Abstract
Recently, convergence has been presented as one of the technical innovations in many industrial sectors and diffusion has been discussed as providing the main influence on convergence. The present study used the VOSviewer to analyze convergence trends and the current state of joint research, complemented by quantitative analysis using information from scientific papers published in 2015 obtained through the Scopus database. The results of this study illustrate that convergence of research occurring in Korea is evident in a variety of sectors, e.g. chemistry, material science, mechanics and the electrical and electronics sectors. We discovered that a sector performing research characterized by convergence also was actively involved in joint research. We also discovered that institutions conducting many studies were doing so as partners within joint research with other institutions. There are two important applications: The present study identified important information that can be used to monitor convergence and diffusion appears to provide the most influence on convergence.
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Jeong, D.-H., Kwon, Y.I., Cho, G., Moon, Y.-H.: An analysis of the effect of joint research networks on the diffusion of kowledge: focusing on the renewable energy field. Indian J. Sci. Technol. 8(S1), 445–451 (2015)
Curran, C.-S.: Anticipating convergence industries using publicly available data. Technol. Forecast. Soc. Chang. 77, 385–395 (2010)
Bores, C.: Technological convergence: a strategic perspective. Technovation 23, 1–13 (2003)
OECD, Technological fusion: a part to innovation, the case of optoelectrionics. Paris: Organization for Economics
Xing, W., Ye, X., Kui, L.: Measuring convergence of China’s ICT industry: an input–output analysis. Technommun Policy 35(4), 301–313 (2011)
Pennings, J. M., Puranam, P. Market convergence & firm strategy: new directions for theory and research. In: ECIS Conference, The Future of Innovation Studies, Eindhoven (Netherlands) (2001)
Stieglitz, N.: Digital dynamics and types of industry convergence-the evolution of the handheld computers market in the 1990s and beyond. In: Christensen, J.F., Maskell, P. (eds.) The Industrial Dynamics of the New Digital Economy. Edward Elgar, London (2003)
Lind, J.: ’Ubiquitos convergence: market redefinitions generated by technological change and the Industry Life Cycle, Paper presented at the DRUID Academy Winter 2005 Conference, Jan 27–29 (2005)
Rogers, E.M.: Diffusion of Innovations, 5th edn. Free Press, New York, NY (2003)
Iacobucci, D.: Concerning the diffusion of network models in marketing. J. Mark. 60(3), 134–135 (1996)
Burt, R.S.: Social contagion and innovation: cohesion versus structural equivalence. Am. J. Sociol. 92, 1287–1335 (1987)
Valente, T.W.: Network Models of the Diffusion of Innovations. Hampton Press, Cresskill, NJ (1995)
Wellman, B.: Structural analysis: from method and metaphor to theory and substance. In: Barry, W., Berkowitz, S.D. (eds.) Social Structures: A Network Approach. Cambridge University Press, New York, NY (1988)
Coleman, J.S., et al.: Medical Innovation: A Diffusion Study. Bobbs Merrill, New York, NY (1966)
Granovetter, M.: The strength of weak ties. Am. J. Sociol. 78(6), 1360–1380 (1973)
Rogers, E.M., Kincaid, D.L.: Communication Networks: Toward a New Paradigm for Research. Free Press, New York, NY (1981)
Becker, M.H.: Sociometric location and innovativeness: reformulation and extension of the diffusion model. Am. Sociol. Rev. 35, 267–282 (1970)
Burkhardt, M.E., Brass, D.J.: Changing patterns of change: the effects of a technology on social network structure and power. Adm. Sci. Q. 35, 104–127 (1990)
Madhavan, R., et al.: Networks in transition: how industry events (re)shape interfirm relationships. Strateg. Manag. J. 19(5), 439–459 (1998)
Abrahamson, E., Rosenkopf, L.: Social network effects on the extent of innovation diffusion: a computer simulation. Organ. Sci. 8(3), 289–309 (1997)
Black, F.L.: Measles endemicity in insular populations: critical community size and its evolutionary implication. J. Theor. Biol. 11, 207–211 (1966)
Bally, N.: Deriving managerial implications from technological convergence along the innovation process: a case study on the telecommunications industry. AboAkademi school of Business (2005)
Choi, D., Valikangas, L.: Patterns of strategy innovation. Eur. Manag. J. 19, 424–429 (2001)
Choi, C., Kim, S., Park, Y.: A patent-based cross impact analysis for quantitive estimation of technological impact: the case of information and communication technology. Technol. Forecast. Soc. Chang. 74(8), 1296–1314 (2007)
Nystroem, A.: What is convergence? Perceptions from the Finnish telecommunications sector. paper presented at the 18th Europe Regional ITS Conference, Istanbul, 2–4 Sept (2007)
Nystroem, A.: Understanding Change Processes in Business Networks: A Study of Convergence in Finnish Telecommunications 1985–2005. Abo Akademi University Press, Turku (2008)
Bröring, S.: The Front End of Innovation in Converging Industries: The Case of Nutraceuticals and Functional Foods. DUV, Wiesbaden, Germany (2005)
Katz, M.L.: Remarks on the economic implications of convergence. Ind. Corp. Chang. 5(4), 1079–1095 (1996)
Nystroem, A., Hacklin, F.: Operation value creation through technological convergence: the case of VoIP. In: International Telecommunication Society(ITS), 16th European Reginal Conference, September, pp. 4–6. Porto, Portugal (2005)
Curwen, P.: Fixed-mobile convergence. Info 8(3), 3–11 (2006)
Vong S., Finger, M.: Fixed to mobile convergence (FMC): technological convergence and the restructuring of the European telecommunications industry. Paper presented at SPRU 40th Anniversity Conference, Brighton, 11–13 Sept 2006
Bierly, P.E., Chakrabarti, A.K.: The Dynamics of Innovation: Strategic and Managerial Implication. Springer, Berlin (1999)
Eck, N.J., Waltman, L.: Software survey: VOSviewer, a computer program for biblometric mapping. Scientometrics 84, 523–538 (2010)
Leydesdorff, L., Rafols, I.: Indicators of the interdisciplinarity of journal: diversity, centrality, and citations. Scientometrics 1, 87–100 (2011)
Jeong, H., Kim, Y.K., Kim, J.: An evaluation-committee recommendation system for national R&D projects using social network analysis. Clust. Comput. 19(2), 921–930 (2016)
Batarfi, O., Shawi, R., Fayoumi, A.G., Nouri, R., Barnawi, A., Sakr, S.: Large scale graph processing systems: survey and an experimental evaluation. Clust. Comput. 18(3), 1189–1213 (2015)
Jin, S., Lin, W., Yin, H., Yang, S., Li, A., Deng, B.: Community structure mining in big data social media networks with MapReduce. Clust. Comput. 18(3), 999–1010 (2015)
Choi, Y.C.: Network structure analysis of regional strategy industry: IT industrysupport network structure analysis. Policy Anal. Eval. Assoc. J. 19(2), 277–304 (2012)
Moon, I.C., Yoon, Y.H., Park, Y.S., You, Y.Y.: Exploratory research on the development of industrial convergence competency model (convergence DNA) for SMEs. Indian J. Sci. Technol. 8(25), (2015). doi:10.17485/ijst/2015/v8i25/81704
Jeong, D.-H.: Analysis of effect of international joint research network and knowledge diffusion on knowledge convergence, Sungkyunkwan University (2015)
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This study was supported by ‘Development & Operation of Creative Economy Town’ project funded by the Ministry of Science, ICT and Future Planning (MSIP, 4500-4545-301) in 2016.
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Yoo, S., Kwon, O.Y. & Jeong, Dh. Research trend analysis on convergence and joint research of Korea using scientific papers. Cluster Comput 22 (Suppl 1), 1939–1948 (2019). https://doi.org/10.1007/s10586-017-0931-3
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DOI: https://doi.org/10.1007/s10586-017-0931-3