Guangdong Province is one of China’s largest and most developed regions. It is home to more than 113 million people and features unique geographical and climatic characteristics. Typhoons that pass through often result in heavy rainfall, which causes flooding. The region’s risk of typhoon and flood disasters, and the resulting indirect economic impacts, have not been fully assessed. The purpose of this paper is to introduce a method for assessing the spatial and temporal cumulative risk of typhoon-induced flood disasters, and the resulting indirect economic impacts, in order to deal with the uncertainty of disasters. We combined an analytic hierarchy process (AHP) and spatial analysis using a geographic information system (GIS) to produce a comprehensive weighted-risk assessment from three different aspects of disaster, vulnerability, and resilience, with 11 indicators. A new method for computing risk based on spatial and temporal cumulative patterns of typhoon-induced flood disasters was introduced. We incorporated those direct impacts into a computable general equilibrium (CGE) model to simulate indirect economic losses in alternative scenarios according to different risk levels. We found that the risk in the coastal area is significantly higher than that in the northern mountainous area. The coastal areas of western Guangdong, Pearl River Delta, and Chaoshan Plain face the greatest risk. Our results indicate that typhoon and flood disasters have negative effects on the real GDP, residents’ income, consumption, and several other macroeconomic indicators. We found differing disaster impacts across industrial sectors, including changes in the output, prices, and flow of labor among industries. Our estimates provide scientific support for environmental planning, spatial planning, and disaster-risk management in this important region. They are also of reference value for the development of disaster management strategies in similar climatic regions around the world.

Intercity travel creates more pronounced interregional linkages and spatial effects than migration. However, few studies have integrated travel into general equilibrium models to assess its welfare and general equilibrium impacts. This study quantifies the impact on regional development of travel by developing a spatial general equilibrium model including trade, migration, and travel to quantify and compare the different effects of these three spatial linkages. We structurally estimate the model using data from 287 prefecture‐level cities in China. The counterfactual analysis reveals that travel significantly impacts regional economic outputs, with effects roughly equivalent to those of migration. Additionally, travel demonstrates distinct mechanisms and effects on population distribution compared to the other two linkages. This study provides both theoretical and empirical insights into how various types of spatial linkages—particularly travel—affect interregional economic development. The findings are particularly pertinent for evaluating spatial policies, such as transportation infrastructure improvement and urban cluster development.

Water can be redistributed physically and virtually. We explored water allocation optimization to mitigate water stresses by constructing a physical–virtual dual water system and optimizing the 1987 Yellow River water allocation scheme. We calculated the virtual water volume, identified the virtual in-basin, out-of-basin, and export water volumes, and compared the total regional water demand (i.e., combined physical and virtual water volumes) with regional water planetary boundaries to optimize basin water allocation schemes. Virtual water accounted for > 90% of the total regional demands, whereas physical flows did not significantly impact them. Moreover, allocation quotas for Qinghai and Inner Mongolia should be reduced by 0.113 and 1.005 billion m³, respectively, for sustainability. Furthermore, improving the efficiency of water-intensive sectors and limiting virtual water outflows from heavy industry to out-of-basin sectors are vital to water intensification. Increased attention should be directed toward physical–virtual water demands than the current focus on supply-oriented water allocation.

With the rapid development of digital technology and the increasing focus on the global supply chain network, it has become a new challenge for international companies to select digital technology innovation projects in an efficient way, so as to improve their supply chain position and competitiveness. Prior works have identified the effects of digital technology adoption on companies’ supply chain positions; however, there has been limited research on the impact of digital technology innovation heterogeneity on companies’ supply chain position and the pathways through which this effect plays out. Hence, based on the global supply chain panel data from Chinese new energy vehicle companies, this study used a two-way fixed-effects model and causal stepwise regression analysis to study the impact of digital technological innovation on companies’ supply chain position and the dynamic mechanisms between them. The empirical results show that all three types of digital technology innovations, in the design and development process, the production and manufacturing process, and the sales and after-sales process, significantly enhance the company’s supply chain position. Further mechanism analysis shows that digital technology innovations enhance the company’s managerial efficiency and profitability mainly by reducing costs and increasing revenues, which ultimately improves the company’s supply chain position. This paper can provide a reference for policy makers to promote the application and development of a company’s digital technology and enhancing the supply chain position.