Puppets Fight as Puppet Masters Wish : The Influence of Shareholder Overlap on Interfirm Rivalry

If two competing firms receive influence from the same large shareholders, how do they compete? From the viewpoint of competitive dynamics and agency theory, I investigate the impact of overlapping shareholders of two competing firms on their competitive behavior. The overlapping shareholders of two competing firms will attempt to reduce the intensity of their competitive activity because they can increase economic surpluses from the competing firms by intentionally creating the stability of rivalry. Accordingly, competitive actions between two competing firms will become less intensive as their overlapping shareholders acquire more power over the firms. By using data on pairs of leaders and challengers in 13 Japanese industries in which they have engaged in lasting head-to-head competition, found support for the hypotheses

Competition Networks: The Influence of Relational and Structural Embeddedness on Competitive Activity

A firm has competitive relationships with its rivals, which themselves have competitive relationships with other rivals. Dyadic competitive relationships between firms compose competition networks among firms. The purpose of this study is to explain competitive dynamics from a network perspective. By integrating an awareness-motivation-capability perspective, which primarily theorizes the dyadic competitive relationships between two firms, with a social network perspective, which mainly scrutinizes the influence of network ties and structure on firm behavior, I have investigated the influence of a firm\u27s relational and structural embeddedness in competition networks on the intensity of the firm\u27s competitive activity, which is composed of action frequency, variety, and magnitude. The main thesis is that a focal firm will engage in less intense competitive activity when it is embedded in a competition network that induces more intense rivals\u27 competitive activity. Since intense retaliation by rivals decreases the focal firm\u27s performance, it will intend to avoid provoking this rivals\u27 intense retaliation. By using a sample of petrochemical companies in Japan from 1986 to 1994, as predicted, I found that a focal firm engages in less intense competitive activity in conditions of stronger inward competitive ties or more betweenness centrality in its competition network.

Competition Networks: The Influence of Relational and Structural Embeddedness on Competitive Activity

A firm has competitive relationships with its rivals, which themselves have competitive relationships with other rivals. Dyadic competitive relationships between firms compose competition networks among firms. The purpose of this study is to explain competitive dynamics from a network perspective. By integrating an awareness-motivation-capability perspective, which primarily theorizes the dyadic competitive relationships between two firms, with a social network perspective, which mainly scrutinizes the influence of network ties and structure on firm behavior, I have investigated the influence of a firm's relational and structural embeddedness in competition networks on the intensity of the firm's competitive activity, which is composed of action frequency, variety, and magnitude. The main thesis is that a focal firm will engage in less intense competitive activity when it is embedded in a competition network that induces more intense rivals' competitive activity. Since intense retaliation by rivals decreases the focal firm's performance, it will intend to avoid provoking this rivals' intense retaliation. By using a sample of petrochemical companies in Japan from 1986 to 1994, as predicted, I found that a focal firm engages in less intense competitive activity in conditions of stronger inward competitive ties or more betweenness centrality in its competition network

The dynamics of inter-organisational adversarial relationships in patenting

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.