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Networks of collaborative alliances: the second order interfirm technological distance and innovation performance

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Abstract

Studies have typically focused on the relationship between technological distance between partners in alliances, and innovation performance, from a direct tie or dyadic perspective. This paper explores the ego network set up in order to disclose how the second order technological distance, which is the distance between the partner and the partner’s partner, affects the innovation performance of the focal firm. To accomplish it, the network of alliances is built using biotechnological joint patents. The main result of this research is the finding of a positive quadratic relationship between the innovative performance of firms and second-order technological distance. This result has two implications. The first one is that the innovative performance of each firm embedded in a network cannot be optimized simultaneously. The second one, is that firm’s decision makers should consider the second-order neighborhood of the focal firm to establish optimal alliance in terms of innovation and enhance firm’s competitive advantage. Overall, this research set a new perspective to understand and improve the role of individual firms in collaborative networks, and help to complement the dominant view emphasizing the role of indirect ties in order to innovate.

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References

  • Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly,45(3), 425–455.

    Google Scholar 

  • Aldieri, L., & Cincera, M. (2009). Geographic and technological R&D spillovers within the triad: Micro evidence from US patents. Journal of Technology Transfer,34(2), 196–211.

    Google Scholar 

  • Anderson, J. C., Håkansson, H., & Johanson, J. (1994). Dyadic business relationships within a business network context. The Journal of Marketing,58(4), 1–15.

    Google Scholar 

  • Angue, K., Ayerbe, C., & Mitkova, L. (2013). A method using two dimensions of the patent classification for measuring the technological proximity: An application in identifying a potential R&D partner in biotechnology. Journal of Technology Transfer,39(5), 1–32.

    Google Scholar 

  • Argote, L., & Ingram, P. (2000). Knowledge transfer: A basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes,82(1), 150–169.

    Google Scholar 

  • Aslesen, H. W., & Jakobsen, S. (2007). The role of proximity and knowledge interaction between head offices and KIBS. Tijdschrift Voor Economische En Sociale Geografie,98(2), 188–201.

    Google Scholar 

  • Bae, L., & Gargiulo, M. (2003). Local action and efficient alliance strategies in the telecommunications industry. Insead.

  • Balland, P. A., Boschma, R., & Frenken, K. (2014). Proximity and innovation: from statics to dynamics. Journal of Regional Studies,49(6), 907–920.

    Google Scholar 

  • Battistella, C., De Toni, A. F., & Pillon, R. (2016). Inter-organisational technology/knowledge transfer: a framework from critical literature review. Journal of Technology Transfer,41(5), 1195–1234.

    Google Scholar 

  • Behner, P., Vallerien, S., Ehrhardt, M., & Rollman, D. (2009). Pharmaceutical companies in the economic storm. New York: Booz&Co.

    Google Scholar 

  • Bell, G. G., & Zaheer, A. (2007). Geography, networks, and knowledge flow. Organization Science,18(6), 955–972.

    Google Scholar 

  • Bierly, P. E., Damanpour, F., & Santoro, M. D. (2009). The application of external knowledge: Organizational conditions for exploration and exploitation. Journal of Management Studies,46(3), 481–509.

    Google Scholar 

  • Borgatti, S., Everett, M., & Johnson, J. (2013). Analyzing social networks (1st ed.). London: SAGE Publications Ltd.

    Google Scholar 

  • Boschma, R. (2005). Proximity and innovation: A critical assessment. Regional Studies,39(1), 61–74.

    Google Scholar 

  • Boyd, D. E., & Spekman, R. E. (2008). The market value impact of indirect ties within technology alliances. Journal of the Academy of Marketing Science,36(4), 488–500.

    Google Scholar 

  • Branstetter, L. G. (2001). Are knowledge spillovers international or intranational in scope? Microeconometric evidence from the U.S. and Japan. Journal of International Economics,53(1), 53–79.

    Google Scholar 

  • Briggs, K. (2015). Co-owner relationships conducive to high quality joint patents. Research Policy,44(8), 1566–1573.

    Google Scholar 

  • Briggs, K., & Wade, M. (2014). More is better: Evidence that joint patenting leads to quality innovation. Applied Economics,46(35), 4370–4379.

    Google Scholar 

  • Broekel, T., & Boschma, R. (2012). Knowledge networks in the Dutch aviation industry: The proximity paradox. Journal of Economic Geography,12(2), 409–433.

    Google Scholar 

  • Buerger, T., & Canter, U. (2011). The regional dimension of sectoral innovativness: an empirical investigation of two specialized suppliers and two science based industries. Papers in Regional Science,90(2, SI), 373–393.

    Google Scholar 

  • Burt, R. S. (1992). Structural holes: The social structure of competition. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Burt, R. S. (1993). The social structure of competition. Explorations in Economic Sociology,65, 103.

    Google Scholar 

  • Camisón, C., & Forés, B. (2010). Knowledge absorptive capacity: New insights for its conceptualization and measurement. Journal of Business Research,63(7), 707–715.

    Google Scholar 

  • Cantner, U., & Graf, H. (2006). The network of innovators in Jena: An application of social network analysis. Research Policy,35(4), 463–480.

    Google Scholar 

  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. Contemporary sociology. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1989). Innovation and learning: the two faces of R & D. The Economic Journal,99(397), 569–596.

    Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly,35(1), 128–152.

    Google Scholar 

  • Cohen, W. M., & Levinthal, D. A. (1994). Fortune favors the prepared firm. Management Science,40(2), 227–251.

    Google Scholar 

  • Coleman, J. (1988). Social capital in the creation of human capital. American Journal of Sociology,94, 95–120.

    Google Scholar 

  • Cowan, R., & Jonard, N. (2008). If the alliance fits …: Innovation and network dynamics. In J. A. C. Baum & T. J. Rowley (Eds.), Network strategy: Advances in strategic management (1st ed., Vol. 25, pp. 427–455). Oxford: Emerald Group Publishing Limited.

    Google Scholar 

  • Cunningham, S. W., & Werker, C. (2012). Proximity and collaboration in European nanotechnology. Papers in Regional Science,91(4), 723–742.

    Google Scholar 

  • Dangelico, R. M., Garavelli, A. C., & Petruzzelli, A. M. (2010). A system dynamics model to analyze technology districts’ evolution in a knowledge based perspective. Technovation,30(2), 142–153.

    Google Scholar 

  • Davis, G. F. (1991). Agents without principles? The spread of the poison pill through the intercorporate network. Administrative Science Quartely,36(4), 583–613.

    Google Scholar 

  • De Carolis, D. M., Litzky, B. E., & Eddleston, K. A. (2009). Why networks enhance the progress of new venture creation: The influence of social capital and cognition. Entrepreneurship Theory and Practice,33(2), 527–545.

    Google Scholar 

  • de Jong, J. P. J., & Freel, M. (2010). Absorptive capacity and the reach of collaboration in high technology small firms. Research Policy,39(1), 47–54.

    Google Scholar 

  • Dubini, P., & Aldrich, H. (1991). Personal and extended networks are central to the entrepreneurial process. Journal of Business Venturing,6(5), 305–313.

    Google Scholar 

  • Easterby-Smith, M., Lyles, M. A., & Tsang, E. W. K. (2008). Inter-organizational knowledge transfer: Current themes and future prospects. Journal of Management Studies,45(4), 677–690.

    Google Scholar 

  • Enkel, E., & Gassmann, O. (2010). Creative imitation: Exploring the case of cross-industry innovation. R & D Management,40(3), 256–270.

    Google Scholar 

  • Enkel, E., Groemminger, A., & Heil, S. J. (2018). Managing technological distance in internal and external collaborations: Absorptive capacity routines and social integration for innovation. The Journal of Technology Transfer, 43(5), 1257–1290.

    Google Scholar 

  • Fang, S.-C., Wang, M.-C., & Chen, P.-C. (2017). The influence of knowledge networks on a firm’s innovative performance. Journal of Management & Organization,23(1), 22–45.

    Google Scholar 

  • Fornahl, D., Broekel, T., & Boschma, R. (2011). What drives patent performance of German biotech firms? The impact of R&D subsidies, knowledge networks and their location. Papers in Regional Science,90(2), 395–418.

    Google Scholar 

  • Fung, M. K., & Chow, W. W. (2002). Measuring the intensity of knowledge flow with patent statistics. Economics Letters,74(3), 353–358.

    Google Scholar 

  • Garcia-Pont, C., Canales, J. I., & Noboa, F. (2009). Subsidiary strategy: The embeddedness component. Journal of Management Studies,46(2), 182–214.

    Google Scholar 

  • Gay, B., & Dousset, B. (2005). Innovation and network structural dynamics: Study of the alliance network of a major sector of the biotechnology industry. Research Policy,34(10), 1457–1475.

    Google Scholar 

  • Gilsing, V. A., Lemmens, C. E. A. V., & Duysters, G. (2007). Strategic alliance networks and innovation: A deterministic and voluntaristic view combined. Technology Analysis & Strategic Management,19(2), 227–249.

    Google Scholar 

  • Gilsing, V., Nootebomm, B., Vanhaverbeke, W., Duysters, G., & van der Oord, A. (2008). Network embeddedness and the exploration of novel technologies: Technological distance, betweenness centrality and density. Research Policy,37(10), 1717–1731.

    Google Scholar 

  • Gilsing, V., & Nooteboom, B. (2005). Density and strength of ties in innovation networks: An analysis of multimedia and biotechnology. European Management Review,2(3), 179–197.

    Google Scholar 

  • Gourieroux, C., Monfort, A., & Trognon, A. (1984). Pseudo maximum likelihood methods: THEORY. Econometrica,52(3), 681–700.

    Google Scholar 

  • Grant, R. M., & Baden-Fuller, C. (2004). A knowledge accessing theory of strategic alliances. Journal of Management Studies,41(1), 61–84.

    Google Scholar 

  • Greunz, L. (2003). Geographically and technologically mediated knowledge spillovers between European regions. Annals of Regional Science,37(4), 657–680.

    Google Scholar 

  • Guisado-González, M., González-Blanco, J., Coca-Pérez, J. L., & Guisado-Tato, M. (2017). Assessing the relationship between R&D subsidy, R&D cooperation and absorptive capacity: an investigation on the manufacturing Spanish case. Journal of Technology Transfer. https://doi.org/10.1007/s10961-017-9579-7.

    Article  Google Scholar 

  • Gulati, R. (1995). Social structure and alliance formation patterns: A longitudinal analysis. Administrative Science Quarterly,40(4), 619–652.

    Google Scholar 

  • Hagedoorn, J. (2002). Inter-firm R&D partnerships: an overview of major trends and patterns since 1960. Research Policy,31(4), 477–492.

    Google Scholar 

  • Hagedoorn, J. (2003). Sharing intellectual property rights—an exploratory study of joint patenting amongst companies. Industrial and Corporate Change,12(5), 1035–1050.

    Google Scholar 

  • Hagedoorn, J., & Cloodt, M. (2003). Measuring innovative performance: Is there an advantage in using multiple indicators? Research Policy,32(8), 1365–1379.

    Google Scholar 

  • Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. Riverside, CA: University of California.

    Google Scholar 

  • Hausman, J., Hall, B., & Griliches, Z. (1984). Econometric models for Count Data with application to the patents-R&D relationship. Econometrica,52(1), 909–938.

    Google Scholar 

  • Hautala, J. (2011). Cognitive proximity in international research groups. Journal of Knowledge Management,15(14), 601–624.

    Google Scholar 

  • Hervas-Oliver, J. L., & Albors-Garrigos, J. (2009). The role of the firm’s internal and relational capabilities in clusters: When distance and embeddedness are not enough to explain innovation. Journal of Economic Geography,9(2), 263–283.

    Google Scholar 

  • Hervas-Oliver, J. L., Albors-Garrigos, J., de-Miguel B, B., & Hidalgo, A. (2012). The role of a firm’s absorptive capacity and the technology transfer process in clusters: How effective are technology centres in low-tech clusters? Entrepreneurship and Regional Development,24(7–8), 523–559.

    Google Scholar 

  • Hilbe, J. M. (2011). Negative binomial regression. Public administration review (Second, Vol. 70). Cambridge: Cambridge University Press.

  • Ibarra, H., Kilduff, M., & Tsai, W. (2005). Zooming in and out: Connecting individuals and collectivities at the frontiers of organizational network research. Organization Science,16(4), 359–371.

    Google Scholar 

  • Jaffe, A. B. (1986). Technological opportunity and spillovers of R&D: Evidence from firms’ patents, profits and market value. The American Economic Review,76(5), 984–1001.

    Google Scholar 

  • Kaiser, U. (2002). Measuring knowledge spillovers in manufacturing and services: An empirical assessment of alternative approaches. Research Policy,31(1), 125–144.

    Google Scholar 

  • Kim, D. H. (1993). The link between individual and organizational learning. Sloan Management Review,33(1), 37–50.

    Google Scholar 

  • Kim, J. W., & Lee, H. K. (2004). Embodied and disembodied international spillovers of R&D in OECD manufacturing industries. Technovation,24(4), 359–368.

    Google Scholar 

  • Kim, C., & Song, J. (2007). Creating new technology through alliances: An empirical investigation of joint patents. Technovation,27(8), 461–470.

    Google Scholar 

  • Knoben, J., & Oerlemans, L. A. G. (2006). Proximity and inter-organizational collaboration: A literature review. International Journal of Management Reviews,8(2), 71–89.

    Google Scholar 

  • Kogut, B. (2000). The network as knowledge: Generative rules and the emergence of structure. Strategic Management Journal,21(3), 405–425.

    Google Scholar 

  • Kumar, J. A., & Ganesh, L. S. (2009). Research on knowledge transfer in organizations: A morphology. Journal of Knowledge Management,13(4), 161–174.

    Google Scholar 

  • Lane, P. J., Koka, B. R., & Pathak, S. (2006). The reification of absorptive capacity: A critical review and rejuvenation of the construct. The Academy of Management Review,31(4), 833–863.

    Google Scholar 

  • Lane, P. J., & Lubatkin, M. (1998). Relative absorptive capacity and interorganizational learning. Strategic Management Journal,19(5), 461–477.

    Google Scholar 

  • Lane, P. J., Salk, J. E., & Lyles, M. A. (2001). Absorptive capacity, learning, and performance in international joint ventures. Strategic Management Journal,22(12), 1139–1161.

    Google Scholar 

  • Laursen, K., Leone, M. I., & Torrisi, S. (2010). Technological exploration through licensing: new insights from the licensee’s point of view. Industrial and Corporate Change,19(3), 871–897.

    Google Scholar 

  • Leenders, R. T. A. J., & Dolfsma, W. A. (2016). Social networks for innovation and new product development. Journal of Product Innovation Management,33(2), 123–131.

    Google Scholar 

  • Lin, C., Wu, Y.-J., Chang, C., Wang, W., & Lee, C.-Y. (2012). The alliance innovation performance of R&D alliances—the absorptive capacity perspective. Technovation,32(5), 282–292.

    Google Scholar 

  • Lo, Y.-J., & Hung, T. M. (2015). Inter-organizational relationships and firm performance: A study of the US equity underwriting market in the investment banking industry. Journal of Management & Organization,21(5), 650–674.

    Google Scholar 

  • MacGarvie, M. (2005). The determinants of international knowledge diffusion as measured by patent citations. Economics Letters,87(1), 121–126.

    Google Scholar 

  • Makri, M., Hitt, M. A., & Lane, P. J. (2010). Complementary technologies, knowledge relatedness, and invention outcomes in high technology mergers and acquisitions. Strategic Management Journal,31(December 2015), 602–628.

    Google Scholar 

  • Martinez, H., Jaime, A., & Camacho, J. (2012). Relative absorptive capacity: A research profiling. Scientometrics,92(3), 657–674.

    Google Scholar 

  • Mattes, J. (2012). Dimensions of proximity and knowledge bases: Innovation between spatial and non-spatial factors. Regional Studies,46(8), 1085–1099.

    Google Scholar 

  • Mazzola, E., Perrone, G., & Kamuriwo, D. S. (2015). Network embeddedness and new product development in the biopharmaceutical industry: The moderating role of open innovation flow. International Journal of Production Economics,160, 106–119.

    Google Scholar 

  • McNamee, R. C. (2013). Can’t see the forest for the leaves: Similarity and distance measures for hierarchical taxonomies with a patent classification example. Research Policy,42(4), 855–873.

    Google Scholar 

  • Meier, M. (2011). Knowledge management in strategic alliances: A review of empirical evidence. International Journal of Management Reviews,13(1), 1–23.

    Google Scholar 

  • Meister, C., & Werker, C. (2004). Physical and organizational proximity in territorial innovation systems: introduction to the special issue. Journal of Economic Geography,4(1), 1–2.

    Google Scholar 

  • Menzel, M. (2008). Dynamic proximities—changing relations by creating and bridging distances. Papers in Evolutionary Economic Geography,8, 1–26.

    Google Scholar 

  • Mizruchi, M. S. (1989). Similarity of political behavior among large American corporations. American Journal of Sociology,95(2), 401–424.

    Google Scholar 

  • Mowery, D. C., & Oxley, J. E. (1995). Inward technology transfer and competitiveness: The role of national innovation systems. Cambridge Journal of Economics,19(1), 67–93.

    Google Scholar 

  • Mowery, D. C., Oxley, J. E., & Silverman, B. S. (1998). Technological overlap and interfirm cooperation: Implications for the resource-based view of the firm. Research Policy,27(5), 507–523.

    Google Scholar 

  • Murray, J. Y., & Fu, F. Q. (2016). Strategic guanxi orientation: How to manage distribution channels in China? Journal of International Management,22(1), 1–16.

    Google Scholar 

  • Nambisan, S. (2013). Industry technical committees, technological distance, and innovation performance. Research Policy,42(4), 928–940.

    Google Scholar 

  • Nieto, M. J., & Santamaría, L. (2007). The importance of diverse collaborative networks for the novelty of product innovation. Technovation,27(6–7), 367–377.

    Google Scholar 

  • Nohria, N., & Garcia-Pont, C. (1991). Global strategic linkages and industry structure. Strategic Management Journal,12(Special Issue: Global Strategy), 105–124.

    Google Scholar 

  • Nooteboom, B. (1999). Inter-firm alliances: Analysis and design. London: Psychology Press.

    Google Scholar 

  • Nooteboom, B. (2000). Learning and innovation in organizations and economies (p. 2000). Oxford: Oxford University Press.

    Google Scholar 

  • Nooteboom, B., Van Haverbeke, W., Duysters, G., Gilsing, V., & van den Oord, A. (2007). Optimal cognitive distance and absorptive capacity. Research Policy,36(7), 1016–1034.

    Google Scholar 

  • Obstfeld, D. (2005). Social networks, the Tertius lungens orientation, and involvement in innovation. Administrative Science Quartely,50(1), 100–130.

    Google Scholar 

  • OECD. (2005). Framework for biotechnology statistics. Paris: OECD.

    Google Scholar 

  • OECD. (2013). Science, technology and industry scoreboard 2013: Innovation for growth. Paris: OECD.

    Google Scholar 

  • Oerlemans, L. A. G., & Knoben, J. (2010). Configurations of knowledge transfer relations: An empirically based taxonomy and its determinants. Journal of Engineering and Technology Management,27(1–2), 33–51.

    Google Scholar 

  • Oliver, A. (2001). Strategic alliances and the learning life-cycle of biotechnology firms. Organization Studies,22(3), 467–489.

    Google Scholar 

  • Orlando, M. J. (2004). Measuring spillovers from industrial R&D: On the importance of geographic and technological proximity. The Rand Journal of Economics,35(4), 777–786.

    Google Scholar 

  • Owen-Smith, J., & Powell, W. W. (2004). Knowledge networks as channels and conduits: The effects of spillovers in the Boston biotechnology community. Organization Science,15(1), 5–21.

    Google Scholar 

  • Pangarkar, N. (2003). Determinants of alliance duration in uncertain environments: The case of the biotechnology sector. Long Range Planning,36, 269–284.

    Google Scholar 

  • Park, H., Yoon, J., & Kim, K. (2013). Identification and evaluation of corporations for merger and acquisition strategies using patent information and text mining. Scientometrics,97(3), 883–909.

    Google Scholar 

  • Peri, G., & Urban, D. (2006). Catching-up to foreign technology? Evidence on the ``Veblen-Gerschenkron’’ effect of foreign investments. Regional Science and Urban Economics,36(1), 72–98.

    Google Scholar 

  • Petruzzelli, A. M. (2011). The impact of technological relatedness, prior ties, and geographical distance on university-industry collaborations: A joint-patent analysis. Technovation,31(7), 309–319.

    Google Scholar 

  • Petruzzelli, A. M., Albino, V., & Carbonara, N. (2009). External knowledge sources and proximity. Journal of Knowledge Management,13(5), 301–318.

    Google Scholar 

  • Pfeffer, J., & Nowak, P. (1976). Joint ventures and interorganizational interdependence. Administrative Science Quarterly,21, 398–418.

    Google Scholar 

  • Phelps, C. C. (2010). A longitudinal study of the influence of alliance network structure and composition on firm exploratory innovation. Academy of Management Journal,53(4), 890–913.

    Google Scholar 

  • Phene, A., Fladmoe-Lindquist, K., & Marsh, L. (2006). Breakthrough innovations in the U.S. biotechnology industry: The effects of technological space and geographic origin. Strategic Management Journal,27(4), 369–388.

    Google Scholar 

  • Portes, A. (1998). Social capital: Its origins and applications in modern sociology. Annual Review of Sociology,24(1), 1–24.

    Google Scholar 

  • Powell, W. W., Koput, K. W., & Smith-doerr, L. (1996). Interorganizational and the collaboration locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly,41(1), 116–145.

    Google Scholar 

  • Quintana-García, C., & Benavides-Velazco, C. A. (2010). Technological relatedness in interfirm cooperation agreements and the generation of innovations. Cuadernos de Economía y Direción de Empresa,45, 43–67.

    Google Scholar 

  • Ritter, T., Wilkinson, I. F., & Johnston, W. J. (2004). Managing in complex business networks. Industrial Marketing Management,33(3), 175–183.

    Google Scholar 

  • Rosenkopf, L. A., & Almeida, P. (2003). Overcoming local search through alliances and mobility. Management Science,49(6), 751–766.

    Google Scholar 

  • Rosenkopf, L., & Nerkar, A. (2001). Beyond local search: Boundary-spanning, exploration, and impact in the optical disk industry. Strategic Management Journal,22(4), 287–306.

    Google Scholar 

  • Rothaermel, F. T., & Deeds, D. L. (2004). Exploration and exploitation alliances in biotechnology: A system of new product development. Strategic Management Journal,25(3), 201–221.

    Google Scholar 

  • Rowley, T., Behrens, D., & Krackhardt, D. (2000). Redundant governance structures: An analysis of structural and relational embeddedness in the steel and semiconductor industries. Strategic Management Journal,21(3), 369–386.

    Google Scholar 

  • Salman, N., & Saives, A.-L. (2005). Indirect networks: an intangible resource for biotechnology innovation. R&D Management,35(2), 203–215.

    Google Scholar 

  • Sampson, R. C. (2007). R&D alliances and firm performance: The impact of technological diversity and alliance organization on innovation. Academy of Management Journal,50(2), 364–386.

    Google Scholar 

  • Sapienza, H. J., Parhankangas, A., & Autio, E. (2004). Knowledge relatedness and post-spin-off growth. Journal of Business Venturing,19(6), 809–829.

    Google Scholar 

  • Schamp, E. W., Reinmaster, B., & Lo, V. (2004). Dimensions of proximity in knowledge based networks: The cases of investment banking and automobile design. European Planning Studies,12(5), 607–624.

    Google Scholar 

  • Scherngell, T., & Barber, M. J. (2009). Spatial interaction modelling of cross-region R&D collaborations: Empirical evidence from the 5th EU framework programme. Papers in Regional Science,88(3), 531–546.

    Google Scholar 

  • Schildt, H., Keil, T., & Maula, M. (2012). The temporal effects of relative and firm-level absorptive capacity on interorganizational learning. Strategic Management Journal,33(10), 1154–1173.

    Google Scholar 

  • Schilling, M. A., & Phelps, C. C. (2007). Interfirm collaboration networks: The impact of large-scale network structure on firm innovation. Management Science,53(7), 1113–1126.

    Google Scholar 

  • Schulze, A., & Brojerdi, G. J. C. (2012). The effect of the distance between partners’ knowledge components on collaborative innovation. European Management Review,9(2), 85–98.

    Google Scholar 

  • Shin, J., & Jalajas, D. (2010). Technological relatedness, boundary-spanning combination of knowledge and the impact of innovation: Evidence of an inverted-U relationship. The Journal of High Technology Management Research,21(2), 87–96.

    Google Scholar 

  • Shumpeter, J. (1939). Business cycles: A theoretical, historical, and statistical analysis of the capitalist process. New York: McGraw Hill.

    Google Scholar 

  • Soh, P. H. (2003). The role of networking alliances in information acquisition and its implications for new product performance. Journal of Business Venturing,18(6), 727–744.

    Google Scholar 

  • Soh, P. H., & Roberts, E. B. (2005). Technology alliances and networks: An external link to research capability. IEEE Transactions on Engineering Management,52(4), 419–428.

    Google Scholar 

  • Steensma, K. H., & Lyles, M. A. (2000). Explaining IJV survival in a transitional economy thorugh social exchange and knowledge based perspective. Academic Management Journal,21(AUGUST), 831–851.

    Google Scholar 

  • Stein, N. V., & Sick, N. (2014). Technological distance in academic collaborations: Evidence from battery research. International Journal of Innovation Management,18(6), 1–22.

    Google Scholar 

  • Tsai, W. (2001). Knowledge transfer in intraorganizational networks: Effects of network position and absorptive capacity on business unit innovation and performance. Academy of Management Journal,44(5), 996–1004.

    Google Scholar 

  • Tsai, K.-H. (2009). Collaborative networks and product innovation performance: Toward a contingency perspective. Research Policy,38(5), 765–778.

    Google Scholar 

  • Tushman, M. L., & Anderson, P. (1986). Technological discontinuities and organizational environments. Administrative Science Quarterly,31(3), 439–465.

    Google Scholar 

  • van de Vrande, V., Vanhaverbeke, W., & Duysters, G. (2011). Technology in-sourcing and the creation of pioneering technologies. Journal of Product Innovation Management,28(6, SI), 974–987.

    Google Scholar 

  • van Wijk, R., Jansen, J. J. P., & Lyles, M. A. (2008). Inter- and intra-organizational knowledge transfer: A meta-analytic review and assessment of its antecedents and consequences. Journal of Management Studies,45(4), 830–853.

    Google Scholar 

  • Vanhaverbeke, W., Gilsing, V., Beerkens, B., & Duysters, G. (2009). The role of alliance network redundancy in the creation of core and non-core technologies. Journal of Management Studies,46(2), 215–244.

    Google Scholar 

  • Vasudeva, G., Zaheer, A., & Hernandez, E. (2012). The embeddedness of networks: Institutions, structural holes, and innovativeness in the fuel cell industry. Organization Science,24(3), 645–663.

    Google Scholar 

  • Verdolini, E., & Galeotti, M. (2011). At home and abroad: An empirical analysis of innovation and diffusion in energy technologies. Journal of Environmental Economics and Management,61(2), 119–134.

    Google Scholar 

  • Wagner, S., & Cockburn, I. (2010). Patents and the survival of Internet-related IPOs. Research Policy,39(2), 214–228.

    Google Scholar 

  • Weick, K. E. (1995). Sensemaking in organizations (3rd ed.). London: Sage Publications.

    Google Scholar 

  • Wincent, J., Anokhin, S., Ortqvist, D., & Autio, E. (2010). Quality meets structure: Generalized reciprocity and firm-level advantage in strategic networks. Journal of Management Studies,47(4), 597–624.

    Google Scholar 

  • Wuyts, S., Colombo, M. G., Dutta, S., & Nooteboom, B. (2005). Empirical tests of optimal cognitive distance. Journal of Economic Behavior & Organization,58(2), 277–302.

    Google Scholar 

  • Zaheer, A., & Bell, G. G. (2005). Benefiting from network position: Firm capabilities, structural holes, and performance. Strategic Management Journal,26(9), 809–825.

    Google Scholar 

  • Zahra, S. A., & George, G. (2002). Absorptive capacity: a review, reconceptualization, and extension. Academy of Management Review,27(2), 185–203.

    Google Scholar 

  • Zahra, Sa, & Hayton, J. C. (2008). The effect of international venturing on firm performance: The moderating influence of absorptive capacity. Journal of Business Venturing,23(2), 195–220.

    Google Scholar 

  • Zhang, J., Baden-Fuller, C., & Mangematin, V. (2007). Technological knowledge base, R&D organization structure and alliance formation: Evidence from the biopharmaceutical industry. Research Policy,36(4), 515–528.

    Google Scholar 

  • Zidorn, W., & Wagner, M. (2013). The effect of alliances on innovation patterns: An analysis of the biotechnology industry. Industrial and Corporate Change,22(6), 1497–1524.

    Google Scholar 

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Correspondence to Hugo Ernesto Martínez Ardila.

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Martínez Ardila, H.E., Mora Moreno, J.E. & Camacho Pico, J.A. Networks of collaborative alliances: the second order interfirm technological distance and innovation performance. J Technol Transf 45, 1255–1282 (2020). https://doi.org/10.1007/s10961-018-9704-2

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