The dynamics of inter-organisational adversarial relationships in patenting

Tomomi Kito, Yuki Murata, Junichi Yamanoi

Research output: Contribution to conferenceConference AbstractScientificpeer-review


Much research has used patent data, deriving various useful insight into future innovation, technological advancement, collaborative knowledge creation, and so on. These existing studies consider patents as a positive sign of invention. However, inter-organisational relationships are fundamentally adversarial/rivalry, and patenting is companies’ core competitive strategic action. This essential aspect has not received much attention in patent network science, and data science in general. This study illuminates patent opposition as a sign of inter-organisational rivalry. A company can oppose a patent to challenge its validity within a certain period after grant. If an opposition is successful, the opposed patent is revoked and cannot take effect. Therefore, companies oppose rivals’ patents clearly intending to hinder their innovation activities. In this study, we constructed and analyzed the network in which the nodes represent companies (rather than patents), and the directed edges represent oppositions that occurred between 1980 and 2018. Data were collected from Orbis Intellectual Property Database [1]. We also added undirected ‘collaboration’ edges representing joint patent ownerships between companies. In social network analysis, negative ties and their interactions with positive ones have attracted increasing interest [2]. The difficulty here lies in obtaining data capturing such ties. Our data directly captures rivalry and collaborative relationships among companies, providing a great opportunity to study their emerging mechanisms and mutual interactions. Here, it must be noted that rivalry may be considerably different from other types of negative feelings (e.g., disliking), since a company consider others as rivals when it admits (and is threatened by) their high value. Indeed, we found that the opposition network exhibits heavy-tailed, power-law-like degree distribution and assortative mixing, differentiating it from other negative-tie networks reported in the existing studies*. We also conducted a temporal network motif analysis, with both opposition and collaboration edges taken into account. The results identified the structurally imbalanced triadic motifs and the temporal patterns of the occurrence of triads formed by a mixture of both types of edges*. Furthermore, we investigated when, and in which situations, companies oppose (or get opposed by) others. Figure 1(a) shows the distribution of proximity [4] between the patent portfolios of company pairs with no opposition edge between them (red) and those with opposition edges (blue). Indeed, oppositions occur when companies’ technological fields largely overlap (i.e., proximity close to 1). Figure 1(b) shows the distribution of proximity between the technological fields of patents that a given company opposed, and its own patent portfolio. The majority of companies oppose a patent that appeared in their core technological fields (proximity close to 1). However, there are a considerable number of companies opposing patents that appeared in the field where they have few (or no) patents (proximity close to 0). We found that these companies tend to publish patents in that field later on. That is, patent opposition may be a good predictor of companies’ strategic directions. (Notes: *: Some part of these results has been published in [5]. The rest of the results are not included in the publication.)
Original languageEnglish
Publication statusPublished - 2021
MoE publication typeNot Eligible
EventNetworks 2021: A Joint Sunbelt and NetSci Conference - Online
Duration: 5 Jul 202110 Jul 2021


ConferenceNetworks 2021
Internet address


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