发表机构
KEDGE Business School; Leeds University Business School, University of Leeds; Department of Economics and Management, University of Ferrara; SEEDS – Sustainability, Environmental Economics and Dynamics Studies（凯德商学院; 利兹大学利兹商学院; 费拉拉大学经济与管理系; SEEDS - 可持续发展、环境经济学与动态研究）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过专利分类代码的创建、添加与清理，揭示分类架构修订如何影响检索效率，发现类别创建和清理可提升引用速度，但分类细节增加未必改善搜索效果。
AI 中文摘要
分类系统塑造了搜索者找到相关对象的方式。我们研究分类架构的修订如何通过改变对象进入考虑范围的路径来影响检索。我们提出理论：创建一个跨领域类别可以减少分类距离和转换成本，而向成熟系统添加路径会增加路径选择和更新成本；类别清理可以恢复对比度。在实证方面，我们利用合作专利分类中Y02/Y04绿色技术代码在2013年的创建和2020年的修订。我们将处理过的专利与技术-队列单元内未变化的绿色专利进行匹配，并估计审查员和申请人特定的首次引用时间和引用量的影响。类别创建与审查员首次引用风险增加25%相关。在成熟系统中，添加路径与审查员风险降低13-15%相关，而清理与风险增加14%和引用量增加12%相关。影响通常对审查员更强，因为其搜索任务与专利分类的耦合更紧密。时间和数量不必同步变动：创建和绿色领域进入改变了时间但未检测到数量的变化，而清理同时提高了速度和记录到的覆盖范围。因此，分类基础设施可能会改变相关对象被发现的时间，即使整体记录到的关注度不变，并且更大的分类细节不一定提高搜索效率。
英文摘要
Classification systems shape how searchers find relevant objects. We study how revisions to classification architecture affect retrieval by changing the routes through which objects enter consideration. We theorize that creating a cross-cutting category can reduce classificatory distance and translation costs, whereas adding routes to an established system can increase route-selection and updating costs; category cleanup can restore contrast. Empirically, we exploit the 2013 creation and 2020 revision of Y02/Y04 green-technology codes in the Cooperative Patent Classification. We match treated patents to unchanged green patents within technology-cohort cells and estimate examiner- and applicant-specific effects on first-citation timing and citation volume. Category creation is associated with a 25% higher examiner first-citation hazard. In the mature system, additions are associated with 13-15% lower examiner hazards, while cleanup is associated with a 14% higher hazard and 12% higher citation volume. Effects are generally stronger for examiners, whose search task is more tightly coupled to patent classification. Timing and volume need not move together: creation and green-domain entry shift timing without detectable changes in volume, while cleanup increases both speed and recorded reach. Classification infrastructure may therefore change when relevant objects are found even when overall recorded attention is unchanged, and greater classificatory detail need not improve search efficiency.
