China has always been a major agricultural country, and the issues of agriculture, rural areas and farmers have always been fundamental issues of China’s reform and development. First of all, most previous studies did not combine agricultural development with rural economic development to consider the rural development status. Through the network-slack-based measure (SBM) model, agricultural development and rural economic development are taken as the first stage and the second stage, respectively, to determine the overall efficiency of rural development. Secondly, most previous studies directly selected a number of agricultural materials as inputs to evaluate agricultural production efficiency, and did not consider the impact of a variety of agricultural materials comprehensively. We use the entropy method to calculate a comprehensive index including a variety of agricultural materials. Third, most previous studies did not take into account the harmful effects of agricultural production on the environment. We take carbon emissions and agricultural non-point source pollution (ANPSP) as undesirable outputs into the model, and consider the impact of agricultural production on the ecological environment comprehensively. On the basis of the above innovation, we adopt the two-stage SBM-undesirable model to comprehensively and systematically study the efficiency of rural development in China. Furthermore, the gap of rural development efficiency is determined by sigma convergence and a convergence test. All the data are from the National Bureau of Statistics of China. The results show that the development level of China’s rural agricultural eco-efficiency is significantly higher than that of rural economic development, and the low efficiency of the whole rural development is mainly affected by the low efficiency of rural economic development. The distribution of efficiency value shows that the eastern region is the best, and the development level of the remaining three regions is very low. The regional development gap is large, and this gap still exists for a long period of time. Nevertheless, the efficiency of rural development has improved year by year. Based on empirical analysis, we put forward some feasible suggestions to provide reference for policymakers in formulating rural development policies, narrowing the regional gap and rural sustainable development.

As crucial international trade and global logistics players, container terminals worldwide handle more than 80% of the global merchandise trade. After analyzing and summarizing the previous studies, we use container terminal companies as the research object to fill the gap left by previous studies. Based on the above research status, this study analyzes the operational efficiency and total factor productivity of 32 container terminal companies in China using the super -efficiency DEA–SBM model and the Malmquist index method. The results show that (1) the operational efficiency level of 32 container terminals in China from 2017 to 2020 has a huge gap, and 15 container terminal companies have operational efficiency below 0.6, which indicates that most container terminals have excess inputs and a waste of resources. (2) The container terminals in the Bohai Rim, Pearl River Delta and Yangtze River Delta regions have higher operational efficiency. This shows that the development of container terminals cannot be separated from the economic hinterland of the cities where the ports are located. (3) The Malmquist index analysis shows a 2.8% decrease in total factor productivity, a 3.2% increase in the composite technical efficiency index and a 5.8% decrease in the technological progress index, which indicates that most container terminal companies have imperfect management practices and decision making. Based on the study’s results, this research provides relevant and feasible recommendations for policymakers who formulate policies for the development of the shipping industry to promote high quality and sustainable development of the shipping industry and the economy.