科技金融生态促进数字经济发展的组态分析——基于模糊集定性比较分析(fsQCA)的研究

Configuration Analysis of Science and Technology Finance Ecology to Promote the Development of Digital Economy——Research Based on Fuzzy Set Qualitative Comparative Analysis(fsQCA)

数字经济是当前发展新质生产力的重要抓手,其需要科技金融生态提供有力支持。本文构建一个由财政投入、风险投资、科技贷款、资本市场、科技保险和科技服务组成的科技金融生态,采用模糊集定性比较分析(fsQCA)方法,探讨我国31个省级行政区科技金融生态促进数字经济发展的组态路径。研究发现:(1)单一金融要素不是数字经济发展的必要条件,科技金融生态通过多要素形成的组态发挥作用;(2)在科技金融生态促进数字经济发展的两类组态中,政府-市场协同模式的绩效高于市场主导模式,说明市场是数字经济发展的基础性因素,而政府与市场协同能促进数字经济发展至更高水平;(3)在数字经济未能实现高水平发展的组态地区中,金融市场发展不足是共性问题。研究结论为各地因地制宜优化科技金融生态提供理论借鉴和政策启示。

The digital economy is an important aspect for the development of new quality productivity,which needs strong support from the science and technology financial ecology.We construct a science and technology finance ecology composed of financial input,venture capital,science and technology loan,capital market,science and technology insurance and science and technology service,and adopt fuzzy set qualitative comparative analysis(fsQCA)method to explore the configuration path of science and technology finance ecology to promote the development of digital economy in 31 provincial administrative regions in China.The findings are as follows:(1)single financial element is not a necessary condition for the development of digital economy,and the technological financial ecology plays a role through the configuration formed by multiple elements.(2)Among the two configurations in which technological financial ecology promote the development of digital economy,the performance of the government-market collaborative model is higher than that of the market-led model,indicating that the market is the basic factor for the development of digital economy,and the collaboration between the government and the market can promote the development of digital economy to a higher level.(3)In regions where high-level digital economic development has yet to be realized,underdeveloped financial markets emerge as a common problem.These conclusions offer theoretical insights and policy implications for optimizing local-specific science and technology finance ecosystems.