本研究以類神經網路探討專利廣度對於公司淨利之影響,並以美國化工產業為研究對象。本研究以專利範疇(Scope of US Patent Classification, Scope of UPC)、專利賀芬德指數(Herfindahl-Hirschman Index of patents, HHI of patents)、最重要技術領域之專利比率(Patent Share, PS)三種專利指標來衡量專利廣度。研究結果顯示,美國專利範疇與最重要技術領域之專利比率對於公司淨利有正向效果,而專利賀芬德指數對於公司淨利有負向效果。因此,美國化工公司必須增加其技術研發之範疇,並提高其專利佈局之廣度,以及提升最重要技術領域之相對核心能力,以進一步提升其淨利。
This study uses artificial neural networks to explore the influence of patent breadth upon net profit in the American chemical industry. This paper applies scope of US Patent Classification (scope of UPC), Herfindahl-Hirschman Index of patents (HHI of patents), and Patent Share (PS) in the most important technological field to measure patent breadth. The results show that scope of UPC and PS positively affect net profit in the American chemical industry, while HHI of patents negatively affect it in this industry. Hence, American chemical companies should increase their R&D scopes, the breadth of patent portfolio, and the relative core competence in the most important technological field to enhance net profit .