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.

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.

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.