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Structural embeddedness and innovation diffusion: the moderating role of industrial technology grouping

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Abstract

Industrial technology grouping is a common phenomenon that occurs as an industry develops and evolves. However, the research on innovation diffusion has given little attention to the role of industrial technology grouping. This paper extends the prior research to analyze the impact of industrial technology grouping on innovation diffusion within the framework of structural embeddedness. In our empirical study, we selected a sample of patents in the smart phone industry during the 2004–2014 period. We used both hierarchical regression analysis and patent citation analysis to explore the impact of industrial technology grouping on innovation diffusion in the two dimensions of clustering and bridging ties, which yielded several valuable results. First, industrial technology grouping is a common phenomenon in the development of industrial technology. Moreover, the dynamic changes of technology clusters are an important driving force shaping the trends and diversity of industrial technology. Second, industrial technology grouping does not have a significant effect on firm innovation diffusion, whereas structural embeddedness directly affects innovation diffusion. Third, industrial technology grouping positively moderates the impact of structural embeddedness on firm innovation diffusion in both dimensions of clustering and bridging ties.

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References

  • Andersen, K. V. (2013). The problem of embeddedness revisited: Collaboration and market types. Research Policy, 42(1), 139–148.

    Article  Google Scholar 

  • Armstrong, A. K., Mueller, J. J., & Syrett, T. (2014). The smartphone royalty stack: Surveying royalty demands for the components within modern smartphones. http://ssrn.com/abstract=2443848. Accessed May 29, 2014.

  • Arregle, J. L., Batjargal, B., Hitt, M. A., Webb, J. W., Miller, T., & Tsui, A. S. (2015). Family ties in entrepreneurs’ social networks and new venture growth. Entrepreneurship Theory and Practice, 39(2), 313–344.

    Article  Google Scholar 

  • Baba, Y., & Walsh, J. P. (2010). Embeddedness, social epistemology and breakthrough innovation: The case of the development of statins. Research Policy, 39(4), 511–522.

    Article  Google Scholar 

  • Baer, M., Evans, K., Oldham, G. R., & Boasso, A. (2015). The social network side of individual innovation: A meta-analysis and path-analytic integration. Organizational Psychology Review, 5(3), 191–223.

    Article  Google Scholar 

  • Baker, A., Donthu, N., & Porter, C. E. (2012). Gender differences in trust formation in virtual communities. Journal of Marketing Theory and Practice, 20(1), 39–58.

    Article  Google Scholar 

  • Baum, J. A. C., Cowan, R., & Jonard, N. (2010). Network-independent partner selection and the evolution of innovation networks. Management Science, 56(11), 2094–2110.

    Article  Google Scholar 

  • Berrou, J.-P., & Combarnous, F. (2011). The personal networks of entrepreneurs in an informal African urban economy: Does the ‘strength of ties’ matter? Review of Social Economy, 70(1), 1–30.

    Article  Google Scholar 

  • Bertrand, O., & Mol, M. J. (2013). The antecedents and innovation effects of domestic and offshore R&D outsourcing: The contingent impact of cognitive distance and absorptive capacity. Strategic Management Journal, 34(6), 751–760.

    Article  Google Scholar 

  • Björk, J., & Magnusson, M. (2009). Where do good innovation ideas come from? Exploring the influence of network connectivity on innovation idea. Journal of Product Innovation Management, 26(6), 662–670.

    Article  Google Scholar 

  • Bohlmann, J. D., Calantone, R. J., & Zhao, M. (2010). The effects of market network heterogeneity on innovation diffusion: An agent-based modeling approach. Journal of Product Innovation Management, 27(5), 741–760.

    Article  Google Scholar 

  • Bond, E. U., Houston, M. B., & Tang, Y. (2008). Establishing a high-technology knowledge transfer network: The practical and symbolic roles of identification. Industrial Marketing Management, 37(6), 641–652.

    Article  Google Scholar 

  • Borgatti, S. P., & Halgin, D. S. (2011). On network theory. Organization Science, 22(5), 1168–1181.

    Article  Google Scholar 

  • Boschma, R. A., & ter Wal, A. L. J. (2007). Knowledge networks and innovative performance in an industrial district: The case of a footwear district in the south of Italy. Industry and Innovation, 14(2), 177–199.

    Article  Google Scholar 

  • Boso, N., Story, V. M., & Cadogan, J. W. (2013). Entrepreneurial orientation, market orientation, network ties, and performance: Study of entrepreneurial firms in a developing economy. Journal of Business Venturing, 28(6), 708–727.

    Article  Google Scholar 

  • Bradford, M., & Florin, J. (2003). Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems. International Journal of Accounting Information Systems, 4(3), 205–225.

    Article  Google Scholar 

  • Bramwell, A., Nelles, J., & David, A. W. (2008). Knowledge, innovation and institutions: Global and local dimensions of the ICT cluster in Waterloo. Canada. Regional Studies, 42(1), 101–116.

    Article  Google Scholar 

  • Buechel, B., & Buskens, V. (2013). The dynamics of closeness and betweenness. Journal of Mathematical Sociology, 37(3), 159–191.

    Article  MathSciNet  MATH  Google Scholar 

  • Burt, R. S. (2004). Structural holes and good ideas. American Journal of Sociology, 110(2), 349–399.

    Article  Google Scholar 

  • Byosiere, P., Luethge, D. J., Vas, A., & Salmador, M. P. (2010). Diffusion of organisational innovation: Knowledge transfer through social networks. International Journal of Technology Management, 49(4), 401–420.

    Article  Google Scholar 

  • Cai, S., Yang, Z., & Jun, M. (2011). Cooperative norms, structural mechanisms, and supplier performance: Empirical evidence from Chinese manufacturers. Journal of Purchasing and Supply Management, 17(1), 1–10.

    Article  Google Scholar 

  • Cantner, U., & Rake, B. (2014). International research networks in pharmaceuticals: Structure and dynamics. Research Policy, 43(2), 333–348.

    Article  Google Scholar 

  • Ceci, F., & Iubatti, D. (2012). Personal relationships and innovation diffusion in SME networks: A content analysis approach. Research Policy, 41(3), 565–579.

    Article  Google Scholar 

  • Centola, D. (2010). The spread of behavior in an online social network experiment. Science, 329(5996), 1194–1197.

    Article  Google Scholar 

  • Chang, S.-B., Lai, K.-K., & Chang, S.-M. (2009). Exploring technology diffusion and classification of business methods: Using the patent citation network. Technological Forecasting and Social Change, 76(1), 107–117.

    Article  Google Scholar 

  • Chien, S.-H., Chen, Y.-H., & Hsu, C.-Y. (2012). Exploring the impact of trust and relational embeddedness in e-marketplaces: An empirical study in Taiwan. Industrial Marketing Management, 41(3), 460–468.

    Article  Google Scholar 

  • Cho, Y., Hwang, J., & Lee, D. (2012). Identification of effective opinion leaders in the diffusion of technological innovation: A social network approach. Technological Forecasting and Social Change, 79(1), 97–106.

    Article  Google Scholar 

  • Choi, H., Kim, S.-H., & Lee, J. (2010). Role of network structure and network effects in diffusion of innovations. Industrial Marketing Management, 39(1), 170–177.

    Article  Google Scholar 

  • Corsaro, D., Cantù, C., & Tunisini, A. (2012). Actors’ heterogeneity in innovation networks. Industrial Marketing Management, 41(5), 780–789.

    Article  Google Scholar 

  • Crona, B., & Bodin, Ö. (2010). Power asymmetries in small-scale fisheries: A barrier to governance transformability? Ecology and Society, 15(4), 32.

    Article  Google Scholar 

  • Delre, S. A., Jager, W., Bijmolt, T. H. A., & Marco, A. J. (2010). Will it spread or not? The effects of social influences and network topology on innovation diffusion. Journal of Product Innovation Management, 27(2), 267–282.

    Article  Google Scholar 

  • Desmarchelier, B., & Fang, E. S. (2016). National culture and innovation diffusion. Exploratory insights from agent-based modeling. Technological Forecasting and Social Change, 105, 121–128.

    Article  Google Scholar 

  • Ertem, Z., Veremyev, A., & Butenko, S. (2016). Detecting large cohesive subgroups with high clustering coefficients in social networks. Social Networks, 46, 1–10.

    Article  Google Scholar 

  • Fleming, L., Mingo, S., & Chen, D. (2007). Collaborative brokerage, generative creativity, and creative success. Administrative Science Quarterly, 52(3), 443–475.

    Article  Google Scholar 

  • Freeman, L. C. (1978/79). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215–239.

  • Fritsch, M., & Kauffeld-Monz, M. (2008). The impact of network structure on knowledge transfer: An application of social network analysis in the context of regional innovation networks. Annals of Regional Science, 44(1), 21–38.

    Article  Google Scholar 

  • Gebreeyesus, M., & Mohnen, P. (2013). Innovation performance and embeddedness in networks: Evidence from the Ethiopian footwear cluster. World Development, 41(1), 302–316.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Giuliani, E. (2011). The Role of technological gatekeepers in the growth of industrial clusters: Evidence from Chile. Regional Studies, 45(10), 1329–1348.

    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 

  • Gonzalez, G. R. C., Danny, P., & Palmatier, R. W. (2014). Synergistic effects of relationship managers’s social networks on sales performance. Journal of Marketing, 78(1), 76–94.

    Article  Google Scholar 

  • Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91(3), 481–510.

    Article  Google Scholar 

  • Greve, H. R. (2009). Bigger and safer: The diffusion of competitive advantage. Strategic Management Journal, 30(1), 1–23.

    Article  Google Scholar 

  • Guan, J., Zhang, J., & Yan, Y. (2015). The impact of multilevel networks on innovation. Research Policy, 44(3), 545–559.

    Article  Google Scholar 

  • Guler, I., & Nerkar, A. (2012). The impact of global and local cohesion on innovation in the pharmaceutical industry. Strategic Management Journal, 33(5), 535–549.

    Article  Google Scholar 

  • Guseo, R., & Guidolin, M. (2010). Cellular automata with network incubation in information technology diffusion. Physica A: Statistical Mechanics and its Applications, 389(12), 2422–2433.

    Article  Google Scholar 

  • Han, K., Oh, W., Im, K. S., Chang, R. M., Oh, H., & Pinsonneault, A. (2012). Value cocreation and wealth spillover in open innovation alliances. MIS Quarterly, 36(1), 291–316.

    Google Scholar 

  • Hendrickson, B., Rosen, D., & Aune, R. K. (2011). An analysis of friendship networks, social connectedness, homesickness, and satisfaction levels of international students. International Journal of Intercultural Relations, 35(3), 281–295.

    Article  Google Scholar 

  • Hernandez, E., Sanders, W. G., & Tuschke, A. (2014). Network defense: Pruning, grafting, and closing to prevent leakage of strategic knowledge to rivals. Academy of Management Journal, 58(4), 1233–1260.

    Article  Google Scholar 

  • Iyengar, R., Bulte, C. V. D., & Valente, T. W. (2010). Opinion leadership and social contagion in new product diffusion. Management Science, 30(2), 195–212.

    Google Scholar 

  • Karamanos, A. G. (2012). Leveraging micro- and macro-structures of enbeddedness in alliance networks for explotatory innovation in biotechnology. R&D Management, 42(1), 71–89.

    Article  Google Scholar 

  • Karna, A., Täube, F., & Sonderegger, P. (2013). Evolution of innovation networks across geographical and organizational boundaries: A study of R&D subsidiaries in the Bangalore IT cluster. European Management Review, 10(4), 211–226.

    Article  Google Scholar 

  • Katila, R., & Ahuja, G. (2002). Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of Management Journal, 45(6), 1183–1194.

    Article  Google Scholar 

  • Katona, Z., Zubcsek, P. P., & Sarvary, M. (2011). Network effects and personal influences: The dffusion of an online social network. Journal of Marketing Research, 48(3), 425–443.

    Article  Google Scholar 

  • Keller, J., Markmann, C., & von der Gracht, H. A. (2015). Foresight support systems to facilitate regional innovations: A conceptualization case for a German logistics cluster. Technological Forecasting and Social Change, 97(1), 15–28.

    Article  Google Scholar 

  • Kim, J. Y. (2016). Message strategies in smartphone patent battles: Ownership and innovation capability. Journal of Communication Management, 20(3), 255–267.

    Article  Google Scholar 

  • Kim, Y., Choi, T. Y., Yan, T., & Dooley, K. (2011). Structural investigation of supply networks: A social network analysis approach. Journal of Operations Management, 29(3), 194–211.

    Article  Google Scholar 

  • Kocsis, G., & Kun, F. (2008). The effect of network topologies on the spreading of technological developments. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), 10014.

    Article  Google Scholar 

  • Kossinets, G., & Watts, D. J. (2009). Origins of homophily in an evolving social network. American Journal of Sociology, 115(2), 405–450.

    Article  Google Scholar 

  • Lahiri, N., & Narayanan, S. (2013). Vertical integration, innovation, and alliance portfolio size: Implications for firm performance. Strategic Management Journal, 34(9), 1042–1064.

    Article  Google Scholar 

  • Lai, Y.-L., Hsu, M.-S., Lin, F.-J., Chen, Y.-M., & Lin, Y.-H. (2014). The effects of industry cluster knowledge management on innovation performance. Journal of Business Research, 67(5), 734–739.

    Article  Google Scholar 

  • Lambiotte, R., & Panzarasa, P. (2009). Communities, knowledge creation, and information diffusion. Journal of Informetrics, 3(3), 180–190.

    Article  Google Scholar 

  • Lee, W., & Choi, J.-I. (2013). Industry-academia cooperation in creative innovation clusters: A comparison of two clusters in Korea. Academy of Entrepreneurship Journal, 19(3), 79–95.

    Google Scholar 

  • Lee, S. H., Cotte, J., & Noseworthy, T. J. (2010). The role of network centrality in the flow of consumer influence. Journal of Consumer Psychology, 20(1), 66–77.

    Article  Google Scholar 

  • Lee, Y.-G., & Song, Y.-I. (2007). Selecting the key research areas in nano-technology field using technology cluster analysis: A case study based on national R&D programs in South Korea. Technovation, 27(1–2), 57–64.

    Article  Google Scholar 

  • Leydesdorff, L., & Rafols, I. (2011). Local emergence and global diffusion of research technologies: An exploration of patterns of network formation. Journal of the American Society for Information Science and Technology, 62(5), 846–860.

    Article  Google Scholar 

  • Li, Y.-M., & Shiu, Y.-L. (2012). A diffusion mechanism for social advertising over microblogs. Decision Support Systems, 54(1), 9–22.

    Article  Google Scholar 

  • Li, W., Veliyath, R., & Tan, J. (2013). Network characteristics and firm performance: An examination of the relationships in the context of a cluster. Journal of Small Business Management, 51(1), 1–22.

    Article  Google Scholar 

  • Lin, J. L., Fang, S.-C., Fang, S.-R., & Tsai, F.-S. (2009). Network embeddedness and technology transfer performance in R&D consortia in Taiwan. Technovation, 29(11), 763–774.

    Article  Google Scholar 

  • Lin, M., & Li, N. (2010). Scale-free network provides an optimal pattern for knowledge transfer. Physica A: Statistical Mechanics and its Applications, 389(3), 473–480.

    Article  Google Scholar 

  • Liu, B. S.-C., Madhavan, R., & Sudharshan, D. (2005). DiffuNET: The impact of network structure on diffusion of innovation. European Journal of Innovation Management, 8(2), 240–262.

    Article  Google Scholar 

  • Liu, X., & Wu, X. (2011). Technology embeddedness, innovation differentiation strategies and firm performance: Evidence from Chinese manufacturing firms. Innovation Management Policy Practice, 131, 20–35.

    Article  Google Scholar 

  • Love, J. H., Roper, S., & Hewitt-Dundas, N. (2010). Service innovation, embeddedness and business performance: Evidence from Northern Ireland. Regional Studies, 44(8), 983–1004.

    Article  Google Scholar 

  • Ma, R., Huang, Y.-C., & Shenkar, O. (2011). Social networks and opportunity recognition: A cultural comparison between Taiwan and the United States. Strategic Management Journal, 32(11), 1183–1205.

    Article  Google Scholar 

  • Maghnati, F., & Ling, K. C. (2013). Exploring the relationship between experiential value and usage attitude towards mobile apps among the smartphone users. International Journal of Business and Management, 8(4), 1–9.

    Article  Google Scholar 

  • Makri, M., Hitt, M. A., & Lane, P. J. (2009). Complementary technologies, knowledge relatedness, and invention outcomes in high technology mergers and acquisitions. Strategic Management Journal, 31(6), 602–628.

    Google Scholar 

  • Markóczy, L., Li Sun, S., Peng, M. W., Stone Shi, W., & Ren, B. (2013). Social network contingency, symbolic management, and boundary stretching. Strategic Management Journal, 34(11), 1367–1387.

    Article  Google Scholar 

  • Mason, C. H., & Perreault, W. D., Jr. (1991). Collinearity, power, and interpretation of multiple regression analysis. Journal of Marketing Research, 28(3), 268–280.

    Article  Google Scholar 

  • McDonald, D. B. (2007). Predicting fate from early connectivity in a social network. Proceedings of the National Academy Sciences of the United States of America, 104(26), 10910–10914.

    Article  Google Scholar 

  • Merwe, R. V. D., & Heerden, G. V. (2009). Finding and utilizing opinion leaders: Social networks and the power of relationships. South African Journal of Business Management, 40(3), 65–76.

    Google Scholar 

  • Morrison, A., Rabellotti, R., & Zirulia, L. (2013). When do global pipelines enhance the diffusion of knowledge in clusters? Economic Geography, 89(1), 77–96.

    Article  Google Scholar 

  • Munari, F., Sobrero, M., & Malipiero, A. (2011). Absorptive capacity and localized spillovers: Focal firms as technological gatekeepers in industrial districts. Industrial and Corporate Change, 21(2), 429–462.

    Article  Google Scholar 

  • Muñiz, A. S. G., Raya, A. M., & Carvajal, C. R. (2008). Spanish and European innovation diffusion: A structural hole approach in the input–output field. Annals of Regional Science, 44(1), 147–165.

    Article  Google Scholar 

  • Opsahl, T. (2013). Triadic closure in two-mode networks: Redefining the global and local clustering coefficients. Social Networks, 35(2), 159–167.

    Article  Google Scholar 

  • Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251.

    Article  Google Scholar 

  • Padula, G. (2008). Enhancing the innovation performance of firms by balancing cohesiveness and bridging ties. Long Range Planning, 41(4), 395–419.

    Article  Google Scholar 

  • Pegoretti, G., Rentocchini, F., & Vittucci Marzetti, G. (2012). An agent-based model of innovation diffusion: Network structure and coexistence under different information regimes. Journal of Economic Interaction and Coordination, 7(2), 145–165.

    Article  Google Scholar 

  • Peterman, A., Kourula, A., & Levitt, R. (2014). Balancing act: Government roles in an energy conservation network. Research Policy, 43(6), 1067–1082.

    Article  Google Scholar 

  • Phelps, 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.

    Article  Google Scholar 

  • Phelps, C., Heidl, R., & Wadhwa, A. (2012). Knowledge, networks, and knowledge networks: A review and research agenda. Journal of Management, 38(4), 1115–1166.

    Article  Google Scholar 

  • Poppo, L., & Zenger, T. (2002). Do formal contracts and relational governance function as substitutes or complements? Strategic Management Journal, 23(8), 707–725.

    Article  Google Scholar 

  • Reinholt, M., Pedersen, T., & Foss, N. J. (2011). Why a central network position isn’t enough: The role of motivation and ability for knowledge sharing in employee networks. Academy of Management Journal, 54(6), 1277–1297.

    Article  Google Scholar 

  • Rogers, E. M. (1995). Diffusion of innovations. New York: Free Press.

    Google Scholar 

  • Roper, S., Vahter, P., & Love, J. H. (2013). Externalities of openness in innovation. Research Policy, 42(9), 1544–1554.

    Article  Google Scholar 

  • Rost, K. (2011). The strength of strong ties in the creation of innovation. Research Policy, 40(4), 588–604.

    Article  Google Scholar 

  • Rothaermel, F. T., & Hess, A. M. (2007). Building dynamic capabilities: Innovation driven by individual-, firm-, and network-level effects. Organization Science, 18(6), 898–921.

    Article  Google Scholar 

  • Schilling, M. A., & Phelps, C. C. (2005). Network effects and personal influences: The diffusion of an online social network. Journal of Marketing Research, 48(3), 425–443.

    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.

    Article  MATH  Google Scholar 

  • Semitiel-García, M., & Noguera-Méndez, P. (2012). The structure of inter-industry systems and the diffusion of innovations: The case of Spain. Technological Forecasting and Social Change, 79(8), 1548–1567.

    Article  Google Scholar 

  • Silvestre, B. S., & Neto, R. E. S. (2014). Capability accumulation, innovation, and technology diffusion: Lessons from a base of the Pyramid cluster. Technovation, 34(5–6), 270–283.

    Article  Google Scholar 

  • Singh, J., & Fleming, L. (2010). Lone inventors as sources of breakthroughs: Myth or reality? Management Science, 56(1), 41–56.

    Article  Google Scholar 

  • Soda, G. (2011). The management of firms’ alliance network positioning: Implications for innovation. European Management Journal, 29(5), 377–388.

    Article  Google Scholar 

  • Song, Z., Sun, Y., Yi, J., & Ni, L. (2015). Methods of importance evaluation for information subsystems in manufacturing enterprises based on centrality. Open Journal of Business and Management, 3(2), 125–134.

    Article  Google Scholar 

  • Spencer, J. W. (2003). Firms’ knowledge-sharing strategies in the global innovation system: Empirical evidence from the flat panel display industry. Strategic Management Journal, 24(3), 217–233.

    Article  Google Scholar 

  • Stam, W., Arzlanian, S., & Elfring, T. (2014). Social capital of entrepreneurs and small firm performance: A meta-analysis of contextual and methodological moderators. Journal of Business Venturing, 29(1), 152–173.

    Article  Google Scholar 

  • Sullivan, B. N., & Tang, Y. (2012). Small-world networks, absorptive capacity, and firm performance: Evidence from the U.S. venture capital industry. International Journal of Strategic Change Management, 4(2), 149–175.

    Article  Google Scholar 

  • Sznajd-Weron, K., Szwabiński, J., Weron, R., & Weron, T. (2014). Rewiring the network. What helps an innovation to diffuse? Journal of Statistical Mechanics: Theory and Experiment, 2014(3), 03007.

    Article  MathSciNet  Google Scholar 

  • Tortoriello, M., Reagans, R., & McEvily, B. (2012). Bridging the knowledge gap: The influence of strong ties, network cohesion, and network range on the transfer of knowledge between organizational units. Organization Science, 23(4), 1024–1039.

    Article  Google Scholar 

  • Tran, M. (2012). Agent-behaviour and network influence on energy innovation diffusion. Communications in Nonlinear Science and Numerical Simulation, 17(9), 3682–3695.

    Article  MathSciNet  Google Scholar 

  • Tsai, K.-H., & Wang, J.-C. (2009). External technology sourcing and innovation performance in LMT sectors: An analysis based on the Taiwanese Technological Innovation Survey. Research Policy, 38(3), 518–526.

    Article  Google Scholar 

  • Tseng, F.-M., Liu, Y.-L., & Wu, H.-H. (2014). Market penetration among competitive innovation products: The case of the smartphone operating system. Journal of Engineering and Technology Management, 32, 40–59.

    Article  Google Scholar 

  • Valente, T. W., & Fujimoto, K. (2010). Bridging: Locating critical connectors in a network. Socical Networks, 32(3), 212–220.

    Article  Google Scholar 

  • van Eck, P. S., Jager, W., & Leeflang, P. S. H. (2011). Opinion leaders’ role in innovation diffusion: A simulation study. Journal of Product Innovation Management, 28(2), 187–203.

    Article  Google Scholar 

  • van Woerkom, M., & Sanders, K. (2010). The romance of learning from disagreement. The effect of cohesiveness and disagreement on knowledge sharing behavior and individual performance within teams. Journal of Business and Psychology, 25(1), 139–149.

    Article  Google Scholar 

  • Vos, S., Janssen, M., Goudsmit, J., Lauwerijssen, C., & Brombacher, A. (2016). From problem to solution: Developing a personalized smartphone application for recreational runners following a three-step design approach. Procedia Engineering, 147, 799–805.

    Article  Google Scholar 

  • Walter, J., Lechner, C., & Kellermanns, F. W. (2007). Knowledge transfer between and within alliance partners: Private versus collective benefits of social capital. Journal of Business Research, 60(7), 698–710.

    Article  Google Scholar 

  • Wang, H., Wang, W., Yang, J., & Yu, P. S. (2002). Clustering by pattern similarity in large data sets. In Proceedings of the 2002 ACM SIGMOD international conference on Management of data, 394–405.

  • Wang, X., Zhang, X., & Xu, S. (2011). Patent co-citation networks of Fortune 500 companies. Scientometrics, 88(3), 761–770.

    Article  Google Scholar 

  • Woerter, M. (2011). Technology proximity between firms and universities and technology transfer. Journal of Technology Transfer, 37(6), 828–866.

    Article  Google Scholar 

  • Wölfer, R., Faber, N. S., & Hewstone, M. (2015). Social network analysis in the science of groups: Cross-sectional and longitudinal applications for studying intra- and intergroup behavior. Group Dynamics: Theory, Research, and Practice, 19(1), 45–61.

    Article  Google Scholar 

  • Yang, H., Lin, Z., & Peng, M. W. (2011). Behind acquisitions of alliance partners: Exploratory learning and network embeddedness. Academy of Management Journal, 54(5), 1069–1080.

    Article  Google Scholar 

  • Zhang, Y., & Li, H. (2010). Innovation search of new ventures in a technology cluster: The role of ties with service intermediaries. Strategic Management Journal, 31(1), 88–109.

    Article  MathSciNet  Google Scholar 

  • Zhang, Y., Li, H., & Schoonhoven, C. B. (2009). Intercommunity relationships and community growth in China’s high technology industries 1988–2000. Strategic Management Journal, 30(2), 163–183.

    Article  Google Scholar 

  • Zhao, J. Z., & Anand, J. (2013). Beyond boundary spanners: The ‘collective bridge’ as an efficient inter-unit structure for transferring collective knowledge. Strategic Management Journal, 34(13), 1513–1530.

    Article  Google Scholar 

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Acknowledgements

This work was supported by National Natural Science Foundation of China under Grant Nos. 71572026 and 71632004.

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Lyu, Y., Liu, Q., He, B. et al. Structural embeddedness and innovation diffusion: the moderating role of industrial technology grouping. Scientometrics 111, 889–916 (2017). https://doi.org/10.1007/s11192-017-2320-3

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