This paper aims to analyze the urban human settlements of 21 megacities and supercities from 2011 to 2020 in China and improve urban human settlements planning and management. First, the data envelopment analysis (DEA)-Malmquist-Tobit model is used to conduct a static and dynamic evaluation of the efficiency of urban human settlements and analyze the main factors that affect it. Then, the coupling coordination degree model is utilized to quantitatively evaluate the coupling coordination degree between urban human settlements and high-quality economic development. Finally, the GM (1, 1) model is established to predict each city's average input-output index during the 14th Five-Year Plan period. It is hoped that this paper could promote sustainable urban development. The empirical results are as follows: (1) the technical efficiency (TE) from CRS DEA of human settlements in China's megacities and supercities is low. Management and technology are the shortcomings in the development of urban human settlements; (2) total factor productivity (TFP) has shown negative growth. Technical progress efficiency (TC) is the key to improving the efficiency of urban human settlements; (3) urban infrastructure has the most significant role when promoting the efficiency of urban human settlements; (4) the coupling degree between the efficiency of human settlements and high-quality economic development is mainly high-level coupling. The degree of coordination is gradually rising; and (5) during the 14th Five-Year Plan period, the investment in human settlements in both types of cities will continue to increase. With the continuous expansion of investment, the output will be imbalanced.

As a necessary infrastructure for new energy vehicles (NEV), charging piles have become a hot topic of social concern. Studying the innovation efficiency of charging pile companies can help to solve the development dilemma of the charging pile industry. This paper uses the generalized fuzzy data envelopment analysis (DEA) method based on game theory to study 23 Chinese listed charging pile manufacturing companies’ innovation efficiency from 2019 to 2021. On this basis, 15 charging pile technological interrelatedness companies are joined to establish a new game environment and to discuss the possibility of charging pile product manufacturing companies shifting to a new business model led by value-added service provision. The results show that the innovation efficiency of each company is significantly improved in the cooperative state, while the opposite is true in the competitive state, so cooperation is the company’s priority choice. Charging pile product manufacturing companies are more inclined to cooperate with technologically interrelated companies. The business model dominated by value-added service provision is conducive to improving the level of industrial innovation. The competition will easily lead to the decline of their innovation efficiency. Hence, companies should carefully choose their competition strategy.

The charging pile is the key "chain" of the new energy automobile industry. It plays an essential role in promoting the new energy industry’s development and even realizing the "carbon peaking and carbon neutrality" goal in China. This paper uses the three-stage DEA-Tobit model, taking 38 charging pile-listed companies from 2017 to 2020 as samples, to analyze the efficiency of technological innovation in the charging pile industry and its influencing factors based on the time delay effect. The research finds that pure technical efficiency is the main factor affecting the efficiency of technological innovation in the charging pile industry. After removing environmental factors’ interference, technological innovation efficiency has been significantly improved on the macro level. Moreover, individual companies’ scale efficiency and pure technical efficiency need to be improved. Tobit regression shows that the technological innovation efficiency of the charging pile company is significantly related to government policies, company size, and scientific research expenditure. It is suggested that the government should refine the evaluation indicators of charging piles and optimize the industrial support policies. Charging pile companies can implement differentiated management, increase investment in innovation, improve charging technology, and improve the efficiency of technological innovation.

Based on the classic IPCC carbon emission calculation theory, this paper calculates the agricultural carbon emissions intensity and efficiency in Zhejiang Province from 2011 to 2020. The LMDI model is further adapted to carry out the influence factors of agricultural carbon emissions. In addition, the grey prediction model GM (1, 1) is used to predict the carbon emissions of Zhejiang Province from 2022 to 2025. The results show that the agricultural carbon emissions and carbon emission intensity in Zhejiang Province have a downward trend. Further, it is concluded that Shaoxing, Hangzhou, Jiaxing, and Huzhou are the cities with low emission and high efficiency, and Wenzhou is the city with high emission and low efficiency. Meanwhile, the improvement of Total Factor Productivity (TFP) results from the joint action of Technical Progress Efficiency (TECH) and Technical Efficiency (EFF). TECH is greater than EFF, and Scale Efficiency (SE) and Pure Technical Efficiency (PTE) contributions change with the years. In general, the contribution of PTE is more significant than that of SE, and its improvement mainly rests on technical progress. Among the factors influencing agricultural carbon emission efficiency, agricultural carbon emission intensity and labor force size have inhibiting effects on agricultural carbon emission efficiency growth. In contrast, agricultural industrial structure, economic development, and urbanization positively affect agricultural carbon emission efficiency. The prediction results show that the overall carbon emissions of Zhejiang Province will get a downward trend. Finally, based on these findings, we offer policy implications.

There is a close relationship between environmental resource efficiency and the high-quality development of the river basin economy. Improving urban environmental resource efficiency is of great significance to the high-quality development of the river basin. Based on the environmental panel data of cities in the Yangtze River Basin from 2004 to 2020, this paper applies the DEA-Malmquist index model to explore the static characteristics and dynamic changes in the overall environmental resource efficiency of cities in the Yangtze River Basin. Then, the spatial and temporal aspects of the environment are discussed by combining the kernel density function method. The Tobit regression model is used to analyze the factors affecting the environmental resource efficiency of cities in the Yangtze River Basin and its importance. Finally, the grey prediction model is utilized to predict the undesirable output data of cities in the Yangtze River Basin from 2023 to 2025. The results show that the overall urban environmental resource efficiency level in the Yangtze River Basin is high. However, the number of cities that achieve DEA efficiency is less than that of non-DEA efficient cities. The Total Factor Productivity (TFP) of cities shows a “high-low-high” trend, and the technical efficiency change (Effch) and pure technical efficiency change (Pech) have an improvement trend. Industrial structure, regional factors, and openness are positively correlated with environmental resource efficiency, during the economic scale and environmental governance level negatively moderate environmental resource efficiency. The forecast results show that the undesired output of cities in the Yangtze River Basin has been somewhat controlled.

基于已有的科技服务业相关研究,本文采用Super-SBM模型对我国30个省份2009—2018年科技服务业的发展质量进行了静态效率分析评价,并运用Malmquist指数进行了动态效率分析,试图阐明目前我国科技服务业生产效率的时空演变情况.研究发现:我国科技服务业整体发展水平较低但呈上升趋势;受地区经济基础、科研水平及开放性程度等因素影响,东部地区发展水平远高于中部及西部地区,区域间差距仍然较大但有缩小趋势.在此基础上进一步分析其变化的原因,并提出要提升科技服务业发展效率,需要完善制度环境、加大科研投入、协调区域发展和推动市场化建设.