Dynamic Changes, Spatiotemporal Differences and Factors Influencing the Urban Eco-Efficiency in the Lower Reaches of the Yellow River

Abstract

The measurement of eco-efficiency is an important tool to evaluate the level of urban sustainable development. Therefore; improving urban eco-efficiency in the lower reaches of the Yellow River ensures the implementation of ecological protection and high-quality development strategies in the Yellow River Basin. In this study; the dynamic changes of urban eco-efficiency and spatiotemporal differences in the lower reaches of the Yellow River were investigated using the Super-SBM (Super-Slack measure model) model with undesirable outputs and standard deviation ellipse. The STIRPAT (Stochastic Impacts by Regression Population; Affluence and Technology) model was introduced to analyze the factors affecting the change in urban eco-efficiency. The results showed that the overall urban eco-efficiency in the lower reaches of the Yellow River has not reached the optimal level. The overall eco-efficiency in the lower reaches of the Yellow River in Shandong Province was higher than that in Henan Province but the gap is narrowing. The spatial differentiation of urban eco-efficiency in the lower reaches of the Yellow River showed the following trends: “blooming in the middle and reverse development at both ends” in the high-value area and gradual decrease in the low-value area. From 2007 to 2018; a direction was notable with respect to the development of urban eco-efficiency in the lower reaches of the Yellow River; with the centripetal force weakening. Although the mean center of urban eco-efficiency located in Shandong Province; it notably shifted to the west during the study period. In terms of driving factors; affluence and technological progress play positive roles in driving eco-efficiency; while investment intensity; industrial structure; and foreign investment intensity hindered the optimization and improvement of urban eco-efficiency in the lower reaches of the Yellow River. The results of this study show that urban eco-efficiency in the lower reaches of the Yellow River is improving; but the regional coordination is poor. The main methods promoting the sustainable development in the study area include changing the mode of extensive investments and the introduction of foreign capital; which improve the energy efficiency and promote faster and better economic development

Spatial-Temporal Pattern and Influencing Factors of Ecological Efficiency in Zhejiang—Based on Super-SBM Method

“…Since then, Tone also proposed a Super-SBM model in conjunction with the super-efficiency DEA model, which remedies the shortcoming of the SBM model that cannot achieve a complete ranking of DMUs [ 34 ]. Recently, some scholars have used the improved Super-SBM DEA method to measure the ecological efficiency of regions [ 35 , 36 ]. However, undesirable outputs are not considered in most of the articles.…”

“…The DEA method and Malmquist index model measure the efficiency of the DMUs, and the two methods do not obtain the key factors affecting the DMUs [ 20 , 35 ]. Therefore, to make more targeted recommendations and suggestions with guidance for the DMUs, an effective influence factor analysis method is needed for analysis.…”

Evolution Characters and Influencing Factors of Regional Eco-Efficiency in a Developing Country: Evidence from Mongolia

“…In the existing research, economic development [70], green technology [70], industry structure [71], population or labor force [42,72], capital [30,31,72], and environmental regulation [73] were the main influencing factors for improving the regional eco-efficiency or green and sustainable development. Therefore, this article referenced existing research [74][75][76] and incorporated the below indicators in the panel Tobit regression model to analyze the influencing factors of eco-efficiency in Mongolia.…”

“…On the city scale, Ren et al (2020) applied the Hybrid distance model (S-EBM) to measure the eco-efficiency of 283 prefecture-level cities in China from 2003 to 2013 and found that an increase in eco-efficiency in surrounding cities would improve eco-efficiency in local cities [29]. Zhang et al (2020) analyzed the regional eco-efficiency of cities along the lower reaches of the Yellow River from 2007 to 2018 using the super SBM model and found that affluence and technological progress were the main drivers of eco-efficiency [30]. Yao et al (2021) used the epsilon-based measure data envelopment analysis (EBM-DEA) model to analyze the regional eco-efficiency of 28 Russian cities along the Northern Sea Route and found that the cities with higher levels of GRPs per capita had higher eco-efficiency [31].…”

Spatial and Temporal Differences in the Green Efficiency of Water Resources in the Yangtze River Economic Belt and Their Influencing Factors

“…As an essential factor in production and life, water resource utilization efficiency has been a hot topic in academia. Improving water use efficiency is the primary way to sustain water resources [ 1 , 2 ]. An efficient and accurate evaluation method depends on water resource utilization and efficiency evaluation.…”