In recent years, rural areas of China have experienced frequent occurrences of various natural disasters. These calamities pose significant threats to the safety, property, and mental well-being of rural residents while also presenting substantial obstacles to the sustainable development of the rural economy. Currently, emergency management in China faces several challenges such as inadequate emergency institutions, insufficient security policies, weak disaster infrastructure, and difficulties in information sharing. In light of this situation, we propose an intelligent command mode based on modern digital technology that capitalizes on its advantages and integrates early warning systems with decision-making processes and rescue operations to establish a comprehensive emergency event processing system. This innovative approach opens up new avenues for exploring and researching effective modes of rural emergency management. The article elaborates on how the construction of a smart rural emergency management mode facilitates the digital integration of disaster elements while enhancing the efficiency of emergency response efforts and promoting sustainable development. The research methodology employed includes literature review methods along with field research techniques and analysis methods. Finally, this discussion evaluates both the benefits and challenges associated with implementing this mode within rural emergency management practices.

This paper delves into optimizing the rotation of relief supplies within the relief supply chain system, concentrating on reserve quantity decisions for governments and humanitarian organizations involved in disaster response. By integrating a trade-in strategy with suppliers, it ensures a precise and timely response to the fluctuating demand for relief supplies post-disaster. Utilizing the newsvendor model, optimization theory, and supply chain coordination principles, we developed a comprehensive model that calculates optimal reserve quantities for pre-positioning demanders. It also outlines the expected profit function for suppliers and a robust supply chain coordination model. The findings highlight that optimal stockpiling decisions for relief supplies are heavily influenced by cost parameters, material characteristics, and the relationship between trade-in pricing and market resale values. Notably, higher trade-in prices generally reduce the government’s optimal reserve quantities, impacting strategic decisions within supply chain coordination. This research adds to disaster management literature by offering strategic insights into how coordination and pricing strategies can improve disaster preparedness and response efficiency and effectiveness.

Marxist political economy provides a theoretical framework for sustainable supply chains, while the implementation of sustainable supply chains embodies and deepens the practical application of Marxist principles. This paper studies supply chain sustainability from the perspective of Marxist political economy, proposing a novel analytical framework to address sustainability challenges. The primary research focuses on (1) Identifying Influencing Factors: Influencing factors of Marxist political economy and supply chain sustainability are categorized into four main areas: society and government, environment, economy, and the supply chain itself. Through classification analysis, 16 key factors influencing sustainable supply chain implementation are identified. (2) DEMATEL Analysis (Decision-Making Trial and Evaluation Laboratory Method): Data are gathered through investigations and questionnaires to construct a direct influence matrix. Subsequently, a decision test method quantitatively analyzes the interactions among these factors, resulting in a comprehensive influence matrix and a cause–effect diagram. To enhance the overall benefits of supply chain sustainability and foster sustainable development.