我國自1999年通過「科學技術基本法」後，將學術研究機構的智慧財產權下放至各單位與個人，以鼓勵研究創新，各校技術移轉中心也如雨後春筍般成立。然相較美國大學技術移轉成效可觀，國內大學運作尚未成熟。本研究藉由探討美國大學技轉績效，找出標竿學校並分析成功之道，以為國內大學技轉學習之參考。
　
資料包絡分析(Data Envelopment Analysis，DEA)被視為有效衡量技術移轉績效的方法，但其結果往往具多重效率單位，無法區分最績優學校。本研究採用兩項資料包絡分析領域嶄新的方法—「兩階段資料包絡分析」(Two-stage DEA)與「以參考網路為基礎的排序方法」(Network-based Ranking Method )。前者將大學技轉效率分為「研究創新」(將研究資源轉化成專利)與「價值創造」(將專利轉化成授權與新創事業)兩階段檢視，探究有效率大學之驅動力；後者將有效率大學排序，找出整體最佳以及各投入與產出項運作良好之學校。配合強弱項分析，讓各大學院校檢討本身不足之處，並參考各標竿學校作為學習的對象，汲取其精華以提升自我之績效表現。本研究並探討大學有無醫學院及其為公立或私立是否會影響其技轉績效。
　
研究資料來源為美國大學技術經理人協會(Association of University Technology Management，AUTM)，選定119間資料較為完整的大學進行研究。研究結果顯示，在第一階段有效率大學遠多於第二階段，可推估大部分大學在授權等商業化過程仍有改善空間。另外，公立大學以及無醫學院的學校在第一階段的表現較佳，至於第二階段則各類型的學校效率表現差異不大。由於我國技轉作法多師法美國，因此，本研究期望藉對美國大學之了解，以對國內大學技術移轉有所助益。

Since the passage of Taiwan’s “Technical Fundamental Law” in 1999, the intellectual property rights in academic and research institutions have been implemented to respective departments and individuals to encourage research and innovation. Since then, technology transfer offices have sprung up. However, compared with the performance of technology transfer of universities in the U.S, the performance of domestic universities has not yet matured. This study discusses the performance of technology transfer of universities in the U.S, and does the school benchmarking to analyze the way to success, as a reference to the technology transfer in domestic universities.
　
Data Envelopment Analysis (DEA) is considered an effective method to measure the performance of technology transfer, but the result usually cannot distinguish the school with the best performance since it often contains the numerous efficient decision making units (DMUs). This study applies two brand-new analysis approaches of DEA – the “Two-stage DEA” and the “Network-based Ranking Method”.
　
In order to evaluate the operational performance of each DMU (university) precisely, two-stage analysis model is used which separates the university performance into the “research and innovation performance (turn research expenditures into patents)” and “value creation performance (turn patents into licenses and start-ups)”, to discuss the driving force of universities with good efficiency. The latter approach ranking the universities with efficiency to find the overall best school and which school has best performance of separate inputs and outputs. In addition, the analysis of strengths and weaknesses allows universities to review their own inadequacies and to improve the self-performances by learn the benchmark. Besides, this study also discusses whether the universities with medicine department or the public/private system will affect their performance in technology transfer.
　
The source of the study is from the Association of University Technology Management (AUTM), which conduct the research of 119 universities. As the research results shown, the amount of school with efficiency of universities at the first stage much more than that at the second stage, which implies that there still much improvement to be expected during the process of commercialization like license or start-up. In addition, public universities and non-medical schools have better performances at the first stage, while the performances at the second stage make little differences. Since most approaches of technology transfer in Taiwan are introduced from the U.S, this study expects to deeply understand the universities in the U.S to make improvement in domestic technology transfer.

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