (Eds.). (2013). Exponential random graph models for social networks: Theory, methods, and applications. Cambridge University Press.Google Scholar
  63. Malecki, E. J. (2010). Global knowledge and creativity: New challenges for firms and regions. Regional Studies, 44(8), 1033–1052.CrossRefGoogle Scholar
  64. Malmberg, A., & Power, D. (2005). (How) do (firms in) clusters create knowledge? Industry and Innovation, 12(4), 409–431.CrossRefGoogle Scholar
  65. Manning, S. (2013). New Silicon Valleys or a new species? Commoditization of knowledge work and the rise of knowledge services clusters. Research Policy, 42, 379–390.CrossRefGoogle Scholar
  66. Markman, G. D., Siegel, D. S., & Wright, M. (2008). Research and technology commercialization. Journal of Management Studies, 45(8), 1401–1423.CrossRefGoogle Scholar
  67. Marrocu, E., Paci, R., & Usai, S. (2013). Proximity, networking and knowledge production in Europe: What lessons for innovation policy? Technological Forecasting and Social Change, 80(8), 1484–1498.CrossRefGoogle Scholar
  68. Marsan, G. A., & Maguire, K. (2011). Categorisation of OECD regions using innovation-related variables. OECD Regional Development Working Papers, 2011/03. Paris: OECD Publishing.Google Scholar
  69. Marsili, O., & Verspagen, B. (2002). Technology and the dynamics of industrial structures: An empirical mapping of Dutch manufacturing. Industrial and Corporate Change, 11(4), 791–815.CrossRefGoogle Scholar
  70. Marzucchi, A., Antonioli, D., & Montressor, S. (2015). Industry-research co-operation within and across regional boundaries. What does innovation policy add? Papers in Regional Science, 94(3), 499–524.CrossRefGoogle Scholar
  71. McCann, P., & Ortega-Argilés, R. (2013). Modern regional innovation policy. Cambridge Journal of Regions, Economy and Society, 6, 187–216.CrossRefGoogle Scholar
  72. McDonald, D. W., & Gieser, S. M. (1987). Making cooperative research relationships work. Research Management, 30(4), 38–42.CrossRefGoogle Scholar
  73. Mellewigt, T., Madhok, A., & Weibel, A. (2007). Trust and formal contracts in interorganizational relationships—Substitutes and complements. Managerial and Decision Economics, 28(8), 833–847.CrossRefGoogle Scholar
  74. Miguélez, E., & Moreno, R. (2015). Knowledge flows and the absorptive capacity of regions. Research Policy, 43, 833–848.CrossRefGoogle Scholar
  75. Monjon, S., & Waelbroeck, P. (2003). Assessing knowledge spillovers from universities to firms: Evidence from French firm-level data. International Journal of Industrial Organization, 21(9), 1255–1270.CrossRefGoogle Scholar
  76. Morgan, K. (2004). The exaggerated death of geography: Learning, proximity and territorial innovation systems. Journal of Economic Geography, 4(1), 3–21.CrossRefGoogle Scholar
  77. Morris, M., Handcock, M. S., & Hunter, D. R. (2008). Specification of exponential-family random graph models: Terms and computational aspects. Journal of Statistical Software, 24(4), 1548–7660.CrossRefGoogle Scholar
  78. Mowery, D. C., & Ziedonis, A. A. (2015). Market versus spillovers in outflows of university research. Research Policy, 44, 50–66.CrossRefGoogle Scholar
  79. Muscio, A., Quaglione, D., & Vallanti, G. (2015). University regulation and university-industry interaction: A performance analysis of Italian academic departments. Industry and Corporate Change, 24(5), 1047–1079.CrossRefGoogle Scholar
  80. Nachum, L., & Zaheer, S. (2005). The persistence of distance? The impact of technology on MNE motivations for foreign investment. Strategic Management Journal, 26(8), 747–767.CrossRefGoogle Scholar
  81. Navarro, M., & Gibaja, J. J. (2009). Patterns of innovation in EU-25 regions: A typology and policy recommendations. Environment and Planning C: Government and Policy, 27, 815–840.CrossRefGoogle Scholar
  82. Niosi, J. (2002). National Systems of innovations are “x-efficient” (and x-effective). Why some are slow learners. Research Policy, 31, 291–302.CrossRefGoogle Scholar
  83. Nooteboom, B., Vanhaverbeke, W., Duysters, G., Gilsing, V., & Van den Oord, A. (2007). Optimal cognitive distance and absorptive capacity. Research Policy, 36(7), 1016–1034.CrossRefGoogle Scholar
  84. OECD. (2007). Higher education and regions: Globally competitive, locally engaged. Paris: OECD.CrossRefGoogle Scholar
  85. OECD. (2013). Regions at a Glance. Paris: OECD.Google Scholar
  86. OECD. (2015). Frascati manual. Proposed standard practice for surveys on research and experimental development. Paris: OECD.Google Scholar
  87. Office, Belgian Science Policy. (2010). Belgian report on science and technology indicators. Brussels: BELSPO.Google Scholar
  88. Ohmae, K. (1995). The borderless world: Power and strategy in an interdependent economy. New York: Harper Business.Google Scholar
  89. Paci, R., & Usai, S. (2009). Knowledge flows across European regions. Annals of Regional Science, 43, 669–690.CrossRefGoogle Scholar
  90. Perkmann, M., & Schildt, H. (2015). Open data partnerships between firms and universities: The role of boundary organizations. Research Policy, 44, 1133–1143.CrossRefGoogle Scholar
  91. Perkmann, M., Tartari, V., McKelvey, M., Autio, E., Broström, A., D’Este, P., et al. (2013). Academic engagement and commercialisation: A review of the literature on university-industry relations. Research Policy, 42, 423–442.CrossRefGoogle Scholar
  92. Perkmann, M., & Walsh, K. (2007). University–industry relationships and open innovation: Towards a research agenda. International Journal of Management Reviews, 9(4), 259–280.CrossRefGoogle Scholar
  93. Ponds, R., Van Oort, F., & Frenken, K. (2007). The geographical and institutional proximity of research collaboration. Papers in Regional Science, 86(3), 423–443.CrossRefGoogle Scholar
  94. Poppo, L., & Zenger, T. (2002). Do formal contracts and relational governance function as substitutes or complements? Strategic Management Journal, 23, 707–725.CrossRefGoogle Scholar
  95. Porter, M. E. (1998). Clusters and the new economics of competition. Harvard Business Review, 76(6), 77–90.Google Scholar
  96. Power, D., & Malmberg, A. (2008). The contribution of universities to innovation and economic development: In what sense a regional problem? Cambridge Journal of Regions, Economy and Society, 1(2), 233–245.CrossRefGoogle Scholar
  97. Ramos-Vielba, I., & Fernández-Esquinas, M. (2012). Beneath the tip of the iceberg: Exploring the multiple forms of university-industry linkages. Higher Education, 64, 237–265.CrossRefGoogle Scholar
  98. Rothaermel, F., Agung, S., & Jiang, L. (2007). University entrepreneurship: A taxonomy of the literature. Industrial and Corporate Change, 16(4), 691–791.CrossRefGoogle Scholar
  99. Santoro, M. D., & Gopalakrishnan, S. (2001). Relationship dynamics between university research centers and industrial firms: Their impact on technology transfer activities. The Journal of Technology Transfer, 26(1–2), 163–171.CrossRefGoogle Scholar
  100. Sanz-Menéndez, L., & Cruz-Castro, L. (2005). Explaining the science and technology policies of regional governments. Regional Studies, 39(7), 939–954.CrossRefGoogle Scholar
  101. Scandura, A. (2016). University-industry collaboration and firms’ R&D effort. Research Policy, 45, 1907–1922.CrossRefGoogle Scholar
  102. Schartinger, D., Rammer, C., Fischer, M. M., & Flöhlich, J. (2002). Knowledge interactions between universities and industry in Austria: Sectoral patterns and determinants. Research Policy, 31(3), 303–328.CrossRefGoogle Scholar
  103. Schepker, D. J., Oh, W. Y., Martynov, A., & Poppo, L. (2014). The many futures of contracts: Moving beyond structure and safeguarding to coordination and adaptation. Journal of Management, 40(1), 193–225.CrossRefGoogle Scholar
  104. Skvoretz, J., & Faust, K. (1999). Logit models for affiliation networks. Sociological Methodology, 29(1), 253–280.CrossRefGoogle Scholar
  105. Snijders, T. (2002). Markov Chain Monte Carlo estimation of exponential random graph models. Journal of Social Structure, 3, 1–40.Google Scholar
  106. Snijders, T. A. B., Pattison, P. E., Robins, G. L., & Handcock, M. S. (2006). New specifications for exponential random graph models. Sociological Methodology, 36(1), 99–153.CrossRefGoogle Scholar
  107. Spithoven, A., & Teirlinck, P. (2015). Internal capabilities, network resources and appropriation mechanisms as determinants of R&D outsourcing. Research Policy, 44(3), 711–725.CrossRefGoogle Scholar
  108. Spithoven, A., Vanhaverbeke, W., & Roijakkers, N. (2013). Open innovation practices in SMEs and large enterprises. Small Business Economics, 41(3), 537–562.CrossRefGoogle Scholar
  109. Sternberg, R., & Litzenberger, T. (2004). Regional clusters in Germany—Their geography and their relevance for entrepreneurial activities. European Planning Studies, 12(6), 767–791.CrossRefGoogle Scholar
  110. Storper, M. (1995). The resurgence of regional economies, ten years later: The region as a nexus of untraded interdependencies. European Urban and Regional Studies, 2(3), 191–221.CrossRefGoogle Scholar
  111. Storper, M., & Venables, A. J. (2004). Buzz: The economic force of the city. Journal of Economic Geography, 4, 351–370.CrossRefGoogle Scholar
  112. Subramani, M. R., & Venkatraman, N. (2003). Safeguarding investments in asymmetric interorganizational relationships: Theory and Evidence. Academy of Management Journal, 46(1), 46–62.Google Scholar
  113. Teirlinck, P., & Spithoven, A. (2005). Spatial inequality and location of private R&D activities in Belgian districts. Tijdschrift voor Economische en Sociale Geografie, 96(5), 558–572.CrossRefGoogle Scholar
  114. Tödtling, F., Lengauer, L., & Höglinger, C. (2011). Knowledge sourcing and innovation in “thick” and “thin” regional innovation systems—Comparing ICT firms in two Austrian regions. European Planning Studies, 19(7), 1245–1276.CrossRefGoogle Scholar
  115. Tödtling, F., & Trippl, M. (2005). One size fits all? Towards a differentiated regional innovation policy approach. Research Policy, 34(8), 1203–1219.CrossRefGoogle Scholar
  116. Torre, A., & Rallet, A. (2005). Proximity and localization. Regional Studies, 39(1), 47–59.CrossRefGoogle Scholar
  117. Trippl, M., Grillitsch, M., Isaksen, A. (2017). Exogenous sources of regional industrial change: Attraction and absorption of non-local knowledge for new path development. Progress in Human Geography (forthcoming).Google Scholar
  118. Trippl, M., Tödtling, F., & Lengaur, L. (2009). Knowledge sourcing beyond buzz and pipelines: Evidence from the Vienna software sector. Economic Geography, 85(4), 443–462.CrossRefGoogle Scholar
  119. Uyarra, E. (2010). Conceptualizing the regional roles of universities, implications and contradictions. European Planning Studies, 18(8), 1227–1246.CrossRefGoogle Scholar
  120. Uzzi, B., & Gillespie, J. J. (2002). Knowledge spillovers in corporate financing networks: Embeddedness and the firm’s debt performance. Strategic Management Journal, 23, 595–618.CrossRefGoogle Scholar
  121. Varga, A., Pontikakis, D., & Chorafakis, G. (2014). Metropolitan Edison and cosmopolitan Pasteur? Agglomeration and interregional research network effects on European R&D productivity. Journal of Economic Geography, 14, 229–263.CrossRefGoogle Scholar
  122. Wang, P., Pattison, P., & Robins, G. (2013). Exponential random graph model specifications for bipartite networks—A dependence hierarchy. Social Networks, 35(2), 211–222.CrossRefGoogle Scholar
  123. Wang, P., Sharpe, K., Robins, G. L., & Pattison, P. E. (2009). Exponential random graph (p*) models for affiliation networks. Social Networks, 31(1), 12–25.CrossRefGoogle Scholar
  124. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  125. Wasserman, S., & Pattison, P. (1996). Logit models and logistic regressions for social networks: I. An introduction to Markov graphs and p*. Psychometrika, 61, 401–425.CrossRefGoogle Scholar
  126. Waxel, A., & Malmberg, A. (2007). What is global and what is local in knowledge generating interaction? The case of the biotech cluster in Uppsala, Sweden. Entrepreneurship and Regional Development, 19, 137–159.CrossRefGoogle Scholar
  127. Woodward, D., Figueiredo, O., & Guimarães, P. (2006). Beyond the Silicon Valley: University R&D and high technology location. Journal of Urban Economics, 60(1), 15–32.CrossRefGoogle Scholar
  128. Zaheer, A., McEvily, B., & Perrone, V. (1998). Does trust matter? Exploring the effects of interorganizational and interpersonal trust on performance. Organization Science, 9, 141–159.CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Belgian Science Policy OfficeBrusselsBelgium
  2. 2.Vrije Universiteit BrusselBrusselsBelgium
  3. 3.Ghent UniversityGhentBelgium

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