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...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.展开更多
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 ...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.展开更多
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....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 spatiotem-poral heterogeneity of NTU on GDE.The results showed that NTU improved,with the highest levels observed in the eastern region,while GDE increased with fluctuations,performing better in both the eastern and western regions.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,its impact on GDE strengthened significantly,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 promote GDE through NTU in China and serve as a valuable reference for sustainable global urbanization.展开更多
Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still...Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still insufficient.Using the super-efficiency epsilon-based measure Malmquist model,kernel density estimation,and spatial econometric model,this study investigated the spatiotemporal evolution characteristics and influencing factors of green innovation efficiency(GIE)in Northeast China from 2005 to 2020.The results reveal that:1)The GIE in Northeast China has obvious phased characteristics,where 2005-2011 was a period of fluctuating decline while 2012-2020 was a period of fluctuating increase,reflecting the severe resource and environmental constraints faced by the green innovation process.2)The GIE in the Northeast China has a significant spatial dependence,which has not formed a relatively stable spatial club feature.The process for improving the GIE in the Northeast China in the future is still arduous and far off.3)The interweaving and mutual influence of nonequilibrium factors have led to the diversity and complexity of the spatiotemporal pattern evolution of GIE.Overall,the level of economic development and industrial structure has a positive effect,while foreign investment and industrial agglomeration have a negative effect.The direct effects of government regulation,resource endowment,science and technology,environmental regulation,and urbanization are not significant.The research conclusion of this article can provide important reference for the revitalization of Northeast China.展开更多
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...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.展开更多
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 soc...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.展开更多
Developing a green economy is key to achieving the 2030 Sustainable Development Goals. This paper uses the SBM-GML index, which includes non-desired outputs, to measure the trend of regional green economic efficiency ...Developing a green economy is key to achieving the 2030 Sustainable Development Goals. This paper uses the SBM-GML index, which includes non-desired outputs, to measure the trend of regional green economic efficiency changes and analyze the impact mechanism and realization path of industrial transformation on green economic efficiency. The research results show that advanced industrial structure has a positive influence on green economic efficiency nationwide, while energy utilization structure and energy utilization efficiency have positive partial intermediary effects in the influence path;industrial structure rationalization is also significantly positively related to green economic efficiency nationwide, and the mediating effect of energy utilization is positive. The impact of industrial transformation on green economic efficiency has regional heterogeneity, and the mediating effect of energy use also differs. Among them, the impact effect in the eastern region is basically consistent with the national sample, but is negative in the central and western regions. This paper proposes countermeasures in terms of adjusting the industrial structure, improving energy efficiency, and perfecting industrial and energy policies, which can provide theoretical and practical references for promoting the transformation and upgrading of regional industrial structure, optimizing energy utilization, and advancing the efficiency of the national and regional green economy.展开更多
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...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.展开更多
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 c...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.展开更多
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 othe...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.展开更多
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 dimensiona...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.展开更多
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....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.展开更多
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 th...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.展开更多
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 o...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.展开更多
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 a...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.展开更多
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. ...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.展开更多
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 a...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.展开更多
Agriculture is undergoing a pivotal transformation,shifting from a singular focus on food security to interdisciplinary research that encompasses food security,environmental protection and sustainable use of resources...Agriculture is undergoing a pivotal transformation,shifting from a singular focus on food security to interdisciplinary research that encompasses food security,environmental protection and sustainable use of resources.The growing global population and climate change exert the urgency to adopt sustainable practices that balance crop productivity and environmental stewardship.The merit of the approach of past agricultural research,typically centered on single processes and limited to specific disciplines and goals,is now a subject to debate.There is need for a multi-objective approach,an enhancement of the whole industry chain enhancement(involves service from the initial raw material stage to the final consumer)and a holistic approach for sustainable agricultural development.To address these challenges,this article presents an innovative agricultural system research approach.This approach integrates interdisciplinary research and advocates for a combined top-down and bottom-up strategy.The concept of innovative agriculture refers to redesigning systems through technological integration for large-scale application,ultimately aiming to enhance overall crop production,environmental sustainability and efficiency.The top-down approach sets yield targets and environmental thresholds at various scales,aligning with national objectives for food security,resource use efficiency and ecological sustainability.This method determines the necessary technical systems and integration methods.In contrast,the bottom-up approach based on Science and Technology Backyard,analyzes the factors that constrain high crop yields and efficiency,and develops systematic methods to achieve high yield and high efficiency.The integrated agricultural research approach can simultaneously address food security challenges,enhances resource use efficiency,and protect the environmental sustainability.This is essential for advancing sustainable agricultural practices in the face of increasing global demands and environmental concerns.展开更多
Rough tourism growth does not promote dual-carbon goals nor the implementation of a comprehensive saving strategy.Accordingly,the booming development of the digital economy in recent years has provided new momentum fo...Rough tourism growth does not promote dual-carbon goals nor the implementation of a comprehensive saving strategy.Accordingly,the booming development of the digital economy in recent years has provided new momentum for structural upgrades and green growth in the tourism industry.This study aims to test the impact and mechanism of developments in the digital economy on the green innovation efficiency(GIE)of the tourism industry.Using provincial panel data from 2011 to 2019,this study quantifies the GIE of the tourism industry using the Su-per-SBM model of unexpected output.In this study,the digital economy development index was measured using principal component analysis and empirically analyzed using a two-way fixed effects regression model.The results of the study revealed that the development of the digital economy has promoted in large part the improvement of Chinese tourism GIE;the enhancement effect of the digital economy development on the eastern region is more noticeable than that of central and western regions;the digital economy can promote the enhancement of Chinese tourism GIE by promoting innovation in green technology and upgrades to industrial structure.Moreover,a distinct threshold in the promotion of tourism GIE by the digital economy exists,corresponding to a nonlinear diminishing marginal product.This study provides a new perspective for assessing the impact of the digital economy on the development of tourism GIE.Moreover,it provides a policy reference for exploring the path of tourism GIE and re-alizing high-quality development.展开更多
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 R...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.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41971222)Planning Project of Philosophy and Social Science in Henan Province(No.2019BJJ019)+2 种基金Program for Innovative Research Team(in Science and Technology)in University of Henan Province(No.21IRTSTHN008)Graduate Education Quality Curriculum Construction Project of Henan Province(No.HNYJS2016KC24)First Class Discipline Development Project in Henan University(No.2019YLZDYJ12)。
文摘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.
基金National Key Research and Development Program of China(2019YFB1600400)National Natural Science Foundation of China(72174035)+2 种基金National Natural Science Foundation of China(71774018)Liaoning Revitalization Talents Program(XLYC2008030)Liaoning Provincial Natural Science Foundation Shipping Joint Foundation Program(2020-HYLH-20)。
文摘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.
基金supported by the Third Xinjiang Scientific Expedition Program(Grant No.2021xjkk0905)the National Natural Science Foundation of China(Grant No.42121001).
文摘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 spatiotem-poral heterogeneity of NTU on GDE.The results showed that NTU improved,with the highest levels observed in the eastern region,while GDE increased with fluctuations,performing better in both the eastern and western regions.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,its impact on GDE strengthened significantly,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 promote GDE through NTU in China and serve as a valuable reference for sustainable global urbanization.
基金Under the auspices of the National Natural Science Foundation of China(No.42571228,42401212)National Natural Science Foundation of Shandong(No.ZR2024MD022)。
文摘Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still insufficient.Using the super-efficiency epsilon-based measure Malmquist model,kernel density estimation,and spatial econometric model,this study investigated the spatiotemporal evolution characteristics and influencing factors of green innovation efficiency(GIE)in Northeast China from 2005 to 2020.The results reveal that:1)The GIE in Northeast China has obvious phased characteristics,where 2005-2011 was a period of fluctuating decline while 2012-2020 was a period of fluctuating increase,reflecting the severe resource and environmental constraints faced by the green innovation process.2)The GIE in the Northeast China has a significant spatial dependence,which has not formed a relatively stable spatial club feature.The process for improving the GIE in the Northeast China in the future is still arduous and far off.3)The interweaving and mutual influence of nonequilibrium factors have led to the diversity and complexity of the spatiotemporal pattern evolution of GIE.Overall,the level of economic development and industrial structure has a positive effect,while foreign investment and industrial agglomeration have a negative effect.The direct effects of government regulation,resource endowment,science and technology,environmental regulation,and urbanization are not significant.The research conclusion of this article can provide important reference for the revitalization of Northeast China.
基金National Natural Science Foundation of China,No.41771131China Scholarship Council,No.202008110050Key Program for Scientific Research of Beijing Union University,No.SKZD202306。
文摘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.
基金Under the auspices of the National Natural Science Foundation of China(No.71974070)‘CUG Scholar'Scientific Research Funds at China University of Geosciences(Wuhan)(No.2022005)。
文摘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.
基金supported by National Natural Science Foundation of China [grant numbers 42371194]。
文摘Developing a green economy is key to achieving the 2030 Sustainable Development Goals. This paper uses the SBM-GML index, which includes non-desired outputs, to measure the trend of regional green economic efficiency changes and analyze the impact mechanism and realization path of industrial transformation on green economic efficiency. The research results show that advanced industrial structure has a positive influence on green economic efficiency nationwide, while energy utilization structure and energy utilization efficiency have positive partial intermediary effects in the influence path;industrial structure rationalization is also significantly positively related to green economic efficiency nationwide, and the mediating effect of energy utilization is positive. The impact of industrial transformation on green economic efficiency has regional heterogeneity, and the mediating effect of energy use also differs. Among them, the impact effect in the eastern region is basically consistent with the national sample, but is negative in the central and western regions. This paper proposes countermeasures in terms of adjusting the industrial structure, improving energy efficiency, and perfecting industrial and energy policies, which can provide theoretical and practical references for promoting the transformation and upgrading of regional industrial structure, optimizing energy utilization, and advancing the efficiency of the national and regional green economy.
基金supported by the National Natural Science Foundation of China[Grant No.72163018]the Yunnan College Students’Innovation and Entrepreneurship Training Program[Grant No.S202310674173]the Yunnan Province Basic Research Program General Project[Grant No.202401AT070393].
文摘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.
基金Jiangxi Provincial Social Science Foundation Project“Research on the Impact of Digital Economy Development on Employment Structure and Quality in Jiangxi Province and Countermeasures”(Grant No.23YJ55D)Jiangxi Province University Humanities and Social Sciences Research Project“Research on the Dynamic Mechanism and Countermeasures of Industrial Digitalization to Promote the High-Quality Development of Jiangxi’s Manufacturing Industry”(Grant No.JJ22218).
文摘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.
基金This research was financially supported by the National Social Science Fund of China(No.18BJY038)National Natural Science Foundation of China(No.72071220)+1 种基金Heilongjiang Philosophy and Social Science Research Planning Project(No.16GLB09)First Class Academic Discipline Construction Project of Central University of Finance and Economics(No.20190807-8).
文摘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.
基金supported by the Humanities and Social Science project of Ministry of Education of China[Grant Number:16YJA790036]the National Natural Science Foundation of China[Grant Number:71503272]
文摘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.
基金Under the auspices of National Natural Science Foundation of China(No.41771138,41801105)。
文摘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.
基金This research is supported by Shanxi Province Philosophy and Social Science Project(Grant No.W20191012)Shanxi province Soft Science Project(Grant No.2019041015-1).
文摘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.
基金Under the auspices of Chinese Ministry of Education Humanities and Social Sciences Project(No.19YJCZH241)Project of Chongqing Social Science Planning Project of China(No.2020QNGL38)+1 种基金Science and Technology Research Program of Chongqing Education Commission of China(No.KJQN201901143)Humanities and Social Sciences Research Program of Chongqing Education Commission of China(No.20SKGH169)。
文摘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.
文摘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.
基金Supported by the National Natural Science Foundation of China under Grant No 61334001the National Key Research and Development Program of China under Grant Nos 2016YFB0400600,2016YFB0400601 and 2016YFB0400100+1 种基金the National Science Foundation for Young Scientists of China under Grant No 21405076the Fund for Less Developed Regions of the National Natural Science Foundation of China under Grant No 11364034
文摘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.
基金supported by the Chongqing Social Science Planning Fund,China(2023BS034)the Science and Technology Project of Chongqing Jiaotong University,China(F1230069).
文摘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.
文摘Agriculture is undergoing a pivotal transformation,shifting from a singular focus on food security to interdisciplinary research that encompasses food security,environmental protection and sustainable use of resources.The growing global population and climate change exert the urgency to adopt sustainable practices that balance crop productivity and environmental stewardship.The merit of the approach of past agricultural research,typically centered on single processes and limited to specific disciplines and goals,is now a subject to debate.There is need for a multi-objective approach,an enhancement of the whole industry chain enhancement(involves service from the initial raw material stage to the final consumer)and a holistic approach for sustainable agricultural development.To address these challenges,this article presents an innovative agricultural system research approach.This approach integrates interdisciplinary research and advocates for a combined top-down and bottom-up strategy.The concept of innovative agriculture refers to redesigning systems through technological integration for large-scale application,ultimately aiming to enhance overall crop production,environmental sustainability and efficiency.The top-down approach sets yield targets and environmental thresholds at various scales,aligning with national objectives for food security,resource use efficiency and ecological sustainability.This method determines the necessary technical systems and integration methods.In contrast,the bottom-up approach based on Science and Technology Backyard,analyzes the factors that constrain high crop yields and efficiency,and develops systematic methods to achieve high yield and high efficiency.The integrated agricultural research approach can simultaneously address food security challenges,enhances resource use efficiency,and protect the environmental sustainability.This is essential for advancing sustainable agricultural practices in the face of increasing global demands and environmental concerns.
基金The National Natural Science Foundation of China(42271238)The Guangdong Natural Science Foundation for Basic and Applied Basic Research(2023A1515011882)。
文摘Rough tourism growth does not promote dual-carbon goals nor the implementation of a comprehensive saving strategy.Accordingly,the booming development of the digital economy in recent years has provided new momentum for structural upgrades and green growth in the tourism industry.This study aims to test the impact and mechanism of developments in the digital economy on the green innovation efficiency(GIE)of the tourism industry.Using provincial panel data from 2011 to 2019,this study quantifies the GIE of the tourism industry using the Su-per-SBM model of unexpected output.In this study,the digital economy development index was measured using principal component analysis and empirically analyzed using a two-way fixed effects regression model.The results of the study revealed that the development of the digital economy has promoted in large part the improvement of Chinese tourism GIE;the enhancement effect of the digital economy development on the eastern region is more noticeable than that of central and western regions;the digital economy can promote the enhancement of Chinese tourism GIE by promoting innovation in green technology and upgrades to industrial structure.Moreover,a distinct threshold in the promotion of tourism GIE by the digital economy exists,corresponding to a nonlinear diminishing marginal product.This study provides a new perspective for assessing the impact of the digital economy on the development of tourism GIE.Moreover,it provides a policy reference for exploring the path of tourism GIE and re-alizing high-quality development.
基金Under the auspices of the post-funded project of National Social Science Foundation of China(No.16FJL009)
文摘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.
