Research on financing efficiency and influencing factors of equipment manufacturing industry——Regression model based on SFA panel data

• Published in: Journal of intelligent & fuzzy systems 2021-01, Vol.40 (4), p.8117-8126
• Main Authors: Wang, Qian, Wang, Jianxu, Li, Hua, Li, Xiang
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Efficiency; Financing; Impact analysis; Longitudinal studies; Manufacturing; Regression models; Turnover rate
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-189635

Equipment manufacturing industry is the core industry of national economy. The development of artificial intelligence technology provides new development opportunities for the transformation and upgrading of equipment manufacturing industry, but in this process, China’s equipment manufacturing enterprises are faced with serious financing constraints and financing efficiency needs to be improved. Based on the panel data of Listed Companies in equipment manufacturing industry from 2009 to 2018, the article constructs a panel data regression model by using stochastic frontier analysis to measure the financing efficiency of equipment manufacturing industry and study its influencing factors. The results show that the average financing efficiency of China’s equipment manufacturing enterprises is in the medium level, while the traditional equipment manufacturing industry is lower; external financing has a positive impact on the financing efficiency of enterprises, and labor input has a negative impact; in the analysis of influencing factors, the Capital structure, R&D investment, Accounts receivable turnover rate, Fixed assets turnover rate have a great impact on the financing efficiency. The research results have a certain reference significance for equipment manufacturing enterprises to improve financing efficiency.