Beyond the front page: In-text citations to patents as traces of inventor knowledge

• 成果类型: Article
• 署名作者: Verluise, Cyril; Cristelli, Gabriele; Higham, Kyle; de Rassenfosse, Gaetan
• 署名单位: University of London; London School Economics & Political Science; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
• 刊物名称: STRATEGIC MANAGEMENT JOURNAL
• ISSN/ISSBN: 0143-2095
• DOI: 10.1002/smj.70027
• 发表日期: 2026
• 关键词: technological-innovation; localization; spillovers; search; microfoundations; appropriability; exploration; geography; strategy; FLOWS

摘要

Research Summary This study introduces in-text patent-to-patent citations-references embedded in the body of patent documents-as a novel data source to trace knowledge flows. Unlike front-page citations, which often reflect legal requirements, in-text citations are more likely to originate from inventors and signal meaningful technological linkages. We show that they exhibit stronger geographic and semantic proximity, greater self-referentiality, and closer alignment with inventor knowledge. Though less frequent than front-page citations, they yield robust results in models of knowledge diffusion. We release a validated dataset and reproducible code to support future research. Our findings offer new opportunities for scholars interested in the microfoundations of innovation, the geography of knowledge flows, and the role of inventors in shaping firms' knowledge trajectories.Managerial Summary This study introduces in-text patent citations-references embedded in the technical description of patent documents-as a new way to trace how knowledge flows among inventors and firms. Unlike traditional front-page citations, which often reflect legal formalities or examiner input, in-text citations originate more directly from inventors and thus capture genuine technological linkages. Using large-scale U.S. patent data, we show that in-text citations connect geographically and thematically closer inventions and are more likely to involve the same firms or inventors. The dataset, released as open data, enables more accurate analyses of innovation dynamics and firm knowledge strategies. Managers can use these insights to better understand how ideas diffuse and where valuable inventive knowledge resides.