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研究生:蘇東明
研究生(外文):Tung-Ming Su
論文名稱:利用資料包絡分析建構專利價值指標─以商業方法為例
論文名稱(外文):A Study on constitution of paten value index bydata envelopment analysis,Example on business method.
指導教授:賴奎魁賴奎魁引用關係張善斌張善斌引用關係
指導教授(外文):Kuei-Kuei LaiShann-Bin Chang
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:企業管理系碩士班
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:2005
畢業學年度:93
語文別:中文
論文頁數:76
中文關鍵詞:資料包絡分析技術鑑價基礎專利
外文關鍵詞:basic patenttechnology evaluationdata envelopment analysis
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在「知識經濟」時代的背景下,現今企業無形資產的價值已遠大於有形資產,亦即企業除了必須具備有形資產的生產要素外,無形資產更是企業在商場上致勝的關鍵。一般而言,無形資產包含行銷能力、供應鏈或客戶關係管理能力、品牌形象、員工教育水平與素質、公司研發能力、公司專利或商標數量等。一家企業所擁有之無形資產愈多其產生之價值亦愈大,例如IBM將其強大的研發能力對應到專利權利金收入,在短短的十年之間其專利的授權金已從3億美元暴漲到10億美元,幾乎佔IBM 2000年稅前營收的九分之一。由上例可知無形資產對企業而言,其重要性已不可同日而語。

故無形資產鑑價制度的建立對於產業界、銀行界實在是一件刻不容緩的事情。在鑑價機制方面,其核心在於如何把無形資產轉換成有價值的商品,具體化的供買賣雙方討論,其主要目的就是要降低專利技術交易訊息的不透明性。(楊國隆,2003)。而現今之技術鑑價方式大多是以財務或會計角度為切入點,例如經驗法則、比較法、淨現值法。但經由這些以財務或會計針對技術鑑價所做的研究嚴重的忽略了技術本身的價值性。若一昧的單以財務的參數指標估計技術本身的價值性,其技術或專利本身的價值將嚴重的遭受扭曲。本研究透過資料包絡分析(Data envelopment analysis)以專利間之引證關係建構評鑑專利之價值指標以助企業在技術授權的過程中,洞悉該項技術真正的價值並以之作為技術鑑價的評估方法。
In the age of knowledge economics, the value of intangible assets in business is far greater than tangible assets. It reflects that corporations must possess not only the tangible production factors, but also the intangible assets, key factor of success. Generally speaking, intangible assets comprise marketing capability, supply chain or customer relationship management, brand image, employees’ educational level, R&D capability and number of patent or trademark etc..
The more intangible asset corporations possess, the greater value can be created. For instance, IBM utilizes its powerful R&D capability to generate patent revenues. Within short ten years, the patent royalties have been raised from 300 mil. USD to 1,000 mil. USD. Almost one ninth of IBM’s income before tax in 2000. From the example, it is clear that the importance of intangible assets become more salient than past ever.
Thus, establishing an evaluation system for intangible assets is an urgent issue for industry and bank. In terms of evaluation mechanism, its core is how to turn intangible assets into valuable products and to be concrete for seller and buyer. The major objective is to reduce the non-transparency of patent transaction information (Yang, 2003).
Nowadays, most of technology evaluation methods are based on the perspectives of finance and accounting, such as empirical rule, comparison method, net present value method. In this case, the value of technology itself is saliently ignored. If we always use other parameters to asses the value of technology, the value of technology or patent itself will be seriously distorted. Therefore, this study constitutes the patent evaluation model through the data envelopment analysis and patent citation relationship. This model assists corporations to insight the real value of technology in the process of technology authorization, and to adopt it as the technology evaluation method.
目錄
中文摘要 i
英文摘要 ii
誌 謝 iii
目錄 iv
表目錄 vi
圖目錄 vii

第一章 緒論 - 1 -
第一節 研究背景 - 1 -
第二節 研究動機 - 2 -
第三節 研究問題與目的 - 4 -
第四節 研究架構 - 4 -
第二章 文獻探討 - 7 -
第一節 商業方法專利 - 7 -
一、商業方法與專利白皮書 - 7 -
二、US Class 705次分類 - 7 -
三、相對應之主要IPC與其他US Class - 8 -
四、商業方法專利與電腦軟體專利之比較 - 10 -
五、電子商務與商業模式 - 11 -
第二節 專利與專利分析 - 11 -
一、專利的性質與意義 - 11 -
二、專利分析的形式 - 12 -
第三節 績效評估 - 15 -
一、績效評估 - 15 -
二、資料包絡分析法 - 17 -
第三章 研究設計 - 27 -
第一節 研究架構 - 27 -
第二節 母體、樣本、分析單位 - 28 -
第三節 專利資料檢索 - 29 -
第四章 總體基礎分析 - 32 -
第一節 技術生命週期 - 32 -
第二節 各國歷年專利件數分析 - 32 -
第三節 公司別分析 - 33 -
第四節 UPC分析 - 34 -
第五章 效率分析 - 36 -
第一節 美國專利公報 - 36 -
一、基本資料 - 36 -
二、引證資料 - 37 -
三、專利內容 - 37 -
四、投入項與產出項之抉擇 - 38 -
第二節 總體效率分析 - 40 -
一、相關分析 - 40 -
二、模型之選取(CCR or BCC) - 42 -
三、Wilcoxon符號檢定 - 43 -
第三節 個體效率分析 - 44 -
一、投入產出項分析 - 44 -
二、個別單位的分析 - 49 -
三、小結 - 51 -
第四節 評估結果 - 52 -
一、專利內容分析 - 52 -
二、專利效率與專利年齡分布圖 - 55 -
第六章 綜合討論與結論 - 57 -
第一節 以資料包絡分析建構專利價值指標 - 57 -
第二節 本論文之貢獻 - 57 -
第三節 研究限制 - 58 -
第四節 後續延伸研究 - 58 -
參考文獻 - 60 -
















表目錄
表2-1 US Class 705 次分類 - 7 -
表2-2 IPC與US Class 705 之對應 - 8 -
表2-3 與US Class 705相關之其他美國專利分類號 - 9 -
表2-4 資料處理相關專利之US Class分類 - 10 -
表2-5 專利分析在管理上之應用 - 14 -
表2-6 CCR模式彙整 - 22 -
表2-7 BCC 模式彙整 - 25 -
表3-1 前50筆入選專利基本資料表 - 30 -
表4-1 所屬國家專利分析表時間範圍(93/01/26-99/12/28) - 33 -
表4-2 公司別專利資料彙整表 - 33 -
表4-3 UPC分類表 - 34 -
表5-1 美國專利INID碼 - 36 -
表5-2 專利內容 - 37 -
表5-3 受評單位投入項、產出項 - 39 -
表5-4 調整前相關分析 - 41 -
表5-5 調整後相關分析 - 41 -
表5-6 投入、產出項變數 - 41 -
表5-7 CCR or BCC效率值 - 42 -
表5-8 Wilcoxon符號檢定 - 43 -
表5-9 剔除受評單位US5,220,501之敏感度分析(CCR模式) - 44 -
表5-10 達相對效率單位之敏感度分析 - 45 -
表5- 11 未達相對效率單位之敏感度分析 - 45 -
表5-12 剔除國際專利分類號之敏感度分析 - 47 -
表5-13 剔除技術知識廣度或技術知識深度之敏感度分析 - 48 -
表5-14 未達相對效率單位投入/產出之改善目標 - 50 -
表5-15 基礎專利 - 51 -
表5-16 US5,220,501專利之Current U.S. Class - 53 -
表5-17 US5,220,501專利之International Patent Class - 53 -
表5-18 引證US5,220,501專利之主要企業 - 54 -




圖目錄
圖1-1 本研究論文章節架構 - 6 -
圖2-1 CCR 與BCC 模式 - 18 -
圖2-2 固定規模報酬與變動規模報酬下之生產前緣 - 24 -
圖3-1 研究架構 - 27 -
圖4-1 技術生命週期圖(93/06/15-99/09/07) - 32 -
圖5-1 五十筆專利效率與專利年齡散佈圖 - 56 -
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