Factors Of Eco-efficiency Research Articles

Eco-Efficiency Evaluation of Integrated Transportation Hub Using Super-Efficiency EBM Model and Tobit Regressive Analysis – Case Study in China

The transportation industry is a key area for ecological civilisation construction and low-carbon development. As the core support of the national integrated transportation system, the ecological development level of integrated transportation hub (ITH) is crucial for enhancing the sustainable development capacity of the national integrated transportation. An eco-efficiency evaluation index system of ITH is established in this study and the eco-efficiencies of twenty international ITHs in China are comprehensively evaluated based on the super-efficient epsilon-based measure (EBM) model. Then the panel Tobit regression model is adopted to analyse the influencing factors of eco-efficiency. The results show that the average eco-efficiency of ITHs in China during 2011–2021 declines first and then rises, with a relatively high level overall but not efficient yet, and there is an obvious gradient distribution characteristic in all eco-efficiencies. Among them, Guangzhou ranks first, followed by Haikou, and Harbin ranks last. It is found that integrated transportation efficiency, urban green coverage, level of opening-up and economic development improve eco-efficiency significantly, while urbanisation rate, industrial structure and technology input have a negative impact. The results are consistent with the actual situation, verifying the practicality of models, and can be used to promote the sustainable development of integrated transportation.

Comparative Study of Cost and Eco-Efficiency Factors of Aluminum and Conventional Formwork in The AYOMA Apartment Construction Project

The AYOMA Apartment construction project used two types of formwork; both aluminum formwork and conventional formwork are applied on one floor. A comparison of the costs of the two types of formwork used has not been carried out in the project planning. This study aimed to obtain a comparison between aluminum formwork and conventional formwork in terms of cost and eco-efficiency factors. The comparison was made specifically on the formwork of the 3rd Floor of the West Tower, The AYOMA Apartment. The unit price analysis of formwork was based on the coefficient of each work item following the regulation on Unit Price Analysis of Public Works and unit price standards applicable in the project location area. The eco-efficiency factors were calculated from the waste produced by manpower. The calculation results showed that the cost of aluminum formwork for the 3rd Floor of West Tower of The AYOMA Apartment is IDR 2,708,328,757.73 or 2.25 times higher than the conventional formwork cost of IDR 1,204,987,034.60. However, when the reusability factor was considered, aluminum formwork is up to 14.83 times more efficient than conventional formwork. In the eco-efficiency factors analysis, the waste produced by manpower for the work of aluminum formwork is less, only 56.48% of the waste produced by manpower for the work of conventional formwork. The amount of waste produced from the main material and the quality of concrete produced by using aluminum formwork support the conclusion that aluminum formwork is more eco-efficient than conventional formwork.

Моделирование суверенного кредитного риска с учетом экологической эффективности

This study contributes to the evaluation of the role of the eco-efficiency factor in explaining sovereign credit risk. The purpose of the study is to develop a model of sovereign credit risk taking into account the environmental efficiency factor. The sample includes the following countries: Argentina, Belgium, China, China, Egypt, Germany, Greece, Nigeria, Pakistan, Portugal, Spain. 58 % of the world’s countries are categorized as investment grade, indicating that more than half of the countries have high and very high solvency. Using the multiple regression method, the factors affecting the sovereign credit rating are identified: GDP per capita, annual change in inflation, international reserves, private sector credit, total public debt, and environmental performance. The results show a strong positive relationship between credit rating and GDP per capita, private sector lending volume, indicating that countries with better GDP per capita have lower credit risk. To prove the relationship between environmental and credit risk, two multiple regression models were constructed: without and with the environmental factor. The results show that including the environmental factor in modeling a country’s credit rating is appropriate because it improves the quality of the model. According to the two comparison criteria, the model including the environmental factor had better results; the coefficient of determination was larger and the approximation error was smaller. Countries have different environmental situations and different degrees of environmental policy management. There is a relationship between environmental and credit risk of countries, but the environmental situation of a country is not the only determinant factor affecting credit risk. If a country has a high environmental performance index value, it may have an average sovereign rating and vice versa. The scientific usefulness of the study lies in the fact that the constructed model can be used by investors, creditors, rating objects to calculate their own values of sovereign credit ratings.

Spatial-temporal differentiation of urban eco-efficiency and its driving factors: A comparison of five major urban agglomerations in China.

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006-2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations.

Spatial and temporal distribution characteristics and influencing factors of tourism eco-efficiency in the Yellow River Basin based on the geographical and temporal weighted regression model.

With economic progression in China, Yellow River Basin serves as a critical economic belt, which has also been recognized as a cradle of Chinese culture. A watershed is a complex structure of social, economic, and natural factors, and the diversity of its components determines its complexity. Studies on the spatiotemporal distribution characteristics and factors influencing the tourism eco-efficiency at the watershed scale are crucial for the sustainable regional socio-economic development, maintaining a virtuous cycle of various ecosystems, and comprehensively considering the utilization and coordinated development of various elements. Based on tourism eco-efficiency, the coordination degree of regional human-land system and the sustainable development levels can be accurately measured. With the tourism eco-efficiency in the Yellow River Basin from 2009 to 2019, the present study considers 63 cities in the Yellow River Basin as the research area by adopting the super-efficiency slacks-based measure (Super-SBM) model. Methods such as trend surface analysis, spatial autocorrelation analysis, elliptic standard deviation analysis, and hot spot analysis were used to explore their spatiotemporal distribution and evolution characteristics. The geographical and temporal weighted regression (GTWR) model was used to determine the factors influencing the tourism eco-efficiency value. The findings are as follows: ①The level of tourism eco-efficiency in the Yellow River Basin is not high, exhibiting a fluctuating upward trend. ②The tourism eco-efficiency in the Yellow River Basin shows significant spatial interdependence and agglomeration. Furthermore, the track of the center of gravity moves from northeast to southwest. ③ The tourism eco-efficiency in the Yellow River Basin is affected by various factors, with the economic development level having the greatest influence.

Spatial–Temporal Characteristics and Influencing Factors of Eco-Efficiency of Cultivated Land Use in the Yangtze River Delta Region

The sustainable utilization of regional cultivated land systems in the Yangtze River Delta (YRD) region over the past 40 years has been severely impacted by rapid urbanization processes. Improving the eco-efficiency of cultivated land use (ECLU) plays a significant role in achieving the sustainable utilization of farmland and high-quality development of agriculture and rural areas. In this study, the spatial–temporal features and influencing factors of the ECLU in the YRD are investigated by various methods, such as a super-efficient SBM model, hot spot analysis, Dagum Gini coefficient, and panel tobit model. The findings indicate the following: the ECLU showed an overall high level from 2000 to 2020; the ECLU varied significantly over time and space in the YRD. The ECLU presented obvious spatial agglomeration in the YRD: southern regions exhibited a concentration of cold spots, while hot spots were primarily found in the east and north of the YRD. The trend of regional differences in ECLU during the research period fluctuated upwards in the YRD, and the density difference super-variable was the main source of regional differences. Increases in urbanization level and GDP per capita contributed to ECLU enhancement in the YRD, and agricultural intensity levels and agricultural industrial structures played a negative role in ECLU improvement. Finally, we suggest that different regions should adapt to local conditions, scientifically and reasonably allocate cultivated land production resources, and promote the coordinated improvement of ECLU. This study could provide a reference for policymakers to formulate better decisions on cultivated land utilization and management.

Empirical analysis of factors influencing industrial eco-efficiency in the Yellow River Basin from a social embeddedness perspective

Measuring industrial eco-efficiency (IEE) is essential to improve environmental quality and industrial restructuring. However, most studies ignore the influence of embeddedness on industrial eco-efficiency and lack analysis of the pathways of influence factors. Therefore, this study assesses industrial eco-efficiency in the Yellow River Basin (YRB) using a super-efficiency model slacks-based measure (Super-SBM) that considers non-desired outputs, outlines the social embeddedness of IEE, and empirically analyzes the driving mechanism of IEE from the perspective of embeddedness by constructing hierarchical linear modeling (HLM) to address the pathways of action of the influencing factors of industrial eco-efficiency. The results showed that 50.79% of the overall differences in IEE in the YRB were caused by social embeddedness. Economic development level, industrial agglomeration, and environmental regulation (ER) are significant direct influencing factors. Increasing cognitive and cultural embeddedness will enhance the positive relationship between economic development level and IEE. Political and relational embeddedness significantly moderates the positive relationship between industrial agglomeration and eco-efficiency. Cultural embeddedness can significantly and directly affect industrial eco-efficiency and weaken the positive relationship between ERs and industrial eco-efficiency. Therefore, improving IEE should consider both fundamental and embedded factors. Our findings are conducive to promoting high-quality development in the YRB and support the government in formulating differentiated policies. In addition, this paper tries to establish an empirical analysis method suitable for social embeddedness theory, and the empirical results help to improve the situation due to the lack of empirical analysis of social embeddedness theory.

Evaluation of China’s provincial eco-efficiency with the explainable boosting machine (EBM) model and Tobit regression

The explainable boosting machine (EBM) model measures China’s provincial eco-efficiency, and the Tobit regression model reveals internal driving factors to provide consultation for promoting China’s green development based on the panel data of 30 provinces from 2000 to 2018. The findings of this article are as follows: provincial-level regional ecological efficiency is low, growth is slow, regional differentiation is significant, and development still has a trend of incoordination and multi-polarization. From the perspective of global autocorrelation, the Moran index is significantly positive, and the province eco-efficiency of the first grade presents a positive spatial correlation and has the characteristics of spatial agglomeration. The regression analysis results show that the economic level, the FDI, the level of technological innovation, and the level of human capital are the main influencing factors of eco-efficiency, and there are spatial differences. Relevant suggestions are based on the status and influencing factors of the unbalanced development heterogeneity of provincial eco-efficiency in China.

Re-measurement and influencing factors of agricultural eco-efficiency under the ‘dual carbon’ target in China

Given that agriculture is both a carbon source and sink, the sustainability goals of carbon peaking and neutrality place high demands on the green and low-carbon agricultural development in China, and the exploration of a realistic path for a sustainable agricultural development is urgently needed. Under the above ‘dual carbon’ target, this study focused on the key issue of how to improve China's agricultural eco-efficiency (AEE) and constructed an innovative AEE indicator system that can reflect carbon constraint and coordinated agricultural economic development, resource use and ecological environment. The super-efficient slack-based measured Data Envelopment Analysis (SBM-DEA) method, which considers undesirable outputs, was applied to re-measure the AEE of 30 provinces and cities in China from 2001 to 2020, and its spatial and temporal evolution was analysed in conjunction with kernel density estimation. The Tobit regression model was used to explore various influencing factors by region. The results show that the AEE re-measurements, which take into account the 'dual carbon' requirement, are significantly better than the traditional AEE. From 2001 to 2020, China had an overall V-shaped fluctuation curve AEE, with a small decline and several inter-annual fluctuations, and exhibited a large potential to rise. China's AEE showed a spatially uneven regional development at different stages of distribution and evident multi-polar differentiation. Inter-provincial differences were observed in China's AEE, and the vicious circle of low-level green and low-carbon agricultural development was difficult to break. Urbanisation had a significant positive effect on national and eastern AEE but a significant negative effect on central AEE. The agricultural carbon offset rate had a significant effect on AEE nationally and in the three regions. Thus, the introduction of ‘dual carbon’ target effectively drove the development of AEE. Agricultural industry structure inhibited the improvement of AEE nationally and in the western region. Agricultural economic development hindered the national AEE improvement but promoted that of the central region, where China showed an environment Kuznets curve. Hopefully, this study can provide data support and theoretical reference for the green and low-carbon agricultural development and help achieve the ‘dual carbon’ target.

Spatial-temporal differentiation characteristics and driving factors of China's energy eco-efficiency based on geographical detector model

As China is striving to build a modernization in which people and nature live in harmony, evaluating energy eco-efficiency (EEE) is an important part of achieving a balanced development of socio-economic construction and ecological civilization. From the perspective of the “energy-economy-ecology-society” system, this study included social welfare elements and PM2.5 into the EEE evaluation index, and the EEE of 30 provinces in China from 2000 to 2019 were examined more comprehensively. The distribution differences and sources of EEE were measured by Trend analysis and the Dagum Gini coefficient. A unique analytical method that reveals the drivers of spatial heterogeneity, the Geographical Detector model (Geodetector), was used to better account for the explanatory power of the drivers and their interactions. The results show that China's EEE has a weak “N"-shaped trend in time series, with significant spatial heterogeneity, and the contribution of this imbalance is ranked as inter-regional (39.83%) > hypervariable density (31.95%) > inter-regional (28.22%). The core factors that dominate the spatial-temporal differentiation in the East, Center and West are energy consumption structure (0.688), environmental regulation (0.414), and the level of urbanization (0.548), respectively. The factor interactions are all greater than the explanatory power of factor independent effects on EEE divergence, and the strongest interaction is between Environmental Regulation and Level of educational development in 2010(0.91). The interactions have regional characteristics, and targeted EEE enhancement paths should be selected for different regions.

Spatial–Temporal Evolution and Influential Factors of Eco-Efficiency in Chinese Urban Agglomerations

Against the background of a high-quality development philosophy, the realization of the coordinated development of the economy, environment, and resources is particularly important. This study adopts the super-efficiency slacks-based measure (SBM) model to evaluate the eco-efficiency of 208 cities in 19 urban agglomerations in China from 2006 to 2020, and the kernel density estimation and spatial econometric specifications are combined to reveal the spatial–temporal evolution. Finally, Tobit regression is used to analyze the driving factors of the eco-efficiency of urban agglomerations in China. The main results can be summarized as follows: (1) The eco-efficiency of Chinese urban agglomerations is generally low, and the differences in eco-efficiency between urban agglomerations are obvious, with different trends of change. (2) In terms of the time series, the sample period shows a “steadily rising” trend followed by a “fluctuating downward” trend. From the results of the kernel density estimation, the internal difference in the overall eco-efficiency of urban agglomerations shows the trend of a small decline followed by a gradual increase. (3) From the spatial point of view, the eco-efficiency of urban agglomerations decreased from the coast to the inland areas, and there was a “cluster effect”. The overall eco-efficiency of urban agglomerations shows a trend of spatial aggregation. (4) From the perspective of influencing factors, fiscal expenditure, opening-up level, and population density have a significant negative correlation with the eco-efficiency of urban agglomerations, while science and technology investment, industrial structure, and urbanization level have a significant positive correlation with the eco-efficiency of urban agglomerations. The research in this paper provides guidance for the coordinated development of urban agglomerations and the formulation of environmental policies.

Spatial Association Network and Driving Factors of Agricultural Eco-Efficiency in the Hanjiang River Basin, China

Reducing agricultural emissions and promoting carbon sequestration are vital for China to achieve its dual carbon goals. Achieving the green transformation of agricultural watersheds requires a thorough understanding of the internal transmission relationships within the watersheds and the underlying spatial correlation structures. This paper used the SBM-3E model to calculate the agricultural ecological efficiency of 17 prefecture-level cities in the Hanjiang River Basin (HRB) from 2010 to 2020, taking agricultural carbon emissions and a comprehensive non-point source pollution index as the unexpected output. The Gravity model and social network analysis methods were used to analyze the evolution characteristics of the network structure of agricultural ecological efficiency, and the secondary assignment procedure method was used to identify the driving factors from the planting structure, water use structure, and resource endowment. First, from 2010 to 2020, the overall agricultural ecological efficiency in the HRB demonstrates a declining trend, with efficiency values of 12.15, 9.40, and 6.67 in the upper, middle, and lower reaches, respectively. Second, the spatial correlation network density of agricultural ecological efficiency in the HRB is 0.17, with a network efficiency of 0.89. The correlation among units within the basin is relatively low, but stability is high. Moreover, the individual network spillover absorption capacity exhibits heterogeneity, and the status of each subject within the watershed follows a “core-edge” structure. Third, total water consumption and corn cultivation have a positive impact on the agricultural ecological efficiency network in the HRB, whereas agricultural water use and rice cultivation negatively influence the network. We propose policy recommendations to facilitate the advancement of green development in China’s agricultural watersheds and the achievement of the dual carbon goals.

Regional Differences in Tourism Eco-Efficiency in the Beijing–Tianjin–Hebei Region: Based on Data from 13 Cities

In order to balance the economic development and ecological impact of tourism, it is essential to study tourism eco-efficiency in the context of sustainable development. This study analyzed regional tourism eco-efficiency based on the panel data of the 13 cities of the Beijing–Tianjin–Hebei region using the super-SBM DEA model. Then, we analyzed the driving factors, compared regional differences, and investigated influencing factors of tourism eco-efficiency by applying the global Malmquist–Luenberger (GML) index, Theil index, and geographically and temporally weighted regression (GTWR) models. The results demonstrate the following: (1) The overall tourism eco-efficiency in the Beijing–Tianjin–Hebei region between 2010 and 2019 was low, but it had an increasing trend. (2) The advancement of technological progress factors was mostly responsible for the increase in tourist eco-efficiency. (3) The results for tourism eco-efficiency were significantly polarizing, but the gap among the 13 cities is gradually narrowing. Regional differences are the main contributors to differences in tourism eco-efficiency. (4) Per capita GDP, the proportion of tertiary industry in GDP, the number of patents granted, and the proportion of urban population in the total population were the main factors affecting tourism eco-efficiency. This study could serve as a model for similar countries and regions seeking to enhance tourism eco-efficiency and achieve the Sustainable Development Goals.

Maximize Eco-Economic Benefits with Minimum Land Resources Input: Evaluation and Evolution of Land Use Eco-Efficiency of Agglomerations in Middle Reaches of Yangtze River, China.

Increasing land-use eco-efficiency can alleviate human-land conflict in urban areas as well as improve regional urbanization quality to achieve sustainable development. As the central urban agglomeration in China, the Middle Reaches of Yangtze River (MRYR) has experienced rapid urbanization and huge land-use change during 2000 to 2020, which poses great threats to its ecological environment. This study adopted the Super-Slack-Based Data Envelopment Analysis (Super SBM-DEA) model to evaluate the eco-efficiency of land use in MRYR. The result shows that the average eco-efficiency value of land use is above 0.77 for each year, indicating that the general efficiency is at a middle level. The trend of the evolution of the eco-efficiency can be summarized as a "U-shape" style curve. The variance between the four urban agglomerations of the MRYR changed over time. Not all capital cities or cities with higher GDP per capita obtain higher eco-efficiency in this study. Policy intervention, population and land use, technique, and environmental pollution are influencing factors of land-use eco-efficiency. Based on slacks analysis, this study proposed the optimization of the land-use structure to improve eco-efficiency from four aspects of land-use structure, investment and labor, ecosystem services value (ESV) and environment pollution, and industry structure.

Spatial differentiation and influencing factors of land eco-efficiency based on low carbon perspective: A case of 287 prefecture-level cities in China

The spatio-temporal evolution and influencing mechanism of land ecological efficiency (abbrev. eco-efficiency) are key to achieving optimal land eco-efficiency and ensuring high-quality economic growth. Therefore, based on 287 cities at prefecture-level and above in China, we constructed an efficiency measurement index system by using resource-capital-labor as the input index, economic-resource-social-ecological benefits as the desirable output and carbon emissions as the undesirable output. Besides, Jenks method, Exploratory Spatial Data Analysis (abbrev. ESDA), Trend Analysis and Standard Deviation Elliptic (abbrev. SDE) model were conducted to delve into the spatio-temporal pattern and influencing factors of land eco-efficiency from 2005 to 2019. The results are as follows: (1) under carbon emission constraints, the average values of land eco-efficiency index were showing a rising trend at first and a falling trend thereafter. Spatially, the difference went from large to small in the western, eastern, northeast and central China. (2) The high-efficiency areas were concentrated around Chongqing and gradually extended. The general-efficiency areas were mainly distributed in the Pearl River Delta and urban agglomerations around the middle reaches of the Yangtze River. The low-efficiency areas were widely distributed in the central China. In the trend analysis, the spatial gradient pattern gradually evolved from “flat” to “high in the west, low in the east” in the east-west direction, and from “flat” to a gentle “U-shape” pattern in the north-south direction. (3) The spatial autocorrelation changed from negative to positive and the spatial agglomeration gradually changed to a positive correlation. The main significant correlation types were between High-High (abbrev. HH) areas and Low-Low (abbrev. LL) areas. (4) The standard deviation ellipse of land eco-efficiency always showed the trend of “northeast-southwest”, and the center of gravity moved significantly along Xiangyang-Nanyang-Luohe-Nanyang. In the future, it will continue to integrate the analysis of the relationship between factor input-output, carbon emissions and ecol-efficiency from different perspectives, with a view to providing support for achieving high-quality regional development.

Study on the Measurement of Agricultural Eco-Efficiency and the Influencing Factors in the Yellow River Basin

Based on the background of getting the “Double Carbon” target and the high-quality advancement of the Yellow River basin, the agricultural carbon emissions and agricultural eco-efficiency of the nine provinces in the Yellow River basin from 2011 to 2021 were quantified using a carbon emissions computation model and an Super-SBM Model. ArcGIS was utilized to clarify the spatiotemporal evolution features of both variables, and a panel Tobit model was utilized to conduct empirical assessment of the contributing factors of agricultural eco-efficiency. The results demonstrated that since 2016, the carbon emissions of the Yellow River basin have shown the “high output-low emissions” of characteristics. The agricultural eco-efficiency is overall at a medium to high level and has constantly improved environmentally, but there are significant inter-provincial differences. Empirical examination analysis indicated that the economic development level of the Yellow River basin is positively U-shaped with regard to agricultural eco-efficiency, and rural per capita disposable income, machine tool density, industrialization level, and the regard of field planting of food crops have a substantial effect on agricultural ecological efficiency. Among them, machine tool density shows a negative effect, while other factors show a positive effect. Based on this, a proposal is designed to improve the structure of agricultural input determinants] by pooling determinant endowments, promote the reasonable assignment of agricultural factor resources among provinces, and enhance agricultural ecological efficiency to support the high-quality promote of the Yellow River basin.

Coupling coordination degree analysis and driving factors of innovation network and eco-efficiency in China

Green and high-quality development has become an important development path for the global response to climate change. Eco-efficiency and innovation, as important indicator and core driver of green and high-quality development respectively, have attracted wide attention. However, the research on the relationship between innovation and eco-efficiency is mostly qualitative research, and the index selection of technological innovation and eco-efficiency is single. Therefore, this paper from the perspective of quantitative research based on the industrial enterprise data of 30 provinces from 2006 to 2019 to explore the mechanism between innovation network and eco-efficiency by constructing a three-stage evaluation model. The first step is to build the network SBM model to measure the innovation network efficiency, and decomposing it to explore the internal development and change rules of the innovation. And the SBM with undesirable output model is employed to evaluate the eco-efficiency and analyze the regional heterogeneity. Second, the coupling coordination model is constructed to quantitatively study the coupling coordination degree between innovation network efficiency and eco-efficiency. Finally, the influencing factors of coupling coordinated degree are discussed. The result shows that the innovation network comprehensive efficiency is lower than that of scientific and technological innovation efficiency and transformation of scientific and technological achievement efficiency, and the eco-efficiency of eastern China develops stably and is higher than that of the other three economic zones. Scientific technological innovation and the eco-efficiency of coupling coordination degree is higher than the transformation technological achievement and eco-efficiency of coupling coordination degree. Information and communication technology plays an important role in promoting innovation network comprehensive efficiency and eco-efficiency at different systems.

The spatial pattern and influencing factors of tourism eco-efficiency in Inner Mongolia, China.

Tourism eco-efficiency is a performance basis for evaluating green total factor productivity and sustainable development. The objective of this study was to measure tourism eco-efficiency in Inner Mongolia and explore its influencing factors. The aim was to provide an accurate reference for improving the quality and efficiency of tourism in Inner Mongolia and promoting the sustainable development of the regional economy and society. Tourism eco-efficiency in Inner Mongolia from 2009 to 2019 was calculated using a super-slacks-based measure (SBM) model with an undesirable output. The spatial variation function was used to explore the spatial evolution pattern of tourism eco-efficiency in Inner Mongolia, and the influencing factors of the spatial evolution were analyzed by geographically weighted regression. Tourism eco-efficiency in Inner Mongolia is relatively low. Eco-efficiency values among cities in Inner Mongolia vary, and their distribution is not balanced. The structural eco-efficiency of tourism in Inner Mongolia has been consistent from 2009 to 2019. The degree of homogenization in the overall direction is relatively good. Furthermore, its spatial distribution form and internal structure evolution show a certain regularity and continuity. The pattern evolution of tourism eco-efficiency in Inner Mongolia is jointly driven by the economic level, environmental regulation, industrial structure, traffic conditions, resource endowment, and tourism reception facilities. These influencing factors show obvious spatial heterogeneity. From the perspective of Inner Mongolia, the difference in the tourism eco-efficiency value from 2009 to 2019 was relatively large, but the number of effective areas in the efficiency frontier generally showed a fluctuating growth trend. The range parameters of tourism eco-efficiency showed a decreasing trend, and the spatial correlation effect of tourism eco-efficiency in Inner Mongolia showed a decreasing trend under the influence of structural and spatial differentiation.

Spatial Correlation and Influencing Factors of Tourism Eco-Efficiency in the Urban Agglomeration of the Yangtze River Delta Based on Social Network Analysis

Tourism eco-efficiency analysis is an effective tool to solve the problem of sustainable tourism development. The tourism eco-efficiency evaluation index system was constructed in the study, and the undesirable output super-slacks-based measure model was used to estimate the tourism eco-efficiency of 26 cities in the Yangtze River Delta. Then, the modified gravity model based on the values of the tourism eco-efficiency analysis of each city was used to construct a spatial correlation network. The structural characteristics of the spatial association networks of tourism eco-efficiency, the interrelationships among different cities, and the roles played by different blocks were explored using a social network analysis. The quadratic assignment procedure (QAP) was applied to analyze the influencing factors that affect the formation of the spatial association network of tourism eco-efficiency. The results show that tourism eco-efficiency has an overall increasing trend, and the gap among cities is decreasing. The structure of the spatial correlation network of tourism eco-efficiency has good connectivity, accessibility, and robustness with the correlations among all of the cities in the network. The spillover effects among the blocks are significant, showing spatial polarization, with the cities such as Shanghai, Suzhou, and Hangzhou occupying the core position of the network. The QAP analysis shows that the spatial correlation network of tourism eco-efficiency is affected by the distance between the cities and the levels of development of the economy and information dissemination. The results of this study innovatively reveal the structural characteristics and influencing factors of the spatial correlation network of tourism eco-efficiency. It could provide valuable insights for the development of corresponding policy measures by government sectors and tourism firms to enhance the sustainability of regional tourism development.

Effective and Sustainable Managed Protected Areas: Evaluation and Driving Factors of Eco-Efficiency of China’s Forest Parks

Forest parks are key protected areas that protect biodiversity and important ecosystems with a high efficiency and low cost and have become an international research area of high interest. Eco-efficiency is an important tool to measure the sustainable development of natural protected areas and provides a valuable decision reference for policy-makers. This research constructs a comprehensive performance evaluation system for forest park ecosystems, economic systems, and environmental systems. The undesired output model (SBM), spatial analysis, and panel Tobit regression model are applied to measure and analyze the forest park eco-efficiency in 30 provinces and autonomous regions of the Chinese mainland from 1990 to 2019, as well as the temporal and spatial differentiation characteristics and their driving factors. The results show that (1) both the average level of eco-efficiency and economic efficiency of forest parks show a declining trend; (2) the eco-efficiency of forest parks shows high-efficiency zones in the northeast and northwest, medium-efficiency zones in the west, and low-efficiency zones in the middle region of the Chinese mainland; (3) forest parks in the eastern region with a higher-than-average efficiency are located in Tianjin and Zhejiang Province, while the western region with lower efficiency is located in Xinjiang, Inner Mongolia, Qinghai, and Gansu Province; and (4) the forest park tourism service quality has an important impact on forest parks’ eco-efficiency, but the entertainment activity has a significant negative impact on the eco-efficiency of forest parks. Finally, suggestions are proposed for the sustainable and green development of forest park ecological tourism.