Affiliations:
Fuzhou University of International Studies and Trade, Changle, Fuzhou City, Fujian, China
Correspondence:
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Corresponding author. Ming Fang, Fuzhou University of International Studies and Trade, No. 28, Yuhuan Road, Shouzhan New District, Changle, Fuzhou City, Fujian, China. E-mail: [email protected].
Abstract: This paper explores the applications of support vector machines (SVM) technique and panel data econometric approach in innovation performance. We proposed Hybrid Fuzzy Logic with SVM based prediction analysis model to predict Innovation Performance of 3C Industry and then we construct the top management innovation awareness by text mining analysis, which differs from traditional methods, and then discusses the mediation function of financial flexibility in the relationship between innovation awareness and enterprise performance. Then, we use the financial econometric method panel regression and apply the SVM, a statistical technique that has gained special popularity in the field of AI to test the relation between innovation performance and innovation awareness of top management in 3C industry. The findings show that there exists a significant position relationship between innovation awareness and innovation performance, and that the mediation function of financial flexibility does work. With the SVM approach, the innovation performance can be predicted well by top management innovation awareness.
Keywords: Support vector machines, text mining, innovation performance, innovation awareness, financial flexibility
