Research on Spatial Correlation Evolution of Marine Ecological Efficiency Based on Social Network and Spatial Correlation Matrix Model

Abstract

Most developed countries in the world are maritime powers. This article constructs an ecological efficiency evaluation system based on the characteristics of the ocean itself while taking into account the relationship between land and sea. Based on social network analysis, the relationship between China’s marine ecological efficiency is regarded as a social network system, and the roles and positions played by 11 coastal cities in the network are analyzed from a relational perspective. Next, based on the unexpected super efficiency model to measure the ocean efficiency value in China’s coastal areas, we explore its spatiotemporal evolution characteristics, and measure the ocean ecological efficiency while incorporating ecological environmental pollution as an unexpected output into the evaluation system. Then, the spatial incidence matrix of marine ecological efficiency is calculated through the modified gravity model, and the characteristics of network structure are described with the help of the social network method. In addition, ArcGIS software is used to visualize the spatial evolution process. Finally, QAP regression is used to explore the key factors affecting the spatial correlation network of marine ecological efficiency in China. The results show the following: (1) In terms of time, the marine eco-efficiency of most provinces is not high, and the difference between provinces is obvious, but on the whole, it shows a fluctuating upward trend. (2) From the perspective of space, the overall displacement of the center of marine eco-efficiency in China is large in the north–south direction and small in the east–west direction, and the center of marine eco-efficiency is always concentrated near the Yangtze River Delta. (3) On the whole, the spatial correlation network of China’s marine eco-efficiency is becoming more and more complex. The number of correlation relationships and network density is increasing, and the network framework is gradually maturing. The spatial adjacency matrix, the difference in economic development level, and the difference in population distribution level can significantly promote the formation and development of the spatial correlation network of marine eco-efficiency. However, the differences in the level of opening to the outside world and in the structure of marine industries restrain their spatial networks. The difference between marine science and technology levels is not significant.