博碩士論文 91444005 詳細資訊




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姓名 王嘉齡(Chia-Ling Wang)  查詢紙本館藏   畢業系所 產業經濟研究所
論文名稱 聚集、績效與門檻—台灣製造業之實證研究
(Agglomeration, Performance, and Threshold model: An Empirical Study of Taiwan Manufacturing Industries)
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摘要(中) 聚集是產業經濟學的領域中非常重要的議題之一,許多國家在制定產業政策時,也都會以促成廠商聚集於特定區域作為施政方向。雖然許多文獻都指出,聚集會為廠商帶來許多經濟的外部性效益,但亦有學者發現聚集有可能會產生競爭或擁擠等不經濟現象;此外,在相關文獻的探討當中,理論方面的研究相當豐富,但實證資料的運用卻相對稀少,難以對理論進行更深入的驗證。本研究即希望在此一背景下,透過實證資料的運用,一方面可稍補足過去文獻不足之處,一方面驗證相關理論,以更清晰地描繪出聚集所產生的影響,供政府與廠商在決策時有更多的參考依據。
基於此,本研究將主題聚焦在聚集及其效益之上,分別使用三種實證資料,進行三個相關主題的實證研究。首先本研究以台灣的整體製造業為標的,透過1986至2001年工商及服務業普查資料所整理出來的產業追蹤資料(panel data),以及以距離為基礎所計算出來的聚集指數,進行對台灣製造業當中各產業聚集程度的動態觀察(第二章),並分析聚集程度對產業績效的影響(第三章)。實證結果顯示產業的聚集程度、每人附加價值、資本密集度、外銷比例、產業規模等,皆會對整體製造業、高科技產業及非高科技產業績效產生影響,且產業的聚集程度與績效間存在著單向因果關係。
其次,本研究將層次由產業轉至廠商,以第二章當中所觀察到出現聚集現象的電腦製造業(2610)為對象,透過1986至2001年工商及服務業普查資料所提供的所有廠商資料,嘗試回答一個重要而關鍵的問題:「位在廠商高度聚集區域內的廠商,是否也會有高績效的表現?」亦即當地理空間中出現廠商高度聚集的區域,原有或新設廠商究竟應該選擇進入高聚集區,抑或離開高聚集區,才能創造高績效。實證結果發現,位於高聚集區內的廠商並不如研究假設般,會擁有較佳的績效表現,反而是中聚集區內的廠商,會有較佳的績效表現。但同時透過對新竹市東區的觀察也發現,仍有高聚集區內的廠商能夠享受到較佳的績效,此一例外顯示新竹市東區內重要的聚集區域—新竹科學園區的存在,形成了特殊的聚集,能夠充分享受聚集帶來的正面效益,而降低聚集帶來的負面效益。因此若政府只是一味地創造高聚集區,卻無法複製新竹科學園區的成功因素,恐怕可能無法達成政策預期的效果。
綜合上述研究成果,本研究建立聚集與績效間可能存在著非線性相關的假設,為進一步驗證此一假設,本研究使用經濟部1992年到2004年「工廠校正暨營運調查」的資料,並整理成追蹤資料(Panel data)來進行實證分析。透過Hansen(1999)的縱橫門檻迴歸(Panel Threshold)模型,並使用廠商每人平均研發存量作為門檻變數,以檢視台灣電子業廠商聚集與績效間是否存在著門檻效果。實證結果發現確實存在著門檻效果,廠商的聚集對於績效間的影響,要視廠商本身的研發存量而定:若為高研發投入的廠商,則聚集對其而言是有利的;但若不是高研發投入的廠商,則聚集反而是不利的。此一結果除了驗證聚集與績效間並非線性相關的假設外,並提供新竹科學園區之所以為一特殊聚集的可能因素,即該區域內多為高研發廠商,故高度聚集相對有利;至於其他的高聚集區域,若廠商並不具高研發特性,則高度聚集反而是有利的。
綜上所述,本研究發現在製造業當中,聚集程度較高的產業(包含了第四章設定之高聚集及中聚集區),其績效表現亦相對較佳;但對於電腦製造業或電子業的廠商而言,卻並不代表要進入高聚集區或盡量靠近聚集重心,而應視自身的特性或資源而定。若不考量其他因素,在一般的情況下,廠商是以中等聚集程度,最能帶來高度的績效表現,亦即適度的聚集,可以享受聚集帶來的好處,又能避免過度聚集帶來的不經濟效益。
摘要(英) In the early empirical studies, many economists focus on the determinant of economies of agglomeration, but few papers to investigate the phenomenon of diseconomies of agglomeration. We empirical evidence suggesting on the economies and diseconomies of agglomeration as clusters evolve.
Covering with 1986, 1991, 1996 and 2001 from Industry, Commerce and Service Census. This study focuses on manufacturing industries and uses the regionally industrial type of data to measured cluster index, Econometric estimation we investigate the performance of industry by using panel unit root test. Panel unit root can increase power in contrast to conventional individual ADF test. By Hausman test, we choose the regression model of fixed effect to confirm the research hypothesis. The results show that no matter cluster index or the other operation factor is positively related to the industry performance.
Next to the finding of part 2, we empirical study of computer manufacturers in Taiwan. We provide further evidence on the rank both firm performance and regionally share ratio. The results show that high agglomeration area without the more return beside East District in Hsinchu City. So we want to find a key factor to successful in East District in Hsinchu City.
In order to achieve this purpose, in part 3, we use panel data from MOEA’’s Factory Adjustment and Operation Survey for all the Taiwan’s electronic firms since 1992 to 2004. To study the relationship between firm agglomeration and R & D stock effects considering with threshold Model which has been published by Hansen (1999). The practical result of threshold effect find three threshold values and four areas threshold effect which are existing between the performance of firms and R&D stock. Three threshold values separately are 631.1749, 1202.2045, and 2970.6946(Unit: NT $ Thousand). Only in the highest level (R & D stock > NT $ 2970.6946 Thousand Dollars), the firms are closer to the center of industry, the more benefit will increase.
關鍵字(中) ★ 門檻模型
★ 聚集
★ 績效
關鍵字(英) ★ Agglomeration
★ Performance
★ Threshold Model
論文目次 第一章 緒論...............................................................................................................1
第一節 研究動機與目的...................................................................................1
第二節 論文架構...............................................................................................3
參考文獻...............................................................................................................5
第二章 台灣製造業聚集之變化:以距離為基礎的動態觀察...............................9
第一節 前言.......................................................................................................9
第二節 資料分析...............................................................................................9
第三節 整體製造業聚集度之觀察.................................................................12
第四節 個別產業聚集情形之觀察.................................................................16
第五節 不同性質產業聚集程度之比較.........................................................19
第六節 跨期比較.............................................................................................21
第七節 結論.....................................................................................................29
參考文獻.............................................................................................................31
第三章 產業聚集與績效表現之研究—以台灣製造業為例.................................33
第一節 前言.....................................................................................................33
第二節 資料整理與研究方法.........................................................................37
第三節 研究方法與設計.................................................................................39
第四節 實證結果.............................................................................................45
第五節 結論.....................................................................................................54
參考文獻.............................................................................................................56
第四章 廠商應進入或離開高聚集區?-台灣電腦及其週邊設備製造業的實證
.....................................................................................................................................60
第一節 前言.....................................................................................................60
第二節 文獻回顧.............................................................................................61
第三節 研究方法與設計.................................................................................66
第四節 實證結果.............................................................................................70
第五節 結論.....................................................................................................79
參考文獻.............................................................................................................81
第五章 不同研發存量下台灣電子業廠商的聚集與績效-門檻模型之應用.....87
第一節 前言.....................................................................................................87
第二節 文獻回顧.............................................................................................88
第三節 研究方法與設計.................................................................................91
第四節 實證結果...........................................................................................103
第五節 結論...................................................................................................110
參考文獻........................................................................................................... 111
參考文獻 1. Aghion, P. & Howitt, P. (1992), “A model of growth through creative destruction”, Econometrica, 60(2):323–352.
2. Albino, V., Garavelli, A. C. & Schiuma G.., (1999), Knowledge Transfer and Inter-Firm Relationship in Industrial Districts: The Role of Leader Firm, Technovation, 19(1), 53-63.
3. Anderson, G. (1994), Industry Clustering for Economic Development, Economic Development Review, 12, 2.
4. Arrow, K. (1962), The Economic Implications of Learning by Doing, Review of Economic Studies 29,155–173.
5. Arthur, W. (1990), Silicon Valley locational clusters: when do increasing returns imply monopoly? Mathematical social Sciences, 19,235-273.
6. Audretsch, D. B. & Feldman, M. P. (1996), R&D Spillovers and the Geography of Innovation and Production, American Economic Review, 86: 630-640.
7. Bahraml, H. & Evans, S. (1995), Flexible Re-Cycling and Height-Technology Entrepreneurship, California Management Review, 37, 3, 62-89.
8. Baptista, R. (1996), Research round up: industrial clusters and technological innovation, Business Strategy Review, 7(2): 59-64.
9. Baptista, R., & P. Swann(1998),Do firms in clusters innovate more? Research Policy, 27: 525-540.
10. Barkley, D. L., Henry, M. S. & Kim, Y. (1999), Industry Agglomerations and Employment Change in Non-Metropolitan Areas, Review of Urban and Regional Development Studies, 11(3): 168-186.
11. Baum, J. A. & Mezias, S. J. (1992), Localized Competition and Organizational Failure in the Manhattan Hotel Industry, 1989-1990, Administrative Science Quarterly, 37(4): 580-604.
12. Beal, B. D. (2001), Geographic Agglomeration, Knolwedge Spillovers, and Competitive Evolution, Academy of Management Proceedings, A1-A6.
13. Beaudry, C., & Swann, P. (2001), Growth in industrial clusters: A bird’s eye view of the United Kingdom. Stanford Institute for Economic Policy Research, Stanford, CA.
14. Bell, G.. G.. (2005), Clusters, Networks, and Firm Innovativeness, Strategic Management Journal, 26(9): 287-295.
15. Belleflamme, P., Picard, P. & Thisse, J. F. (2000), An Economic Theory of Regional Clusters, Journal of Urban Economics, 48, 158-184.
16. Bernstein(1988), Cost of Production, Intra- and Interindustry R & D Spillovers: Canadian Evidence, Canadian Journal of Economics, 21:324-347.
17. Blind, K. & Grupp, H. (1999), “Interdependencies Between the Science and Technology Infrastructure and Innovation Activities in German Regions: Empirical Findings and Policy Consequence”, Research Policy, 28:451-468.
18. Branch, Ben (1974), “Research and Development Activity and Profitability: A Distributed Lag Analysis,” The Journal of Political Economy, 82 (5):999-1011.
19. Brenner,M.S. and Rushton,B.M.(1989), “Sales Growth and R&D in the Chemical Industry. ” Research-Technology Management, 32(2): 8.
20. Breschi, S. (2000), The geography of innovation: a cross-sector analysis, Regional Studies, 34(3):59
21. Busch, M. L., & Reinhardt, E. (1999), Industrial Location and Protection: The Political and Economic Geography of U.S. Nontariff Barriers, American Journal of Political Science, 43(4): 1028-1050.
22. Carlson, V. L. & Matton, R. H. (1994), Industry Targeting: A New Approach to Local Economic Development, Chicago Fed Letter, 77.
23. Chan, K. S.(1993), Consistency and Limiting Distribution of the Least Squares Estimator of a Threshold Autoregressive Model, The Annals of Statistics, 21: 520-533.
24. Ciccone, A. & Hall, R. E. (1996), Productivity and the Density of Economic Activity, Amreican Economic Review, 86(1): 54-70.
25. Ciccone, A. (2002), Agglomeration Effects in Europe, European Economic Review, 46:.213-227.
26. d' Aspremont, C., Gabszewicz, J.J. & Thisse, J. F. (1979), On Hotel ling' s Satbility in Competition, Econometrica , 47, 1145-1150.
27. Davies, R.B. (1977) , “Hypothesis testing when a nuisance parameter is present only under the alternative,” Biometrika, 64:247-254.
28. Davies, R.B. (1987) , “Hypothesis testing when a nuisance parameter is present only under the alternative,” Biometrika, 74:33-43.
29. Dosi, G. (1988), Sources, procedures, and microeconomic effects of innovation, Journal of Economic Literature, 26:1120-71.
30. Effie, K. & Adam, S. (2008), Local Knowledge Spillovers, Innovation and Export Performance in Developing Countries: Empirical Evidence from the Uruguay Software Cluster, European Journal of Development Research, 20(2): 281-98.
31. Ellison, G., & Glaeser, E. L. (1997), Geographic concentration in U.S. manufacturing industries: A dartboard approach, Journal of Political Economy 105: 889-927.
32. Emerson, R. M. (1962), Power Dependence Relations, American Sociological Review, Vol. 27(1):31-41.
33. Engle, R.F. & Granger, C.W. J. (1987) ,“Co-integration and Error Correction: Representation, Estimation, and Testing,” Econometrica, 55: 251-276.
34. Enright, M. (1996), Regional Clusters and Economic Development: A Research Agenda, in Staber, U., Schaefer, N. and Sharma, B., (Eds.) Business Networks: Prospects for Regional Development, Berlin: Walter de Gruyter, pp. 190- 213.
35. Ermst, H. (2001), Patent applications and subsequent changes of performance: evidence from time-series cross-section analyses on the firm level, Research Policy, Vol. 30(3):143-157.
36. Feldman, M. P. & Florida, R. (1994), The Geographic Sources of Innovation: Technological Infrastructure and Product Innovation in The United States, Annals of the Association of American Geographers, 84(2):210-229.
37. Feldman, M. P. (1994), The Geography of Innovation , Kluwer Academic Publishers, Boston.
38. Feser, E. J. & Bergman, E. M. (2000), National Industry Cluster Templates:A 136 Framework for Applied Regional Cluster Analysis, Regional Studies, 34: 1-19.
39. Folta, T. B., Cooper, A. C. & Baik, Y. S. (2006), Geographic cluster size and firm performance, Journal of Business Venturing, 21: 217-242.
40. Fujita, M. (1989), Urban Economic Theory : Land Use and Cuty Size, Cambridge: Cambridge University Press.
41. Furman, Porter & Stern (2002), The determinants of national innovative capacity , Research Policy, 31(6): 899-933.
42. Gale, B.T, & Branch, B.S. (1982), Concentration Versus Market Share: Which Determines Performance and Why Does it Matter?, Antitrust Bulletin, 27: 83-106.
43. Ganesan, S., Malter, A. J. & Rindfleisch, A. (2005), Does Distance Still Matter? Geographic Proximity and New Product Development, Journal of Marketing, 69 (4): 44-60.
44. Gilbert, R. (1984), Bank market structure and competition: a survey. Journal of Money, Credit, and Banking, 16: 617-660.
45. Goss, E., & Vozikis, G.. S. (1994), High-tech manufacturing: firm size, industry and population density, Small Business Economics, 6: 291-297.
46. Granger, C. W. J. & Newbold, P. (1974),”Spurious regressions in econometrics”, Journal of Econometrics, 2(2): 111-120.
47. Granger, C. W. J. (1969), Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424-438.
48. Griliches, Z. (1979), “Issues in assessing the contributions of research and development to productivity growth”, Bell Journal of Economics, 10: 92-116.
49. Griliches, Z. (1986), “Productivity, R&D, and the Basic Research at the Firm Level in the 1970's,” American Economic Review, 76(1):141-54
50. Grossman, G. M. & Helpman, E. (1990), “Comparative advantage and long run growth”, American Economic Review, 80, 796–815.
51. Hall, B. H. (1993), “The stock market’s valuation of R&D investment during the 1980’s”, American Economic Review, 83(2):259–264.
52. Hansen, B.E. (1999), Threshold effects in non-dynamic panels:Estimation, testing, and inference, Journal of Econometrics, 93: 345-368.
53. Hansen, B.E., (1996), Inference when a nuisance parameter is not identified under the null hypothesis, Econometrica 64: 413-430.
54. Henderson, J. V. (1986), Efficiency of resource usage and city size, Journal of Urban Economics, 19(1): 47-70.
55. Henderson, J. V. (2003), Marshall’s Scale Economies, Journal of Urban Economics, 53:1-28.
56. Henderson, J. V., Kuncoro, A. & Turner, M. (1994), Industrial Development in Cities, Journal of Political Economy, 103: 1067-1090.
57. Hill, J.,& Naroff, J. L., (1984), The effect of location on the performance of high-technology firms, Financial Management, 13: 27-36 (Spring).
58. Holmes, T. J. (1999), Localization of Industry and Vertical Disintegration, The Review of Economics and Statistics, 81(2): 314-325.
59. Hoover, E. M. (1948), The Location of Economic Activity, New York: McGraw-Hill Press.
60. Hotelling, H. (1929), “tability in Competition, Economic Journal, 39:41-57.
61. Howells, J. (2002), “Tacit Knowledge, Innovation and Economic Geography”, Urban Studies, 39:871-884.
62. Hung, S. W. & Yang, C. (2003), The IC fables industry in Taiwan: current status and future challenges, Technology in Society, Vol. 25(4):385-402.
63. Hurlin, C. & Venet, B. (2001), Granger causality tests in panel data models with fixed coefficients, Mimeo, University of Paris IX.
64. Im, K. S., Pesaran, M. H., & Shin, Y. (2003), Testing for unit orrts in heterogeneous panels, Journal of Econometrics, 115(1): 53-74.
65. Jaffe, A. B., Trajtenberg, M. & Henderson, R. (1992), Geographic Localization of Knowledge Spillover as Evidences by Patents Citations, NBER Working Paper, No. 3993.
66. Kaiser, U. (2000), Measuring knowledge spillover in manufacturing and services: an empirical assessment of alternative approaches, Research Policy, 31: 125-144.
67. Keller, W. (2000), Geographic Localization of International Technology Diffusion, NBER Working Paper, No. 7509.
68. Krugman, P. (1991), Geography and trade. Cambridge, Mass: MIT Press.
69. Krugman, P. (1995), Development, Geography and Economic Theory, Mass: MIT Press.
70. Lanjouw, J. O., & Schankerman, M. (1999), The Quality of Ideas: Measuring Innovation with Multiple Indicators, NBER working paper, pp.7345.
71. Lev, B. & Theodore, S. (1996), “The Capitalization, Amortization, and Value-relevance of Rand D,” Journal of Accounting and Economics, 21 (February):107-138.
72. Levin, Andrew, & Lin, C. F. (1993), Unit Root Tests in Panel data: A New Result, Discussion Paper, University of California at San Diego.
73. Levin, Andrew, Lin, C. F., & Chu, C. S. James(2002), Unit root tests in panel data: Asymptotic and finite-sample properties, Journal of Econometrics, 108(1): 1-24.
74. Li, S. (2004), Location and Performance of Foreign Firm in China, Management International Review, 44(2): 151-169.
75. Maddala, G. S & Kim, I. M. (1998), Unit Roots, Cointegration, and Structural Change, Cambridge University Press.
76. Mai, C. C. & Peng, S. K. (1999), Cooperation V.S. Competition in a Spatial Model, Regional Science and Urban Economics, 29:463-472.
77. Malmberg, A. & Maskell, P. (2002), The elusive concept of localization economies: towards a knowledge-based theory of spatial clustering, Environment and Planning A, 34 (3): 429-49.
78. Mano, Y. & Otsuka, K.(2000), Agglomeration Economics and Geographical Concentration of Industries: A Case Study of Manufacturing Sectors in Postwar Japan, Journal of the Japanese and International Economies, 14: 189-203.
79. Marshall, A. (1920), Principles of Economics, New York : Macmillan for the Royal Economic Society, 1960(9th ed).
80. Martin, R. & Sunley, P. (2003), Deconstructing clusters: chaotic concept or policy panacea? Journal of Economic Geography, 3 (1): 5-35.
81. Maskell, P. & Kebir, L. (2005), What Qualifies as a Cluster Theory?, DRUID Working Papers 05-09, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
82. Maskell, P. & Malmberg, A.(1999), Localised Learning and Industrial Competitiveness, Cambridge Journal of Economics, 23:165-178.
83. Mukkala, K.(2004), Agglomeration Economics in the Finnish Manufacturing Sector, Applied Economics, 36: 2419-2427.
84. Nachum, L.& Wymbs, C. (2005), Product differentiation, external economies and MNE location choices: M&As in global cities. Journal of International Business Studies, 36(4): 415-434.
85. Nelson, C. & Plosser, C. (1982), Trends and random walks in macroeconomic time series, Journal of Monetary Economics, 10: 139-162.
86. Olson, K. (1998), Strategic Clustering, Executive Excellence, 15:12.
87. Porter, M. E. (1980), Competitive Strategy, New York: Free Press.
88. Porter, M. E. (1990), The Competitive Advantage of Nations, New York: Free Press.
89. Porter, M. E. (1993), The Competitive Advantage of Nations, The Free Press.
90. Porter, M. E. (1998), “Clusters and the New Economics of Competition”, Harvard Business Review, November-December, 77-90.
91. Porter, M.E. & Stern, S. (2001), Innovation: Location matters, Sloan Management Review, 42(4): 28-36.
92. Pouder R. & St. John, C. H. (1996), Hot Spots and Blind Spots:Geographical Clusters of Firms and Innovation, Academy of Management Review, 21(4):1192-1225.
93. Prevezer, M. (1997), The dynamics of industrial clustering in biotechnology. Small Business Economics, 9: 255-271.
94. Ripley, B. D. (1977), Modeling Spatial Patterns, Journal of the Royal Statistical Society, 39(2): 172-212.
95. Robinson, J. (1933), The Economics of Imperfect Competition, London: Macmillan.
96. Romer, P. (1984), Increasing Returns and Long-run Growth, Journal of Political Economy, 94: 1002–1037.
97. Romer, P. M (1986), Increasing Return and Long-Run Growth, Journal of Political Economy, 94:1002-1037.
98. Romer, P. M. (1990), Endogenous Technological Change, Journal of Political Economy, 98: 71-102.
99. Saxenian, A. (1994), Regional Advantage: Culture and Competition in Silicon Valley and Route 128, Cambridge, MA: Harvard University.
100. Scherer, F. M. & Ross, D. (1990), Industrial Market Structure and Economic Performance, Boston: Houghton Mifflin.
101. Shaver, J. M. & Flyer, F. (2000), Agglomeration Economies, Firm Heterogeneity, and Foreign Direct Investment in the United States, Strategic Management Journal, 21(2): 1175-1193.
102. Shen, C. H. (2000) , “Banking and Currency Crises: Are They Really Twin? ,” Working Paper, Chengchi University, Department of Money and Banking. Retrieved Feb 25, 2009, from http://www.it.nccu.edu.tw/IEcenter/Home2/Paper/shen.pdf
103. Sougiannis, T. (1994), “The Accounting Based Valuation of Corporate R and D,” The Accounting Review, 69 (January): 44-68.
104. Staber, U. (1998), Organizational survival in small-firm clusters. Paper Presented at the Academy of Management, San Diego, CA 1998.
105. Steinle, C. & Schiele, H. (2002), When Do Industries Cluster? A Proposal on How to Assess an Industry's Propensity to Concentrate at a Single Region or Nation, Research Policy, 31(6):849-858.
106. Stigler, G. J. (1951), The Division of Labor is Limited by the Extent of the Market, Journal of Political Economy, 59:331-59.
107. Stuart, T. E. (2000), Inter-organizational alliances and the performance of firms: a study of growth and innovation rates in high-technology industry, Strategic Management Journal, Vol. 21(4):791-811.
108. Suarez-Villa, L. & Walrod, W.(1997), “Operational Strategy, R&D and Intra-metropolitan Clustering in a Polycentric Structure: The Advanced Electronics Industries of the Los Angeles Basin,” Urban Studies, 34: 1343 - 1380.
109. Suarez-Villa, L., (2002), High Technology Clustering in the Polycentric Metropolis : A View from the Los Angeles Metropolitan, International Journal of Technology Management, 24(7/8):818-842.
110. Swann, G.M.P. (1998), Towards a Model of Clustering in High Technology Industries, in Swann, G.M.P., Prevezer, M. and Stout, D., (Eds.), The Dynamics of Industrial Clustering: International Comparisons in Computing and Biotechnology (pp. 52-76). Oxford: Oxford University Press.
111. Swann, G.M.P. and Prevezer, M. (1996) A Comparison of the Dynamics of Industrial Clustering in Computing and Biotechnology, Research Policy, 25:1139-1157.
112. Thomas, H. (2002), A theory of strategic venture investing, Journal of Financial Economics, Vol. 64(3):285-314.
113. Tirole, J. (1988), The Theory of Industrial Organization. Cambridge, MA.: MIT Press.
114. Tong, H. (1978), On a Threshold Model, in C. H. Chen (ed.), Pattern Recognition and Signal Processing, 101–141, Amsterdan: Sijthoff and Noordhoff.
115. Tong,H. & Lim, K. (1980), Threshold Autoregressions, Limit Cycles, and Data, Journal of the Royal Statistical Society, 42: 245-292.
116. Tsai, D. H. A. (2005), “Knowledge spillovers and high-technology clustering:Evidence from Taiwan’s Hsinchu science-based industrial park”,Contemporary Economic Policy, 23(1):116–128.
117. Von Hipple, E.(1994) “Sticky information and the locus of problem solving: implications for innovation” Management Science, 40: 429-439.
118. W.C. Lu, Chen, J.R. & Wang, C.L. (2006) , Granger Causality Test on R&D Spatial Spillovers and Productivity Growth, Applied Economics Letters, 13(13): 857-861.
119. Waits, M. J. (2000), The Added Value of The Industry Cluster Approach to Economic Analysis, Strategy Development, and Service Delivery, Economic Development Quarterly, 14(1):35-51.
120. Weber, A. (1929), The Theory of Location of Industries, University of Chicago Press, New York.
121. Yang, X. & Ng, S.(1998), Specialization and Division of Labour: A Survey, in Arrow, K. J., Ng, Y-K, & Yang, X. (ed), Increasing Returns and Economic Analysis, pp. 3-63, New York: St. Martin's Press; London: Macmillan Press.
122. Yeh, C. C. & Chang, P. L. (2003), The Taiwan system of innovation in the tool machine industry: a case study, Journal of Engineering and Technology Management, 20(3):367-380.
123. Zheng, X. P. (2001), Determinants of agglomeration economies and diseconomies: empirical evidence from Tokyo, Socio-Economic Planning Sciences, 35:131-144.
124. 王素彎(2008),《中小企業產業群聚創新與策略發展之研究》。台北市:經濟部中小企業處委託研究。
125. 伍家德、杜啟躍(2006),“創新氛圍、知識外溢與產業群聚對科學園區廠商競爭優勢影響性之研究”,《科技管理學刊》,11(3):53-88。
126. 朱南玉(2003),「從研發知識及產業群聚效益建立地方創新能力模型之研究」,台北大學都市計劃研究所未出版博士論文。
127. 宋佩珊(2007),「研發外溢效果對高科技廠商表現之貢獻-台灣新竹科學園區之實証分析,清華大學經濟學系碩士論文。
128. 周添城、林志誠(1999),《台灣中小企業的發展機制》,台北:聯經。
129. 周祥生(2000)。鋁軋壓品專題研究。台北市:經濟部技術處產業技術知識服務計畫(ITIS)。
130. 金家禾、周志龍(2007),“臺灣產業群聚區域差異及中國效應衝擊”,《地理學報》,49:55-79。
131. 胡太山(2002),“創新聚群與地區發展:產業發展體系建構之研究”,《同濟大學城市規劃匯刊》,139: 20-27。
132. 胡太山、林建元與錢學陶(2005),“產業創新群聚浮現與科技社群互動對創新活動影響之探討-以新竹科學園區及周邊為例”,《建築與規劃學報》,6(1):43–61。
133. 袁建中、陳坤成、虞孝成與王明妤(2005),“產業群聚對企業經營影響之因果檢定:以台灣精密機械業為例”,《科技管理學刊》,第十卷第四期,43-80。
134. 產業、科技、人製作小組(2000)。產業、科技、人。台北市:資訊與電腦出版社。
135. 莊奕琦與許碧峰(1999),“研究發展對生產力的貢獻及產業間的外溢效果—台灣製造業實證”,《經濟論文》,27(3):407-432。
136. 許財良(2002),「廠商創新能力、產業發展與政府科技政策對科學園區廠商競爭優勢及績效影響之研究」,成功大學企業管理研究所碩士論文。
137. 郭迺鋒、劉孟俊、詹立宇、游淑慧(2004), “企業聚集化程度、電子化傾向及研發活動對勞動生產力的影響: 台灣製造業引力模型(Gravity Model) 之應用”, 《經濟情勢暨評論》, 10(1):140–163。
138. 郭鳳儀(2006),「台灣電子業廠商研發與生產力成長之門檻效果」,中央大學產業經濟研究所碩士論文。
139. 陳介英(2002),“台灣產業聚落形成與發展的社會基礎”,《第一屆華人社會的比較研究學術研討會論文》(12月7-8日),2005年2月17日,取自http://140.128.105.41/firework/conference2002120708/conference%20paper/Chenchisenying.htm。
140. 陳正倉、林惠玲、陳忠榮、莊春發(2007),《產業經濟學》,台北:雙葉書廊。
141. 陳坤成、袁建中(2008),“產業群聚與企業經營模式關聯性之探討—以臺灣精密機械產業為例”,《科技管理學刊》,第十三卷第三期,pp.87-125。
142. 陳忠仁,張陽隆(2006),“產業群聚對廠商行為及組織績效影響之研究-以台灣高科技產業為例”,《中山管理評論》,14(2),315-338。
143. 陳忠榮、陳威勳(1992),“研究發展外溢效果對廠商利潤績效之影響—以自動化新產業為例”,《經濟論文叢刊》,20(2):155-175。
144. 楊志海、陳忠榮(2001),“研究發展、技術引進與專利-一般動差法於可追蹤資料的應用”,《經濟論文叢刊》,29(1),頁69-87。
145. 楊志海、陳忠榮(2002),“研究發展、專利與生產力”,《經濟論文叢刊》,30(1):27-48。
146. 楊志海.陳忠榮(2001),“創新活動的投入、產出與效率— 科學園區內外高科技廠商的比較”,《台大管理論叢》, 11(2):129–153。
147. 詹立宇(2005),“產業聚集效應對就業創造之影響—台灣製造業的實證”,《人文及社會科學集刊》, 17(4):683-713。
148. 詹立宇(2005)。台灣製造業聚集之研究。國立中央大學未出版博士論文。
149. 詹立宇、張明宗、徐之強(2004),“台灣製造業垂直分工與產業聚集之關係”, 《經濟論文叢刊》,32(4):483-511。
150. 詹立宇與王嘉齡(2004),台灣製造業產業聚集之觀察-以距離為基礎”, 《台灣經濟論衡》,2(5): 41-71。
151. 詹立宇、張明宗、王嘉齡(2003),“產業群聚、垂直分工與企業競爭策略”,《產業金融季刊》,119:127-145.
152. 劉正田 (2002),“無形資產、成長機會與股票報酬關係之研究”,《會計評論》,35:1-29。
153. 歐陽利姝、朱世琳(2008),“研發、研發外溢與員工學歷結構差異對台灣資訊電子業研發廠商生產力之貢獻”,《經濟論文叢刊》,36(4):515-550。
154. 蔡光第、楊浩彥(1996),“多層次巢覆式R&D外溢效果與其對台灣製造業不同部門之貢獻”,《經濟論文叢刊》,24(1):29-60。
155. 蔡政軒(1998),「產業群聚與研發行為:台灣製造業之實證研究」,暨南國際大學經濟研究所碩士論文
156. 蔡蕙安(2008),“台灣高科技產業之發展與相關實證課題探討”,《經濟論文叢刊》,36(2):183–233。
157. 蔡蕙安、陳致綱(2002),“研究發展外溢之產出成長效果與動態調整過程—台灣電力電子業之實證研究”,《人文及社會科學集刊》, 14(3):289–327。
158. 鄭秀玲、劉育碩 (2000),”銀行規模、多角化程度與經營效率分析:資料包絡法之應用“,《人文及社會科學集刊》,12:1,103-48頁。
159. 瞿宛文(1993),“成長的因素--台灣自行車產業的研究”,《台灣社會研究季刊》,15:65-92。
指導教授 陳忠榮(Jong-Rong Chen) 審核日期 2009-6-24
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