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研究生: 周涵穎
Cheo, - Harn Ying
論文名稱: 基因改造食物技術之發展軌跡與知識網路之研究
Analyzing Developmental Trajectories and Knowledge Diffusion Networks In Genetically Modified Food Technology
指導教授: 何秀青
Mei H.C. Ho
口試委員: 劉顯仲
John S. Liu
陳宥杉
Yu-Shan Chen
盧文民
Wen-Min Lu
學位類別: 碩士
Master
系所名稱: 管理學院 - 科技管理研究所
Graduate Institute of Technology Management
論文出版年: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 117
中文關鍵詞: 知識擴散基因改造技術中介角色發展路徑技術地位
外文關鍵詞: knowledge flows, GM food technology, brokerage
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  • 基因改造技術是農業革命發展史上發展得最快的技術,同時也被全世界農民廣泛接受
    和採用,而基因改造農作物的種植面積持續增加似乎宣告了這項技術能為社會經濟和環境
    帶來正面效益。然而時至今日仍未有科學證實基因改造技術存有的風險,例如對於生態環
    境或人體健康的危害。 基於科學技術與知識掌握上的不確定性,本研究採用文獻計量學方
    法,分別從美國專利資料庫(USPTO)和科學文獻索引資料庫(WOS)來探討基因改造的技
    術擴散路徑和科學發展路徑,更進一步解析不同國家的技術擁有者在知識網路中的技術地
    位及其扮演的中介角色。此外,本研究也藉由了解各國技術擁有者扮演的中介角色來討論
    各國和各機構國内間和國際間知識擴散的行爲的影響因子。
    本研究共收集4365 篇專利,多數專利集中在已開發國家,其中美國擁有了過半數的專
    利,而科學文獻則較平均地分布在已開發和發展中國家。本研究從技術擴散路徑了解基因
    改造技術已發展至第三階段,即基因改造技術可增加食物的附加價值,使之應用在藥物和
    工業用途上,而此發展途徑以技術為導向。科學發展路徑則偏向以風險預防為導向,以探
    討Bt 抗蟲基因農作物所產生的抗體可能對環境和生態的危害等相關議題爲主要研究方向。
    經迴歸分析,本研究發現美國廠商能促進國内知識擴散的行爲,因美國擁有最關鍵的基因
    改造技術,較其他國家更能有效推動國内知識的流動及整合所需的資源。
    本研究亦發現大學能促進國内知識擴散的行爲,在知識的傳遞上也有著舉足輕重的地
    位。此外,愈早投入此領域及擁有多角化專利佈局的廠商,或擁有創新能力的廠商無論在
    國内或國外皆能促進知識擴散的行爲。最後,扮演產、官、學協調者的廠商能促進國內外
    知識擴散的行爲。政府的積極推動和資金援助在推動產、官、學三者互動模式中具有推波
    助瀾的效用,使基因改造產業邁向創新的經營模式。


    The fastest adoption rate and the controversy issues in GM food technology give the purpose for this
    study to understand the developmental trajectories and the stakeholders' position in knowledge diffusion
    network. We apply citation based approach, using patents and scientific literature databases to generate
    technological and scientific main path analysis. This study explores in-depth the brokerage role among the
    involving stakeholders as well as the determinants to affect how they diffuse knowledge from one region
    to another.
    Statistic data shows that the distributions of patents are dominated by developed countries while the
    publication of scientific literatures are distributed by developed and developing countries. Technological
    main path shows that the development of GM food technology is moving to the third generation to
    produce GM food for pharmaceutical or industrial purposes, presenting the development tends to be
    technology oriented at different time span. However, based on scientific main path analysis, the
    development of GM food technology tends to be precautionary approach rather than technology focused
    as it puts emphasis on the environmental and ecological concerns of Bacillus thuringiensis resistance
    crops.
    Regression model shows that the stakeholders in the U.S. facilitate the knowledge diffusion within
    domestically owned firms. They possess most of the critical knowledge and perform relatively better than
    other countries in coordinating resources within their domestic area. University is crucial to facilitate the
    domestic knowledge diffusion as it collaborates frequently with other domestic firms. Besides, firms that
    invest early in this industry and involve in diverse patent portfolio as well as consist of high innovation
    capacity make contribution to both domestic and international knowledge diffusion.
    Lastly, firms that are able to become cross institutional liaison have positive effect on both domestic
    and international knowledge diffusion. We suggest that the support and funding of government sectors
    play an important role to facilitate University-Industry-Government relationships which could foster the
    development of GM food technology.

    Abstract I 中文摘要 II Table of Contents IV List of Tables VII List of Figures VIII CHAPTER ONE: INTRODUCTION 1 1.1 Research Background and Motivation 1 1.2 Objectives of the research 3 1.3 Summary of research framework 4 CHAPTER TWO: LITERATURE REVIEWS 6 2.1 Development of Genetically Modified Food 6 2.1.1 The growth of GM food 6 2.1.2 Intellectual property (IP) rights in Genetically Modified food 11 2.2 Societal aspects of GM food 15 2.2.1 Benefit and risk of GM food 15 2.2.2 Overview of legislation and regulatory system of GM food 17 2.3 The measurement of knowledge spillovers and diffusion 19 2.3.1 Research process and the technological trajectory of GM food 20 2.3.2 Measuring technological change through patents data and patent citations 21 2.3.3 Geographic localization of knowledge and technological spillovers 23 2.3.4 Factors that affect knowledge spillover effect 24 2.4 Stakeholder positions in the GM food industry 25 2.4.1 The evolution of agricultural industry 26 2.4.2 Innovation process in agriculture development 29 2.4.3 University-Industry-Government (Triple Helix) concept 31 2.4.4 Brokerages facilitate knowledge flows in the industry 35 CHAPTER THREE: METHODOLOGIES 38 3.1 Data Collection 38 3.1.1 Patent data from USPTO 39 3.1.2 Scientific data from WOS 40 3.1.3 Exclusion of non-relevant records in both USPTO and WOS databases 41 3.2 Main path analysis 41 3.3 Assignee network and brokerage analysis 43 3.4 Regression analysis 44 CHAPTER FOUR: DEVELOPMENTAL TRAJECTORIES BASED ON SCIENTIFIC AND TECHNOLOGICAL PERSPECTIVES 47 4.1 Descriptive statistics of patents data 47 4.1.1 The growth trend of patents 47 4.1.2 Distribution of patents by countries 49 4.1.3 Distribution of patents by institutions 50 4.1.4 Diversity of technology area of patents among assignees 50 4.2 Technological main path analysis 52 4.3 Descriptive statistics of scientific publication records 56 4.3.1 The growth trend of scientific bibliographic records 56 4.3.2 Distribution of scientific bibliographic records by countries 57 4.4 Scientific main path analysis 59 4.4.1 Overall scientific bibliometric main path analysis that includes the societal aspects 60 4.5 Differences between technological and scientific perspectives 61 CHAPTER FIVE: ANALYSIS OF STAKEHOLDERS' BEHAVIOR IN KNOWLEDGE DIFFUSION NETWORKS 63 5.1 Assignees’ network analysis 63 5.1.1 Assignees’ network analysis among actors 64 5.1.2 Assignees’ network analysis among countries 66 5.1.3 Assignees’ network analysis among institutions 68 5.2 Assignees’ brokerage role analysis 69 5.2.1 Cross-nation brokerage 69 5.2.2 Cross-institution brokerage 71 5.3 Regression analysis 73 5.3.1 The U.S. stakeholders facilitate the domestic diffusion 73 5.3.2 Universities facilitate the domestic diffusion 73 5.3.3 Firms that act as cross institutional liaison facilitate both domestic and international diffusions 74 5.3.4 Input capacity and output capacity facilitate both domestic and international diffusions 75 5.3.5 Summary of the regression analysis 77 CHAPTER SIX: CONCLUSIONS 78 6.1 Differences in developmental trajectories based on scientific and technological perspectives 78 6.2 Stakeholders' behavior in knowledge diffusion networks 79 6.3 Facing new challenges in development of GM food technology 81 6.4 Limitations of this study 82 References 83 Appendix I: Database Keywords Searching 88 Appendix II: Non-relevant keywords 94 Appendix III Descriptive Statistics and Correlations 101 Appendix IV Scientific main path analysis 102 Appendix V Overall scientific main path analysis that includes the societal aspects 105

    Arnold, E., and Bell, M. (2001). Some new ideas about research for development. Partnerships at the leading edge: a Danish vision for knowledge, research and development, 279-319.
    2. Audretsch, D. B., and Feldman, M. P. (1996). R&D spillovers and the geography of innovation and production. The American economic review, 630-640.
    3. Basberg, B. L. (1987). Patents and the measurement of technological change: a survey of the literature. Research policy 16, 131-141.
    4. Batagelj, V. (2003). Efficient algorithms for citation network analysis. arXiv preprint cs/0309023.
    5. Bernauer, T. (2003). "Genes, trade, and regulation: The seeds of conflict in food biotechnology," Princeton University Press.
    6. Burt, R. S. (1982). Toward a structural theory of action: network models of social Structure, Perception, and Action.
    7. Byerlee, D., and Fischer, K. (2002). Accessing modern science: policy and institutional options for agricultural biotechnology in developing countries. World Development 30, 931-948.
    8. Caloghirou, Y., Kastelli, I., and Tsakanikas, A. (2004). Internal capabilities and external knowledge sources: complements or substitutes for innovative performance? Technovation 24, 29-39.
    9. Clapp, J., and Fuchs, D. A. (2009). "Corporate power in global agrifood governance," MIT Press.
    10. Coe, D. T., Helpman, E., and Hoffmaister, A. W. (2009). International R&D spillovers and institutions. European Economic Review 53, 723-741.
    11. Criliches, Z. (1990). PATENT STATISTICS AS ECONOMIC INDICATORS: A SURVEY PART I. NBER Working Paper 3301.
    12. de Nooy, W., Mrvar, A., and Batagelj, V. (2005). "Exploratory social network analysis with Pajek," Cambridge University Press.
    13. Deeds, D. L., DeCarolis, D., and Coombs, J. (2000). Dynamic capabilities and new product development in high technology ventures: an empirical analysis of new biotechnology firms. Journal of Business venturing 15, 211-229.
    14. Delmer, D. P., Nottenburg, C., Graff, G. D., and Bennett, A. B. (2003). Intellectual property resources for international development in agriculture. Plant Physiology 133, 1666-1670.
    15. Duke, S. O., and Powles, S. B. (2009). Glyphosate-resistant crops and weeds: now and in the future. AgBioForum 12, 346-357.
    16. Etzkowitz, H. (2002a). Incubation of incubators: innovation as a triple helix of university-industry-government networks. Science and Public Policy 29, 115-128.
    17. Etzkowitz, H. (2002b). Networks of Innovation: Science, Technology and Development in the Triple Helix Era. International Journal of Technology Management & Sustainable Development 1.
    18. Etzkowitz, H., and Leydesdorff, L. (2000). The dynamics of innovation: from National Systems and “Mode 2” to a Triple Helix of university–industry–government relations. Research policy 29, 109-123.
    19. Fulton, M., and Giannakas, K. (2002). Agricultural biotechnology and industry structure.
    20. Gould, R. V., and Fernandez, R. M. (1989). Structures of mediation: A formal approach to brokerage in transaction networks. Sociological methodology, 89-126.
    21. Graff, G., Wright, B., Bennett, A., and Zilberman, D. (2004). Access to intellectual property is a major obstacle to developing transgenic horticultural crops. California Agriculture 58, 120-126.
    22. Graff, G., and Zilberman, D. (2001). An intellectual property clearinghouse for agricultural biotechnology. Nature Biotechnology 19, 1179-1180.
    23. Graff, G. D., Cullen, S. E., Bradford, K. J., Zilberman, D., and Bennett, A. B. (2003). The public-private structure of intellectual property ownership in agricultural biotechnology. Nature biotechnology 21, 989-995.
    24. Graff, G. D., and Newcomb, J. (2003). Agricultural biotechnology at the crossroads. BioEconomic Research Associates, 23-25.
    25. Granovetter, M. (1973). The strength of weak ties. American journal of sociology 78, l.
    26. Griliches, Z. (1992). "The search for R&D spillovers." National Bureau of Economic Research.
    27. Gruere, G. P. (2006). "An analysis of trade related international regulations of genetically modified food and their effects on developing countries," Intl Food Policy Res Inst.
    28. Hagedoorn, J., and Cloodt, M. (2003). Measuring innovative performance: is there an advantage in using multiple indicators? Research policy 32, 1365-1379.
    29. Hall, A. (2006). Public–private sector partnerships in an agricultural system of innovation: Concepts and challenges. International Journal of Technology Management & Sustainable Development 5.
    30. Hall, A., Mytelka, L., and Oyeyinka, B. (2005a). Innovation systems: Implications for agricultural policy and practice. ILAC Brief 2.
    31. Hall, A., Mytelka, L., and Oyeyinka, B. (2006). "Concepts and guidelines for diagnostic assessments of agricultural innovation capacity," UNU-MERIT, Maastricht Economic and Social Research and Training Centre on Innovation and Technology.
    32. Hall, B. H., Jaffe, A., and Trajtenberg, M. (2005b). Market value and patent citations. RAND Journal of economics, 16-38.
    33. Harhoff, D., Scherer, F. M., and Vopel, K. (2003). Citations, family size, opposition and the value of patent rights. Research Policy 32, 1343-1363.
    34. Hayenga, M. (1999). Structural change in the biotech seed and chemical industrial complex.
    35. Ho, M. H. C., and Verspagen, B. (2006). "The role of national border and regions in knowledge flows. In N. Lorenz & A. Lundvall (Eds.), How Europe’s Economies Learn,” ".
    36. Howard, P. H. (2009). Visualizing consolidation in the global seed industry: 1996–2008. Sustainability 1, 1266-1287.
    37. Hummon, N. P., and Dereian, P. (1989). Connectivity in a citation network: The development of DNA theory. Social Networks 11, 39-63.
    38. Jaffe, A. B. (1989). Real effects of academic research. The American Economic Review, 957-970.
    39. Jaffe, A. B., Trajtenberg, M., and Henderson, R. (1993). Geographic localization of knowledge spillovers as evidenced by patent citations. the Quarterly journal of Economics 108, 577-598.
    40. James, C. (2013). ISAAA Brief 43, Global Status of Commercialized Biotech/GM Crops: 2011. ISAAA Briefs. Ithaca, New York: International Service for the Acquisition of Agri-biotech Applications (ISAAA). Retrieved November.
    41. Joly, P.-B., and Lemarie, S. (1999). Industry Consolidation, Public Attitude, and the Future of Plant Biotechnology in Europe.
    42. Kamasak, R., and Bulutlar, F. (2010). The influence of knowledge sharing on innovation. European Business Review 22, 306-317.
    43. Khramova, E., Meissner, D., and Sagieva, G. (2013). Statistical patent analysis indicators as a means of determining country technological specialisation. Higher School of Economics Research Paper No. WP BRP 9.
    44. Klerkx, L., and Leeuwis, C. (2008). Matching demand and supply in the agricultural knowledge infrastructure: Experiences with innovation intermediaries. Food Policy 33, 260-276.
    45. Krugman, P. R. (1991). "Geography and trade," MIT press.
    46. Kryder, R. D., Kowalski, S. P., and Krattiger, A. F. (2000). "The intellectual and technical property components of pro-Vitamin A rice (GoldenRice): A Preliminary Freedom-to-Operate Review," ISAAA Ithaca, New York.
    47. Kutchan, T. (2000). The Biotechnological Exploitation of Medicinal Plants. In "The Role of Natural Products in Drug Discovery", pp. 269-285. Springer.
    48. Li, X., Weng, J. K., and Chapple, C. (2008). Improvement of biomass through lignin modification. The Plant Journal 54, 569-581.
    49. Lin, H.-F. (2007). Knowledge sharing and firm innovation capability: an empirical study. International Journal of Manpower 28, 315-332.
    50. Liu, J. S., and Lu, L. Y. (2012). An integrated approach for main path analysis: Development of the Hirsch index as an example. Journal of the American Society for Information Science and Technology 63, 528-542.
    51. Loof, H., and Brostrom, A. (2008). Does knowledge diffusion between university and industry increase innovativeness? The Journal of Technology Transfer 33, 73-90.
    52. Lundvall, B.-A. (1992). National innovation system: towards a theory of innovation and interactive learning. Pinter, London.
    53. Lundvall, B.-A., and Johnson, B. (1994). The learning economy. Journal of industry studies 1, 23-42.
    54. Marco, A. C., and Rausser, G. C. (2008). The role of patent rights in mergers: Consolidation in plant biotechnology. American Journal of Agricultural Economics 90, 133-151.
    55. Narin, F. (1994). Patent bibliometrics. Scientometrics 30, 147-155.
    56. Narin, F., Noma, E., and Perry, R. (1987). Patents as indicators of corporate technological strength. Research policy 16, 143-155.
    57. Nelson, R. R., and Winter, S. G. (1977). In search of useful theory of innovation. Research policy 6, 36-76.
    58. O’Mahony, M., and Vecchi, M. (2009). R&D, knowledge spillovers and company productivity performance. Research Policy 38, 35-44.
    59. Paarrlberg, R., Gruhn, P., Goletti, F., and Yudelman, M. (2000). "Governing the GM Crop Revolution: Poilicy Choices for Developing Countries," Free downloads from IFPRI.
    60. Parayil, G. (2003). Mapping technological trajectories of the Green Revolution and the Gene Revolution from modernization to globalization. Research Policy 32, 971-990.
    61. Pianta, M., and Archibugi, D. (1996). Measuring technological change through patents and innovation surveys. Technovation, 451-468.
    62. Potrykus, I. (2001). Golden rice and beyond. Plant Physiology 125, 1157-1161.
    63. Pray, C., Oehmke, J. F., and Naseem, A. (2005). Innovation and dynamic efficiency in plant biotechnology: An introduction to the researchable issues.
    64. Pray, C. E., and Fuglie, K. O. (2001). "Private investment in agricultural research and international technology transfer in Asia," US Department of Agriculture, Economic Research Service.
    65. Qaim, M. (2009). The economics of genetically modified crops. Resource 1.
    66. Singh, J. (2005). Collaborative networks as determinants of knowledge diffusion patterns. Management science 51, 756-770.
    67. Singh, J. (2007). External collaboration, social networks and knowledge creation: Evidence from scientific publications. In "Danish Research Unit of Industrial Dynamics Summer Conference", pp. 1-43.
    68. Smith, H. A., Swaney, S. L., Parks, T. D., Wernsman, E. A., and Dougherty, W. G. (1994). Transgenic plant virus resistance mediated by untranslatable sense RNAs: expression, regulation, and fate of nonessential RNAs. The Plant Cell Online 6, 1441-1453.
    69. Soule, M., Klotz-Ingram, C., Daberkow, S., and Goodhue, R. (2002). Adoption of Bioengineered Crops. By Jorge Fernandez-Cornejo and.
    70. Spielman, D. J., and von Grebmer, K. (2004). "Public-private partnerships in agricultural research: an analysis of challenges facing industry and the Consultative Group on International Agricultural Research," Intl Food Policy Res Inst.
    71. Tallman, S., Jenkins, M., Henry, N., and Pinch, S. (2004). Knowledge, clusters, and competitive advantage. Academy of management review 29, 258-271.
    72. Taube, V. G. (2004). Measuring the social capital of brokerage roles. Connections 26, 29-52.
    73. Tollefson, J. (2011). Brazil cooks up transgenic bean. Nature 478, 168.
    74. USDA Recent Trends in GE adoption. June Agriculture Survey, U.S. Dept. of Agriculture, National Agriculture Statistics Service (NASS).
    75. Vain, P. (2006). Global trends in plant transgenic science and technology (1973–2003). TRENDS in Biotechnology 24, 206-211.
    76. Vain, P. (2007a). Thirty years of plant transformation technology development. Plant biotechnology journal 5, 221-229.
    77. Vain, P. (2007b). Trends in GM crop, food and feed safety literature. Nature biotechnology 25, 624-626.
    78. Van Wijk, J., Cohen, J., and Komen, J. (1993). "Intellectual Property Rights for Agricul-tural Biotechnology: Options and Implications for Developing Countries. A Biotech-nology Research Management Study." ISNAR Research Report.
    79. Yoon, B., and Park, Y. (2004). A text-mining-based patent network: Analytical tool for high-technology trend. The Journal of High Technology Management Research 15, 37-50.
    80. Young, T. R. (2004). "Genetically Modified Organisms and Biosafety: A background paper for decision-makers and others to assist in consideration of GMO issues," IUCN.
    81. Zucker, L. G., Darby, M. R., and Armstrong, J. (1998). Geographically localized knowledge: spillovers or markets? Economic Inquiry 36, 65-86.
    82. Zucker, L. G., Darby, M. R., and Brewer, M. B. (1999). "Intellectual capital and the birth of US biotechnology enterprises." National Bureau of Economic Research.

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