Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/146662
|
| Title: | 網絡社區結構的跨界和異質性學習與創新效果：全球半導體公司間的專利引用網絡分析
Trans-Community and Heterogeneous Learning of Network Community Structure and Innovation Effects: An Analysis of Patent Citation Networks among Global Semiconductor Firms |
| Authors: | 江韋築
Jiang, Wei-Zhu |
| Contributors: | 熊瑞梅
鄭力軒
Hsung, Ray-May
Cheng, Li-Hsuan
江韋築
Jiang, Wei-Zhu |
| Keywords: | 全球半導體技術知識場域
公司間專利相互引用網絡
社區偵測
跨界
異質性
Global semiconductor technical knowledge field
Patent citation network among firms
Community detection
Trans-community
Heterogeneity |
| Date: | 2023 |
| Issue Date: | 2023-08-02 14:25:08 (UTC+8) |
| Abstract: | 本研究企圖從技術知識場域的觀點進行技術創新之網絡結構型態分析。透過社會網絡分析，本研究從專利相互引用資料中描繪出半導體製程技術的全球技術知識場域，並以組織場域的概念探究全球頂尖半導體公司的技術知識學習創新行動。本研究企圖整合技術知識場域的知識叢集化與地位層級化結構特徵，並探討公司在這些結構條件下如何進行異質知識探索與創新。本研究利用社區偵測方法辨識技術知識場域中的不同技術領域，並探討公司的異質領域知識探索如何促進公司在場域中得到的創新評價。「跨界」與「異質性」概念區分了技術知識領域內與外的差異，並提供公司一面進行領域內的知識累積，另一面進行領域外的異質性知識學習的同步並進之圖像。並且，本研究進一步檢視不同地位條件的公司進行跨界異質性學習探索的行為模式及創新回報模式的差異。
本研究有四個主要發現。（1）半導體技術知識場域的社區結構由混亂演變到穩定，多數公司的跨界探索從積極轉向溫和狀態，且異質性探索也越趨活躍。隨著場域社區結構演化，跨界探索發展出過猶不及之特性，異質性探索促進創新的效果也逐漸增強。（2）對高地位公司來說，鞏固領域內知識優勢有利維持其創新評價，但高地位公司普遍更積極進行跨界探索，反映出高地位公司之間可能存在著競逐長期技術優勢的激烈競爭。較寬鬆的「最佳跨界比例區間」使高地位公司採取次佳策略仍不會輕易流失地位。高地位公司仰賴異質性探索來提昇創新評價。（3）對低地位公司來說，中等偏高的跨界有利提昇其創新評價，然而最低地位的公司有較高的過度跨界傾向，再加上較窄的「最佳跨界比例區間」，使其向上流動的機會受限制。低地位公司較少進行高度異質性探索，但異質性探索對低地位公司有更顯著的助益。（4）邏輯、記憶體和設備領域相較於其他技術領域有更顯著的跨界過猶不及特性，突顯出此三領域是整體半導體製造技術場域中，技術深化與創新需求最活躍的領域。
This study attempts to analyze the network structures of technological innovation from the approach of the knowledge field. Using social network analysis, it configures the global knowledge field of semiconductor process technology based on patent citation data, and explores the actions which top semiconductor companies learn and innovate from the approach of the organizational field. This research attempts to integrate characteristics of knowledge clustering, hierarchical status in the technological knowledge field, and explores how to proceed the heterogeneous exploration and innovation under these structure conditions. Using community detection methods to identify different technological domains, this study investigates how exploring diverse knowledge promotes the evaluation of firm innovation. The concepts of "trans-community" and "heterogeneity" distinguish between knowledge within and outside the domain, and provide the configuration of simultaneous processing of inside knowledge accumulation and outside heterogeneous learning. This study further examines the differentiated effects of trans-community and heterogeneous learning on the return of innovation under hierarchical status conditions.
The findings show that (1) The community structure of the global semiconductor technical knowledge field evolves from chaos to stability. The trans-community exploration for most companies has shifted from proactive to moderate state, and heterogeneous exploration has also been increasingly active. As the field community structure evolves, trans-community exploration has developed a balance-required characteristic, and the effect of heterogeneous exploration on innovation has also been increasingly strong. (2) As to high-status companies, consolidating knowledge advantages within the domain is beneficial for maintaining their evaluation of innovation, but they usually perform trans-community exploration more proactively. It implies that there may be intense competition for a long-term technology advantage among high-status companies. A broader "optimal trans-community ratio range" allows them to adopt suboptimal strategies without losing position. High-status companies rely on heterogeneous exploration to level up evaluation of innovation. (3) As to low-status companies, moderately high trans-community exploration enhances their evaluation of innovation, but companies with the lowest status rank tend to perform excessive exploration which, combined with a narrower "optimal trans-community ratio range", hinders upward mobility. Highly heterogeneous exploration is less frequent for low-status companies but more beneficial for them. (4) The balance-required characteristics is more significant in logic, memory, and equipment technology domains, which indicates these three domains have the most active technology deepening and innovation demand in the entire field. |
| Reference: | 參考書目
王振寰，2010，《追趕的極限 : 台灣的經濟轉型與創新》高雄：巨流圖書。
朱浩筠，2011，〈論專利說明書中引用文獻與揭露要件之關連性－兼述智慧財產法院 97 行專訴字第 63 號判決〉。《智慧財產權月刊》145：61-78。
林亦之、熊瑞梅，2012，〈台灣IC產業組織間技術網絡的槓桿機制：後進追趕與創新擴散〉。《戰略管理》1：72-98。
洪世章，2021，《打造創新路徑：改變世界的台灣科技產業》新北市：聯經。
柯佩均，2008，《台灣社會學門的知識生產網絡機制 : 以2001-2006年社會學門學術期刊引用網絡為例》。台北：政治大學社會學研究所碩士論文。
柯佩均、熊瑞梅、盧科位，2012，〈台灣社會學門專業期刊間引用網絡之結構分析〉。《教育資料與圖書館學》49（4）：533-561。
施敏、伍國珏 著，張鼎張、劉柏村 譯，2008，《半導體元件物理學》新竹市：國立交通大學出版社。
陳東升，2008，《積體網路：台灣高科技產業的社會學分析》台北：群學。
陳豐年，2011，〈專利權之歷史溯源與利弊初探〉。《智慧財產權月刊》146:63-87。
劉國讚、柯正怡，2013，〈隱藏在專利件數背後的專利強度指標〉。《專利師》13：1-16。
蘇國賢，2004，〈社會學知識的社會生產：台灣社會學者的隱形學群〉。《台灣社會學刊》8：133-192。
Ahuja, G., 2000,"Collaboration Networks, Structural Holes, and Innovation: A Longitudinal Study." Administrative Science Quarterly 45(3):425–455.
Albert, Réka, and A. L. Barabási, 2002,“Statistical Mechanics of Complex Networks.”Reviews of Modern Physics 74(1):47–97.
Anderson, P., and Tushman, M. L., 1990, "Technological Discontinuities and Dominant Designs: A Cyclical Model of Technological Change." Administrative Science Quarterly 35(4): 604–633.
Bonacich P., 1987, “Power and Centrality: A Family of Measures.” American Journal of Sociology 92(5):1170-1182.
Bourdieu, Pierre, 1975,“The Specificity of the Scientific Field and the Social Conditions for the Progress of Reason.”Social Science Information 14(6):19–47.
Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., Bolker, B.M., 2017,“glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling.” The R Journal 9(2): 378–400.
Burt, R. S., 1992, Structural Holes: The Social Structure of Competition. Harvard University Press.
Castellucci, Fabrizio, and Joel M. Podolny, 2017, "The dynamics of position, capability, and market competition." Industrial and Corporate Change 26(1): 21-39.
DiMaggio, P. J., and Powell, W. W., 1983, "The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields." American Sociological Review 48(2):147–160.
Foster, J. G., Rzhetsky, A., and Evans, J. A., 2015, "Tradition and Innovation in Scientists’ Research Strategies." American Sociological Review 80(5): 875–908.
Granovetter, Mark, 1973, "The Strength of Weak Ties." American Journal of Sociology 78(6):1360-1380.
Granovetter, Mark, 1985, "Economic Action and Social Structure: The Problem of Embeddedness." American Journal of Sociology 91(3):481-510.
Hall, P. and Soskice, D., 2001, "An Introduction to Varieties of Capitalism." Pp. 1-70 in Varieties of Capitalism: The Institutional Foundations of Comparative Advantage, edited by Hall, P. and Soskice, D. Oxford: Oxford University Press.
Heger, Diana, and Alexandra K. Zaby, 2018, "Patent breadth as effective barrier to market entry." Economics of Innovation and New Technology 27(2), 174-188.
Hollstein, Betina, 2021,“Georg Simmel’s Contribution to Social Network Research.”Pp. 44-59 in Personal Networks: Classic Readings and New Directions in Egocentric Analysis, edited by Mario Small, Brea Perry, Bernice Pescosolido, and Edward Smith. New York : Cambridge University Press.
Jiang, Lin, Tan, Justin and Thursby, Marie C., 2010, "Incumbent Firm Invention in Emerging Fields: Evidence from the Semiconductor Industry" Strategic Management Journal 32 (1): 55-75.
Kuhn, Thomas S, 1962, The Structure of Scientific Revolutions. Chicago: University of Chicago Press.
Luke, D., 2015, A User’s Guide to Network Analysis in R. Springer Cham.
Lundvall, Bengt-Åke, 2010, National Systems of Innovation: Toward a Theory of Innovation and Interactive Learning. Anthem Press.
Mani, Dahlia, and James Moody, 2014, "Moving beyond Stylized Economic Network Models: The Hybrid World of the Indian Firm Ownership Network." American Journal of Sociology 119(6):1629-1669.
March, James, 1991, "Exploration and Exploitation in Organizational Learning." Organization Science 2(1):71-87.
McPherson, Miller, L. Smith-Lovin, and J. Cook, 2001,“Birds of a Feather: Homophily in Social Networks.” Annual Review of Sociology 27:415–44.
Merton, Robert K. 1973. “The Normative Structure of Science.” Pp. 267–278 in The Sociology of Science, by Robert K. Merton. Chicago: University of Chicago Press.
Moody, James, and Douglas R. White, 2003,“Social Cohesion and Embeddedness: A Hierarchical Conception of Social Groups.”American Sociological Review 68 (1):103–128.
Newman, M.EJ., 2006, "Modularity and Community Structure in Networks." Proceedings of the National Academy of Sciences 103(13):8577-8582.
Nooy, W.D., Mrvar, A., and Batagelj, V., 2018, Exploratory Social Network Analysis with Pajek. Cambridge University Press
Podolny, J. M., 2005, Status signals : a sociological study of market competition. Princeton University Press.
Powell, W. W., 1990, "Neither Market Nor Hierarchy: Network Forms of Organization." Research in Organizational Behavior 12: 295-336.
Powell, W. W., White, D. R., Koput, K. W., and Owen-Smith, J., 2005, "Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life Sciences." American Journal of Sociology 110(4): 1132–1205.
Radicchi, F., Fortunato, S., Vespignani, A., 2012, "Citation Networks." Pp. 233-260.In Models of Science Dynamics: Understanding Complex Systems, edited by Scharnhorst, A., Börner, K., van den Besselaar, P. Berlin, Heidelberg : Springer.
Rosvall, Martin, D. Axelsson, and Carl T. Bergstrom, 2009,“The Map Equation.” European Physical Journal Special Topics 178(1):13–23.
Sauder, Michael, Freda Lynn, and Joel M. Podolny, 2012, "Status: Insights from Organizational Sociology." Annual Review of Sociology 38:267-283.
Schumpeter, J.A., 1934, The Theory of Economic Development: An Inquiry into Profits, Capital, Credits, Interest, and the Business Cycle. Transaction Publishers, Piscataway.
Scott, John, 2000, Social Network Analysis: a handbook. 2nd Edition, London: Sage Publications.
Shwed, U., and Bearman, P. S., 2010,"The Temporal Structure of Scientific Consensus Formation." American Sociological Review 75(6):817–840.
Simmel, Georg, 1950, The Sociology of Georg Simmel (Translated & Edited by Kurt H. Wolff). Glencoe, Illinois: The Free Press.
Spence, A. Michael, 1974, Market Signaling: Information Transfer in Hiring and Related Process. Cambridge, MA: Harvard University Press.
Sturgeon, Timothy J., 2002, "Modular production networks: a new American model of industrial organization." Industrial and Corporate Change 11(3):451–496.
Wasserman, S., and Faust, K., 1994, Social network analysis: Methods and applications. Cambridge University Press.
Williamson, Oliver E, 1981,“The Economics of Organization: The Transaction Cost Approach.” American Journal of Sociology 87:548–577. |
| Description: | 碩士
國立政治大學
社會學系
110254004 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0110254004 |
| Data Type: | thesis |
| Appears in Collections: | [社會學系] 學位論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| 400401.pdf | | 21560Kb | Adobe PDF2 | 90 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
