Abstract
Patents are intellectual properties that often reflect innovative activities of companies and organizations. Many studies have investigated the citations among the patents, but only a few addressed the relations between the patent owners. We use patent data from Orbis IP database [1] to analyze the adversarial and collaborative relations among the companies, where the former is formed by the patent opposition, a legal activity in which a company challenges the validity of a patent, and the latter is implied by the co-ownership of patents by multiple companies. Characterizing the patent oppositions, collaborations, and the interplay between them is important for understanding how innovation happens. Temporality is an important aspect in this context as the order and frequency of oppositions and collaborations are key to identify and characterize complex relations among companies.
In this study, we construct a two-layer temporal network to model the patent oppositions and collaborations among the companies from 1980 to 2018. We utilize temporal motifs [2] to analyze the oppositions and collaborations from structural and temporal perspectives. We have three main findings. First, the opposition layer contains significantly more wedge motifs than the triangle motifs (see Table 1), which is coherent with the structural balance theory [3] since oppositions are negative relations. Second, if a company receives a burst of oppositions, it is likely to be a large company which is attacked by small companies, and if a company files a burst of oppositions, it is usually a large company targeting other large companies. Third, the companies with collaborations in the past are likely to oppose the same company or be opposed by the same company. In summary, our analysis discovers underlying business relations in the patent data, which we believe will advance the studies in business strategy and management.
In this study, we construct a two-layer temporal network to model the patent oppositions and collaborations among the companies from 1980 to 2018. We utilize temporal motifs [2] to analyze the oppositions and collaborations from structural and temporal perspectives. We have three main findings. First, the opposition layer contains significantly more wedge motifs than the triangle motifs (see Table 1), which is coherent with the structural balance theory [3] since oppositions are negative relations. Second, if a company receives a burst of oppositions, it is likely to be a large company which is attacked by small companies, and if a company files a burst of oppositions, it is usually a large company targeting other large companies. Third, the companies with collaborations in the past are likely to oppose the same company or be opposed by the same company. In summary, our analysis discovers underlying business relations in the patent data, which we believe will advance the studies in business strategy and management.
Original language | English |
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Title of host publication | Abstracts for NERCCS 2021: Fourth Northeast Regional Conference on Complex Systems |
Publisher | Complex Systems Society |
Pages | 54-54 |
Number of pages | 1 |
Publication status | Published - 2021 |
MoE publication type | Not Eligible |
Event | Fourth Northeast Regional Conference on Complex Systems, NERCCS 2021 - Online Duration: 31 Mar 2021 → 2 Apr 2021 https://nerccs2021.github.io/ |
Conference
Conference | Fourth Northeast Regional Conference on Complex Systems, NERCCS 2021 |
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Period | 31/03/21 → 2/04/21 |
Internet address |
Fingerprint
Dive into the research topics of 'Temporal motifs in patent opposition and collaboration networks'. Together they form a unique fingerprint.Prizes
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Best Poster Award NERCC 2021
Kito, T. (Recipient), Liu, P. (Recipient), Masuda, N. (Recipient) & Sarıyüce, A. E. (Recipient), 2021
Prize: Prize for a work