中国省域大数据产业与金融集聚耦合协调发展研究

Coupling Coordinated Development between China’s Provincial Big Data Industry and Financial Agglomeration

基于大数据产业发展与金融集聚的现状和特点,选取2013—2017年中国31个省域的指标原始数据,运用犹豫模糊语言TOPSIS灰色关联投影法对31个省域的大数据产业发展水平和金融集聚水平进行测度;并采用耦合协调度模型计算大数据产业-金融集聚的耦合协调度。实证结果表明,总体上,31个省域的大数据产业-金融集聚的耦合协调类型跨越了初级协调发展、勉强协调发展、濒临失衡衰退、轻度失衡衰退和中级失衡衰退等5个等级;空间上,大数据产业-金融集聚的协调发展程度呈现出东部地区高于中部地区、中部地区又高于西部地区和东北地区的总体特征;时间上,2013—2017年广东、安徽、湖北、湖南的耦合协调类型上升一个等级,而辽宁则下降一个等级,31个省域的系统耦合协调度呈现升多降少的总体趋势。

Based on the current situation and characteristics of the development of big data industry and financial agglomeration,this paper selects the index original data of 31 provinces in China from 2013 to 2017,and then uses the hesitant fuzzy linguistic TOPSIS grey relation projection method to measure the development level of big data industry of 31 provinces,as well as the financial agglomeration level.Through the coupling coordinated degree model,the coupling coordinated degree between big data industry and financial agglomeration is further calculated.The empirical results show that,on the whole,the coupling coordinated types of 31 provinces span five levels:primary coordinated development,barely coordinated development,near imbalance recession,slight imbalance recession and moderate imbalance recession.In terms of space,the degree of coordinated development in the eastern region is higher than that in the central region,and that in the central region is higher than that in the western region and the northeast region.In terms of time,from 2013 to 2017,the coupling coordinated types in Guangdong,Anhui,Hubei and Hunan increases by one level,while that in Liaoning decreases by one level.The overall trend of the coupling coordinated degrees in 31 provinces is that there are more rising provinces than falling provinces.