Super-SBM Model Research Articles

An improved approach for measuring the efficiency of low carbon city practice in China

To meet the dual carbon goal, Chinese cities have invested a lot of human, material and financial resources in practicing low carbon city (LCC) and have made great progress. However, it seems that the efficiency of LCC performance remains unexplored. This study aims to propose an improved method for measuring LCC performance from an efficiency perspective (LCCE method). In developing this method, LCC practice is considered as a system, and the input factors of LCCE consist of labor force, capital stock, and energy consumption. Economic growth and carbon emissions are overall output factors, and four dimensional output factors, such as optimizing industrial structure are identified. Subsequently, the super-SBM model of LCCE is built up by integrating multiple inputs and outputs. A demonstration of the proposed LCCE method was conducted using data of 256 prefecture-level cities in China from 2006 to 2019. The research findings reveal that: (1) LCCE of cities in the western region performed slightly better than the other three regions; (2) LCCE of Chinese cities shows a U-shaped relationship with city size. This study proposes an improved approach for measuring LCCE and provides an essential reference for central and local governments in China to better formulate low-carbon strategies.

The impact of high-tech industrial agglomeration on China’s green innovation efficiency: A spatial econometric analysis

Eco-efficiency is an important factor in assessing the quality of development, and high-tech industries are crucial for countries to forge green innovation paths. However, few studies have examined whether and how high-tech industrial agglomeration affects green innovation efficiency. To fill this gap, we measure the degree of high-tech industrial agglomeration and the level of specialized and diversified agglomeration using the location entropy index and agglomeration factor, and calculate green innovation efficiency using the super-SBM model with undesirable outputs. Based on Chinese provincial panel data from 2006 to 2020, a dynamic spatial Durbin model was constructed to explore the impact of high-tech industrial agglomeration and different agglomeration patterns on green innovation efficiency. Our study found that high-tech industrial agglomeration is a significant contributor to green innovation efficiency. There is an inverted U-shaped relationship between specialized agglomeration and green innovation efficiency, and diversified agglomeration contributes to green innovation efficiency. Given the regionally uneven nature of China’s economic development, there is some variation in the impact effects within different economic regions. We demonstrated the leading role of scientific high-tech industrial agglomeration patterns and appropriate levels of agglomeration in green innovation, providing theoretical guidance for the formulation of China’s high-quality development policies.

How Does the Competitiveness Index Promote Foreign Direct Investment at the Provincial Level in Vietnam? An Integrated Grey Delphi–DEA Model Approach

Foreign direct investment (FDI) is an important factor in building a strong economy for a country, particularly in developing and emerging markets. Both domestic enterprises and policy makers have been motivated to attract FDI for the benefits of FDI, such as technological transfers, spillover benefits, and rising competition. There is a need for a functional model to assess how the competitive index affects FDI attractiveness. Therefore, in this study, the authors use an integrated model of Grey Delphi, the Data Envelopment Analysis Super Slack-Based Measure Model (DEA–Super SBM), and the Malmquist Model (DEA–Malmquist) to evaluate the FDI attractiveness of Vietnamese provinces from 2017 to 2021. Firstly, ten critical dimensions of the provincial competitive index (PCI) affecting the number of FDI by cases and amount of FDI capital were validated via the Grey Delphi method. Secondly, the Super-SBM model is applied to assess the FDI efficiency of 63 provinces in Vietnam from 2017 to 2021. Then, the DEA–Malmquist model is employed to analyze the total change in the productivity of 63 provinces’ FDI performance in Vietnam. The findings of this study revealed that the efficiency of FDI in Vietnam’s provinces is relatively low, and there is a significant variation in the attractiveness of FDI among the provinces. This study can provide valuable insights for policy makers and other stakeholders in developing effective strategies to attract FDI and foster economic development.

The impact of green credit on firms' green investment efficiency: Evidence from China

We investigated the impact of green credit on the green investment efficiency of 588 listed Chinese green companies from 2009 to 2019 using an extended super-SBM model. Our findings reveal that green credit can enhance a firm's green investment efficiency, with a more prominent effect observed among state-owned enterprises and firms operating in high-growth industries. Further analysis suggests that the positive impact of green credit on green investment efficiency is moderated by corporate governance, innovations, and financial constraints. Our study provides novel evidence that underscores the importance of green credit in stimulating corporate green investment efficiency in China.

Can technological finance cooperation pilot policy improve energy efficiency? Evidence from a quasi-experiment in China.

Whether the technological finance cooperation pilot (TFCP) policy in China can promote energy efficiency remains under investigated. Using the dataset covering 284 cities in China from 2003 to 2019, this paper adopts the Super-SBM model with undesirable outputs to measure energy efficiency. Based on this efficiency, the Difference-in-Differences model (DID) and Spatial Durbin model (SDM) are employed to discuss the impact of TFCP policy on energy efficiency. Results demonstrate that TFCP policy has significantly promoted energy efficiency. And the conclusion is still valid after the robustness checks and endogenous treatment has been carried out. The impact of the TFCP policy on energy efficiency is heterogeneous, depending on the geographical, administrative, and resource characteristics of cities. To be specific, the promotion effect tends to be pronounced in east-central cities, high-ranking cities, and high-tech cities. Moreover, TFCP policy could significantly improve energy efficiency through the effects of technological innovation, industrial upgrading, and financial development. A further policy spillover analysis shows that TFCP policy has exerted a remarkable incentive influence on energy efficiency locally, while the neighboring cities are inhibitive. To sum up, this research is of important theoretical value and policy-making reference on green economy transformation for cities with differential features and energy utilization capacity, by shedding light on the impacts of such a technological finance cooperation system on energy efficiency.

The impact of urban sprawl on green total factor productivity: A spatial econometric analysis in China

The rapid expansion of Chinese cities has led to serious urban productivity and eco-environment changes, and has therefore attracted considerable international academic attention. The main objective of this study is to investigate the theoretical mechanisms and practical effects of urban sprawl on green total factor productivity (GTFP), in order to provide a reference for optimizing the spatial layout of cities and promoting high-quality economic development. Realistic urban land area and population characteristics are extracted using DMSP/OLS and NPP/VIIRS nighttime lighting data, and LandScan global population dynamics statistics to measure the urban sprawl index. GTFP is measured using a super-SBM model that considers undesirable output. Based on the panel data of Chinese cities from 2006 to 2020, a spatial Durbin model was constructed to carry out the empirical analysis. The results show that, overall, urban sprawl in China is detrimental to its own GTFP, while contributing to the GTFP of neighboring cities. The impacts of urban sprawl vary markedly across cities of different sizes and across regions.

Unearthing marine ecological efficiency and technology gap of China’s coastal regions: A global meta-frontier super SBM approach

With the promotion of the maritime power strategy and progressively increasing and severe environmental problems, marine ecological efficiency is fast becoming an essential object of research in achieving sustainable development. By applying the meta-frontier super SBM model and the global Malmquist-Luenberger index, this paper aims to explore the marine ecological efficiency of coastal regions in China and the technology gaps between different regions during 2006–2017. On this basis, the changes in marine ecological efficiency were decomposed to investigate the driving factors. The results indicate that the marine ecological efficiency of China’s coastal regions was still ineffective, and there was a significant gap between the group production technology and the potential optimal production technology. Also, there was a significant regional technological heterogeneity. The Yangtze River Delta region had optimal production technology level, while the Beibu Gulf region distinctly had a sizeable technological gap with the other three regions. Besides, the primary factor affecting marine ecological efficiency was technological progress. Finally, the results of this paper passed the robustness check. Based on these conclusions, some specific policy suggestions are provided for China’s coastal regions.

CO2 emission reduction pathways of iron and steel industry in Shandong based on CO2 emission equity and efficiency

In the context of the “dual carbon” goal, the governance of CO2 emissions should comprehensively consider efficiency and equity. Shandong is a major province of the iron and steel industry, and the transformation of its high-CO2 emission development model is urgent. Based on the CO2 emission data of the iron and steel industry in 14 prefecture-level cities in Shandong from 2011 to 2020, this paper adopted the Super-SBM model and constructed a CO2 emission equity indicator to measure the CO2 emission efficiency and equity respectively. According to the “equity-efficiency” combination, the 14 cities were divided into four types of regions, and different corresponding CO2 emission reduction pathways were designed. The results demonstrated that: (1) The CO2 emission equity exhibited an upward trend, mainly due to the expansion of the iron and steel industry and the increase of employees. The CO2 emission efficiency fluctuated slightly and was ineffective due to the ineffective scale effect. (2) From the perspective of CO2 emission trading, the iron and steel industry in most cities was expected to purchase CO2 emission allowances, while that in Linyi and Rizhao was expected to sell them. (3) The CO2 emissions as a whole had the characteristics of “high equity and low efficiency”.

Does green finance improve carbon emission efficiency? Experimental evidence from China.

As a noteworthy initiative of financial supply-side reform to precisely support the green development system, can green finance (GF) help achieve the dual goals of "carbon peaking" and "carbon neutrality"? Using data from China's provincial panel between 2007 and 2019, this paper measured the green finance index by the entropy method and the carbon emission efficiency (CEE) with carbon emission as the non-desired output by the Super-SBM model. Then, the influence of GF on CEE was empirically investigated by the dynamic panel model and the spatial Durbin model. The findings show that GF can significantly improve CEE and has a positive spillover impact on CEE in provinces with close economic ties; the upgrading of the industrial structure is a key mediator in the transmission of GF to CEE; and regional heterogeneity analysis finds that GF notably improves CEE in eastern, high development levels of economic and GF regions. The research can offer some theoretical and empirical references for green finance to contribute to low-carbon economic growth.

Indices Development for Player’s Performance Evaluation through the Super-SBM Approach in Each Department for All Three Formats of Cricket

Player performance evaluations in all three formats of cricket have been a topic of great concern for sports analysts and research experts. This study proposed a comprehensive performance estimation tool that incorporates all the essential inputs–outputs and evaluates a cricketer’s overall performance. This research introduced three different estimation indices for player efficiency in all three formats of cricket for batting, bowling, and fielding. Further, this research employed the DEA Super-SBM model to evaluate the player’s efficiency in batting, bowling, and fielding departments of all three formats. The study estimates the most efficient batsman, bowler, and fielder in cricketing history by using the data of international cricketers (1877–2019). The results indicate that, compared to the traditional parameters, the proposed study indices are more accurate and comprehensive in nature. The most efficient batsman, bowler, and fielder in all three formats are given, respectively: (i) Sir Bradman, Sachin Tendulkar, and Virat Kohli; (ii) Muralitharan, Mitchell Starc, and Umar Gul; and (iii) Saleem Yousuf, Luke Ronchi, and Scott Edwards. For teams, England, Australia, and India were determined to be the most efficient in batting for all three formats; the West Indies, Australia, and Pakistan are the most efficient in bowling; and the Australian (Test & ODIs) and South African teams are efficient in the fielding department.

Does Environmental Regulation Promote the Infrastructure Investment Efficiency? Analysis Based on the Spatial Effects.

Infrastructure investment plays a key role in steady economic growth. Investment in infrastructure is gradually increasing; however, large-scale infrastructure investment is also associated with efficiency problems and environmental problems, which need to be carefully examined. The entropy weight method and the Super-SBM model are implemented to measure environmental regulation and infrastructure investment efficiency, respectively; and the spatial Durbin model is applied to analyze the influence mechanism and spatial effects of environmental regulation on infrastructure investment efficiency. The results show that spatial agglomeration characteristics exist in both environmental regulation and infrastructure investment efficiency. Besides, environmental regulation can promote infrastructure investment efficiency in general, but it develops an inverted U-shaped relationship as the intensity increases. Lastly, the spillover effects of environmental regulation on infrastructure investment efficiency present a U-shaped relationship. The conclusion is that both environmental regulation and infrastructure investment efficiency in China increased from 2008 to 2020. Besides, moderate environmental regulation is beneficial to infrastructure investment efficiency and restrains spatial spillover, but strict environmental regulation appears to be the opposite. This research expands the literature on environmental regulation and production efficiency and provides a reference basis for formulating effective policies to improve infrastructure investment efficiency from the perspective of the ecological environment.

A Effectiveness-and Efficiency-Based Improved Approach for Measuring Ecological Well-Being Performance in China.

Finding solutions to the challenges posed by China's urbanization is an urgent, pressing global concern. An effective approach for evaluating the ecological well-being performance (EWP) is a guideline for improvement. Most previous studies have focused on the evaluation of EWP efficiency without considering the effectiveness of the EWP, which may mislead the practice of improving the EWP. This paper proposed a bi-dimensional effectiveness and efficiency perspective evaluation of the EWP for pursuing sustainable development goals. The Ecological Consumption Index and the Human Development Index are selected to evaluate indicators for the EWP. The entropy method, line-weighted method, and four-quadrant evaluation framework are used to disclose EWP effectiveness. A Super SBM model and the DEA moving split-windows analysis method are applied to calculate the EWP efficiency. Data from 30 provinces in China for the period of 1997 to 2019 have been collected for empirical study to demonstrate the effectiveness of the proposed method. The main findings of the case study are: (1) The ECI and HDI increased during the study period, while the annual average value of the EWP efficiency among 30 provinces in China has decreased with fluctuation; (2) provinces in southern China and Chongqing have a low level of ECI and demonstrate good performance in the HDI; and (3) most developed regions, such as Beijing, Shanghai, and Guangdong, have not presented the best EWPs. The results of this study can provide a basis for understanding the EWP in China so as to formulate targeted sustainable-development strategies.

How Does Agricultural Mechanization Service Affect Agricultural Green Transformation in China?

Agricultural mechanization service (AMS) is a critical path to achieving agricultural green transformation with smallholders as the mainstay of agricultural production. Based on the panel data of 30 Chinese provinces from 2011 to 2020, this paper measures the AGTFP using the Super-SBM model and examines the effects of different AMS supply agents on AGTFP and spatial spillover effects through the spatial Durbin model. The main conclusions are as follows: First, China's AGTFP showed a stable growth trend, with the mean value increasing from 0.1990 in 2011 to 0.5590 in 2020. Second, the specialization (SPO) and large-scale (LSO) of AMS supply organizations have significantly positive effect on the AGTFP of the local province. However, SPO has a significantly positive effect on the AGTFP of the neighboring provinces, while LSO has the opposite effect. Third, the specialization of AMS supply individuals (SPI) has significantly negative effect on the AGTFP of the local province. In contrast, the large-scale AMS supply individuals (LSI) has the opposite effect. Furthermore, the spatial spillover effects of both are insignificant. Fourth, the spatial spillover effect of AGTFP shows asymmetry among different regions and indicates that AMS resources flow from non-main grain production and economically developed regions to main grain production and less developed regions. These findings provide helpful policy references for constructing and improving the agricultural mechanization service system and realizing the agricultural green transformation in economies as the mainstay of agricultural production.

Does fiscal decentralization support green economy development? Evidence from China.

China, as the world's largest energy consumer, has made the green economy a central component of its economic development strategy. However, how to effectively play the government's crucial role in promoting the development of the green economy has become the focus of research by a significant number of economic experts. This paper uses the Super-SBM model to measure the green economy development index by introducing carbon dioxide emissions and industrial "three wastes" emissions and analyzes the relationship between fiscal decentralization, green technology innovation, and the green economy from the vantage point of local government behavior. It is discovered that fiscal decentralization significantly inhibits the development of the green economy, and local green technology innovation activities in the last period will amplify this negative impact. The above findings pass the robustness test. After introducing comparative analysis of economic growth indicators that are measured by the stochastic frontier analysis (SFA), the results show that only in the eastern region does fiscal decentralization both drive economic growth and do not inhibit green economy development by local government officials' political promotion motives and self-interested preferred expenditures, but overall economic promotion and green economy inhibition caused by fiscal decentralization exist simultaneously in the Yangtze River Economic Belt region, and significant heterogeneity differences exist in the rest of the regions. The findings suggest that regulating local government fiscal behavior and improving fiscal transparency are very important to promote the development of China's green economy.

Study on the Temporal and Spatial Evolution of China’s Carbon Dioxide Emissions and Its Emission Reduction Path

Based on the total carbon emission data of 30 provinces and cities in China from 2000 to 2020, this paper used non-parametric kernel density estimation and traditional and spatial Markov probability transfer matrix methods to explore the temporal and spatial dynamic evolution characteristics of carbon dioxide emissions in China and then used a super-SBM model to calculate the carbon emission reduction potential of each province. The results showed that: (1) from 2000 to 2020, the total carbon emissions in China showed an upward trend of fluctuation, from 1.35 Gt to 4.90 Gt year by year, with an annual growth rate of 13.10%. (2) The core density curve showed a double peak form of “main peak + right peak,” indicating that a polarization phenomenon occurred in the region. (3) The overall trend of carbon dioxide emissions shifting to superheavy carbon emissions was significant, and the probability of transition was as high as 74.69%, indicating that it was challenging to achieve leapfrog transition in the short term. (4) Based on the principle of fairness and efficiency of provincial carbon emission reduction, mainland China’s 30 provincial administrative regions can be divided into four types. Finally, the carbon emission reduction path is designed for each province.

Research on the efficiency of green development of industry in Chinese prefecture-level oil and gas cities based on super-efficient SBM-DEA model and Malmquist index

With the proposal of Industrial Green Development Plan (2016–2020), it is particularly urgent to focus on the industrial green development of oil and gas cities, actively promote industrial energy efficiency, reduce pollution emissions, and measure the efficiency of their industrial green development. Based on the actual situation of oil and gas cities, we apply the Super-SBM model to measure the industrial green development efficiency of oil and gas cities in 15 years from 2004 to 2018, analyze the spatial and temporal evolution trends and characteristics of industrial green development efficiency, and also calculate the Malmquist index to dynamically analyze the industrial green development efficiency of oil and gas cities. The results show that the industrial green development efficiency of oil and gas cities as a whole is not high from 2004 to 2018, showing a gentle “W” type fluctuation change. From the spatial dimension, there are significant differences in industrial green development efficiency among oil and gas cities in the east, central and west, with the efficiency value is relatively higher in the west. The total factor productivity of industrial green development is most influenced by the changes of technical efficiency and technological progress. In view of the above problems, it is recommended to broaden green technology innovation channels, increase green technology innovation investment, build a new mechanism for regional synergistic development, and formulate regional graded development strategies.

Study on the Interaction between Green Competitiveness of Coastal Ports and Hinterland Economy

Accelerating the construction of green ports and promoting the green transformation of the economy and society are important trends in port and regional development today. This research explores the interaction between the green competitiveness of coastal ports and the hinterland economy from 2007 to 2019 by taking the 10 largest coastal ports in China as the research object and combining the Super-SBM Model with the panel data model. The results show that the green competitiveness of coastal ports is fluctuating, and the green competitiveness of Qingdao and Shanghai ports is stronger in the production frontier surface. Compared with the size of ports, the level of port technology is an important factor to improve the green competitiveness of ports. In terms of interaction, the total economic volume of the hinterland, the proportion of the added value of the tertiary industry, and the waterway transportation between the port and the hinterland have a significant positive impact on the green competitiveness of the port, and the improvement of the green competitiveness of the port and the waterway transportation between the port and the hinterland effectively drive the economic development of the hinterland. This study provides an important basis for the rational use of the port–hinterland interaction and promotes the coordinated and healthy development of both.

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.

中国旅游业碳排放效率趋同演变及其趋势预测

PDF HTML阅读 XML下载 导出引用 引用提醒 中国旅游业碳排放效率趋同演变及其趋势预测 DOI: 10.5846/stxb202108102207 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家社会科学基金青年基金项目(19CGL030) Convergent evolution and trend prediction of carbon emission efficiency in China's tourism industry Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:低碳旅游是实现旅游业可持续发展的必然之路,准确把握中国旅游业碳排放效率趋同演变及其发展趋势,对中国"双碳"目标的实现具有重要的意义。基于超效率-SBM模型对2009-2019年中国旅游业碳排放效率科学测度,再采用空间自相关分析与时空Markov链,检验其趋同效应并深入探析其时空趋同特征,最后结合Markov链的无限分布矩阵,科学预测中国旅游业碳排放效率的发展趋势。结果表明:(1)时间特征上,2009-2019年中国旅游业碳排放效率呈"过山车式"波动上升态势,东部效率均值大于西部大于中部。研究期内效率均呈显著的俱乐部趋同分布,从2009-2014年偏向于较低效率"单峰"趋同向2015-2019年偏向于低效率和高效率的"双峰"趋同演变,且相邻效率等级俱乐部更容易发生转移,其中后期比前期的俱乐部趋同效应更强。(2)空间特征上,不同空间滞后条件下,中国旅游业碳排放效率均呈显著的俱乐部趋同分布,但趋同程度随滞后水平的提升有所减弱。空间滞后水平越高,效率向上转移可能性越大。(3)省域效率转移上,大多中西部省份效率保持平稳,但部分沿海发达省份和西部省份实现向上转移,仅少数中东部省份向下转移。(4)省域及邻域效率转移上,大多数省域与其邻域保持相同的转移方向,其中中西部省份处于"近墨者黑"的困境,少数东部沿海和西南省市摆脱邻域效率"下滑"陷阱,实现向上转移.(5)发展趋势上,未来中国旅游业碳排放效率将整体有所提升,空间分布由"双峰"向"单峰"趋同演变,但仍聚类于较低效率趋同。随着空间滞后水平的提升,俱乐部趋同程度有所减弱,但趋同质量显著提升。最后本文提出针对性地建议,以期促进中国旅游业的可持续发展,助推"双碳"目标的实现。 Abstract:Low-carbon tourism is an inevitable way to realize the sustainable development of tourism. Accurately grasping the convergence characteristic and development trend of China's tourism carbon emission efficiency are of great significance to realization of China's "dual carbon" goal. This paper is based on the Super-SBM model to scientifically measure the carbon emission efficiency of China's tourism industry from 2009 to 2019. Then, the spatial autocorrelation analysis and spatio-temporal Markov chain were used to test its convergence effect and in-depth analysis of its temporal and spatial convergence characteristics. Finally, combined with the infinite distribution matrix of the Markov chain, we scientifically predicted the development trend of China's tourism carbon emission efficiency. The result shows that: (1) In terms of time characteristics, the carbon emission efficiency of China's tourism industry has fluctuated and increased in a "roller coaster style" from 2009 to 2019. The eastern region has the highest average efficiency, followed by the western and finally the central region. During the study period, the efficiency showed a significant club convergence distribution, from a "single peak" distribution biased towards lower efficiency in 2009-2014 to a "double peak" distribution biased towards low efficiency and high efficiency in 2015-2019, and clubs with adjacent efficiency levels are more likely to transfer, and the later period is stronger than the earlier period of club convergence effect. (2) In terms of spatial characteristics, under different spatial lag conditions, the carbon emission efficiency of China's tourism industry has a significant club convergence distribution, but the degree of convergence has weakened as the lag level increases. The higher the level of spatial lag, the greater the possibility of an upward shift in efficiency. (3) In terms of provincial efficiency transfer, the efficiency of most central and western provinces remained stable, but some developed coastal provinces and western provinces achieved upward transfer, and only a few central and eastern provinces transferred downward. (4) In terms of the efficiency transfer of provinces and neighbors, most provinces and their neighbors maintain the same transfer direction. Among them, the central and western provinces are in the "with the bad, it also goes bad" situation, and a few eastern coastal and southwestern provinces get rid of the trap of decline in their neighborhoods and realized upward shifts. (5) In terms of the development trend, in the future, the overall carbon emission efficiency of China's tourism industry will be improved, and the spatial distribution will evolve from a "double peak" to a "single peak", but it will still be clustered towards lower efficiency. With the increase in the level of spatial lag, the degree of club convergence has weakened, but the quality of convergence has improved significantly. Finally, this article puts forward specific suggestions in order to promote the sustainable development of China's tourism industry and promote the realization of the "dual carbon" goal. 参考文献 相似文献 引证文献

Spatial-Temporal Evolution and Its Influencing Factors on Urban Land Use Efficiency in China’s Yangtze River Economic Belt

Improving urban land use efficiency is a feasible way to realize sustainable development and alleviate urban land pressure on the city. The main purpose of this article is to measure the urban land use efficiency of the Yangtze River Economic Belt, and explore its evolutionary trends and influencing factors, so as to provide references for policy formulation to promote efficient land use and sustainable development. Therefore, we calculated the value of urban land use efficiency in the Yangtze River economic belt from 2004 to 2019, based on the super efficiency SBM model, including unexpected output. Further, we analyzed the spatial-temporal evolution, and spatial correlation and its influencing factors. The main results are as follows: Firstly, urban land use efficiency in the Yangtze River economic belt continues to improve as a whole, but it is higher in the east and lower in the west. In the kernel density evolution map, the development trend is steep at first and then slows, and the gap tends to decrease. Secondly, the spatial correlation of urban land use efficiency in the Yangtze River economic belt increases year by year, showing a positive correlation overall. The high-high agglomeration shifts to the east, low-low agglomeration shifts to the west, and low-high and high-low agglomeration show scattered distribution. The hot and cold spots are distributed regionally and have a diffusion trend. Thirdly, the results of the spatial Dubbin model show that the urbanization level, government expenditure and industrial instruction transformation can promote the improvement of urban land use efficiency, and people density and land use scale can inhibit its improvement. Additionally, there is remarkable heterogeneity in the effect of these influencing factors. On the whole, the effect of non-resource-based cities is better, and it is more so in the cities of the eastern region.