Investigating the Mobility Network and Dynamic Changes of Chinese Marine Research Talents: A Data Analysis Based on CNKI

Abstract

Talent is a crucial factor for regional development, and its development and cultivation are important dimensions for measuring the innovation capability of a region. Talent attractiveness is the best reflection of the vitality of regional development. The development of the marine economy and the construction of maritime power require continuous attention to maritime talent. Although there is a substantial amount of literature on marine talent, investigations of marine research talent, which is an indispensable part of marine talent, are relatively scarce. This study revealed the flow characteristics and spatial agglomeration features of marine talent, which could provide references for establishing a reasonable mechanism for marine talent flow, enhancing the efficiency of regional talent allocation, and promoting the high-quality development of coastal cities' marine economies. Author information regarding the changes in their affiliations was extracted from research papers published in marine-related core journals in the China National Knowledge Infrastructure (CNKI) from 2000 to 2020, and a corresponding database was constructed. Using complex network analysis methods and techniques, such as ArcGIS and Gephi, the dynamic characteristics of marine research talent mobility were systematically analyzed. The results show that: 1) During the 20-year period, the number of marine research talent mobility showed a changing trend of increasing and then decreasing, and the network exhibited a typical "pyramid structure," which was controlled by a few hub-type node cities. 2) The spatial distribution pattern of marine research talent mobility was relatively stable, forming a diamond-shaped spatial structure with Qingdao as the core and Dalian, Beijing, Shanghai, and Guangzhou as the vertices. Marine research talent migration can be classified into two modes: intracity closed-loop and intercity migration. The proportion of closed-loop migration increased, and the phenomenon of intra-city migration was highlighted. 3) A considerable spatial imbalance existed in the mobility of marine research talent. The spatial distribution of the net inflow of marine research talent tended to be balanced, whereas the outflow of talent tended to be concentrated. The net inflow of marine research talent was active in the eastern and southern regions of China, whereas the net outflow of talent was active in the northeastern, central, and Beijing regions. The problem of high-intensity net inflow in the southern and eastern regions and high-intensity net outflow in the central and northeastern regions began alleviating. 4) The marine research talent mobility network exhibited an obvious core-periphery structure, and the "Matthew effect" was substantial. Qingdao was always at the core of the network, and there was a strong talent flow between the semi-peripheral and core cities. There was also strong relationship flows between them. Marine research talent in peripheral cities flows mainly to core and semi-peripheral cities. Overall, marine research talent is crucial for the development of coastal cities. Their mobility has a profound impact on both the source and destination cities. Therefore, it is necessary to formulate relevant policies based on the city's position within the marine research talent mobility network and optimize the allocation of marine talent, ultimately promoting the development of the marine economy.

Keywords

• marine research talent
• talent mobility
• spatial distribution
• network structure
• china