As a consequence of the convergence between manufacturing technology and the foundation technologies of Industry 4.0, it is becoming more important for firms to formulate an innovation strategy for their technological capabilities. In this context, the present study measures firm-level technology convergence (TC) capability using patent network analysis. A firm's TC capabilities are measured using three centrality indices pertaining to a patent network, which is constructed based on the relationship between patents and their international patent classification. For the empirical analysis, panel regression is conducted to observe the effect of TC capabilities on innovation for the top 30 firms in four manufacturing industries. We find that the TC degree positively influences the firms' overall innovation, namely their total number of patents, and negatively influences their convergent innovation, calculated as the ratio between the number of TC patents and the total number of patents, while the effect of TC betweenness is the opposite. These findings imply that while concentrating on similar technologies may promote quick technology application, it could hamper the enhancement of a TC's potential. To promote TC, a firm should thus develop technologies more likely to be involved in TC.

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As more technologies and industries converge, technology standards are more likely to be a strategic factor for firms and governments that are interested in the market with standards-based competition. From the previous research, a new standardisation framework was proposed by combining network analysis and the game theory model but was constrained by feasibility and dynamic approach. In this study, the case of the standards war between HD-DVD and Blu-ray was analyzed with patent data as an empirical case considering a dynamic framework. With this framework, we observed a change in a firm's technology relations and could predict the decline in a firm's preference and the shift of equilibrium ahead of Toshiba's resignation.

This study aims to understand the nature of information and communication technology in technology convergence. We form a knowledge network by applying social network theories to Korean patent data collected from the European Patent Organization. A knowledge network consists of nodes representing technology sectors identified by their International Patent Classification codes and edges that link International Patent Classification codes when they appear concurrently in a patent. We test the proposed hypotheses using four indices (degree centrality, E-I index, entropy index, and clustering coefficient). The results show that information and communication technology is easily attached but tends to converge with similar technology and has the greatest influence on technology convergence over other technologies. This study is expected to help practitioners and policymakers understand the structure and interaction mechanisms of technology from a systematic perspective and improve national-level technology policies.

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