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研究生:林建餘
研究生(外文):LIN, CHIEN-YU
論文名稱:結構性方法辨識侵權訴訟與知識流動網路的位置與角色:以智慧型手機公司為例
論文名稱(外文):A Structured Approach to Identify the Position and Role on Litigation and Knowledge Flows Network: Evidence from Smartphone companies
指導教授:黃邦寧黃邦寧引用關係賴奎魁賴奎魁引用關係
指導教授(外文):Hwang, Bang-NingLal, Kuei-Kuei
口試委員:陳世良張世其陳宥杉蘇芳霈
口試委員(外文):CHEN, SHIEH-LIANGCHANG, SHIH-CHICHEN, YU-SHANSu, Fang-Pei
口試日期:2017-12-04
學位類別:博士
校院名稱:國立雲林科技大學
系所名稱:企業管理系
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2018
畢業學年度:106
語文別:中文
論文頁數:81
中文關鍵詞:專利侵權訴訟網絡分析網絡中心性角色與位置知識流
外文關鍵詞:Patent Infringement LitigationNetwork AnalysisNetwork CentricityRole and LocationKnowledge Flow
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甚多學者探討辨識網絡中的位置與角色的方法,然而這些分析方法缺乏結構性的分析步驟。因此,本研究的目的是透過結構化的網絡分析、多變量分析與知識流動的模式,來辨識網絡上的位置與角色。第一步:計算網絡的結構性質的統計量。第二步:以多變量分析中的主成分分析縮減數個主成分元件。再利用主成分元件做為集群變數進行兩階段集群分析。首先以階層式集群分析決定適當的分群數目k,再以K-means進行集群分析,並以MANOVA檢定k個位置的顯著性。以新的相鄰矩陣計算位置內與位置間之關係強度,並訂定強度的cut off value檢定其顯著性,並依每一位置的關係與位置內公司的共同性質,對每一位置訂定合宜角色的標名。此結構方法建立後,以智慧型手機業者間的訴訟關係網絡為實證,結果顯示此一結構方法有效地辨識訴訟網絡中的位置與角色。
再以專利引用網絡分析,將代表標準化的知識淨流出量的O-I指標與中介中心性,辨識智慧型手機業者在知識流中所扮演的位置與角色。本研究發現,當O-I指標接近0時,此模式可能會失靈。若公司落在O-I指標接近0且仲介中心性很高的區域,該公司可能同時擁有極高的向外與向內中心性。此區域的公司獨立在先前研究的四種分類之外,既不屬於知識吸收者也不屬於知識生產者,形成新的一種分類,稱為「知識轉化者」,研究結果顯示在智慧型手機中「知識轉化者」通常是產業的重要公司。

Many scholars explore approaches to identify the position and role of the network, however, these approaches lack structural analysis steps. The purpose of this study is to identify the position and role of the network through network analysis, multivariate analysis and knowledge flow patterns analysis. The first step, Calculated the structural network statistics. The second Step, Principal component analysis was used to extract cluster variables to facilitate two-stage cluster analysis. Firstly, the hierarchical cluster analysis was used to determine the appropriate number of clusters k, then cluster analyzed with K-means, and tested the significance of k position with MANOVA. The new adjacency matrix was used to calculate the intensity of the relationship within positions and between positions, and the cut off value of intensity was determined to test significance of each location, then labeled the role for each position according to the relationship between positions.After the establishment of this Structural approach, taking the litigation network of smart phone manufacturers as an example, the results show that this approach can effectively identify the position and role of the litigation network.
The patent citation network was analyzed to identify the position and role of the mobile phone manufacturers in the knowledge flow through O-I index which represents the standardization net outflow of knowledge and betweenness centrality. This study found when the O-I index approaches 0, this mode may fail. If a company falls into an area near zero of O-I index and have a high degree of betweenness centrality, the company may hold both outward and inward centrality. Companies in this area form a new category called "knowledge converters" which is independent of the four categories previously studied, neither belong to the knowledge absorber nor belong to the knowledge producer,they were showed usually an important company in the industry.

摘要 I
Abstract II
誌謝 III
目錄 IV
表目錄 VI
圖目錄 VII
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 4
1.3 研究目的 7
1.4 研究範疇 10
1.5 論文章節架構 11
第二章 文獻探討 12
2.1 社會網絡 12
2.2 訴訟網絡 16
2.3 技術網絡 18
2.4 知識流 21
第三章 研究方法 25
3.1 資料收集 28
3.2 訴訟資料分析 30
3.3 專利引用資料分析 38
第四章 訴訟關係位置的角色分析 46
4.1 訴訟關係網絡結構性質 46
4.2 計算中心性統計量,呈現訴訟關係之網絡結構與性質 46
4.3 決定集群變數與集群分析 49
第五章 系爭專利公司間知識流的位置的角色分析 57
5.1 引用關係網絡結構性質 57
5.2 計算中心性統計量,呈現引用關係之網絡結構與性質 57
5.3 知識關係位置的角色分析 63
第六章 結論 67
6.1 結論 67
6.2 專利指標管理意涵 72
6.3 研究限制 72
參考文獻 74
一、中文部分 74
二、英文部分 75


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