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題名 核心技術創新的公司財務績效之探討-以半導體產業中DRAM技術為例
The Financial Performance of Core Technology Innovation - The Case of DRAM Technology in the Semiconductor Industry作者 陳韋璇
Chen, Wei-Xuan貢獻者 李浩仲<br>李文傑
Li, Hao-Chung<br>Lee, Wen-Chieh
陳韋璇
Chen, Wei-Xuan關鍵詞 半導體
專利網絡
核心技術
財務績效
Semiconductor
Patent Citation
Core Technology
Firm Performance日期 2022 上傳時間 2-Sep-2022 15:27:38 (UTC+8) 摘要 半導體產業與我們現在的生活密不可分，而半導體產業屬於高技術產業，必須藉由不斷的研發與創新才能保持其不被市場所淘汰，在DRAM市場上的競爭尤為激烈，目前以美光科技、SK海力士與三星獨大，三家廠商的市占率高達95%，為一寡占市場。本研究藉由半導體1980年到2021年的專利文獻建構專利引用網絡，並進一步找尋核心專利分布的廠商，以此探討DRAM廠商在市場競爭時，所掌握的核心技術與市場表現之關聯。研究結果顯示，在DRAM產業中，廠商擁有越多的核心專利，並且專業化集中於少數技術領域，能達到更好的財務表現。因此，創新是DRAM公司在成長過程中一個很重要的因素，擁有更多核心專利與專業化的技術，在未來的產業發展上可為公司帶來更多獲利。
Understanding key successful factors (KSF) in a competition is crucial to a firm`s sustainable growth in the relative business environment. For example, the Dynamic Random Access Memory (DRAM) industry has long been believed as the most competitive field in semiconductor manufacturing and the business’s exit is rampant. In this vein, this research intends to identify the KSFs for DRAM firms` survival. Via the computation of DRAM patents` citation networks, the main components of DRAM patents are back out and then utilized to DRAM firms` patent concentration as well as intensity index. The results show that those DRAM firms with their patent development concentrated in specialized areas will benefit the most from their long-term survival and sustainable growth in the operational financial performance in the industry.參考文獻 中文文獻王苡潼，(2018)。從三星的策略看DRAM產業，TEJ信用風險評估專刊。李文傑，(2022)。資源錯置與產業動態：以台灣的動態隨機存取記憶體產業為例。金捷幡，(2019)。【歷史】內存的故事 (紀念DRAM量產50年)，擷取日期：2022 年 5 月 30 日，網址：https://kknews.cc/tech/o3kmgxq.html陳玠瑋，(2011)。2011 年全球 DRAM 產業發展趨勢，工研院產業經濟與趨勢研究中心。彭茂榮，(2014)。2014 年全球 DRAM 產品發展趨勢，工研院產業經濟與趨勢研究中心。彭茂榮，(2017)。2017 年全球 DRAM 產品發展趨勢，工研院產業經濟與趨勢研究中心。彭茂榮，(2017)。全球記憶體產品市場發展趨勢與主要廠商，工研院產業經濟與趨勢研究中心。彭茂榮，(2021)。各國半導體產業發展政策概況，工研院產業經濟與趨勢研究中心。彭國柱，(2008)。DRAM 混戰：韓廠進逼、台廠且戰且走、 日廠迂迴鞏固戰略高地，工研院產業經濟與趨勢研究中心。劉美君，(2019)。突破與創新-看全球記憶體技術與市場發展變動趨勢，工研院產業經濟與趨勢研究中心。劉美君，(2020)。蛻變與新生-2019 年全球記憶體產業回顧 與 2020 年展望，工研院產業經濟與趨勢研究中心。蘇孟宗，(2013)。2013-2015科技與產業趨勢，工研院產業經濟與趨勢研究中心。英文文獻Bahk, B.-H. and Gort, M. (1993). Decomposing Learning by Doing in New Plants. Journal of Political Economy. 101(4), 561–583.Benkard, C. L. (2000). Learning and Forgetting: The Dynamics of Aircraft Production. American Economic Review. 90(4), 1034–1054.Camisón, C. and A. Villar-López (2014), Organizational innovation as an enabler of technological innovation capabilities and firm performance, Journal of Business Research, 67(1), 2891-2902.Connolly, R.A. & Hirschey, M. (1988). Market Value and Patents: A Bayesian Approach. Economics Letters, Vol. 27, pp. 83.Garfield, E. (1955). Citation indexes for science: A new dimension in documentation through Association of Ideas. Science, 122(3159), 108-110.Hashi, I. and N. Stojčić (2013), The impact of innovation activities on firm performance using a multi-stage model: Evidence from the Community Innovation Survey 4, Research Policy, 42(2), 353-366.Hirshleifer, D., P. H., Hsu, and D. Li (2013). Innovative efficiency and stock returns. Journal of Financial Economics, 107(3), 632–54.Hummon, N.P. & Doreain, P. (1989). Connectivity in a Citation Network: The Development of DNA Theory. Social Networks, 11, 39-63.Jarmin, R. S. (1994). Learning by Doing and Competition in the Early Rayon Industry. RAND Journal of Economics, 25(3), 441–454.Kim, D & Kim, N & Kim, W. (2018). The effect of patent protection on firms’ market value: the case of the renewable energy sector. Renewable and Sustainable Energy Reviews, 2018; 82: 4309-19.Lanjouw, J. O. & Schankerman, M. (2004). Patent quality and research productivity: Measuring innovation with multiple indicators. The Economic Journal, 114(495), 441-465.Lin, B. W., C. J., Chen, H. L., Wu (2006). Patent portfolio diversity, technology strategy, and firm value. IEEE Transactions on Engineering Management, 53(1), 17-26.Ma, Daw and John Mark (2003). The DRAM Market Structure: The Rise and Fall in Concentration. The 8th Annual Cambridge International Manufacturing Symposium, Cambridge, UK.Markman, G. D., M. I., Espina, and P. H., Phan (2004). “Patents as Surrogates for Inimitable and Non-Substitutable Resources”, Journal of Management, 30(4), 529-544.Murillo, L.E. (1993). “The International Dynamic Random Access Memory Industry From 1970 to 1993 Examined Under the Dynamic Capabilities Prism: Implications for Technology Policy [Ph.D. Thesis],” University of California, Berkeley.Newman, Mark. (2004). Fast algorithm for detecting community structure in networks. Physical review E, 69(6), 066133.Singh A. & Triulzi G. & Magee C. (2021). Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description. Research Policy, 50.Thompson, P. (2001). How Much Did the Liberty Shipbuilders Learn?: New Evidence for an Old Case Study. Journal of Political Economy, 109(1), 103–137.Thornton, R. A. & Thompson, P. (2001). Learning from Experience and Learning from Others: An Exploration of Learning and Spillovers in Wartime Shipbuilding. American Economic Review, 91(5), 1350–1369Trajtenberg, M., R. Henderson & A. Jaffe, (1997). University Versus Corporate Patents: A Window on The Basicness of Invention. Economics of Innovation and New Technology, vol. 5, no. 1, pp. 19-50.Triulzi, G. (2015). Looking for the right path: technology dynamics, inventive strategies and catching-up in the semiconductor industry. Maastricht: Datawyse /Universitaire Pers Maastricht.Triulzi, G. & Alstottc, J. & Magee C. (2020). Estimating technology performance improvement rates by mining patent data. Technological Forecasting & Social Change,158.Valentini, G. (2012). Measuring the effect of M&A on patenting quantity and quality. Strategic Management Journal (33), 336-346.Verspagen, B. (2007). Mapping Technological Trajectories as Patent Citation Networks. A Study on the History of Fuel Cell Research. Advances in Complex Systems 10, 93-115. 描述 碩士
國立政治大學
經濟學系
109258039資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109258039 資料類型 thesis dc.contributor.advisor 李浩仲<br>李文傑 zh_TW dc.contributor.advisor Li, Hao-Chung<br>Lee, Wen-Chieh en_US dc.contributor.author (Authors) 陳韋璇 zh_TW dc.contributor.author (Authors) Chen, Wei-Xuan en_US dc.creator (作者) 陳韋璇 zh_TW dc.creator (作者) Chen, Wei-Xuan en_US dc.date (日期) 2022 en_US dc.date.accessioned 2-Sep-2022 15:27:38 (UTC+8) - dc.date.available 2-Sep-2022 15:27:38 (UTC+8) - dc.date.issued (上傳時間) 2-Sep-2022 15:27:38 (UTC+8) - dc.identifier (Other Identifiers) G0109258039 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/141747 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description (描述) 109258039 zh_TW dc.description.abstract (摘要) 半導體產業與我們現在的生活密不可分，而半導體產業屬於高技術產業，必須藉由不斷的研發與創新才能保持其不被市場所淘汰，在DRAM市場上的競爭尤為激烈，目前以美光科技、SK海力士與三星獨大，三家廠商的市占率高達95%，為一寡占市場。本研究藉由半導體1980年到2021年的專利文獻建構專利引用網絡，並進一步找尋核心專利分布的廠商，以此探討DRAM廠商在市場競爭時，所掌握的核心技術與市場表現之關聯。研究結果顯示，在DRAM產業中，廠商擁有越多的核心專利，並且專業化集中於少數技術領域，能達到更好的財務表現。因此，創新是DRAM公司在成長過程中一個很重要的因素，擁有更多核心專利與專業化的技術，在未來的產業發展上可為公司帶來更多獲利。 zh_TW dc.description.abstract (摘要) Understanding key successful factors (KSF) in a competition is crucial to a firm`s sustainable growth in the relative business environment. For example, the Dynamic Random Access Memory (DRAM) industry has long been believed as the most competitive field in semiconductor manufacturing and the business’s exit is rampant. In this vein, this research intends to identify the KSFs for DRAM firms` survival. Via the computation of DRAM patents` citation networks, the main components of DRAM patents are back out and then utilized to DRAM firms` patent concentration as well as intensity index. The results show that those DRAM firms with their patent development concentrated in specialized areas will benefit the most from their long-term survival and sustainable growth in the operational financial performance in the industry. en_US dc.description.tableofcontents 目次第一章 緒論 1第一節 專利價值 1第二節 核心技術的重要性 2第三節 研究動機 4第二章 文獻回顧 8第一節 專利引用網絡 8第二節 主要路徑與技術分析 9第三節 DRAM產業特性 10第四節 專利與公司財務績效 11第三章 研究方法 12第一節 研究流程 12第二節 專利網絡與中心性 13第三節 專利技術水平 16第四節 子技術分群 17第五節 專利知識持久性 19第六節 研究假設與迴歸模型 22第四章 資料 26第一節 資料來源 26第二節 資料處理流程 27第三節 敘述統計 30第五章 研究結果 45第一節 DRAM 之廠商專利品質 45第二節 模型結果 53第六章 結論與建議 55參考文獻 57附錄 61 zh_TW dc.format.extent 3419377 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109258039 en_US dc.subject (關鍵詞) 半導體 zh_TW dc.subject (關鍵詞) 專利網絡 zh_TW dc.subject (關鍵詞) 核心技術 zh_TW dc.subject (關鍵詞) 財務績效 zh_TW dc.subject (關鍵詞) Semiconductor en_US dc.subject (關鍵詞) Patent Citation en_US dc.subject (關鍵詞) Core Technology en_US dc.subject (關鍵詞) Firm Performance en_US dc.title (題名) 核心技術創新的公司財務績效之探討-以半導體產業中DRAM技術為例 zh_TW dc.title (題名) The Financial Performance of Core Technology Innovation - The Case of DRAM Technology in the Semiconductor Industry en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 中文文獻王苡潼，(2018)。從三星的策略看DRAM產業，TEJ信用風險評估專刊。李文傑，(2022)。資源錯置與產業動態：以台灣的動態隨機存取記憶體產業為例。金捷幡，(2019)。【歷史】內存的故事 (紀念DRAM量產50年)，擷取日期：2022 年 5 月 30 日，網址：https://kknews.cc/tech/o3kmgxq.html陳玠瑋，(2011)。2011 年全球 DRAM 產業發展趨勢，工研院產業經濟與趨勢研究中心。彭茂榮，(2014)。2014 年全球 DRAM 產品發展趨勢，工研院產業經濟與趨勢研究中心。彭茂榮，(2017)。2017 年全球 DRAM 產品發展趨勢，工研院產業經濟與趨勢研究中心。彭茂榮，(2017)。全球記憶體產品市場發展趨勢與主要廠商，工研院產業經濟與趨勢研究中心。彭茂榮，(2021)。各國半導體產業發展政策概況，工研院產業經濟與趨勢研究中心。彭國柱，(2008)。DRAM 混戰：韓廠進逼、台廠且戰且走、 日廠迂迴鞏固戰略高地，工研院產業經濟與趨勢研究中心。劉美君，(2019)。突破與創新-看全球記憶體技術與市場發展變動趨勢，工研院產業經濟與趨勢研究中心。劉美君，(2020)。蛻變與新生-2019 年全球記憶體產業回顧 與 2020 年展望，工研院產業經濟與趨勢研究中心。蘇孟宗，(2013)。2013-2015科技與產業趨勢，工研院產業經濟與趨勢研究中心。英文文獻Bahk, B.-H. and Gort, M. (1993). Decomposing Learning by Doing in New Plants. Journal of Political Economy. 101(4), 561–583.Benkard, C. L. (2000). Learning and Forgetting: The Dynamics of Aircraft Production. American Economic Review. 90(4), 1034–1054.Camisón, C. and A. Villar-López (2014), Organizational innovation as an enabler of technological innovation capabilities and firm performance, Journal of Business Research, 67(1), 2891-2902.Connolly, R.A. & Hirschey, M. (1988). Market Value and Patents: A Bayesian Approach. Economics Letters, Vol. 27, pp. 83.Garfield, E. (1955). Citation indexes for science: A new dimension in documentation through Association of Ideas. Science, 122(3159), 108-110.Hashi, I. and N. Stojčić (2013), The impact of innovation activities on firm performance using a multi-stage model: Evidence from the Community Innovation Survey 4, Research Policy, 42(2), 353-366.Hirshleifer, D., P. H., Hsu, and D. Li (2013). Innovative efficiency and stock returns. Journal of Financial Economics, 107(3), 632–54.Hummon, N.P. & Doreain, P. (1989). Connectivity in a Citation Network: The Development of DNA Theory. Social Networks, 11, 39-63.Jarmin, R. S. (1994). Learning by Doing and Competition in the Early Rayon Industry. RAND Journal of Economics, 25(3), 441–454.Kim, D & Kim, N & Kim, W. (2018). The effect of patent protection on firms’ market value: the case of the renewable energy sector. Renewable and Sustainable Energy Reviews, 2018; 82: 4309-19.Lanjouw, J. O. & Schankerman, M. (2004). Patent quality and research productivity: Measuring innovation with multiple indicators. The Economic Journal, 114(495), 441-465.Lin, B. W., C. J., Chen, H. L., Wu (2006). Patent portfolio diversity, technology strategy, and firm value. IEEE Transactions on Engineering Management, 53(1), 17-26.Ma, Daw and John Mark (2003). The DRAM Market Structure: The Rise and Fall in Concentration. The 8th Annual Cambridge International Manufacturing Symposium, Cambridge, UK.Markman, G. D., M. I., Espina, and P. H., Phan (2004). “Patents as Surrogates for Inimitable and Non-Substitutable Resources”, Journal of Management, 30(4), 529-544.Murillo, L.E. (1993). “The International Dynamic Random Access Memory Industry From 1970 to 1993 Examined Under the Dynamic Capabilities Prism: Implications for Technology Policy [Ph.D. Thesis],” University of California, Berkeley.Newman, Mark. (2004). Fast algorithm for detecting community structure in networks. Physical review E, 69(6), 066133.Singh A. & Triulzi G. & Magee C. (2021). Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description. Research Policy, 50.Thompson, P. (2001). How Much Did the Liberty Shipbuilders Learn?: New Evidence for an Old Case Study. Journal of Political Economy, 109(1), 103–137.Thornton, R. A. & Thompson, P. (2001). Learning from Experience and Learning from Others: An Exploration of Learning and Spillovers in Wartime Shipbuilding. American Economic Review, 91(5), 1350–1369Trajtenberg, M., R. Henderson & A. Jaffe, (1997). University Versus Corporate Patents: A Window on The Basicness of Invention. Economics of Innovation and New Technology, vol. 5, no. 1, pp. 19-50.Triulzi, G. (2015). Looking for the right path: technology dynamics, inventive strategies and catching-up in the semiconductor industry. Maastricht: Datawyse /Universitaire Pers Maastricht.Triulzi, G. & Alstottc, J. & Magee C. (2020). Estimating technology performance improvement rates by mining patent data. Technological Forecasting & Social Change,158.Valentini, G. (2012). Measuring the effect of M&A on patenting quantity and quality. Strategic Management Journal (33), 336-346.Verspagen, B. (2007). Mapping Technological Trajectories as Patent Citation Networks. A Study on the History of Fuel Cell Research. Advances in Complex Systems 10, 93-115. zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202201233 en_US
