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범용기술 관점에서 ICT 공급자의 경쟁적 노력에 관한 연구

The Competitive Efforts of ICT Providers in the Perspective of General Purpose Technology

  • 홍희정 (연세대학교 대학원 기술경영학 협동과정) ;
  • 정재원 (연세대학교 대학원 기술경영학 협동과정) ;
  • 이정훈 (연세대학교 정보대학원)
  • Hong, Hee-Jung (The Graduate School of Yonsei University Management of Technology) ;
  • Jung, Jae-Won (The Graduate School of Yonsei University Management of Technology) ;
  • Lee, Jung-Hoon (Graduate School of Information, Yonsei University)
  • 투고 : 2018.02.05
  • 심사 : 2018.03.20
  • 발행 : 2018.03.28

초록

ICT의 파급으로 다양한 응용은 기술 수용자뿐만 아니라 기술 공급자에게도 새로운 기회가 되며 그들 간에는 경쟁적 관점에서의 기술혁신 노력이 필수적으로 요구될 수밖에 없다. 범용기술의 혁신적 보완의 특징으로 인해 급격한 기술 변화는 분명 높아지는 지식 장벽을 형성하여 높은 기회와 전유성을 보장하게 되지만 이러한 ICT의 슘페터적 패턴 속에서 과연 ICT 공급자는 어떤 노력을 기울여야 하는가에 대한 질문을 가지고 연구를 진행한다. 혁신의 확산에서 말하는 혁신의 존재에 대한 지식을 수용자가 갖게 하기 위해서 혁신 기술 시도와 기술 공급자의 흡수 역량이 필요하다는 가설 검증을 위해 5,700여개의 북미 상장사를 대상으로 ICT 기업이 출원하는 기술 특허의 확산을 실증적으로 관찰한다. 기술의 출현으로 생겨나는 기술 적소(Technological niche)의 개념을 도입하고 이후 이 기술 적소에 참여하는 후발 비 ICT 기업의 참여 사건의 발생 위험률을 독립변수로 하는 생존분석을 통해 혁신적인 기술 시도와 흡수 역량의 유의성을 밝힌다.

The research analysis will be proceeded with a specific question: The kind of endeavors the ICT providers must focus on within the ICT industry's Schumpeterian pattern of using barriers of knowledge during the rapid technological transformation and pursuing appropriability of guaranteed opportunities. The study was carried out by targeting and conducting empirical observations on the proliferation of technological patent applications made by ICT companies among approximately 5,700 listed North American corporations. The risk of arising cases, in which late-coming non-ICT companies adopt and participate in the technical pertinence and concept derived from the technological advent, will be treated as an independent variable in a survival analysis. Through this analysis, innovative technological attempts and absorption capabilities indicate significance.

키워드

참고문헌

  1. J. G. March. (1991). Exploration and exploitation in organizational learning.. Organization Science 2(1), 71-87. https://doi.org/10.1287/orsc.2.1.71
  2. P. Davis. (1990). The dynamo and the computer. The American Economic Review 80(2), 355-361.
  3. T. F. Bresnahan & M. Trajtenberg. (1995). General purpose technologies 'Engines of growth. Journal of econometrics 65(1), 83-108. https://doi.org/10.1016/0304-4076(94)01598-T
  4. P. A. David & G. Wright. (1999). General Purpose Technologies and Surges in Productivity: Historical Reflections on the Future of the ICT Revolution.
  5. B. Jovanovic & P. L. Rousseau. (2005). General purpose technologies. Handbook of economic growth 1: 1181-1224.
  6. T. F. Bresnahan & S. Greenstein. (2001). The economic contribution of information technology: towards comparative and user studies. Journal of Evolutionary Economics 11(1): 95-118. https://doi.org/10.1007/PL00003859
  7. F. Malerba & L. Orsenigo. (1996). Schumpeterian patterns of innovation are technology-specific. Research Policy 25(3), 451-478. https://doi.org/10.1016/0048-7333(95)00840-3
  8. N. Corrocher et al. (2007). Schumpeterian patterns of innovative activity in the ICT field.. Research Policy 36(3), 418-432. https://doi.org/10.1016/j.respol.2007.01.002
  9. R. T. Frambach & N. Schillewaert. (2002). Organizational innovation adoption: A multi-level framework of determinants and opportunities for future research. Journal of Business Research 55(2), 163-176. https://doi.org/10.1016/S0148-2963(00)00152-1
  10. E. M. Rogers. (2010). Diffusion of innovations, Simon and Schuster.
  11. M. L. Markus. (1987). Toward a "critical mass" theory of interactive media universal access, interdependence and diffusion. Communication research 14(5), 491-511. https://doi.org/10.1177/009365087014005003
  12. M. L. Katz & C. Shapiro. (1994). Systems competition and network effects. The Journal of Economic Perspective, 93-115.
  13. R. E. Kraut, et al. (1998). Varieties of social influence: The role of utility and norms in the success of a new communication medium. Organization Science 9(4), 437-453. https://doi.org/10.1287/orsc.9.4.437
  14. E. J. Hultink, E. J. (1997). Industrial new product launch strategies and product development performance. Journal of Product Innovation Management 14(4), 243-257. https://doi.org/10.1016/S0737-6782(97)00009-X
  15. R. T. Frambach, et al. (1998). Adoption of a service innovation in the business market: an empirical test of supply-side variables. Journal of Business Research 41(2), 161-174. https://doi.org/10.1016/S0148-2963(97)00005-2
  16. C. Easingwood & C. Beard. (1989). High technology launch strategies in the UK. Industrial Marketing Management 18(2), 125-138. https://doi.org/10.1016/0019-8501(89)90029-1
  17. T. S. Robertson & H. Gatignon. (1986). Competitive effects on technology diffusion. The Journal of Marketing, 1-12.
  18. L. E. Ostlund. (1974). Perceived innovation attributes as predictors of innovativeness. Journal of consumer Research: 23-29.
  19. L. G. Tornatzky & K. J. Klein. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. Engineering Management, IEEE Transactions on(1), 28-45.
  20. S. L. Holak, et al. (1987). The role of expectations in the adoption of innovative consumer durables: Some preliminary evidence. Journal of Retailing.
  21. W. T. Robinson. (1990). Product innovation and start-up business market share performance. Management science 36(10), 1279-1289. https://doi.org/10.1287/mnsc.36.10.1279
  22. E. Mansfield. (1993). The diffusion of flexible manufacturing systems in Japan, Europe and the United States. Management science 39(2), 149-159. https://doi.org/10.1287/mnsc.39.2.149
  23. M. Fishbein & I. Ajzen (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
  24. S. G. Winter & R. R. Nelson. (1982). An evolutionary theory of economic change. University of Illinois at Urbana-Champaign's Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship.
  25. S. Wuyts, et al. (2005). Empirical tests of optimal cognitive distance. Journal of Economic Behavior & Organization 58(2), 277-302. https://doi.org/10.1016/j.jebo.2004.03.019
  26. B. Nooteboom, et al. (2007). Optimal cognitive distance and absorptive capacity. Research Policy 36(7), 1016-1034. https://doi.org/10.1016/j.respol.2007.04.003
  27. L. Vygotsky. (1978). Interaction between learning and development. Readings on the development of children 23(3), 34-41.
  28. N. Rosenberg & M. Trajtenberg. (2001). A General purpose technology at work: the Corliss steam engine in the late 19th Century US, National Bureau of Economic Research.
  29. W. M. Cohen & D. A. Levinthal. (1990). Absorptive capacity: a new perspective on learning and innovation. Administrative science quarterly: 128-152.
  30. H. F. Harlow. (1949). The formation of learning sets. Psychological review 56(1), 51. https://doi.org/10.1037/h0062474
  31. F. Malerba & L. Orsenigo. (1995). Schumpeterian patterns of innovation. Cambridge Journal of Economics 19(1), 47-65.
  32. L Fleming, (2001). Recombinant uncertainty in technological search. Management science 47(1), 117-132. https://doi.org/10.1287/mnsc.47.1.117.10671
  33. J. M. Podolny & T. E. Stuart. (1995). A Role-Based Ecology of Technological Change. American Journal of Sociology 100(4), 1224-1260. https://doi.org/10.1086/230637
  34. P. D. Allison. (2010). Survival analysis using SAS: a practical guide, Sas Institute.
  35. Song, et al. (1996). Survival Analysis, Cheongmungak.
  36. D. G. Kleinbaum. (1998). Survival Analysis, a Self-Learning Text. Biometrical Journal 40(1), 107-108. https://doi.org/10.1002/(SICI)1521-4036(199804)40:1<107::AID-BIMJ107>3.0.CO;2-9
  37. J. M. Podolny, et al. (1996). Networks, knowledge, and niches: Competition in the worldwide semiconductor industry, 1984-1991. American Journal of Sociology: 659-689.
  38. T. E. Stuart & J. M. Podolny. (1996). Local search and the evolution of technological capabilities. Strategic management journal 17(S1), 21-38.
  39. A. B. Jaffe, et al. (1992). Geographic localization of knowledge spillovers as evidenced by patent citations, National Bureau of Economic Research.
  40. E. C. Engelsman & A. F. van Raan. (1994). A patent-based cartography of technology. Research Policy 23(1), 1-26. https://doi.org/10.1016/0048-7333(94)90024-8
  41. H. J. No, et al. (2014). A structured approach to explore knowledge flows through technology-based business methods by integrating patent citation analysis and text mining. Technological Forecasting and Social Change.
  42. G. Salton & M. J. McGill. (1986). Introduction to modern information retrieval.
  43. H. Schildt, et al. (2012). The temporal effects of relative and firm-level absorptive capacity on interorganizational learning. Strategic management journal 33(10), 1154-1173. https://doi.org/10.1002/smj.1963
  44. S. A. Zahra & G. George (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of management review 27(2), 185-203. https://doi.org/10.5465/amr.2002.6587995
  45. G. Todorova & B. Durisin. (2007). Absorptive capacity: valuing a reconceptualization. Academy of management review 32(3), 774-786. https://doi.org/10.5465/amr.2007.25275513
  46. J. Sall, et al. (2005). JMP start statistics, JSTOR.
  47. D. Schoenfeld (1982). Partial residuals for the proportional hazards regression model. Biometrika 69(1), 239-241. https://doi.org/10.1093/biomet/69.1.239
  48. S. Kaplan & M. Tripsas. (2008). Thinking about technology: Applying a cognitive lens to technical change. Research Policy 37(5), 790-805. https://doi.org/10.1016/j.respol.2008.02.002