Green Development Efficiency Research Articles

Can Data Assets Promote Green Innovation in Enterprises?

This study found that the more data assets held by a company, the higher its level of green innovation. This result was still significant after the instrumental variable method, exogenous policy shock mitigation endogeneity and a series of robustness tests. Data assets promote green innovation by alleviating the constraints on corporate financing and increasing the efficiency of green research and development. Further analysis showed that data assets could continuously increase the level of green innovation and promote enterprises to choose to apply for green invention patents. This study provides useful insights for identifying and utilizing the value of data resources.

The Path to Urban Sustainability: Urban Intelligent Transformation and Green Development—Evidence from 286 Cities in China

Urban intelligence is reshaping urban innovation patterns, accelerating urban transformation, and significantly influencing green and sustainable development. By applying the non-radial directional distance function and an improved entropy method, this study measures the green development efficiency and levels across 286 Chinese cities from 2006 to 2020. The objectives of this study are twofold: first, to examine the impact of urban intelligence transformation on green development, and second, to investigate how urban intelligence influences common prosperity. The analysis employs a double/debiased machine learning model, with the “Smart City Pilot” policy as the focal point. The findings indicate that (1) urban intelligence transformation enhances both the level and efficiency of green development in Chinese cities; (2) this transformation fosters green development by driving urban innovation, upgrading industrial structures, and promoting green finance; and (3) the impact of urban intelligence varies across cities with different sizes, resource endowments, and marketization levels. Furthermore, the study constructs a common prosperity index to assess how urban intelligence contributes to residents’ well-being and social equity. The results suggest that urban intelligence transformation not only advances green development but also contributes to improving residents’ quality of life, thereby promoting a more equitable and prosperous society. These insights offer crucial policy guidance for China and other countries facing environmental and economic challenges in the digital age.

Research on the efficiency and spatiotemporal evolution characteristics of agricultural green development in central cities of the Yangtze River Delta

IntroductionAgricultural green development (AGD) prioritizes sustainable growth by integrating economic, ecological, and social dimensions, aiming to harmonize agricultural economic development with environmental protection and social progress.MethodsThis study integrates the three-stage super-efficiency DEA-SBM model with the BP algorithm, creating an advanced DEA-SBM-BP model to overcome the shortcomings of traditional DEA in evaluation and management processes. The study further applies the Dagum Gini coefficient, kernel density estimation (KDE), and Moran’s index to assess and forecast the efficiency and spatiotemporal evolution patterns of green agricultural development in key cities within the Yangtze River Delta.ResultsThe analysis shows that AGD in the central city of the Yangtze River Delta is overall balanced; however, substantial variations exist among cities within individual provinces. Factors like macroeconomic conditions, workforce quality, and policy support play a crucial role in promoting the efficiency of AGD. Among these, macroeconomic development level has a negative impact, while labor quality and policy support exhibit bidirectional effects. Infrastructure construction, digitalization of agricultural economy, and rural security have become key factors in the green development of modern agriculture. The green advancement of agriculture in the central Yangtze River Delta region typically exhibits a marked clustering effect; however, the local clustering reveals a trend toward dispersed development.DiscussionDespite the emergence of new characteristics in agricultural production in China within the context of high-quality development, differences in resource endowments and economic structures among cities continue to be significant factors contributing to regional imbalances and changes in the agglomeration patterns of agricultural development.

The impact of energy consumption permit trading scheme on green development efficiency: firm-level evidence in China

The impact of energy consumption permit trading scheme on green development efficiency: firm-level evidence in China

How does new-type urbanization promote green development efficiency in China? The mediating role of governments, enterprises, and residents

New-type urbanization (NTU) is proposed by China to solve unsustainable issues and improve green development efficiency (GDE) during the process of rapid urbanization. However, the impact mechanism of NTU on GDE is unclear. Using panel data of 282 prefecture-level cities in China from 2010 to 2019, we measured NTU and GDE to describe their spatiotemporal pattern and relationship evolution. The fixed effects panel model and mediating effect panel model were further utilized to analyze the benchmark impact, mediating mechanism and spatiotemporal heterogeneity of NTU on GDE. The results showed that NTU improved whose level in eastern region was the highest, while GDE increased in fluctuations whose level in eastern and western regions performed better. With the proportion of double-high cities increasing from 13.83% to 43.62%, the NTU-GDE relationship was upgraded. Overall, every 1% improvement in NTU increased GDE by 0.3111%, and the enterprise effect, resident effect and government effect played a positive mediating role from high to low. During the later stage of NTU, it improved GDE more strongly and the mediating role of governments was optimized. The eastern region was the only region with three positive mediating roles of governments, enterprises and residents. These findings will facilitate GDE through NTU in China and have reference significance for the sustainability of global urbanization.

The Synergistic Evolution Characteristics and Influencing Factors of Tourism Economy and Urban Green Development Efficiency in the Yellow River Basin

In the context of the “ecological priority and green development” strategy, examining the co-evolution between the tourism economy and the efficiency of urban green development can offer both theoretical insights and quantitative foundations to support ecological preservation and high-quality development in China’s Yellow River Basin. This research utilized approaches such as the Haken model and the geographically and temporally weighted regression model to investigate the spatiotemporal patterns, synergistic characteristics, and driving factors of the tourism economy and urban green development efficiency within the Yellow River Basin. The findings reveal the following: (1) Regional disparities in the tourism economy are progressively widening, whereas the efficiency of green development tends to decline. Furthermore, both the tourism economy and urban green development efficiency display “high-high clustering” and “low-low clustering” spatially. (2) The synergistic evolution of the two systems displays spatial characteristics of transitioning from polarization to trickle-down effects. (3) Natural factors such as topography and vegetation coverage, as well as human economic factors like industrial structure and the degree of openness, positively promote the synergy. However, elements such as temperature, precipitation, economic development level, and openness to innovation have a certain inhibitory effect on the synergistic evolution.

Research on the Evaluation of Green Development Efficiency of Zhejiang Province Industry under the Background of ‘Dual-carbon’

Research on the Evaluation of Green Development Efficiency of Zhejiang Province Industry under the Background of ‘Dual-carbon’

Estimation of Urban High-Quality Development Level Using a Three-Stage Stacks-Based Measure Model: A Case Study of Urban Agglomerations in the Yellow River Basin

The high-quality development paradigm, which emphasizes the organic unity of efficiency, equity, and sustainability, has gained increasing global recognition as an extension of the concept of sustainable green development. In this study, we use green development efficiency as a metric of high-quality development and employ a three-stage Stacks-based Measure Model (SBM) in order to assess the true green development efficiency (GDE) levels of urban agglomerations in China’s Yellow River Basin (YRB) from 2011 to 2020. The results indicate that external environmental factors significantly impacted the green development efficiency levels of these urban agglomerations; after removing these factors, their green development efficiency shifted from trendless fluctuations to more consistent upward trends. Additionally, the disparities between different urban agglomerations are the primary sources of overall differences in green development efficiency in the YRB. Influenced by economic development levels and administrative divisions, the degree of internal development imbalance varies among urban agglomerations; however, regional disparities show a decreasing trend, indicating a catch-up effect. Based on these findings, we further propose relevant policy recommendations in this paper. The results of this study help us to understand the current status and trends of high-quality development in the urban agglomerations of the YRB, providing empirical evidence for policy formulation.

Do Market-Based Environmental Regulations Promote Green Development? A Quasi-Natural Experiment Based on Carbon Emissions Trading Pilot of China

ABSTRACT Using panel data of 30 Chinese provinces from 2008 to 2019, we utilized the Super-efficiency SBM-DEA model to estimate green development efficiency (GDE) and analyzed the impact of carbon emissions trading scheme (ETS) on GDE via the DID model. Our findings indicate that ETS significantly reduces carbon emissions and enhances GDE. Further analysis reveals a time lag and regional heterogeneity, with effects becoming more pronounced three years later, particularly in the developed eastern regions. Additionally, the mediating effect test suggests that green technology innovation (GTI), notably green patents, serves as a vital conduit for ETS to bolster GDE.

Spatial spillover effects and correlation network analysis of green construction development efficiency in China

Green construction has been implemented globally to address resource depletion and environmental degradation. The effectiveness of green construction development depends on the efficiency of resource utilization and the common progress of all regions. However, existing studies have paid limited attention to green construction development efficiency (GCDE) and its spatial correlation. This study uses the super-efficiency slacks-based measure (Super-SBM) model, spatial econometric models, and social network analysis (SNA) method to reveal the spatial distribution, spatial spillover effects, and spatial correlation of GCDE across 30 provinces in China. The results indicate significant disparities in GCDE among regions, with the eastern region exhibiting considerably higher GCDE than the western and northeastern regions. There is evidence of spatial spillover effects, and the spatial correlation of GCDE is strengthening. Provinces with high GCDE occupy central positions in the GCDE network and exert spillover effects on other provinces, while underdeveloped provinces have opportunities to benefit from regional cooperation. The findings provide policy insights for the implementation and enhancement of green construction development actions. Moreover, they provide Chinese experience for green construction practices in other areas of the world.

Analysis of the spatio-temporal variability and convergence of green development efficiency of city clusters in the middle reaches of the Yangtze River in China

The advantageous geographical location of the middle reaches of the Yangtze River (YRMR) plays an important role in promoting high-quality development in China and accelerating the development of the Yangtze River Economic Belt(YREB). In the new stage of development, green development efficiency (GDE) is an important metric for assessing the balance between economic development and ecological civilization. Therefore, taking three city clusters in China's YRMR as the study area, this research employs the Super-SBM model to assess their GDE in 2010–2020 in order to analyze the problem of GDE at the city scale. On this basis, spatio-temporal analyses, dynamic evolution, and convergence analyses have been carried out using the Thiel index, GML index model, and convergence model. The findings indicate that overall GDE has not yet reached an effective level and generally exhibits a two-stage fluctuating upward trend. Spatially, the pattern of distribution is "high in the southwest, low in the northeast". The differences within the city clusters in the YRMR in terms of green development are gradually narrowing, with differences within the same regions contributing the most to overall differences. The GML index shows a trend of fluctuating growth, indicating that the overall GDE growth is in good condition. GDE has grown significantly as a result of technological advancements, with the Wuhan metropolitan area (cluster A) experiencing the fastest growth in this regard, followed by the Chang-Zhu-Tan and the Poyang Lake rim city clusters (clusters B and C). The YRMR and its three major city clusters exhibit both σ- and β-convergence patterns. The convergence of GDE is simultaneously affected by several factors, including economic development (RGDP), urbanization level (UR), industrial structure (IND), technological development (TEC), and the level of openness (LO). Regional heterogeneity also exists. The above study provides decision-making references and empirical evidence for promoting green development in China's city clusters in the YRMR and advancing the improvement of economic-environmental incongruence in this area.

Green siphon or green spillover: Analyzing the spatial implications of industrial relocation on green development

Industry relocation has a profound impact on the green development of recipient cities and their neighboring areas, driven by various factors such as investment and technological progress. This study investigates the impact of industrial relocation on the green development efficiency (GDE) of recipient cities and its spatial spillover effect using national city-level data and the establishment of national-level Industrial Relocation Demonstration Zones (IRDZ) as a policy shock, employing spatial difference-in-differences models. Both theoretical analysis and empirical tests show that industrial outflow increases the GDE of recipient cities, but reducing the GDE of neighboring cities. This effect decays with spatial distance and only affects non-resource cities. In addition, regional integration and the influence of large cities can significantly mitigate the adverse effects of industrial relocation. Industrial agglomeration, environmental regulation, green innovation, and energy intensity are the main direct and indirect pathways through which industrial relocation affects GDE in recipient and neighboring cities. The findings of this study are significant for promoting industrial relocation, energy conservation, and emission reduction in developing regions, as well as enhancing green cooperation among governments.

Beyond skyline and borders: Unraveling the evolution and drivers of tourism green development efficiency in the Beijing–Tianjin–Hebei urban agglomeration, China

Beyond skyline and borders: Unraveling the evolution and drivers of tourism green development efficiency in the Beijing–Tianjin–Hebei urban agglomeration, China

Fiscal decentralization and the transformation of regional energy structures in China: Spatial spillover effects and the mediating role of technological innovation

The transformation of regional energy structures plays a pivotal role in enhancing ecological quality and advancing national green development efficiency. However, this transformation is characterized by dual externalities, necessitating governmental intervention to rectify market failures. Therefore, this study focuses on the critical influence and mechanisms through which local governments affect regional energy structure transformation, particularly within the context of China's unique fiscal decentralization. This study explores the impact of fiscal decentralization on the transformation of China's regional energy structures and its spatial correlations. Employing a bidirectional fixed-effect model and a spatial Durbin model, we analyze Chinese provincial panel data from 2002 to 2021 to explore the effects of fiscal decentralization on regional energy structure transformation and its spatial spillover. Findings reveal that fiscal decentralization significantly enhances the efficiency of regional energy structure transformation, with an effect coefficient of 0.127. Additionally, the fiscal decentralization mechanism positively influences spatial spillover effects on regional energy transformation, with these effects becoming more pronounced alongside higher degrees of economic agglomeration. Moreover, local governments are found to foster regional scientific and technological innovation, thereby facilitating adjustments in the regional industrial structure and promoting energy structure transformation. The intermediary effect test highlights the role of local governments in promoting scientific and technological advancements that drive industrial restructuring and energy transformation. The study recommends for a long-term strategy to balance central and local financial development, aiming to enhance the efficiency of regional energy structure transformation. These findings offer a theoretical foundation and policy recommendations for optimizing and transforming energy structures in pursuit of China's green and high-quality development goals. These findings offer globally relevant insights into leveraging fiscal decentralization for energy structure transformation, supporting sustainable development and green growth worldwide.

Measuring The Efficiency of Green Development Enabled by Digital Economy in China's Provinces and Regions - Based on DEA Model and Malmquist Index

Measuring The Efficiency of Green Development Enabled by Digital Economy in China's Provinces and Regions - Based on DEA Model and Malmquist Index

Does energy transformation improve green development efficiency? Evidence from Sichuan Province, China

Green sustainable development has become an important topic of concern to human society.Energy clean and low-carbon transformation is an important lever for promoting regional green development. Investigating the driving mechanisms of energy transformation is helpful to explore the effective path for accelerating the process of green development. Meanwhile, Sichuan Province is a demonstration province of clean energy and an important energy transportation hub in China, and it should play an exemplary role in the process of high-quality development. In this regard, this study uses the two-stage super-efficiency network SBM model to measure the green development efficiency based on the dual perspectives of green production and environmental governance. Based on historical data from 2006 to 2022, Technological innovation, industrial structure, and foreign direct investment are selected as transmission variables, and the fixed effects regression model is used to empirically analyse the direct and indirect impact effects of ET on GDE. The results show that the green development efficiency in Sichuan Province has gradually increased from 0.8303 in 2006–0.9270 in 2022, which is at a relatively high level. Energy transformation is helpful to improve the green development efficiency in Sichuan Province. However, due to insufficient complementary power sources and challenges in balancing energy supply and demand, the incentive level needs to be strengthened. Technological innovation, industrial structure, and foreign direct investment show indirect heterogeneous transmission effects in the process of influence.

Spatiotemporal dynamics and determinants of medical service efficiency in China

BackgroundMedical service efficiency is an important indicator for measuring the equity of medical services. Therefore, this study primarily focuses on investigating the spatiotemporal domain to explore both spatial and temporal characteristics, as well as influencing factors that affect medical service efficiency across diverse provinces in China.MethodsThe super Epsilon-based Measure (EBM) unexpected model has previously been utilized to quantify energy eco-efficiency, carbon emission efficiency, and green development efficiency. However, limited studies have applied this method to assess the efficiency of healthcare services. Therefore, this study investigates the application of the super-EBM-unexpected model in evaluating medical service efficiency, and further integrates spatial econometric models to explore the influencing factors of medical service efficiency and aims to identify potential avenues for improvement.ResultsThe average efficiency of medical services in the 31 provinces of China ranges from 0.6 to 0.7, indicating predominantly low efficiency values. However, economically developed coastal areas exhibit relatively high efficiency levels above 1. Conversely, regions with relatively lower levels of economic development demonstrate lower efficiency rates at approximately 0.3. Evidently, substantial regional disparities exist. For the influencing factors, the enhancement of residents' living standards can effectively foster the medical service efficiency, while residential living standards of nearby areas can also exert an impact in this region. The influence of educational attainment on medical service efficiency exhibits a significant inhibitory effect.ConclusionsThe majority of China's 31 provinces exhibit suboptimal medical service efficiency, with notable regional disparities. Future policy initiatives should be tailored to address the unique challenges faced by regions with lower levels of economic development, prioritizing enhancements in both the efficacy and quality of their healthcare systems.

Pilot policies for low-carbon cities in China: a study of the impact on green finance development and energy carbon efficiency

ABSTRACT Improving the efficiency of energy carbon emissions (ECEE) is crucial for China's pursuit of high-quality development. This paper assesses the low-carbon city pilot policy (LCCPP) as a strategic measure to enhance ECEE and its alignment with global efforts to mitigate climate change. By analyzing panel data from 205 Chinese cities from 2003 to 2016, this study evaluates the LCCPP's effectiveness and its spatial spillover effects on ECEE. Results indicate a 6.5% increase in ECEE in pilot cities compared to non-pilot counterparts, with these findings substantiated through extensive robustness checks. The analysis of underlying mechanisms reveals that the LCCPP boosts ECEE by promoting green finance and the co-agglomeration of producer services and manufacturing. Furthermore, the policy's impact varies: it is more substantial in non-resource-based cities and in those with advanced green finance and synergistic industry agglomerations. Employing a spatial difference-in-differences approach, the study uncovers an inverted U-shaped pattern in the spillover effects of the LCCPP on ECEE, suggesting a nuanced regional influence of the policy. This research contributes to the understanding of policy-driven environmental improvements and their economic co-benefits within urban settings.

Towards sustainability: How does the digital-real integration affect regional green development efficiency?

Integrating the digital economy into the real economy (thereafter referred to as digital-real integration) is one of the important ways to promote the efficiency improvement of green development. We adopt the panel data of 30 provinces and cities in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2011 to 2021 as the basis of our study. We also use the coupled coordination model to measure the level of digital-real integration in each region. Then, we set up a spatio-temporal geographically weighted regression model to examine the spatio-temporal distribution pattern and the specific mechanism of its impact on the efficiency of regional green development. Our study finds that the vast majority of provinces in the country are in the coupling and coordination state on the verge of dysfunction and mild dysfunction. Moreover, coordinating with the development speed of the digital economy to reach the state of dynamic interconnection and constraints is difficult for the real economy. Second, the level of digital-real integration can contribute to the improvement of green development efficiency, and that in Xinjiang and Qinghai is lower than in other provinces. Further in terms of spatial distribution, the digital-real integration in the Yangtze River Delta region (Shanghai, Jiangsu, Zhejiang, Anhui) and Fujian Provinces during the 11-year period obviously promotes the efficiency of green development. Finally, through the mechanism analysis, the digital-real integration development can be found to promote the improvement of green development efficiency via three channels: industrial structure rationalization, factor market development degree, and government intervention. Findings of this paper provide some basis and reference for better promoting the digital-real integration and then realizing the long-term sustainable development of the region.

Spatio-temporal pattern evolution of green development efficiency in Northeastern China and its driving factors

Scientific analysis of green development efficiency is crucial for promoting healthy green development at home. The subjects of this study were 181 counties in three provinces in Northeast China. As a first step, the Super-SBM model is utilized to estimate the efficiency of 181 counties from 2006 to 2020; in addition, spatial autocorrelation analysis is applied to assess green development efficiency, spatially and temporally, of 181counties; and to examine the driving factors and spillover effects associated with the efficiency of 181 counties, the Spatial Durbin model (SDM) is utilized. The conclusions show that 181 counties have low levels of green development efficiency and are all on a downward trajectory. Liaoning Province has the highest level, Jilin Province has the second highest level, and Heilongjiang Province has the lowest level. According to the geographical distribution, the locations with high and very high green development efficiency are roughly located in Mohe City, Huma County, Xunke County, Daqing Municipal District, Harbin Municipal District, Changchun Municipal District, Wafangdian City, Dalian Municipal District, and Zhuanghe City. There is a favorable spatial connection of efficiency across regions, but the positive spatial agglomeration trend first diminishes and then gradually increases. Economic development, industrial structure, policy regulations, and environmental protection play significant roles in economic development, industrial structure, policy regulations, and environmental protection. The contribution of this essay is of paramount importance for understanding the status quo and potential for green development in different counties in Northeast China and for realizing coordinated regional green development.