The purpose of innovation is to consume fewer natural resources in order to create sustainable performance; therefore, innovation can ease the pressure of the ecological load and promote the sustainable development of the economy. Taking the 269 enterprises listed on the main board of the electronic information industry from 2010 to 2019 as samples, using the threshold panel data model, the nonlinear relationship between the knowledge-based network structure hole and the short-term and long-term innovation performance of the enterprises were studied, and the threshold effect of R&D investment intensity was discussed. When the R&D investment intensity is from 1.96% to 15.96%, the knowledge-based network structure hole has a significant positive impact on short-term innovation performance. When the R&D investment intensity is from 5.72% to 10.64%, the knowledge-based network structure hole has a significant positive effect on long-term innovation performance. Lower R&D investment intensity can make the knowledge-based network structure hole promote the increase of short term innovation performance, but to make the knowledge-based network structure hole have a positive impact on long term innovation performance, the R&D investment intensity should be increased by more than 5.72%. When R&D investment intensity is not higher than 15.96%, the knowledge-based network structure hole has a significant positive impact on short term innovation performance, but to make the knowledge-based network structure hole maintain the positive effect on long term innovation performance, R&D investment intensity should not exceed 10.64%. Therefore, enterprises should be guided to optimize the knowledge-based network structure according to the R&D investment intensity in order to improve the short term and long-term innovation performance of an enterprise. These research results can help enterprises to save resources and promote the sustainable development of the economy.
It provides specific theoretical guidance to enhance the enterprise’s independent innovation capabilities by studying the knowledge utilization and the evolution of innovation under different innovation strategies and revealing the law of innovation path. Based on the data of invention patents of 579 electronic information enterprises from 2010 to 2019, this paper constructs a knowledge-based network based on social network analysis to study the evolution process of density, centrality, and structural holes of knowledge. The evolution analysis of 3360 knowledge-based networks shows that the electronic information industry’s overall knowledge integration capacity is in the middle and lower reaches. The widespread knowledge reliance in the electronic information industry is small, the industry is out of the ‘capacity traps’, and diversified development has gradually become a trend. At the same time, cross-domain knowledge reorganization is increasing. The results show that the overall knowledge reliance degree of enterprises applying an exploitative innovation strategy is deeper than that of enterprises applying an exploratory innovation strategy. The knowledge integration capabilities and cross-domain knowledge reorganization capabilities of enterprises applying exploratory innovation strategies are higher than those of enterprises applying exploitative innovation strategy.
This study analyzes how knowledge-based network affects the dual innovation performance. Dual innovation includes exploratory and exploitative innovation, and knowledge-based network represents the relationships among knowledge-based elements. We take 269 enterprises having gone public in Shanghai and Shenzhen stock markets of the electronic information industry of China as samples and get the patent data for 5 years from 2014 to 2018. We consider building the knowledge-based network structure based on social network analysis method, and measure three features of the knowledge-based network, that are density, centralization and structure hole. We test the relationship between three network features and dual innovation performance through negative binomial regression method. The results indicate that there is an inverted U-Curve relationship between density and exploitative innovation performance. There is an inverted U-curve relationship between centralization and exploratory innovation performance. There is an inverted U-curve connection between the structure hole and the dual innovation performance.
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