本研究以專利分析探討美國製藥業產業之經營績效,並以類神經網路(ANN)中之倒傳遞類神經網路(BPN)方式進行分析,探討平均專利年齡、發明人數及專利範疇對公司淨利率之影響。專利資料取自於美國專利暨商標局(USPTO)之專利文獻資料,而財務資料取自於COMPUSTAT資料庫。研究結果發現,平均專利年齡對公司績效呈現倒U型的影響,而發明人數對公司績效也呈現倒U型的影響;此外,專利範疇對公司績效具有正向的影響,因此建議美國製藥公司應調整其平均專利年齡與發明人數至最適點,並同時朝向技術的多樣性發展,以提昇公司獲利。
This study uses patent analysis to explore the corporate performance of the American Pharmaceutical industry by use of back-propagation network(BPN) of artificial neural network (ANN). Besides, this paper explores the influence of average age of patents, number of inventors, and patent scope upon net-profit margin of the companies. The patent data are collected from U.S. Patent & Trademark Office (USPTO), and financial data are collected from the database of COMPUSTAT. We find that the average age of patents and the number of inventors have inverse U-shaped influences upon corporate performance, while patent scope has a positive effect on corporate performance. Therefore, we suggest the American pharmaceutical companies should adjust their average age of patents and number of inventors into the optimal points and enhance their patent scope in order to increase their profitability.