专利侵权损害赔偿价值评估研究

Research on the Valuation of Damages for Patent Infringement

摘要: 在全球化深入发展与国家创新驱动战略推动下，专利密集型产业已成为国家战略竞争的关键领域与企业核心竞争力的重要源泉。创新活动高度活跃推动了专利数量迅猛增长，伴随而来的是专利侵权纠纷频发，我国司法实践面临赔偿数额偏低、法定赔偿适用泛化及权利人举证困难等困境。因此，本文立足资产评估理论视角，遵循收益法基本原理，以权利人实际损失为计算基准，首先运用神经网络算法，以企业盈利水平相关指标为输入变量，预测假设未侵权情境下企业的预期收益；其次采用熵权法与灰色模糊综合评价相结合的方法量化专利贡献率，确定侵权所致收益损失；最后引入要素累加法量化惩罚性赔偿倍数。本文旨在为相关职能部门和研究人员开展专利侵权损害赔偿价值评估研究提供一定的借鉴。

Abstract: Amid deepening globalization and the national innovation-driven development strategy, patent-intensive industries have emerged as a strategic domain of national competition and a primary source of enterprise core competitiveness. While surging innovation activities have precipitated exponential growth in patent filings, they have concurrently engendered a proliferation of patent infringement disputes. The adjudication of patent infringement disputes in China is currently confronted with structural challenges, including inadequate compensation awards, over-reliance on statutory damages, and evidentiary difficulties confronting rights holders. Grounded in asset evaluation theory and anchored in the income approach methodology, this study develops a quantitative model for determining actual damages. First, a neural network algorithm is employed with multi-dimensional indicators—including corporate profitability, operational efficiency, and innovation capacity—as input variables to forecast expected revenue under counterfactual non-infringement scenarios. Second, the entropy weight method is integrated with grey fuzzy comprehensive evaluation to determine the patent contribution rate, thereby quantifying the income loss attributable to infringement. Third, the element accumulation method is introduced to scientifically calibrate punitive damages multipliers. This research contributes to the theoretical framework of intellectual property infringement assessment and offers methodological support for judicial adjudication, particularly in alleviating evidentiary burdens and enhancing the rationality of damage awards.