臺灣博碩士論文加值系統

本研究基於混沌理論的觀點與特性，探討產業與技術改變之演化行為是否具有混沌現象。在變數操作與衡量上，本研究以產業的技術產出，即為專利權申請數目，做為產業與技術改變之代理指標，搭配李雅普諾夫指數做為產業時間序列的衡量係數，並佐以全球軟體產業、半導體產業與生物科技產業為例，探討說明混沌現象對產業與技術改變的啟示。本研究的實證結果顯示，產業與技術改變遵從回饋循環、內生變化、路徑依賴與制度角色的概念性隱喻，特別在關鍵創新行動引發系統產生內生變化後，該系統所表現之混沌現象更為顯著。本文最後並討論理論與實務意涵，並延伸說明處於該產業中廠商應採取的技術策略。

In this paper, we apply chaos theory to study the nonlinear nature of industrial and technological change. Methodologically, we focus on the analyses of three industries - software, semiconductor and biotechnology - with the use of Lyapunov exponent as an indicator to the measurement of chaos. Results show that the three industries were developed to promote the conditions of feedback loops, endogenous change, path dependence and role of institutions, all centered on the edge of chaos. This kind of observation is particularly applied to industry growth following a gale of creative destruction. Implications for theory, research and practicing managers are drawn out.

目錄
中文摘要 I
英文摘要 II
目錄 IV
圖目錄 VI
表目錄 VII
第一章、導論 1
第一節 研究動機 1
第二節 研究目的 2
第三節 論文組織架構 3
第二章、文獻回顧 5
第一節 何謂混沌理論？ 5
第二節 混沌理論應用至策略 11
第三節 混沌理論應用至產業及技術發展 13
第三章ヽ研究方法 16
第一節 技術演化之代理指標（專利權申請數目） 16
第二節 資料來源 18
第三節 李雅普諾夫指數分析方式原理解析 20
第四章ヽ分析結果 23
第一節 實證結果說明 23
第二節 關鍵創新事件的技術演化 30
一、全球軟體產業 30
二、半導體產業 32
三、生物科技產業 36
第五章ヽ結論與建議 38
參考文獻 41
附錄一、全球軟體產業 46
附錄二、半導體產業 50
附錄三、生物科技產業 54
圖目錄
圖 1 本研究的流程概念圖 4
圖 2 蝴蝶效應（摘錄自LORENZ, 1963） 9
圖 3 混沌理論與產業及技術改變的相關性隱喻 14
圖 4 SOFTWARE之專利權申請數目趨勢圖（1981-2000） 23
圖 5 SEMICONDUCTOR之專利權申請數目趨勢圖（1981-2000） 24
圖 6 DNA之專利權申請數目趨勢圖（1981-2000） 24
表目錄
表 1 混沌理論的提出學者與論點說明 6
表 2 混沌理論與對產業與技術發展系統之延伸意涵的對照 15
表 3 全球軟體產業分析結果彙整表 26
表 4 半導體產業分析結果彙整表 27
表 5 生物科技產業分析結果彙整表 28
表 6 研究對象的分析結果 29
表 7 全球軟體產業從1981年1月到2000年12月的專利權申請數目 46
表 8 全球軟體產業之李雅普諾夫指數的分析過程 48
表 9 半導體產業從1981年1月到2000年12月的專利權申請數目 50
表 10 半導體產業之李雅普諾夫指數的分析過程 52
表 11 生物科技產業從1981年1月到2000年12月的專利權申請數目 54
表 12 生物科技產業之李雅普諾夫指數的分析過程 56

劉秉正，1994，非線性動力學與混沌基礎，台北市：徐氏基金會出版。
洪世章＆徐玉娟，2001，資訊革命與技術演化，中山管理評論, 9: 245-270。
Alison, T. R. 2001. Bioethics: The new frontier. Business and Society Review, 106: 127-142.
Allen, P. M. 1988. Dynamics models of evolving systems. System Dynamics Review, 4: 109-130.
Basberg, B. L. 1987. Patents and the measurement of technological change: a survey of the literature. Research Policy, 16: 131-141.
Brock, W., & Malliaris, A. 1989. Differential Equations, Stability and chaos in Dynamic Systems. North-Holland: New York.
Brown, T. A. 1996. Measuring Chaos Using the Lyapunov Exponent in Douglas, L. K. and Euel, E. (ed.) Chaos Theory in the Social Science: 53-66.
Brown, S. L. and Eisenhardt, K. M. 1998. Competing on the edge: strategy as structured chaos. Harvard Business School Press: Boston.
Butler, A. 1990. A methodological approach to chaos: are economists missing the point? Federal Reserve Bank of St. Louis, 72: 36-48.
Cambell, R.S. 1983. Patenting the future: a new way to forecast changing technology. The Futurist, 17: 62-68.
Chase, R. 1985. A theory of socioeconomic change: entropic processes, technology, and evolutionary development. Journal of Economic Issue, 19: 797-823.
Crutchfield, J., Farmer J. D., Packard N. H. and Shaw R. S. 1986. Chaos. Scientific American, 225: 46-57.
Detlev, J. H., Cyriac R. R., Gert P., Sandro, K. L. and Ralph M. 2002. Secrets of Software Success: Management Insights from 100 Software Firms Around the World. Harvard Business School Press: USA.
Evenson, R.E. 1993. Patents, R&D, and invention potential: International evidence. American Economic Review, 83: 463-469.
Feder, J. 1988. Fractals. Plenum Press: New York.
Feigenbaum, M. J. 1983. Universal behavior in nonlinear systems. Physica, 7: 16-39.
Flaherty, M. T. 1984.Field research on the link between technological innovation and growth: evidence from the international semiconductor industry. Microeconomics of Innovation and Productivity Growth, 74: 67-72.
Francis, N., Elliot, N. and Ross, P. 1987. Patents as indicators of corporate technological strength. Research Policy, 16: 143-156.
Freeman, C. 1981. Long waves, inventions, and innovations. Futures, 13: 308-323.
Gleick, J. 1987. Chaos: Making a New Science. Penguin Books: New York.
Grupp, H. 1994. The measurement of technical performance of innovations by technometrics and its impact on established technology indicators. Research Policy, 23: 175-194.
Hilborn, R. C. 1994.Chaos and Nonlinear Dynamics. Oxford University Press: New York.
Holger, E. 2001. Patent applications and subsequent changes of performance: evidence from time-series cross-section analyses on the firm level. Research Policy, 30: 143-157.
Irene, S. 1999. Chaos theory and institutional economics: metaphor or model? Journal of Economic Issue, 33: 141-167.
Kauffman, S. A. 1991. Antichaos and adaptation. Scientific American, 265: 78-84.
Kelsey, D. 1988. The economics of chaos of the chaos of economics. Oxford Economic Papers, 40: 1-31.
Kingston, W. 2001. Innovation needs patent reform. Research Policy, 30: 403-423。
Levy, D. 1994. Chaos theory and strategy: theory, application, and managerial implications. Strategic Management Journal, 15: 167-178.
Lorenz, E. 1993. Deterministic nonperiodic flow. Journal of the Atmospheric Sciences, 20: 130-141.
Mandelbort, B. 1977. The Fractal Geometry of Nature. Freeman: New York.
Martin, S. 1996. Protection, promotion and corporation in the European semiconductor industry. Review of Industrial Organization, 11: 721-735.
Mary, E. M. 2000. Foreign patenting behavior of small and large firms. International Journal of Technology Management, 19: 149-164.
May, R. M. 1976. Simple Mathematical Models with Very Complicated Dynamics. Nature, 261: 459-467.
Mayer-Kress, G. and Grossman S. 1989. Chaos in the international arms race. Nature, 337: 701-704.
Mcdonough, P. V., Noonan J. P. and Hall G. R. 1995. A new chaos detector. Computers Electronic Engineering, 21: 417-431.
Prigogine, I. & Stengers, I. 1984. Order out of chaos: Man’s New Dialogue with Nature. Bantam: New York.
Radzicki, M. J. 1988. A note on Kelsey’s the economics of chaos or the chaos of economics. Oxford Economic Papers, 40: 692-693.
Radzicki, M. J. 1990. Institutional dynamics, deterministic chaos, and self-organizing systems. Journal of Economics Issue, 24: 57-101.
Richard, K. 2000. The Power Laws: The Science of Success. Nicholas Brealey Press: London.
Richard, N. L. and Steinmueller W. E. 2000. Strategy and circumstance: the response of American firms to Japanese competition in semiconductors, 1980-1995. Strategic Management Journal, 21: 1163-1173.
Richardson, G. P. 1984. Loop dominance, loop polarity, and the concept of dominant polarity. In Proceedings of the 1984 International Conference of the System Dynamics Society: Oslo, Norway, 156-174.
Rivise, M. 2001. Peculiar patents. Field & Stream, 105: 83-84.
Ruelle, D. and Takens, F. 1971. On the nature of turbulence. Communications Math Physics, 20: 167-192.
Ruelle, D. 1989. Chaotic Evolution and Strange Attractors. Cambridge University Press: New York.
Saperstein, A. M. 1984. Chaos: a model for the outbreak of war. Nature, 309: 303-305.
Teece, D. J. 1996. Firm organization, industrial structure, and technological innovation. Journal of Economic Behavior and Organization, 31: 193-224.
West, B. J. & Goldberger, A. L. 1987. Physiology in Fractal Dimensions. American Scientist, 75: 354-365.
Wyke, A. 1998. A Survey of Biotechnology the Genetic Alternative. The Economist, 307: 1-17.
Yin, R. K. 1994. Case Study Research: Design and Methods. SAGE Publications: London.
Young, T. R. 1991. Change and chaos theory: metaphysics of the postmodern. The Social Science Journal, 28: 289-305.