Research On The Influence Of Network Embedment On Innovation Performance Of Manufacturing Enterprises

China’s economy is in a critical period of structural adjustment,and manufacturing enterprises are the main battlefield of "innovation-driven,transformation and upgrading".On the other hand,economic globalization and the era of big data are intertwined,and the innovation mode of manufacturing enterprises is gradually showing network development,and the innovation network embedding has become an important factor in the innovation of manufacturing enterprises.Based on the realistic situation and supported by social network theory,knowledge-based theory and dynamic capability theory,this paper integrates network embedding,knowledge transfer,big data capability and innovation performance into a research framework.In order to explore the influence path of network embeddedness on the innovation performance of manufacturing enterprises,this paper divides network embeddedness into structural embeddedness and relational embeddedness,and uses knowledge transfer and its two dimensions of knowledge acquisition and knowledge integration as intermediaries to describe the mechanism in detail.Finally,the moderating effect of big data capability is tested.Through literature review,it is found that although existing studies have explored the relationship between network embeddedness and innovation performance,the relationship between the two and the influencing mechanism are still unclear.Secondly,manufacturing enterprises are the most important application market of big data and information technology.Whether the internal dynamic capability built through data resources can help enterprises’ innovation activities and improve the efficiency of knowledge internalization needs further research.This paper adopts the questionnaire survey method to investigate the manufacturing enterprises in the eastern region,and finally obtains 311 valid sample data through the questionnaire screening,and empirically tests the research model and hypothesis with the help of software SPSS25.0 and AMOS26.0.The results show that:First,the two dimensions of network embeddedness have significant positive effects on innovation performance;Secondly,the two dimensions of network embedding have significant positive effects on both dimensions of knowledge transfer.Third,both dimensions of knowledge transfer have significant positive effects on innovation performance.Fourth,knowledge transfer plays a mediating role in the relationship between network embeddedness and innovation performance.Fifth,big data capability positively moderates the relationship between knowledge transfer and innovation performance.Through theoretical analysis and empirical testing,the theoretical research in the fields of network embedding,knowledge transfer,big data capability and innovation performance is enriched,which helps manufacturing enterprises to deeply think about how to maintain their core competitiveness by carrying out innovation activities in the new era,and helps enterprises to actively use external network embedding to seek required knowledge resources.Improve the integration and utilization efficiency of their own big data capabilities on knowledge resources,and help enterprises innovate.