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考量專利品質下之台灣IC設計產業研發效率分析 / R&D Efficiency Analysis of IC Design Industry in Taiwan with Patent Quality Consideration臧友文 Unknown Date (has links)
本研究旨在探討民國88年至94年台灣IC設計產業之研發效率分析。採兩階段資料包絡分析法(Data Envelopment Analysis, DEA):第一階段以保證區域資料包絡分析法(Assurance Region DEA,AR/DEA)衡量績效,以避免傳統DEA方法可能出現產出或投入的乘數為0之狀況。第二階段採資料切齊的(censored) TOBIT迴歸模型探討影響研發效率值的效率因子。
研究發現:
(1)只考量專利數量與納入專利品質考量下之統計檢定結果,雖沒有顯著的差
異,但對少數的廠商的研發效率值與排名確實有變動,納入專利品質考
量,可以掌握更多研究發展資訊,了解廠商專利真正的價值。
(2)專利被引證次數與研發效率值呈現顯著正相關。
(3)TOBIT迴歸實證結果顯示:
研發效率與公司規模無顯著關係;研發效率與研發人力密集度無顯著相
關;研發效率與研究發展費用率呈負向關係;研發人員年約收入對研發技
術效率無顯著影響;外來知識流量占自有知識存量比例會正向影響研發效
率表現。 / This study investigates R&D efficiency analysis of IC design industry in Taiwan from 1999 to 2005 by using the two-stage Data Envelopment Analysis (DEA). To avoid the situations that the multiplier of the input or output might be zero, we adapt the method of Assurance Region DEA (AR/DEA) to measure achievements in the first stage. We then use censored TOBIT regression model to study the factors that influence the efficiency value in the second stage. Through our study, we conclude that:
(1) Although there is no significant difference in the
results of statistical test whether we take patent
quantity into account or not, both the value of R&D
efficiency and ranking of a few firms do change. We can
grasp more information of research and development and
understand the true value of firm’s patent as we put
patent quality into account.
(2) The correlation coefficient between the amount of
patent cited and the value of R&D efficiency is
positive significantly.
(3) The empirical results of TOBIT regression show that:
a. There is no significant relationship between the R&D
efficiency and the company’s scale.
b. There is no significant relationship between the R&D
efficiency and the density of R&D workers.
c. There is a negative relationship between the R&D
efficiency and the ratio of R&D expense.
d. The yearly revenue of R&D workers does not
significantly influence the R&D and technology
efficiency.
e. The ratio between the flow rate of external knowledge
and the owned knowledge storage affects positively on
R&D efficiency.
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