如何提升小微企业金融政策扶持的有效性?——基于时间管理经典理论及大数据分析

How to Improve the Supporting Effectiveness of Financial Policy for Small and Micro Enterprises?——Based on the Classic Theory of Time Management And Big Data Analysis

本文基于3万家小微企业近百万条大数据,通过机器学习的方法,从企业利润和社会效益平衡点的角度对小微企业差异化扶持问题进行了研究,并借鉴时间管理经典理论,形成了“四象限”企业库。结果显示,本文对企业的评分与分类的有效性较好,且从政策扶持的角度看更为真实。最后,本文进一步提出了小微企业差异化扶持策略及相关建议。

Based on nearly one million pieces of big data from 30,000 small and micro enterprises,this paper uses machine learning methods to study the issue of differentiated support for small and micro enterprises from the perspective of profit balance and social benefit balance,then this paper refer to classic theory of time management to form a"Four-quadrant"enterprise library.The results show that the effectiveness of the scoring and classification of enterprises is relatively good,and it is more realistic from the perspective of policy support.Finally,this paper further proposes the differentiated support strategies and suggestions for small and micro enterprises.