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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. [ABSTRACT FROM AUTHOR]

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As the gateway of China's opening to the outside world, port forms a gateway-city system with hierarchical and functional division through interaction with carrier cities. Based on the port data of 2001 and 2018, this paper measures the gateway function changes of port cities by transforming the urban flow model, so as to reveal the evolution characteristics and laws of China 's gateway system since the 21st century. The research shows that: (1) Since the start of new century, the external service level of gateway-city has significantly improved, the external service function and value of passenger transport and freight have increased by 4 and 8 times compared with those in 2001. But the external service value of freight is less than that of passen‐ ger transport. Although passenger transport and freight are gradually decreasing in the whole country, the decline of freight in East China has been steeper than the other three regions. There are also significant regional and urban differences in external passenger and freight services in different transport sectors. (2) China's gateway-city property indexes have formed a regional evolution pattern of eastern leading, central and western strengthening and northeast weakening. Using the Dagum Gini coefficient method found that the regional spatial gap of gateway proper‐ ty has been reduced, and the main source for the spatial differentiation of gateway function in China is the disparity among regions. (3) All gateway cities can be divided into four grades: na‐ tional gateway cities, regional gateway cities, provincial gateway cities and local gateway cities, the hierarchical structure of China gateway-city shows a stable 'pyramid' shape. [ABSTRACT FROM AUTHOR]

Taking the marine industry as the breaktlirough point, based on tlie data of joint patent application of marine industry in tlie last 20 years, tliis study analyzes the cooperative network of different stages using complex network analysis. This approach reveals tlie evolution process, spatial structure, and influencing factors of network innovation perfbmiance of China's marine industry. The results reveal the following: (1) The cooperative network in 2000-2001 does not have tlie characteristics of complex networks. From 2002 to 2019, tlie "small world" and scale-free characteristics of the cooperation network gradually became obvious, indicating that China's marine industry had fbnned an organic connection of industry-university-research cooperation network since 2002. Before 2008, the network expansion speed was slow and tlie network structure gradually loosened. From 2009 to 2016, the network expansion speed accelerated and the network was optimized. After 2017, the network expanded rapidly and inter-agency cooperation was efficient. Taking 2008 and 2016 as dividing points, the network was divided into embryonic, exploration, and rapid development stages. The cooperative network has exliibited a loose, dual-core multilateral radiation structure, and has gradually evolved into a single-core topology witli China Offshore Oil Group Co., Ltd. (2) In the evolution process of cooperative innovation networks, universities have always been an important network resource transfer hub and have control of most resources. With the enhancement of the dominant position of innovation, state-owned enterprises' ability to control resources has greatly improved, gradually occupying the core position of the network. Under tlie influence of policy promotion, market selection, and practical needs for tlie transfbniiation and development of tlie marine industry, an industry-university-research cooperation network has been fbnned, with the enterprise-enterprise cooperation mode as tlie core and the enterprise-research cooperation mode and school-enterprise cooperation mode as tlie focus. (3) Under tlie impetus of coastal cities, the number of patents with which inland cities cooperate increased tlie fastest. The main body of industry-university-research innovation is concentrated in Beijing-Tiaiyin-Hebei, Yangtze River Delta, and Pearl River Delta. Beijing occupies tlie core position of the urban innovation network witli an absolute advantage. The urban cooperative network is characterized by an "umbrella" structure and has obvious "heavy tail" characteristics. Tliis shows tliat the development of marine science and teclmology mainly depends on the cooperation and innovation between coastal cities and a small number of inland cities, such as Beijing and Wuhan, affected by geographical distance and urban economic development level. (4) Impulse response analysis reveals that network scale, marine industry GDP, and scientific research personnel input can positively promote the innovation perfbnnance of cooperative networks. The research institutions, universities, and enterprises in the innovation subjects can stimulate the innovation output of the network and the importance of the tliree decreases in turn. Network density and small-world quotient are negatively correlated with network innovation output. [ABSTRACT FROM AUTHOR]

As the most significant international transportation infrastructure, the operation and external links of ports are affected by more complicated aspects, resulting in immense changes not seen in a century. Related studies have long been interested in and have followed the evaluation of port location advantage as a comprehensive response to ports' economic and trade conditions. Location advantage reflects the overall resource advantage of a location. Transportation infrastructure can be evaluated from various perspectives, and the choice of different indicators sets the evaluation slant for its use. A port's ability to operate depends on natural navigational conditions, high-quality infrastructure, an appropriate economic hinterland, favorable geographic relationships, and a global environment. Port location advantage has traditionally been focused on from the perspective of transportation routes, hinterland economy, etc. The geographical proximity of nations also has a significant impact on how ports function in today's complex international development environments. To evaluate the advantages of port location along the route, this study uses the geo-relationships between various countries as well as the physical, functional, and economic links between ports as its research objects. It then homogenizes the national-scale WGI Global Governance Index to ports and incorporates it with port-scale maritime distances and route linkages as an integrated model of the degree of location advantage of the ports, using ports along the Maritime Silk Road from 2008 to 2018 as case studies to show how much the ports' advantage in location affects their significance in the real world international environment. The research findings are as follows. 1) Because of the relative position of the hinterland economy in international economic and trade exchanges, the port location advantage also exhibits some scale-free characteristics, and the quantitative expression of geo-relationships between ports emphasizes the importance of ports. As a representative of Asia's emerging economies, China has added more ports with more significant location advantages. 2) The strength of location connections between ports follows the law of distance attenuation, and the shift in the center of gravity of port location connections to Asia reflects the formation of a port location connection pattern dominated by internal Asia with the development of many emerging economies therein. 3) Comparison with mainstream complex network indicators found that although the concentration of factor flow has been formed under the "flow space" in the era of globalization, primary geographical attributes such as geographical relationships and spatial distance still maintain their independence and do not exhibit spatial imbalance under the influence of the reconstruction of global industries and trade. The location of ports based on geographical relationships and port location dominance avoids the limitations of a single perspective in evaluating port location in the international shipping network and can serve as a new basis for assessing the importance of ports in shipping networks; the expression of geographical spatial relationships fills the evaluation gap of existing network indicators. [ABSTRACT FROM AUTHOR]

As the connection point between sea and land, coastal ports are constantly extending and innovating logistical operations, which paves the way for rapid development of the coastal port logistics industry. In recent years, with increasing economic globalization and the development of production and trade networks in various countries, integrated logistics services have steadily replaced the conventional loading and unloading services provided by ports. These services now play a significant part in the worldwide network of cargo commerce. The primary function of port logistics firms, as a significant provider of port logistics activities, is the cross-regional organization of these activities. The earliest version of the port logistics network may be seen in the concentration of port logistics businesses inside the city and their dispersion between cities. Nevertheless, there is still a dearth of studies on the coastal port logistics organization network. At the same time, there is notable variation in the infrastructure of coastal ports and coastal cities' economic development, with fierce competition between domestic and provincial ports. To evaluate the evolution of the geographical features of China's port logistics network from 2009 to 2019, this paper utilizes world city network analysis and social network theory analysis, using the years 2009, 2014, and 2019 as time nodes. This paper aims to serve as a guide for improving the physical architecture and network design of Chinese coastal port logistics, to further advance the effective arrangement and configuration of social resources in the port logistics sector, and to offer a more favorable environment for the sector's development. The findings indicate that: 1) from 2009 to 2019, China's coastal ports' logistics network structures tended to mature. The network's geographic area was increased with the installation of additional city nodes, which also reduced the typical distance between cities and enhanced connectivity. However, from the perspective of network development as a whole, the overall network density was low, and the majority of cities still experienced weak connections. 2) The network connection space upholds the core-edge structure, in which Tianjin, Dalian, Qingdao, Ningbo, Shenzhen, and Xiamen radiate from Shanghai to form the core network, whereas the marginal cities primarily join the network by connecting to the core city, and the interaction between the marginal cities is weak. 3) The coastal port logistics network's hierarchical structure is clear. The core-subcore-general-edge four-level circle layer structure is presented in accordance with the different urban statuses in the network and the intensity of inter-circle connection steadily declines with the drop in circle level. 4) Balanced development of information basis level has a negative impact on the development of the port logistics network. However, differentiated development of coastal port logistics market scale, port infrastructure, urban economic development level, and headquarters scale of port logistics enterprises has a positive impact on development. [ABSTRACT FROM AUTHOR]

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