基于DEA-Tobit方法的人工智能行业上市公司融资效率研究

人工智能产业发展对实现我国总体产业升级和供给侧结构性改革具有重要意义。该领域投资态势向好,但融资渠道较为混乱。本文结合我国37家人工智能产业上市公司2013~2016年的融资数据,首先采用了DEA方法对我国人工智能产业上市公司融资效率进行测度,同时采用Malmquist指数法从动态角度来反映人工智能产业上市公司融资变化,然后通过Tobit方法构建融资效率影响因素模型。从实证结果可以看出,人工智能产业融资效率不高,大多数企业并未达到DEA有效,综合技术效率的不高主要是由于规模效率较低引起的;资本结构、企业的营业能力和成长性与融资效率具有显著的相关性,是影响融资效率的重要因素。最后从提高融资资金利用率、优化融资结构两个方面提出了相关建议。

Research into Financing Efficiency of Artificial IntelligenceIndustry Based on DEA-Tobit Method

The development of artificial intelligence industry is of great significance to the realization of overall industrial upgrading and supply-side structural reform in China. The investment trend in this field is good, but the financing channels are more confused. Based on the financing data in 2013~2016 of 37 listed companies of artificial intelligence industry in China, we first use the DEA method to measure the financing efficiency of 37 listed companies of the artificial intelligence industry in China. At the same time, we use Malmquist index method to reflect the financing changes of the listed companies of artificial intelligence industry from the dynamic perspective, and then we construct the model of the influencing factors of the financing efficiency by Tobit method. From the empirical results, it can be seen that the financing efficiency of the artificial intelligence industry is not high, and the most of the companies are not effective in DEA. The low comprehensive technical efficiency is mainly due to the low scale efficiency. And the capital structure, the business ability and growth of the enterprise, which are the important factor that affects the financing efficiency, are remarkably related to the financing efficiency. Finally,some suggestions are put forward from two aspects: raising the utilization rate of financing funds and optimizing the financing structure.