The supply and demand allocation and logistics optimization of emergency materials are important support for emergency materials management and decision-makings. This study proposes a supply-demand analysis based material supply point allocation method, which on the basis of the optimal supply and demand allocation model. This method takes into account the constraint condition that the market reserve point must simultaneously supply both the affected and original demand points with supportive materials. Compared to traditional methods, this approach further improves the rationality and accuracy of material supply and demand analysis. Based on the allocation of material supply points, a method for optimizing the emergency material distribution path under flood scenarios is further developed. This method is based on real road networks, using “Degree”, “Squares Clustering Coefficient “ and “Road Design Daily Traffic Volume” to evaluate the reliability of road sections, and fully considers the impact of the flood disaster on the road travel time. It aims to achieve the shortest path travel time and the highest path reliability, using heuristic algorithms to solve the optimal path. A case study was conducted in Fengxian District, Shanghai, China. Through comparative analysis of multiple scheme scenarios of collaborative supply between the market and government, it was found that the G scheme (100% government supply) required a longer distribution time and resulted in a higher overall time cost, which could lead to the timeout situation for emergency response missions. The S plan (100% market supply) had a lower delivery efficiency and was prone to waste of human and transportation resources. However, the S1500 scheme (the market supplies the shelters within the 1 500 m coverage range and the government supplies the remaining shelters) was a collaborative supply scheme that was suitable for all 3 types of materials (water, rice, milk (infant formula)) in the case study. The research results can provide decision supporting for emergency rescue and relief efforts of relevant departments in the study area. The methods proposed in this paper can provide methodological references for related studies in other regions.

New infrastructure is not only the cornerstone of the fourth industrial revolution, the engine for the high-quality development of regional economy and the rise of a great nation, but also the frontier and important research field of economic geography. From the perspective beyond technology, this paper systematically combs the relevant theories about new infrastructure in current economic geography, including the theory of technological relatedness, the theory of key enabling technology, the theory of technology-system co-evolution and the theory of regional integration. On this basis, 3 scientific issues and research ideas that need to be focused on are proposed, namely, the research on the path and mechanism of the new infrastructure technologysystem collaborative evolution, the research on the innovation and development mechanism of the new infrastructure enabling industry, and the research on the overall layout of the new infrastructure and the operation mechanism of regional integration. This paper aims to establish a theoretical framework for new infrastructure to promote regional economic development, in order to provide theoretical support for China to better play the strategic potential of new infrastructure and promote regional high-quality development.

The new waves of information technology revolution give rise to digital infrastructure exemplified by 5G base stations, big data centers, and industrial internet, constituting strategic components of the modern infrastructure system. Proliferated studies on digital infrastructure range from diverse disciplines and perspectives. Given the unclear principal line of research progress in geographical studies on digital infrastructure, along with ambiguous disciplinary contribution and future research avenues, this paper therefore seeks to review and compare research progress on digital infrastructure from a geographical perspective in and out of China, and to draw upon key research agendas for academic attention. In general, overseas studies have an early start, with rapid research progress and diversified themes, and have been consistently intensified and widened. By contrast, domestic studies exhibit a late start but have increased explosively since 2019 mainly by scholars in the field of economics and management. Based on a critical perspective and demand side, overseas studies pay much attention to the digital gap, socio-spatial inequality, and digital transformation of disadvantaged regions. Domestic studies, which place more emphasis on a functional perspective and supply side, focus on how digital infrastructure empowers regional digital economic development and connectivity within and among regions. In short, the new waves of digital technology revolution, justice and equity requirements in the information society, and national strategic demands facilitate the rise and development of digital infrastructure studies in geography. Although overseas and domestic studies share similar themes, but they exhibit different priorities. Knowledge production and theoretical construction of digital infrastructure in China by geographers are still in its infancy. Looking forward, this paper suggests that: 1) geographical studies on digital infrastructure in China should balance the supply and demand sides, in order to strengthen the interaction and systematization of research achievements; 2) digital infrastructure needs to be better incorporated into related theoretical frameworks in geography, deepening disciplinary knowledge production and theoretical contribution; and 3) comprehensiveness of geography should be sufficiently employed as an advantaged way to lead multi-disciplinary studies on digital infrastructure.

Return migration has become a notable socio-economic trend in the new stage of China's urbanization, and the analysis of its driving mechanism has received extensive academic attention. As a micro behavior, the return of migrants is not only affected by personal and family factors, but also closely related to external environment. However, existing studies have focused on the role of individual factors, but not enough research has been conducted on the relationship between regional contexts and return migration. We introduce a gradient boosting decision tree model in the field of machine learning, based on the data from the 2017 China Migrants Dynamic Survey, with the return intention as the response variable and the regional contexts—Both in the place of origin and destination—As well as migrants' personal and household factors as the explanatory variables, focusing on the non-linear influence of the regional contexts on the return migration intentions and the threshold effect. The results show that: 1) The total contribution of the local contexts of the place of place of the origin and destination to the intentions of the migrants to return is 44.1%, which is an important factor influencing the return intentions, and the contributions of the two places is roughly equal. Among these, medical and health resources and air pollution are extremely important in both places. In addition, economic growth in the place of origin is also important for the return intention of migrants, while the climatic condition in the place of destination is more important; 2) There are both non-linear and linear relationships between local contextual factors and migrants' intention to return. Among them, medical and health resources, basic education resources, air pollution have obvious non-linear effects on the return intention, while economic growth and temperature conditions have mainly linear effects; 3) The influence of individual factors on return intention is mainly nonlinear effect. There is an irregular U-shaped relationship between age, migration duration and return intention, and the non-linear influence of household income is more complex. There is an obvious threshold effect between household housing expenditure and return intention, and a negative correlation between migrant's education level and return intention. This study incorporates the local contexts of the place of origin and destination into the analytical framework for the mechanism of return migration, identifies the relative importance of the local context and individual characteristics of the two places on the return intention of the migrants, and reveals the specificity and complexity of internal return migration in China, which contributes to deepening the research on migration in the new era and provides scientific reference for policy makers.

With the increase of uncertainty in the development environment at home and abroad, coastal cities are more exposed to various risk disturbances than other regions, and the evolution process of economic resilience is more complicated, however, there is a lack of coupling analysis from multiple scales such as regions, industries, and enterprises. Therefore, scientifically revealing the evolution characteristics and influence mechanism of economic resilience of coastal cities is an important support for promoting the scientific development of coastal cities and consolidating the leading position in the opening up of eastern coastal areas. By constructing the economic resilience analysis framework of coastal cities, taking Lianyungang as a case, the paper analyzes the economic resilience characteristics and influence mechanism of coastal cities with the economic resilience measurement model and the Esteban-Marquillas extended model from 1996 to 2020. The results show that: 1) The macro-economic resilience of coastal cities showed a periodic change of weakening-strengtheningweakening, and the secondary industry dominated the development of Lianyungang's economic resilience. 2) The resilience of traditional path industry in coastal cities was weaker than that of emerging path industry, and the strength of industrial mix effect, competitive advantage effect and allocation effect had a has a dynamic and staged feature. The evolution of the economic resilience of coastal cities was determined by the development of emerging industries. Emerging industries were not necessarily high-tech industries, but adapted to local conditions. 3) The resilience of enterprises in coastal cities tended to weaken, and the resilience of enterprises in emerging industries was stronger than that in traditional industries. The new enterprises of new path industries and chemical industry of the traditional path showed path dependence on specific spatial locations such as ports and high-tech zones, which indicated port location had a positive impact on enterprise survival. Therefore, guiding the agglomeration of industries in ports and development zones (high-tech zones) was the key path to improving the economic resilience of coastal cities.

Based on the panel data of 31 provinces (cities and districts) in China from 2013 to 2020, this paper measures the level of new infrastructure development and the degree of coordinated regional economic development in each province and then uses the coupling coordination model to measure the coupling coordination degree of the two and analyzes their spatial and temporal evolution patterns and influencing factors. The results show that: 1) The level of development in China's new infrastructure and regional economic coordination degree has been improving each year, with increasing coupling and coordination between the two. Despite starting from a lower level, the growth rate of new infrastructure has been significant since 2018, reaching 29.96% in 2020. Similarly, there has been a noticeable upward trend in the degree of regional economic coordination and the coupling between new infrastructure and regional economic coordination degree. 2) The coupling and coordination between new infrastructure and regional economic coordination degree exhibit spatial heterogeneity, with the eastern region surpassing the central and northeastern regions, while the western region lags behind. This discrepancy can be attributed to the relatively higher levels of new infrastructure development and regional economic coordination degree in the eastern provinces, as well as the smaller internal differences within the central and northeastern provinces. On the other hand, the western provinces exhibit greater disparities. 3) The level of new infrastructure development demonstrates negative spatial spillover effects among provincial regions, whereas the degree of regional economic coordination and the coupling between new infrastructure and regional economic coordination degree exhibit positive spatial spillover effects among provincial regions. 4) The factors that primarily influence the coupling and coordination between new infrastructure and regional economic coordination degree are related to industrial structure and urbanization processes. Conversely, factors such as government management and population density have less discernible effects on this coupling and coordination. The article investigates the evolutionary characteristics and influencing factors of the level of new infrastructure development, the degree of coordinated regional economic development, and the degree of coupling and coordination of the two in China, and expects to provide a reference for decision-making on the benign interaction between new infrastructure and coordinated regional economic development in China.