Research on Hierarchical Classification Management of University Patents —— Practice of Beijing University of Chemical Technology

At present, Chinese universities generally suffer from a large stock of patents, low conversion efficiency and prominent resource misallocation. The traditional extensive management model cannot meet the requirements of high-quality development of intellectual property rights. To solve the dilemma of university patent management, this paper conducted a study on the construction of a hierarchical and classified patent management system for universities oriented toward operational transformation. Taking a total of 13,452 patent groups of Beijing University of Chemical Technology from 2004 to 2024 as research samples, this paper relied on the Yipatent database to conduct quantitative patent scoring from five dimensions including patent quality, technical level, economic benefit, scientific research strength and development prospect. A five-level patent classification standard was established, and the distribution characteristics of patents were clarified combined with patent legal status. On this basis, adopting research methods such as the PatSnap evaluation system, interdisciplinary expert review and analytic hierarchy process, this paper constructed a full-process differentiated management system covering high-value, medium-and-low-value and special-state patents, and designs an intelligent patent management database with a three-layer architecture. The research results showed that the constructed hierarchical and classified system can realize accurate patent identification, and the supporting management strategies can effectively activate stock patents and optimize the allocation of innovative resources. Part of the research achievements have been applied in Beihua University Science and Technology Park with favorable practical effects. This study made up for the deficiency of poor operability of the existing university patent management schemes, improved the theoretical system of university intellectual property management, and provided a reference for similar universities to optimize patent management and enhanced the level of patent industrialization. Meanwhile, the study found deficiencies such as subjective deviation of patent evaluation indicators and limited universality of management strategies. In the future, it is necessary to further optimize the intelligent evaluation model, expand research samples, improve the general university patent management scheme, and continuously promote the transformation of university scientific and technological achievements into real productive forces. 针对中国高校专利数量庞大、转化率偏低、资源错配严重的行业痛点，为落实知识产权高质量发展战略，破解高校专利粗放式管理难题，本文以运营转化为导向，探究高校专利分级分类科学管理体系构建方法。本文以北京化工大学2004—2024年13 452组专利为研究样本，依托壹专利数据库，从专利质量、技术性、经济性、科研能力、发展前景五个维度完成专利价值量化评分，划分五级专利层级，并结合专利法律状态开展分类统计，明晰该校专利价值分布特征。基于专利分级结果，本文结合智慧芽评估系统、跨学科专家评审、层次分析法等研究手段，构建覆盖高价值、中低价值及特殊状态专利的全链条差异化管理策略，同时搭建三层架构智能化专利管理数据库。研究结果表明：所构建的分级分类管理体系可实现专利精准划分，配套优化策略能够有效盘活存量专利、优化资源配置。目前该研究部分成果已落地应用于北化大科技园，实践成效良好。本研究弥补了现有高校专利管理方案实操性不足的缺陷，丰富了高校知识产权管理理论体系，为同类高校优化专利管理、提升专利转化效率提供参考范本。此外，研究发现专利评估存在主观偏差、策略普适性有限等问题，未来可优化智能评估模型，扩大研究样本，完善通用性专利管理方案，助力高校科技成果产业化发展。