Haining Jiang

This study attempts to determine whether there is a spatial correlation between electricity generation and economic scale promoting coordinated development in Africa. We explore the spatial similarity and gray correlation degree between electricity generation and economic scale in Africa since the 21st century by adopting barycenter coupling and Gray Correlation Analysis method. We argue that there is a strong correlation between electricity generation and economic scale. Our findings indicate a significant spatial difference in electricity generation, mainly concentrated in Northern and Southern Africa. Furthermore, spatial pattern remains largely consistent over time, mirroring trends observed at the economic scale. Electricity generation and economic scale were concentrated in six countries- South Africa, Egypt, Algeria, Nigeria, Morocco, and Libya- and did not change significantly over time. A correlation analysis between electricity generation and the economic scale further confirmed this, with a linear coefficient of 0.907. Both the gravity centers of economic scale and electricity generation in Africa move farther in the north-south direction than in the East-West direction, with the former showing a Southwest-Northeast-Southwest track feature and the latter a Northeast-Southwest track feature. The spatial distribution of the gravity centers of electricity generation and the gravity centers of the economic scale in Africa are highly consistent; electricity generation highly correlates with the economic scale, consistent with the research conclusion obtained by the Gray Correlation Analysis method. This study suggests the coordinated development of electricity generation and economic scales in various African countries.

【目的】人居环境建设对黄河流域城市的高质量发展具有重要意义。本文旨在立足于韧性与人居环境理论，厘清黄河流域不同类型资源型城市的人居环境韧性水平与障碍度，丰富人居环境韧性相关研究，深化对人居环境这一复杂体系的理解。【方法】本文基于自然、人类、居住、社会、支撑5个子系统，构建黄河流域资源型城市人居环境韧性综合评价指标体系，运用HP滤波分析、三维核密度、热点分析、障碍度模型等方法，分析其2007—2021年的时空演化特征，并对影响人居环境韧性的障碍因子进行科学诊断。【结果】①从时序演化特征看，黄河流域资源型城市人居环境韧性整体处于波动上升态势，其演化周期经历了“低位停滞—渐进提升—波动骤升”3个阶段；不同类型资源型城市人居环境韧性日益提升的趋势均比较明显，其中成熟型、再生型城市韧性水平的提升幅度明显高于衰退型、成长型城市。②从空间演化特征看，城市人居环境韧性水平在空间上呈现“外围高于中心、下游高于上游”的格局特征，且空间集聚变化较为稳定，形成黄河流域外围热点区域空间集聚的特征。③从准则层看，各子系统障碍度变化相对稳定，整体大小表现为支撑韧性>自然韧性>社会韧性>人类韧性>居住韧性，具体到因子层面，单位面积水资源量、研发投入占GDP比重、污染物综合指数等为主要障碍因子，且不同类型资源型城市人居环境韧性的主要障碍因子存在空间异质性。【结论】黄河流域资源型城市的人居环境韧性水平总体处于上升趋势，且存在显著的空间区域差异。未来亟需从水资源、区域创新以及环境污染等方面优化人居环境韧性。

The distribution characteristics of urbanisation level and per capita carbon emissions from 2006 to 2019 were investigated by the ranking scale rule, using 108 cities in the Yangtze River Economic Belt of China. A coupling coordination model was established to analyse the relative development relationship between the two, and exploratory spatial–temporal data analysis (ESTDA) was applied to reveal the spatial interaction characteristics and temporal evolution pattern of the coupling coordination degree. The results demonstrate that: (1) The urbanisation level and per capita carbon emissions of the Yangtze River Economic Belt show a stable spatial structure of ‘high in the east and low in the west’. (2) The coupling and coordination degree of urbanisation level and carbon emissions show a trend of ‘decreasing and then increasing’, with a spatial distribution of ‘high in the east and low in the west’. (3) The spatial structure exhibits strong stability, dependence, and integration. The stability is enhanced from west to east, the coupling coordination degree has strong transfer inertia, and the spatial pattern’s path dependence and locking characteristics show a trend of weak fluctuation. Therefore, the coupling and coordination analysis is required for the coordinated development of urbanisation and carbon emission reduction.

As a great practice of building a community of shared future for mankind, the Belt and Road Initiative is facing geopolitical risk brought by great power games, regional conflicts and terrorism. It is an important mission of geopolitical research to scientifically deal with the geopolitical risk along the Belt and Road. This study systematically constructs the geopolitical risk assessment index system and analyzes the spatiotemporal evolution, obstacle factors and risk types of geopolitical risk of countries along the Belt and Road by using the entropy weight TOPSIS model, obstacle degree model and minimum variance method. The research results showed that: (1) From 2005 to 2020, the polarization of geopolitical risk in countries along the Belt and Road was very significant, and the overall trend of geopolitical risk tended to deteriorate. (2) The Middle East and Eastern Europe were the most important geopolitical risk zones along the Belt and Road, and Afghanistan, Iraq, Russia and Ukraine were the main high geopolitical risk centers, with significant risk spillover effects from these centers. (3) Terrorism and close relations with the United States were the most important obstacle factors for geopolitical risk in countries along the Belt and Road, and military intervention politics, trade dependence degree and foreign debt burden were important obstacle factors for geopolitical risk in countries along the Belt and Road. (4) Geopolitical risk along the Belt and Road can be divided into sovereign risk dominant type, sovereign and military risk dominant type, sovereign and major power intervention risk dominant type, and sovereign and military and major power intervention risk jointly dominated type, among which sovereign and military and major power intervention risk jointly dominated type was the most important geopolitical risk type. In order to scientifically deal with geopolitical risk in countries along the Belt and Road, it is necessary to strengthen geopolitical risk awareness, pay attention to the dominant geopolitical risk factors, strengthen the control of regional geopolitical risk spillover and formulate reasonable risk prevention and control scheme based on geopolitical risk types.

With the advances of the Belt and Road Initiative (BRI), the geo-economic interactions between China and countries along the 21st-Century Maritime Silk Road counties (MSRCs) continue to increase, and analyzing the geo-economic relations between China and the MSRCs is extremely important for a scientific understanding of bilateral geo-economic cooperation. Differently from the traditional logic of geo-economic competition and cooperation, we constructed a new framework based on the dominant factors of geo-economic relations and used an extreme random forest regression model to classify the geo-economic relation types between China and MSRCs from 2006 to 2017. The results show that the unbalanced development of investment and trade between China and MSRCs hindered the enhancement of the intensity of bilateral geo-economic linkage from 2006 to 2017. The “Matthew effect” of China’s geo-economic flow linkage with MSRCs is significant. There are obvious differences in the dominant factors affecting the types of geo-economic relations between China and MSRCs, and the distribution of the importance of the indices of the types of geo-economic relations in each country is disordered. Geopolitics, markets, and resources have played important roles in the geo-economic linkages between China and MSRCs. There are five types of geo-economic relations between China and the MSRCs: market-oriented type, resource-oriented type, market-resource-oriented type, market-geopolitics-oriented type, and resource-geopolitics-oriented type, of which the market-oriented type is the most important type of geo-economic relations. In the future, China should focus on regional powers along the Maritime Silk Road for bilateral geo-economic cooperation, actively promote the balanced development of bilateral geo-economic elements flows, strengthen geopolitical cooperation with MSRCs, and formulate cooperation plans according to the types of geo-economic relations.

The impact of technological innovation on water pollution is an important parameter to determine and monitor while promoting and furthering a region’s economic development. Here, exploratory spatial data analysis was used to analyze: the spatial patterns of technological innovation and water pollution in the Yangtze River, the changes in technical innovation and the resulting changes in water pollution, and the impact of technological innovation on water pollution. The following major inferences were drawn from the obtained results: (1) The spatial pattern of innovation input has a single-center structure that tends to spread. The patent innovation output has evolved, from a single spatial pattern with Shanghai as the core to a diffusion structure with three cores-Hangzhou, Shanghai, and Nanjing. (2) The aggregation mode of water pollution has evolved from the original “Z” mode to a new mode of core agglomeration, and water pollution is constantly being reduced. (3) The trends of change in patent innovation output and innovation input are roughly the same, while the trends of both and that of water pollution are contrary to each other. (4) The correlations between innovation input, patented innovation output, and water pollution are relatively low. From the perspective of spatial distribution, the number of cities with medium and high levels of gray correlation with water pollution is the same.

Since the 2008 global food crisis, food security vulnerability has been a prominent topic in the food policy debate. However, vulnerability is inherently difficult to conceptualize and is more challenging to operationalize and measure. This study constructs a mathematical model and takes China as a case study to measure the vulnerability and sensitivity of China with its partners in the international grain trade. The results show that 1) the degree of interdependence between China and its grain trading partners is asymmetric, which generates trade vulnerability or economic power; 2) the vulnerability of China’s food trade shows a high spatiotemporal heterogeneity among countries: the higher vulnerability zones are concentrated in North America and Northeast Asia, and the scope of the higher vulnerability zones tends to expand; 3) Our results also reveal that China also has different sensitivities to fluctuations in grain markets from different countries, and the higher sensitive zones of the grain trade in China are mainly distributed in America, Europe, and Oceania. The main contribution of this paper is the development of a methodology for food trade vulnerability assessment and examines the influence of international food trade on food security in importing countries, measured using the vulnerability index and sensitivity index. Nevertheless, the conclusions of this study can be considered preliminary, and there remains great potential for future studies to deepen and broaden our analyses further.

Spatial coupling analysis, cointegration, and the Granger causality test model were adapted from a geographical perspective to analyse the relationship between sci-tech talent and economic growth, as well as their spatial differences in the Pan-Yangtze River Delta from 1998 to 2019. The results demonstrate that the sci-tech talent centre of gravity and economic centre of gravity are close to each other, showing as two parallel chains, and there is higher spatial overlap and variation consistency between centres of gravity. Sci-tech talent and economic growth are in a long-term relationship of equilibrium, showing a better fitting cointegration equation, in which the latter affects the former. Shanghai has the greatest elasticity, with a 2.119 coefficient of sci-tech talent, while Zhejiang has the smallest elasticity with a coefficient of 0.859. There are differences in the causal nexus between sci-tech talent and economic growth. Economic growth has a unidirectional effect on sci-tech talent in Shanghai and Jiangsu while sci-tech talent has a unidirectional effect on economic growth in Zhejiang. There is a bidirectional effect between sci-tech talent and economic growth in Anhui. There is also a unidirectional effect from economic growth to sci-tech talent in the entire Pan-Yangtze River Delta.

Attractions of overseas high‐level returned talents have become a widely practiced talent policy, and the spatial structures of city‐related interactions are drawing the attention of researchers from various fields. China is particularly an interesting case in point, as it has moved toward an innovation‐oriented economy. Based on the movement trajectories of 2,846 returnees in a program entitled “Young Thousand Talents Plan” during 2011–2016, this paper identifies three city types in China: national core city, regional excellent city, and regional special city. Subsequently, this paper employs spatial visualization and qualitative interviews. This paper also goes on to show that the national core cities that possess dense research resources that coincide with premium life conditions and have objectively more favorable conditions, wider opportunities for attracting highly qualified specialists. Moreover, the backflow pattern can be divided into circle route and linear route, which is driven by social proximity and innovation context.