Abstract
In organizations, knowledge creation activities are embedded in collaborative networks and are influenced by their partners. Therefore, we examine how entire networks change over time in this study, as well as the reasoning behind the structures of ego networks based on unique scientific research discoveries published in the emerging cross-disciplinary field of nano-energy. These data were extracted from Science Citation Index Expanded. Specifically, we mainly focus on two dimensions of ego network changes: network growth and diversity. Results demonstrate the recent remarkable growth of inter-organizational collaborative networks in the nano-energy field and empirically prove that the subsequent growth and diversity of ego networks are caused by three coexisting driving forces (collaborative capacity, network status position and cohesion) that act collectively. Our study is conducted at the organizational level because we investigate the universities, research institutes and firms that participate in nano-energy scientific research and the collaborative networks formed through co-authorships among these institutions in knowledge creation processes. Moreover, our study has significant implications for the scientific research conducted by organizations in developing countries and emerging fields.
Similar content being viewed by others
Notes
The 5-year moving window has also been implemented in our study process, but it did not affect the empirical results significantly.
Although many universities, research institutes, and other types of organizations conduct nano-energy scientific research in China, our empirical test considered only organizations performing stable or long-term scientific research in the nano-energy field because of the repeated entries of new organizations and the exits of existing organizations.
References
Ahuja, G., Soda, G., & Zaheer, A. (2012). The genesis and dynamics of organizational networks. Organization Science, 23(2), 434–448.
Alivisatos, P., Cummings, P., De Yoreo, J., Fichthorn, K., Gates, B., Hwang, R., et al. (2005). Nanoscience research for energy needs. Alexandria, VA, USA: Report of the National Nanotechnology Initiative Grand Challenge Workshop.
Arora, S. K., Porter, A. L., Youtie, J., & Shapira, P. (2013). Capturing new developments in an emerging technology: An updated search strategy for identifying nanotechnology research outputs. Scientometrics, 95(1), 351–370.
Barabási, A.-L. (2012). Network science: Luck or reason. Nature, 489(7417), 507–508.
Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92(5), 1170–1182.
Borgatti, S. P. (2005). Centrality and network flow. Social Networks, 27(1), 55–71.
Borgatti, S. P., & Halgin, D. S. (2011). On network theory. Organization Science, 22(5), 1168–1181.
Bouty, I. (2000). Interpersonal and interaction influences on informal resource exchanges between R&D researchers across organizational boundaries. Academy of Management Journal, 43(1), 50–65.
Broad, W. J. (1981). The publishing game: Getting more for less. Science, 211(4487), 1137–1139.
Buchmann, T., & Pyka, A. (2013). The evolution of innovation networks: The case of a German automotive network. FZID discussion papers, No. 70-2013. http://nbn-resolving.de/urn:nbn:de:bsz:100-opus-8338.
Burt, R. S. (1992). Structural holes: The social structure of competition. Cambridge: Harvard University Press.
Cannella, A. A., & McFadyen, M. A. (2013). Changing the exchange the dynamics of knowledge worker ego networks. Journal of Management. doi:10.1177/0149206313511114.
Cattani, G., & Ferriani, S. (2008). A core/periphery perspective on individual creative performance: Social networks and cinematic achievements in the Hollywood film industry. Organization Science, 19(6), 824–844.
Chandler, D., Haunschild, P. R., Rhee, M., & Beckman, C. M. (2013). The effects of firm reputation and status on interorganizational network structure. Strategic Organization, 11(3), 217–244.
Connelly, M. C., & Sekhar, J. A. (2012). US energy production activity and innovation. Technological Forecasting and Social Change, 79(1), 30–46.
Contractor, N. S., Wasserman, S., & Faust, K. (2006). Testing multitheoretical, multilevel hypotheses about organizational networks: An analytic framework and empirical example. Academy of Management Review, 31(3), 681–703.
Cricelli, L., & Grimaldi, M. (2010). Knowledge-based inter-organizational collaborations. Journal of Knowledge Management, 14(3), 348–358.
Demirkan, I., Deeds, D. L., & Demirkan, S. (2013). Exploring the role of network characteristics, knowledge quality, and inertia on the evolution of scientific networks. Journal of Management, 39(6), 1462–1489.
Eagle, N., Macy, M., & Claxton, R. (2010). Network diversity and economic development. Science, 328(5981), 1029–1031.
Ebbers, J. J., & Wijnberg, N. M. (2010). Disentangling the effects of reputation and network position on the evolution of alliance networks. Strategic Organization, 8(3), 255–275.
EIA U. (2014). International energy outlook 2014. Washington, DC: United States Energy Information Administration. http://www.eia.gov/countries/cab.cfm?fips=CH
Forti, E., Franzoni, C., & Sobrero, M. (2013). Bridges or isolates? Investigating the social networks of academic inventors. Research Policy, 42(8), 1378–1388.
Freeman, L. C. (1979). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215–239.
Fromer, N. A., & Diallo, M. S. (2013). Nanotechnology and clean energy: Sustainable utilization and supply of critical materials. Journal of Nanoparticle Research, 15(11), 2011.
Gans, J. S., & Murray, F. (2013). Credit history: The changing nature of scientific credit. National Bureau of Economic Research (NBER working paper no. w19538). http://www.nber.org/papers/w19538
Goerzen, A., & Beamish, P. W. (2005). The effect of alliance network diversity on multinational enterprise performance. Strategic Management Journal, 26(4), 333–354.
Gonzalez-Brambila, C. N., Veloso, F. M., & Krackhardt, D. (2013). The impact of network embeddedness on research output. Research Policy, 42(9), 1555–1567.
Granados, F. J., & Knoke, D. (2013). Organizational status growth and structure: An alliance network analysis. Social Networks, 35(1), 62–74.
Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.
Guan, J., & Liu, N. (2014). Measuring scientific research in emerging nano-energy field. Journal of Nanoparticle Research, 16(4), 2356.
Guan, J., & Zhao, Q. (2013). The impact of university–industry collaboration networks on innovation in nanobiopharmaceuticals. Technological Forecasting and Social Change, 80(7), 1271–1286.
Gulati, R., & Gargiulo, M. (1999). Where do interorganizational networks come from? American Journal of Sociology, 104(5), 1439–1493.
Gulati, R., Sytch, M., & Tatarynowicz, A. (2012). The rise and fall of small worlds: Exploring the dynamics of social structure. Organization Science, 23(2), 449–471.
IWEP. (2013). The Chinese academy of social sciences institute of world economics and politics, World Energy China Outlook 2013–2014. Beijing, China: Social Sciences Academic Press.
Jensen, M., & Roy, A. (2008). Staging exchange partner choices: When do status and reputation matter? Academy of Management Journal, 51(3), 495–516.
Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397.
Koka, B. R., Madhavan, R., & Prescott, J. E. (2006). The evolution of interfirm networks: Environmental effects on patterns of network change. Academy of Management Review, 31(3), 721–737.
Lee, J. J. (2010). Heterogeneity, brokerage, and innovative performance: Endogenous formation of collaborative inventor networks. Organization Science, 21(4), 804–822.
Lee, K., & Lee, S. (2013). Patterns of technological innovation and evolution in the energy sector: A patent-based approach. Energy Policy, 59, 415–432.
Lee, S., Lee, H. J., & Yoon, B. (2012). Modeling and analyzing technology innovation in the energy sector: Patent-based HMM approach. Computers & Industrial Engineering, 63(3), 564–577.
Leung, R. C. (2013). Networks as sponges: International collaboration for developing nanomedicine in China. Research Policy, 42(1), 211–219.
Li, E. Y., Liao, C. H., & Yen, H. R. (2013). Co-authorship networks and research impact: A social capital perspective. Research Policy, 42(9), 1515–1530.
Ma, N., & Guan, J. (2005). An exploratory study on collaboration profiles of Chinese publications in molecular biology. Scientometrics, 65(3), 343–355.
Makadok, R. (2001). Toward a synthesis of the resource-based and dynamic-capability views of rent creation. Strategic Management Journal, 22(5), 387–401.
Menéndez-Manjón, A., Moldenhauer, K., Wagener, P., & Barcikowski, S. (2011). Nano-energy research trends: Bibliometrical analysis of nanotechnology research in the energy sector. Journal of Nanoparticle Research, 13(9), 3911–3922.
Miao, X. (2014). Science ethics: Young scientists speak. Science, 345(6192), 24–25.
Milanov, H., & Shepherd, D. A. (2013). The importance of the first relationship: The ongoing influence of initial network on future status. Strategic Management Journal, 34(6), 727–750.
Obstfeld, D. (2005). Social networks, the tertius iungens orientation, and involvement in innovation. Administrative Science Quarterly, 50(1), 100–130.
Phelps, C., Heidl, R., & Wadhwa, A. (2012). Knowledge, networks, and knowledge networks a review and research agenda. Journal of Management, 38(4), 1115–1166.
Podolny, J. M. (2001). Networks as the pipes and prisms of the market. American Journal of Sociology, 107(1), 33–60.
Podolny, J. M. (2005). Status signals: A sociological study of market competition. Princeton: Princeton University Press.
Ronda-Pupo, G. A., & Guerras-Martín, L. Á. (2010). Dynamics of the scientific community network within the strategic management field through the strategic management journal 1980–2009: The role of cooperation. Scientometrics, 85(3), 821–848.
Rosenkopf, L., & Padula, G. (2008). Investigating the microstructure of network evolution: Alliance formation in the mobile communications industry. Organization Science, 19(5), 669–687.
Sci2Team. (2009). Science of science (Sci2) tool. Bloomington: Indiana University and SciTech Strategies. http://sci2.cns.iu.edu
Shannon, C. E. (2001). A mathematical theory of communication. ACM SIGMOBILE Mobile Computing and Communications Review, 5(1), 3–55.
Simcoe, T. S., & Waguespack, D. M. (2011). Status, quality, and attention: What’s in a (missing) name? Management Science, 57(2), 274–290.
So, D. S., Kim, C. W., Chung, P. S., & Jhon, M. S. (2012). Nanotechnology policy in Korea for sustainable growth. Journal of Nanoparticle Research, 14(6), 854.
Sosa, M. E. (2011). Where do creative interactions come from? The role of tie content and social networks. Organization Science, 22(1), 1–21.
Stuart, T. E. (1998). Network positions and propensities to collaborate: An investigation of strategic alliance formation in a high-technology industry. Administrative Science Quarterly, 43(3), 668–698.
Sun, Y.-T., & Liu, F.-C. (2013). Measuring international trade-related technology spillover: A composite approach of network analysis and information theory. Scientometrics, 94(3), 963–979.
Tegart, G. (2009). Energy and nanotechnologies: Priority areas for Australia’s future. Technological Forecasting and Social Change, 76(9), 1240–1246.
Uzzi, B. (1997). Social structure and competition in interfirm networks: The paradox of embeddedness. Administrative Science Quarterly, 42(1), 35–67.
Wang, Z.-Z., & Zhu, J. J. (2014). Homophily versus preferential attachment: Evolutionary mechanisms of scientific collaboration networks. International Journal of Modern Physics C, 25(05), 40014.
Wasserman, S. (1994). Social network analysis: Methods and applications (Vol. 8). Cambridge: Cambridge University Press.
Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440–442.
Xie, F., & Levinson, D. (2007). Measuring the structure of road networks. Geographical analysis, 39(3), 336–356.
Zaheer, A., & Soda, G. (2009). Network evolution: The origins of structural holes. Administrative Science Quarterly, 54(1), 1–31.
Author information
Authors and Affiliations
Corresponding author
Appendix: Definition of search queries for nano-energy articles in the SCI-E database
Appendix: Definition of search queries for nano-energy articles in the SCI-E database
Searching terms | |
---|---|
Nanotechnology | |
#1 | TS = (nano*) |
#2 | TS = ((“quantum dot*” OR “quantum well*” OR “quantum wire*”) NOT nano*) |
#3 | TS = (((“self assembl*” OR “self organiz*” OR “directed assembl*”) AND MolEnv-I) NOT nano*) |
#4 | TS = ((“molecul* motor*” OR “molecul* ruler*” OR “molecul* wir*” OR “molecul* devic*” OR “molecular engineering” OR “molecular electronic*” OR “single molecul*” OR fullerene* OR buckyball OR buckminsterfullerene OR C60 OR “C-60” OR methanofullerene OR metallofullerene OR SWCNT OR MWCNT OR “coulomb blockad*” OR bionano* OR “Langmuir-Blodgett” OR Coulombstaircase* OR “PDMS stamp*” OR graphene OR “dye-sensitized solar cell” OR DSSC OR ferrofluid* OR “core-shell”) NOT nano*) |
#5 | TS = ((((TEM or STM or EDX or AFM or HRTEM or SEM or EELS or SERS or MFM) OR “atom* force microscop*” OR “tunnel* microscop*” OR “scanning probe microscop*” OR “transmission electron microscop*” OR “scanning electron microscop*” OR “energy dispersive X-ray” OR “xray photoelectron*” OR “x-ray photoelectron” OR “electron energy loss spectroscop*” OR “enhanced raman-scattering” OR “surface enhanced raman scattering” OR “single molecule microscopy” OR “focused ion beam” OR “ellipsometry” OR “magnetic force microscopy”) AND MolEnv-R) NOT nano*) |
#6 | TS = (((NEMS OR Quasicrystal* OR “quasi-crystal*” OR “quantum size effect” OR “quantum device”) AND MoleEnv-I) NOT nano*) |
#7 | TS = (((biosensor* OR NEMS OR (“sol gel*” OR solgel*) OR dendrimer* OR CNT OR “soft lithograph*” OR “electron beam lithography” OR “e-beam lithography” OR “molecular simul*” OR “molecular machin*” OR “molecular imprinting” OR “quantum effect*” OR “surface energy” OR “molecular sieve*” OR “mesoporous material*” OR “mesoporous silica” OR “porous silicon” OR “zeta potential” OR “epitax*”) AND MolEnv-R) NOT nano*) |
#8 | SO = (Fullerene* OR IEEE Transactions on Nano* OR Journal of Nano* OR Nano* OR Materials Science Engineering C* OR ACS Nano OR Current Nanoscience OR Digest Journal of Nanomaterials and Biostructures OR IEE Proceedings Nanobiotechnology OR IET Nanobiotechnology OR International Journal of Nanomedicine OR International Journal of Nanotechnology OR Journal of Biomedical Nanotechnology OR Journal of Computational and Theoretical Nanoscience OR Journal of Experimental Nanoscience OR Nature Nanotechnology OR Photonics and Nanostructures* OR Wiley Interdisciplinary Reviews Nano*) NOT TS = (nano*) |
#9 | TS = (plankton* OR n*plankton OR m*plankton OR b*plankton OR p*plankton OR z*plankton OR nanoflagel* OR nanoalga* OR nanoprotist* OR nanofauna* OR nano*aryote* OR nanoheterotroph* OR nanophtalm* OR nanomeli* OR nanophyto* OR nanobacteri* OR *270 organism names beginning with nano* OR nano2 OR nano3 OR nanos OR nanog OR nanor OR nanoa OR nano- OR nanog- OR nanoa- OR nanor- OR nanosatellite* OR 270 organism names beginning with nano*) |
#10 | TS = (nanometer* OR nano-metre OR nano-meter OR nano-metre OR nanosecond* OR nano-second OR nanomolar* OR nano-molar OR nanomole(s) OR nanogram* OR nano-gram OR nanoliter* OR nanolitre* OR nano-liter OR nano-litre*) |
Total Nanotechnology = ((#1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8) NOT #9 NOT (#10 NOT (#1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8))) | |
Energy | |
#1 | TS = (energ* SAME (“energy sector” OR “power source*” OR renewable* OR “power supply” OR “energy convers*” OR “energy storag*” OR sustainab* OR use* OR “distribution loss*” OR harvest* OR “wind energy” OR eolic OR tidal OR biomas* OR geotherm* OR hydroelectric* OR (wave SAME (ocean OR sea)) OR fos$il OR oil OR “natural gas” OR coal OR “nuclear energy” OR fuel OR tide OR petroleum OR heat$storag* OR thermal$insulator OR batter* OR super$capacitor* OR capacitor* OR flywheel* OR photovoltaic* OR “solar cell*” OR power*station OR carge$carrier OR “fuel cell*” OR electro$catalys* OR photoelectrochem* OR thermo$electric* OR turbin* OR transducer* OR “water photoelectrolys*” OR power$generat* OR biofuel* OR biodiesel* OR water$oxidation OR “combustion engine” OR “thermal rectifier” OR “hydrogen* production”)) |
#2 | TS = (photosynthesis OR obesity OR diet* OR food OR cellular OR glucose OR DNA OR astrophys* OR astronom* OR chlorop* OR phyto*) OR SO = (astrophys* OR astronom* OR biolog* OR nutriti* OR botanic* OR American Journal of Clinical Nutrition OR Monthly Notices of the Royal Astronomical Society OR Biotechnology and Bioengineering OR Annual Review of Nutrition OR Journal of Geophysical Research-Space Physics) |
Total Energy = #1 NOT #2 | |
Total Nano-energy = Total Nanotechnology AND Total Energy |
Rights and permissions
About this article
Cite this article
Liu, N., Guan, J. Dynamic evolution of collaborative networks: evidence from nano-energy research in China. Scientometrics 102, 1895–1919 (2015). https://doi.org/10.1007/s11192-014-1508-z
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-014-1508-z