Network Approach of Autonomous Car's Industry Structure: An Analysis of Patents and Alliances

Worldwide digitalization and convergence has led incremental and rapid change in landscape of automobile industry. Consequently, increasing numbers of ICT and auto companies are actively constructing alliances with various companies from different industry. For investigating the characteristics of firms’ strategic behaviors in autonomous car industry, we conducted data mining analysis and 2 social network analysis (degree centrality analysis, community analysis) by using 440 US patents data and 120 alliance data. Firstly, we found that Google is mostly focused on the information area, while Ford and GM are mostly on control and detection technology. Hyundai and Nissan are focused on most of the technologies. Secondly, with a frist network analysis (degree centrality) on alliance data, we found that Google has the highest degree centrality with other firms. GM, Ford, Nissan, Hyundai, Toyota also have the relatively high degrees of centrality. Finally, from the 2nd network analysis (community analysis) on alliance data, we found five significant alliance groups. Group 1 so called Google-German alliance, group 2 so called GM-China alliance, group 3 so called GM-Ford alliance, group 4 Korean alliance and group 5 Japanese alliance. Among those groups, Chinese-related alliances can be categorized into two competitive groups: GM-SOEs (State-Owned Enterprises) which focus on business model and Ford-private enterprises which focus on technology and manufacturing. In case of Korean and Japanese alliance, although their structure is similar, Japanese alliance is more active and international. Lastly, inside Google -German alliance, mutual competitive behavior was detected.