Evaluation and Influence Factor of Green Efficiency of China’s Agricultural Innovation from the Perspective of Technical Transformation

Agricultural innovation is important for the green transformation of agriculture.Based on the perspective of technology transformation,this paper builds a theoretical analysis framework and evaluation index system for green efficiency of agricultural innovation,and discusses the evolution laws and influencing factors of the green efficiency of China’s agricultural innovation from 2005 to 2017 utilizing the DEA model,Malmquist index,and Tobit regression analysis.The results show that:1)The overall green efficiency of China’s agricultural innovation is not high,the green efficiency of agricultural innovation in eastern China is mainly driven by pure technical efficiency,while that in central and western China is mainly driven by the scale efficiency.The green efficiency of agricultural innovation shows significant spatial differences,and the low efficiency and relatively low-efficiency regions moved to central and southeastern China.2)Technical progress is the main force affecting the change of green total factor productivity of China’s agricultural innovation,seeing a trend of decrease followed by an increase.Pure technical efficiency and scale efficiency exhibit an increasing-decreasing trend,and gradually transform into key factors that restrict the improvement of the green total factor productivity of agricultural innovation.3)Agricultural technologies’diffusion,absorption,and implementation are three influencing factors of the green efficiency of agricultural innovation.The local level of informatization,the number of agricultural technicians in enterprises and institutions,average education level of residents,and the level of agricultural mechanization have positive impacts on the promotion of the green efficiency of agricultural innovation,promoting the diffusion,absorption and implementation of agricultural innovation technology can significantly improve the green efficiency of agricultural innovation.

Are cities greener because of innovation?Independent innovation policy and green economic efficiency

The national independent innovation demonstration zone(NIIDZ)is an independent innovation policy that plays a crucial role in implementing strategies.Given the importance of the NIIDZ,this study uses panel data of 278 prefecture-level cities in China from 2006 to 2020 and empirically examines the effect and internal mechanism of the NIIDZ on green economic efficiency(GEE)using the difference-in-difference model(DID).The results show that the NIIDZ effectively enhances the growth of GEE,and the results remain valid through several robustness tests,such as year-by-year propensity score matching.The transmission mechanism suggests that the NIIDZ indirectly drives GEE by accelerating scientific and technological investment,promoting talent concentration,and optimizing the industrial structure.Moreover,heterogeneity analysis reveals that the promotion effect of the NIIDZ on GEE is more prominent in the eastern region and high green development level areas.The study’s findings can serve as a reference for China to further utilize the policy effectiveness of the NIIDZ and accelerate the high-quality development of the green economy in the future.

A Study of the Impact of the Digital Economy on the Efficiency of Urban Green Economy--Based on the Yangtze River Delta City Cluster

This paper adopts the non-expected output-super-efficiency SBM(Slacks-Based Model)model and principal component analysis to calculate the green economy efficiency and the digital economy level of 27 prefecture-level cities in China’s Yangtze River Delta urban agglomeration between 2011 and 2019,respectively,and examines the impact of the digital economy on the green economy efficiency by using benchmark regression and mechanism analysis.The findings show that,first,the digital economy has a significant contribution to the green economic efficiency of cities,and this conclusion still holds after robustness tests such as replacing explanatory and interpreted variables and introducing province-fixed effects.Second,through the mechanism test,it is found that the digital economy can indirectly promote urban green economic efficiency through the positive mechanism effect of promoting industrial structure upgrading.

Evaluation of Green Development Efficiency in Chongqing Municipality Based on Super-SBM and Malmquist Models

The green development of Chongqing municipality is crucial in establishing a major ecological shield in the upper reaches of the Yangtze River.By developing a Super-SBM model and using the Malmquist index to analyze and calculate the green development efficiency and its influencing factors in Chongqing from 2011 to 2021,this study reveals an accelerating trend in the overall green development efficiency in Chongqing.The significant enhancement of green development efficiency in Chongqing is primarily attributed to changes in returns to scale.Pure technical efficiency and technological advancements have a considerable potential impact on improving green development efficiency in Chongqing.Furthermore,there are discernible disparities in green development efficiency among districts and counties in Chongqing,with different factors influencing these variations.Chongqing is suggested to promote clean and efficient energy utilization,bolster the application and commercialization of scientific and technological advancements,consistently advance ecological restoration and management,and elevate the quality of green development to a higher level.

Green transformation paths of resource-based cities in China from the configuration perspective

Green transformation is an unavoidable choice for resource-based cities(RBCs)that face resource depletion and environmental pollution.Existing research has focused primarily on specific RBCs,making it challenging to apply green transformation strategies universally across cities.The fuzzy set qualitative comparative analysis(fsQCA)is a combination of qualitative and quantitative analyses that can handle multiple concurrent causality problems and determine how different conditions combine into configurations and generate an outcome.Thus,to address this gap,in this study,we established a research framework for green transformation and utilized the fsQCA to examine the configurations of 113 RBCs in China.By incorporating the element of time,this study explored the dynamic evolution of solutions in 2013,2016,and 2019.The main findings indicate that individual elements do not constitute the necessary conditions for improving the green transformation efficiency(GTE),and the systematic combination of multiple conditions is an effective path for realizing the improvement of the GTE in RBCs.Green transformation paths of RBCs exhibit the same destination through different paths.Additionally,the combination of system environment elements and system structure elements is both complementary and alternative.Differences in RBCs have led to various factor combinations and development paths,but there are some similarities in the key elements of the factor combinations at different stages.Economic environment,government support,and technological innovation are key factors that universally enhance the GTE in RBCs.These insights can assist city managers in formulating policies to drive green transformation and contribute to a better theoretical understanding of green transformation paths in RBCs.

Dynamic evolution trend of comprehensive transportation green efficiency in China:From a spatio-temporal interaction perspective

It is urgent and important to explore the dynamic evolution in comprehensive transportation green efficiency(CTGE)in the context of green development.We constructed a social development index that reflects the social benefits of transportation services,and incorporated it into the comprehensive transportation efficiency evaluation framework as an expected output.Based on the panel data of 30 regions in China from 2003-2018,the CTGE in China was measured using the slacks-based measure-data envelopment analysis(SBM-DEA)model.Further,the dynamic evolution trends of CTGE were determined using the spatial Markov model and exploratory spatio-temporal data analysis(ESTDA)technique from a spatio-temporal perspective.The results showed that the CTGE shows a U-shaped change trend but with an overall low level and significant regional differences.The state transition of CTGE has a strong spatial dependence,and there exists the phenomenon of“club convergence”.Neighbourhood background has a significant impact on the CTGE transition types,and the spatial spillover effect is pronounced.The CTGE has an obvious positive correlation and spatial agglomeration characteristics.The geometric characteristics of the LISA time path show that the evolution process of local spatial structure and local spatial dependence of China’s CTGE is stable,but the integration of spatial evolution is weak.The spatio-temporal transition results of LISA indicate that the CTGE has obvious transfer inertness and has certain path-dependence and spatial locking characteristics,which will become the major difficulty in improving the CTGE.

Enhancing the green efficiency of fundamental sectors in China’s industrial system:A spatial-temporal analysis

Due to sectoral interactions in the economy,the overall green efficiency(GE)of China’s industrial system relies heavily on fundamental sectors that contribute substantial energy to the supply chain production of other sectors but shows low sectoral GE.For the three fundamental sectors in China’s industrial systems,namely the smelting and pressing of nonferrous metals(SPNFM),the processing of petroleum,coking,and nuclear fuel(PPCNF);and the manufacturing of nonmetallic mineral products(MNMMP),we employed a three-stage data envelopment analysis(DEA)model to measure GE in the fundamental sectors in 30 provinces from 2010 to 2015.We then adopted a stochastic frontier analysis(SFA)model to evaluate the influence of technological innovation(TI),industrial agglomeration(IA),environmental regulation(ER),and intraindustry competition(IC).The results showed that GE in the three fundamental sectors varied spatially.Specifically,TI promoted GE in MNMMP,but the effect was not obvious in the SPNFM and PPCNF sectors.Moreover,ER had positive impacts on GE in the fundamental sectors.The effects of IA and IC on GE in the fundamental sectors varied in direction and strength.After eliminating the impacts of environmental effects and statistical noise,the real GE in the three fundamental sectors varied significantly compared to the comprehensive GE.Policy opportunities for enhancing GE in the fundamental sectors mainly lie in region-specific policy and regulations that avoid a“one-size-fits-all”governance approach.

Study on the efficiency and regional disparity of green technology innovation in China's industrial companies

This paper first constructed a system to evaluate the innovation efficiency of industrial companies within China's Mainland.Then,a principal component analysis(PCA) was performed to these indicators for dimensionality reduction,so as to figure out the technology innovation efficiency in these two phases,respectively.Finally,the overall efficiency of industrial companies in different regions was estimated and factorized via data envelopment analysis(DEA).The results showed that:(1)the efficiency of green technology innovation of industrial companies in China was relatively low as a whole,which mainly resulted from pure technical efficiency(PTE).Further,this huge gap continues to expand in these regions.And both PTE and scale efficiency(SE) in central and western regions leave much to be expected.(2)In the first phase of green technology development,when environmental factors were concerned,the efficiency was much lower than that without environmental considerations.Besides,the central and western regions were facing increasingly severe environmental problems,and there was a wide disparity in technology development efficiency among eastern,central,and western regions.(3)In the second phase of green technology commercialization,there were still more rooms for improvement in raising the efficiency of green technology innovation,and the efficiency in eastern,central,and western regions was ranked from highest to lowest.(4)Liaoning,Hebei,Heilongjiang,Xinjiang,Shanxi,Inner Mongolia,Yunnan,and Qinghai should focus on improving their technology;Jilin,Jiangxi,Anhui,and Guangxi should make their efforts to reduce resource redundancy;whereas Ningxia and Gansu should try to solve the above two issues.

Spatial-temporal Characteristics of Green Development Efficiency and Influencing Factors in Restricted Development Zones:A Case Study of Jilin Province,China

Green development is an important issue of sustainable development in China.Due to the relatively backward economy and the fragile ecological environment,restricted development zones need to embrace green development.Taking 38 counties in Jilin Province as the empirical research objects,and based on cross-sectional data for each county in 2005,2010,and 2015,we accurately depicted the spatiotemporal evolutionary characteristics of green development efficiency(GDE)in restricted development zones of Jilin Province using the slacks-based measure-data envelope analysis(SBM-DEA)model.Moreover,the factors that influence GDE were further analyzed using the Tobit model.We found that:first,GDE showed a V-shaped trend in restricted development zones of Jilin Province.The differences in GDE in the eastern,central,and western Jilin Province increased gradually.Second,76%of counties in the restricted development zones had high or higher efficiencies.The resource-based cities were the main areas with low or lower GDE.Third,the economic development level was the core factor affecting GDE.Urbanization level had a significant negative effect on GDE in the restricted development zones.The effect of technological innovation level on GDE fluctuated,and we found that a‘backward mechanism’of technological innovation was beginning to form.Industrial structure and environmental governance had no significant effects on GDE.

Influence of technological innovation on regional green development efficiency in China(2004-2017):An empirical analysis based on the spatial Durbin model

Under the background of green development,the function direction of technological innovation to green development efficiency,which includes economy,resources and environment,needs to be observed by demonstration.In this paper,the green development efficiency of 30 provinces(cities and districts)in China from 2004 to 2017 is measured and its intertemporal changes,regional differences of green development efficiency are analyzed by using the super efficiency SBM model,further through theoretical analysis and empirical study,the influence of technological innovation on regional green development efficiency and its impact mechanism are investigated.The influence mechanisms of the technological innovation on green development efficiency are clarified and empirically tested by spatial econometric models from the perspectives of the growth sources and quantitative analysis.The results show that during the observation period,the green development efficiency in China exhibits a U-shaped variation,but there are huge regional differences with the obvious polarization in Eastern and Midwestern regions,and that technological innovation has some effect in promoting the regional green development efficiency,but not significant enough,which are heterogeneous according to the time periods and regions.

Spatiotemporal Dynamics of Green Total-factor Water-use Efficiency and Its Influencing Factors in China

In this study,we developed an evaluation index system for green total-factor water-use efficiency(GTFWUE)which reflected both economic and green efficiencies of water resource utilization.Then we measured the GTFWUE of 30 provinces/municipalities/autonomous regions(hereafter provinces)in China(not including Tibet,Hong Kong,Macao,Taiwan as no data)from 2000 to 2018 using a minimum distance to the strong frontier model that contained an undesirable output.We further analyzed the regional differences and spatial correlations of GTFWUE using these values based on Global and Local Moran’s I statistics,and empirically determined the factors affecting GTFWUE using a spatial econometric model.The evaluation results revealed that the GTFWUE differed substantially between the regions.The provinces with high and low GTFWUE values were located in the coastal and inland areas of China,respectively.The eastern region had a significantly higher GTFWUE than the central and western regions.The GTFWUEs for all three regions(eastern,central,and western regions)decreased slowly from 2000 to 2011(except 2005),remained stable from 2012 to 2016,and rapidly increased in 2017 before decreasing again in 2018.We found significant spatial correlations between the provincial GTFWUEs.The GTFWUE for most provinces belonged to the high-high or low-low cluster region,revealing a significant spatial clustering effect of provincial GTFWUEs.We also found that China’s GTFWUE was highly promoted by economic growth,population size,opening-up level,and urbanization level,and was evidently hindered by water endowment,technological progress,and government influence.However,the water-use structure had little impact on GTFWUE.This study fully demonstrated that the water use mode would be improved,and water resources needed to be used more efficiently and green in China.Moreover,based on the findings of this study,several policy recommendations were proposed from the aspects of cross-regional cooperation,economy,society,and institution.

The Efficiency Droop of InGaN-Based Green LEDs with Different Superlattice Growth Temperatures on Si Substrates via Temperature-Dependent Electroluminescence

InGaN-based green light-emitting diodes （LEDs） with different growth temperatures of superlattice grown on Si （111） substrates are investigated by temperature-dependent electroluminescence between 100 K and 350K. It is observed that with the decrease of the growth temperature of the superlattice from 895℃ to 855℃, the forward voltage decreases, especially at low temperature. We presume that this is due to the existence of the larger average size of V-shaped pits, which is determined by secondary ion mass spectrometer measurements. Meanwhile, the sample with higher growth temperature of superlattice shows a severer efficiency droop at cryogenic temperatures （about 100 K-150 K）. Electron overflow into p-GaN is considered to be the cause of such phenomena, which is relevant to the poorer hole injection into multiple quantum wells and the more reduced effective active volume in the active region.

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

Green development is a critical component of sustainable tourism, which prioritizes a comprehensive, ecologically-friendly, and people-oriented approach to development. This study presents a case study of the Beijing–Tianjin–Hebei(BTH) urban agglomeration from 2001 to 2021 to analyze the spatio-temporal evolution characteristics and influencing factors of tourism green development efficiency(TGDE). The study defines the concept of tourism green development and constructs an evaluation system, which is used to explore the internal differences and spatial patterns of TGDE within the urban agglomeration. The methodological approach includes the SBM–Undesirable model, kernel density estimation, Markov chain, and spatial gravity model. The findings indicate that the TGDE in the BTH urban agglomeration is generally favorable, displaying a temporal phase of “rising–declining–rising.” However, the study observes lower TGDE in tourism node cities compared to tourism regional center cities and tourism core hub cities. The non-equilibrium degree of each region indicates significant spatio-temporal evolution patterns and internal differences among the three regions, with a spatially decreasing distribution of “core hub-regional center-node city.” The TGDE in the urban agglomeration experienced an evolutionary trend of “first decreasing and then increasing” with apparent endogenous evolution characteristics. The linkage pattern of green development efficiency in the tourism industry between cities is relatively stable. Furthermore,neighboring cities generally exhibit a higher spatial connectivity strength of green development efficiency in the tourism industry compared to non-neighboring cities. Economic development level, industrial structure, and science and education level are identified as key factors that affect TGDE. However, the study finds that the factors influencing TGDE in tourism core hub cities, tourism regional center cities, and tourism node cities differ somewhat. Economic development level, industrial structure, science and education level, openness, and government regulation impact TGDE in tourism core hub cities and tourism regional center cities, while economic development level, industrial structure, and tourism resource endowment are the primary factors affecting TGDE in tourism node cities. The study provides policymakers and tourism practitioners with valuable insights into enhancing the green development of the tourism industry in the BTH urban agglomeration and other similar regions.Corresponding policy recommendations based on the results are proposed to improve the TGDE of the tourism industry in these regions, promote sustainable tourism development,improve the quality of life of local residents, and protect the ecological environment.

Spatial-temporal Divergence Characteristics and Driving Factors of Green Economic Efficiency in the Yangtze River Economic Belt of China

The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable socio-economic development.The research focused on the Yangtze River Economic Belt(YREB)and employed the miniumum distance to strong efficient frontier DEA(MinDs)model to measure the green economic efficiency of the municipalities in the region between 2008 and 2020.Then,the spatial autocorrelation model was used to analyze the evolution characteristics of its spatial pattern.Finally,Geodetector was applied to reveal the drivers and their interactions on green economic efficiency.It is found that:1)the overall green economic efficiency of the YREB from 2008 to 2020 shows a W-shaped fluctuating upward trend,green economic efficiency is greater in the downstream and smallest in the upstream;2)the spatial distribution of green economic efficiency shows clustering characteristics,with multi-core clustering based on‘city clusters-central cities'becoming more obvious over time;the High-High agglomeration type is mainly clustered in Jiangsu and Zheji-ang,while the Low-Low agglomeration type is clustered in the western Sichuan Plateau area and southwestern Yunnan;3)from input-output factors,whether it is the YREB as a whole or the upper,middle and lower reaches regions,the economic development level,labor input,and capital investment are the leading factors in the spatial-temporal evolution of green economic efficiency,with the com-prehensive influence of economic development level and pollution index being the most important interactive driving factor;4)from so-cio-economic factors,information technology drivers such as government intervention,transportation accessibility,information infra-structure,and Internet penetration are always high impact influencers and dominant interaction factors for green economic efficiency in the YREB and the three major regions in the upper,middle and lower reaches.Accordingly,the article puts forward relevant policy re-commendations in terms of formulating differentiated green transformation strategies,strengthening network leadership and informa-tion technology construction and coordinating multi-factor integrated development,which could provide useful reference for promoting synergistic green economic efficiency in the YREB.

Industrial Green Spatial Pattern Evolution of Yangtze River Economic Belt in China

We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.

Impacts of Market-based Environmental Regulation on Green Total Factor Energy Efficiency in China

This study employed a difference-in-differences design to assess the effect of marketbased environmental regulation on green total factor energy efficiency(GTFEE)in a quasi-natural experiment that investigated China's carbon emissions trading scheme(ETS).The empirical results show that ETS had a positive effect on GTFEE.A series of robustness tests revealed that the results were robust.Potential mechanisms through which ETS can improve GTFEE include the promotion of technological innovation and the upgrading of industrial structure.The positive effects varied in different cities and diferent regions-the result was pronounced in eastern China and developed cities,but it was insignificant in central and western areas and developing cities.This study confirms the satisfactory performance of China's ETS in improving GTFEE,and this is relevant for other emerging countries.

Green economic efficiency in the Yangtze River Delta:spatiotemporal evolution and influencing factors

Based on economic-social-resource-environment perspective,which people’s welfare was considered compared with the traditional perspective,using SSU and PP model,spatial analysis method,spatial econometric model to study green economy efficiency(GRE)of 26 Cities in the Yangtze River Delta from 2005 to 2015.The results show the following:Corrected GRE is markedly lower than conventional efficiency;Stage characteristics are obvious of GRE.An overall spatial pattern has emerged of lower efficiency in the east and higher efficiency in the west,and exist clear signs of spatial agglomeration.The spatial Dubin model has abetter fitting effect.The biggest direct effect on local green economic efficiency and spatial spillover effects on nearby areas is proportion of tertiary industry.

Investigating the role of emissions trading policy to reduce emissions and improve the efficiency of industrial green innovation

Rapid economic development usually leads to serious environmental pollution problems.In order to solve the problem of pollutant emission in sustainable industrial development,it is urgent to examine the implementation effect of emissions trading policy(ETP)and its impact on green industrial development.This study adopts China's ETP as a case study and selects provincial panel data from 2004 to 2018.We first use a non-radial,non-directed,slack-based measure-directional distance function(SBM-DDF)to measure industrial green innovation efficiency.Then we use a difference in differences(DID)model to empirically test the emissions reduction effect of China's policy and whether it promotes industrial green innovation.Thereafter,results show that:(1)the ETP reduces sulfur dioxide(SO2)emissions indicating the effectiveness of the policy;(2)the policy significantly improves industrial green innovation efficiency,meaning it promotes the sustainable development of the economy;(3)heterogeneity analysis highlights that ETP produces greater benefits for the most polluted regions of China which have more strict environmental regulations.The study examines the effect of emissions trading policy implementation from a new perspective.The study also provides a reference point for China to further refine its policy mechanisms and for other countries to formulate suitable ETP.

Over 9% efficiency achieved for all-polymer solar cells processed by a green solvent

Bulk-heterojunction polymer solar cells （PSCs） have at- tracted considerable attention owning to their potential for fabricating flexible, light-weight and large area solar cell panels via high-throughput roll-to-roll technologies. Compared with conventional PSCs comprising small mol- ecule acceptors, such as fullerenes, all-polymer solar cells （all-PSCs） containing blends of p-type/n-type polymers in the photoactive layer provide advantages including easily tunable absorption band, enhanced absorption coefficient,

Fuel efficient,environmental protection,green manufacturing The orientation of China's auto industry--experts

Green manufacturing is a new way out for the auto industry—ZHAO Hang, president of CATARC The green manufacturing means a lot, in terms of the manufacturing process, material and techniques. China spares no efforts to producing vehicles and it