Comparing examiner citations and applicant citations: insights into technology evolution

Patent citation data is widely used in the study of technology evolution, but existing research has overlooked an issue that there may be potential differences between examiner citations and applicant citations, which may introduce biases from examiner citations. Yet, there is still a lack of systematic comparative study on the differences between applicant citations and examiner citations for technology evolution. To address this, we conducted a comprehensive comparison using USPTO patent data across four dimensions: technology profiling, technology relevance, technology diversity, and technology evolution pathways. For our case study, we selected the promising research area of photovoltaic cells. After comparing nine sub-technologies in this area, we have drawn some conclusions: (1) Applicants tend to provide more citations than examiners, and examiners tend to cite more recent patents than applicants; (2) There is no apparent inclination for applicants to avoid citing particularly relevant patents. On average, examiner citations are slightly closer in technological proximity to their invention than those cited by applicants; (3) The degree of diversity for applicant citations, examiner citations, and applicant & examiner citations at a single patent level lacks consistency. However, their average trend by year or by sub-technology is similar after adding examiner citations; (4) Merging family members strongly impacts main pathways through added examiner citations, which is quite contrary in the citation network with only USPTO-granted patents without merging patent members; (5) In sub-technologies at the growth stage, applicants and examiners both cite more recent patents and tend to integrate border technologies from other fields, which can be used as an indicator for evaluating the potential to become emerging. The findings remind us to pay extra attention to the context in which citation data is used to measure technology evolution, and can serve as signals for technology assessment as well.