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In order to explore practical ways to test the eco-efficiency of low-carbon tourism and its drivers in Jiangsu Province, this paper empirically tests the effects of selected driving variables on the eco-efficiency of low-carbon tourism using a spatial lag model. It measures the eco-efficiency of low-carbon tourism in 13 prefecture-level cities in Jiangsu Province based on a modified two-stage network SBM model. According to the direct effect test results, per capita tourism income ( PTI ) had the most significant effect on the eco-efficiency of low-carbon tourism, with an impact coefficient of 0.5437, environmental pollution governance ( EPG ) had the second most significant effect, energy consumption intensity ( ECI ) and carbon emission intensity ( CEI ) had adverse effects with effect coefficients of − 0.3815 and − 0.4415, respectively, and R&D input intensity ( RDII ) had the slightest effect on the eco-efficiency of low-carbon tourism, with an impact coefficient of – 0.0836. According to indirect effect test results, RDII has the most significant positive effect with a coefficient of 0.3848, PTI has the second most significant adverse effect on the eco-efficiency of low-carbon tourism with a coefficient of − 0.3245, ECI has the third most significant adverse effect with a coefficient of − 0.2567, EPG has the fourth largest positive effect with a coefficient of 0.2162, and CEI has the slightest adverse effect with an impact coefficient of − 0.2147.

Agricultural eco-efficiency is a meaningful index that assesses agricultural sustainable development. Based on the super SBM-DEA approach incorporating agricultural carbon emissions and panel data regression, this study evaluates agricultural eco-efficiency and investigates the influencing factors in the agricultural production zone of Jilin Province. The empirical results show the following. (1) During the observation period, the average agricultural eco-efficiency exhibits a flat “M-shaped” fluctuating trend, a trend of fluctuant growth with phase characteristics, and the agricultural eco-efficiency of each county still has much room for improvement. (2) Significant spatial differences exist in agricultural eco-efficiency across counties. All of the studied counties, except for Nong’an, Huadian, Lishu, Yitong, Gongzhuling, and Qianguo, need to change their input and output structure to optimize agricultural eco-efficiency. (3) The panel data regression estimation results indicate that the agricultural technology extension level, multiple-crop index, agricultural economic development level, agricultural technology extension level, and urbanization level have close correlations with agricultural eco-efficiency. (4) The research findings have important implications for policy makers formulating agricultural environmental policies in accordance with the local conditions of various counties.

Eco-efficiency is a tool for sustainability analysis that indicates how to carry out economic activities effectively. This paper assesses agricultural eco-efficiency using data envelopment analysis (DEA) and the Theil index approach. Using basic data of 31 provinces in China during 2003–2013, we analyzed the agricultural eco-efficiency development level and spatial pattern in China. The results show that the agricultural eco-efficiency of only four provinces has been relatively efficient in the entire study period, namely, Zhejiang, Hainan, Chongqing, and Tibet. The results also show that agricultural eco-efficiency was higher mainly in south of the Qinling Mountains-Huaihe River Line and north of the Yangtze River area, that agricultural eco-efficiency is mainly affected by pure technical efficiency, and that highly efficient areas are mainly concentrated in the densely populated areas, i.e., the economic developed areas (except Tibet). The Theil index results show that the agricultural eco-efficiency difference weakened between provinces in China, as did western and northeast regions, but eastern and central regions show a slight upward trend.

The integral development of agriculture and tourism heavily depends on natural resources, especially agricultural resources, and it also may contribute to the sustainability of agriculture. The sustainability of agriculture is usually measured by the agricultural eco-efficiency. The main objective of this paper is to demonstrate the impact of the agriculture and tourism integration on agricultural eco-efficiency, so as to reflect the role of the agriculture and tourism integration on promoting agricultural sustainability. Applying panel data of 19 provinces in Yangtze River Basin and Yellow River Basin in China from 2008 to 2019, this paper uses a PSTR model to demonstrate the impact of agriculture and tourism integration on agricultural eco-efficiency and its mechanisms. It is found that in the study area, the integration of agriculture and tourism can contribute to improvements in agricultural eco-efficiency, and when levels of integration are high, the promotional effect is enhanced. However, impacts vary among different regions to some extent. In terms of influencing mechanisms, inputs of agricultural labor, sown crop area, effective irrigation area and other factors decrease with continuous improvements of integration. The input of pesticides, fertilizers and other factors does not decrease in the initial stage of integration but undergoes a rapid decrease after crossing a threshold value. And it demonstrates that the integration of agriculture and tourism is beneficial for improving the agricultural eco-efficiency, so that it will contribute to agricultural sustainability. Meanwhile, this paper offers a new research perspective for discovering effects of agriculture and tourism integration, providing implications for formulating regional policies for the integration.

Decisions on measures reducing environmental damage or improving environmental impact are usually constrained by financial limitations. Eco-efficiency analysis has emerged as a practical decision support tool by integrating environmental and economic performance. Environmental impact, as well as economic revenues and expenses, are usually distributed over a certain time scale. The temporal distribution of economic data is frequently assessed by discounting while discounting of environmental impact is rather uncommon. The scope of this paper is to reveal if this assumed inconsistency is common in eco-efficiency assessment literature, what reasons and interrelations with indicators exist and what solutions are proposed. Therefore, a systematic literature review is conducted and 35 publications are assessed. Theoretical eco-efficiency definitions and applied eco-efficiency indicators, as well as applied environmental and economic assessment methods, are compared here, but it is revealed that none of the empirical literature findings applied or discussed environmental discounting. It was, however, found in methodical literature. It is concluded that the theoretical foundation for the application of discounting on environmental impact is still insufficient and that even the theoretical foundation of economic discounting in studies is often poor. Further research and, eventually, a practical framework for environmental discounting would be beneficial for better-founded, more “eco-efficient” decisions.

To realize maximum benefits and minimize environment pollution, the eco-efficiency of cultivated land utilization (ECLU) is becoming a vital indicator in weighing the rationality of regional land use. Scientific analysis of spatial–temporal pattern variations, as well as factors influencing the ECLU, is of great significance to cultivated land protection, economic development and ecological environment protection in black soil region of Northeast China, and has become a global strategic issue related to the sustainable development. However, assessments of the indicators are still incomplete, the lack of information may inhibit planning guideline for the sustainable development of cultivated land resources. Thus, this study attempts to fill the gaps by incorporating the net carbon sink and non-point source pollution emissions into the measurement framework of ECLU. The super-efficiency slack-based measure (SBM) model with undesirable output and the Malmquist–Luenberger (ML) index were used to measure the ECLU and changes in the total factor productivity (TFP) of cultivated land use in the Songnen Plain from 1989 to 2019. Moran index and LISA clustering were used to reveal spatial correlation of ECLU, and Kernel density estimation, and trend surface analysis maps were drawn to analyze variation tendency of the ECLU. Geographical detector model was employed to further analyze the influencing factors of ECLU. The study results revealed that: (1) The ECLU showed an overall development trend of \"rising first and then declining\", all of which were below the frontier efficiency. (2) The polarization of ECLU is prominent, and the ECLU had a significant heterogeneity and spatial correlation. (3) The TFP showing an increasing trend, technological progress is the main driving force to promote the progress of TFP, while the technological efficiency is the bottleneck for increasing the TFP of the cultivated land use. (4) According to the magnitude of influencing factor, increasing agricultural science and technology investments, lowering carbon emission, and controlling agrochemical investment could significantly enhance the ECLU. These findings have important implications for promoting high-efficient, low-carbon utilization of cultivated land resources and sustainable regional development in black soil region of Northeast China.

Facing the severe situation of environmental problems, coordinating the sustainable development of tourism and the construction of new urbanization is conducive to regional sustainable development. Based on the perspective of uncoupling coordination, this paper evaluates the coordination relationship between the sustainable development of tourism and the development of new urbanization, analyzes their temporal and spatial characteristics, and analyzes the restriction mechanism behind the uncoordinated relationship from the dynamic interaction. The findings are as follows: (1) At present, Shanghai, Jiangsu and Anhui are at a low level of uncoordinated development, while other regions are at an antagonistic uncoordinated development stage. (2) The regional difference of uncoupling coordination degree between tourism eco-efficiency and new urbanization is getting smaller and smaller, and it tends to develop in a balanced way, which accords with the strategic goal of coordinated development. However, the degree of uncoupling coordination changes from relatively weak aggregation to relatively strong aggregation. (3) From the long-term dynamic impact, the eco-efficiency of tourism has a negative impact on the development of new urbanization in Shanghai, Chongqing, Yunnan and a positive impact on Jiangsu and Hubei, with the contribution rates of 26%, 66%, 58%, 24% and 51%, respectively. New urbanization has a positive impact on the eco-efficiency of tourism in Anhui and a negative impact on Guizhou, with the contribution rates of 65% and 57%, respectively. The uncoupling coordination relationship and the interaction between the two systems are closely related.

Eco-efficiency, especially the total-factor eco-efficiency, measured by DEA models considering undesirable outputs, has been a popular instrument to evaluate sustainable development in recent years. However, sustainable development pursues not only high eco-efficiency which ensures that the utilization of natural resource and environment is in a sustainable way, but also good effectiveness which ensures that the development is in the right direction. In this paper, firstly, the efficiency of sustainable urban development is measured, i.e., measuring the eco-efficiency of 35 major cities in China during the period of 2011–2015 based on a super-efficiency SBM–DEA model with undesirable outputs and the Malmquist–Luenberger index is used to explore the dynamic change of eco-efficiency. Secondly, the effectiveness of urban development is measured by overall well-being including urban HDI and life satisfaction. Thirdly, a comprehensive analysis based on efficiency and effectiveness is conducted to evaluate sustainable urban development. The results indicate that: (1) the overall efficiency of 35 major cities in China as a whole is at a low level during the 12th five-year plan period, and the improvement of total-factor ecological productivity is mainly enhanced by technological progress. (2) With regarding to the effectiveness of urban development, Hangzhou, Jinan, Ningbo, Xiamen and Qingdao rank top five, while the cities with a high level of urban HDI like Guangzhou, Changsha and Beijing only rank in the middle due to a relatively low level of life satisfaction. (3) Based on efficiency and effectiveness, most of the cities perform with a low-level efficiency or poor effectiveness, only four cities including Qingdao, Changchun, Ningbo and Tianjin perform with a relatively high efficiency and good effectiveness. Finally, some implications and policy suggestions are proposed based on the above findings.

An important breakthrough in the coordinated development of China’s low-carbon goals and food security strategies is agricultural development oriented toward quality, safety, green, and low carbon. This study integrated command-control and market-incentive environmental regulation (ER), agricultural eco-efficiency (ACEE), and food quality and safety (FQS) into a unified theoretical framework. The unexpected output-oriented Super-SBM model was used to calculate the ACEE of China’s provinces and cities from 2011 to 2020 and test the bidirectional causality between ACEE and FQS through the system generalized moment estimation model. A dynamic panel smooth transition (PSTR) model was used to explore the nonlinear impact mechanisms of different types of ERs on ACEE and FQS. The results showed that there was a long-term, two-way causal relationship between ACEE and FQS. The impact of environmental regulations on ACEE and FQS has a nonlinear relationship. Among them, the role of market-incentivized ER is more significant. Therefore, building an interregional coordinated development mechanism, improving the utilization rate of agricultural resources such as fertilizers and pesticides, and coordinating the positive effects of different types of ERs are the keys to improving the ACEE and ensuring the coordinated development of FQS.

As an important indicator of sustainable development, industrial eco-efficiency (IEE) has aroused growing attention from governments all over the world including China, in recent decades. The Chinese government has introduced numerous environmental regulations; however, the environmental pollution issue does not appear to have been solved. Moreover, although several earlier studies have shown that environmental regulations may promote innovation, there is no consensus on their ultimate effects on IEE. Therefore, this study took a critical look at the connection between environmental regulations and IEE in 36 Chinese sub-sectors from 2009 to 2018. Based on the weak Porter hypothesis (weak PH) and strong Porter hypothesis (strong PH), this paper constructed two panel regression models and conducted group analysis by pollution intensity to check the relationships among environmental regulations, technological innovation, and IEE. It was found that environmental regulations can improve technological innovation and IEE, but these impacts vary across different pollution groups. Specifically, environmental regulations have a U-shaped or inverted U-shaped relationship with technological innovation and IEE. Of the 36 sub-sectors, 26 prove the existence of the Weak PH while 10 verify the Strong PH, indicating that environmental regulations generally advocate technological innovation for most sub-sectors but only promote IEE in a few sub-sectors at present. Finally, differentiated policy implications for environmental regulations and technological innovation are provided for decision-makers.