Tax is the main source of national and regional income, and the efficiency of tax collection and administration is of great significance to the sustainable development. In order to improve the efficiency of tax collection and administration in the less developed regions of western China due to the slow economic development, the low volume of tax revenue, and the high cost of tax collection and administration, this study extends the two‐stage DEA model to the case of asymmetric two‐stage efficiency values and analyzes the tax collection and administration efficiency of Yunnan Province by the improved model. The results show that the average value of tax collection and administration efficiency of Yunnan Province in 2020 is 0.944, and the overall efficiency values of tax collection and administration in most of the states and cities are within the range of 0.8–1.0. The overall tax collection and administration efficiency of Yunnan Province is relatively ineffective and can be improved. This study also makes relevant suggestions on how to improve the efficiency of organizations to promote the sustainable development of regions and the nation.

Reasonable siting layout of reserve emergency supplies plays a critical role in rapid response and accurate rescue after disaster. People’s life safety and health, as well as the psychological satisfaction brought by the government’s excellent emergency rescue level, is an important guarantee for maintaining social stability and sustainable development. Based on the coverage model, considering demand graduation, this paper develops a bi-objective optimization model to determine the optimal location plan of graduated supplies by maximizing the rescue satisfaction and minimizing the number of warehouses. A heuristic multi-center clustering location algorithm is designed to solve the model. This model is applied to the prepositioning of emergency supplies in an earthquake affected area in Sichuan province, China to verify the effectiveness of the model and algorithm. Finally, the paper discusses the influence of demand graduation on the location of emergency supplies. The results show that reasonable location planning of different levels of supplies can effectively improve the rescue satisfaction.

This study employs the principles of computer science and statistics to evaluate the efficacy of the linear random effect model, utilizing Lasso variable selection techniques (including Lasso, Elastic-Net, Adaptive-Lasso, and SCAD) through numerical simulation and empirical research. The analysis focuses on the model’s consistency in variable selection, prediction accuracy, stability, and efficiency. This study employs a novel approach to assess the consistency of variable selection across models. Specifically, the angle between the actual coefficient vectorβand the estimated coefficient vector $\hat {\beta }$ is computed to determine the degree of consistency. Additionally, the boxplot tool of statistical analysis is utilized to visually represent the distribution of model prediction accuracy data and variable selection consistency. The comparative stability of each model is assessed based on the frequency of outliers. This study conducts comparative experiments of numerical simulation to evaluate a proposed model evaluation method against commonly used analysis methods. The results demonstrate the effectiveness and correctness of the proposed method, highlighting its ability to conveniently analyze the stability and efficiency of each fitting model.

After an earthquake, affected areas have insufficient medicinal supplies, thereby necessitating substantial distribution of first-aid medicine from other supply centers. To make a proper distribution schedule, we considered the timing of supply and demand. In the present study, a “sequential time window” is used to describe the time to generate of supply and demand and the time of supply delivery. Then, considering the sequential time window, we proposed two multiobjective scheduling models with the consideration of demand uncertainty; two multiobjective stochastic programming models were also proposed to solve the scheduling models. Moreover, this paper describes a simulation that was performed based on a first-aid medicine distribution problem during a Wenchuan earthquake response. The simulation results show that the methodologies proposed in this paper provide effective schedules for the distribution of first-aid medicine. The developed distribution schedule enables some supplies in the former time windows to be used in latter time windows. This schedule increases the utility of limited stocks and avoids the risk that all the supplies are used in the short-term, leaving no supplies for long-term use.