The moderate level of digital transformation: from the perspective of green total factor productivity.

In the context of accelerated development of the digital economy, whether enterprises can drive green total factor productivity (GTFP) through digital technology has become the key to promoting high-quality development of the economy and achieving the goal of "dual-carbon", However, the relationship between digital transformation and GTFP is still controversial in existing studies. Based on the data of 150 listed companies in China's A-share energy industry from 2011 to 2021, this study empirically analyzes the impact of digital transformation on GTFP using a fixed-effect model. The study shows an inverted U-shaped nonlinear effect of digital transformation on enterprises' GTFP, and the conclusion still holds after a series of robustness tests. Mechanism analysis shows that enterprise investment efficiency and labour allocation efficiency play a significant mediating role in the above inverted U-shaped relationship, in which the inverted U-shaped relationship between digital transformation and GTFP mainly stems from the influence of enterprise investment efficiency. Heterogeneity analysis finds that the inverted U-shaped relationship between digital transformation and GTFP of enterprises is more significant in large-scale enterprises, new energy enterprises and enterprises in central and western regions. The study's findings provide important insights for enterprises to promote digital transformation and realize the green and high-quality development of the energy industry.

Healthcare services efficiency and its intrinsic drivers in China: based on the three-stage super-efficiency SBM model.

BACKGROUND: The purpose of this study is to examine the development of healthcare services efficiency in China since the reform of the healthcare system. By examining the development environment of healthcare services in China and examining the driving factors affecting the efficiency of healthcare services, we provide a reference for the future high-quality development of healthcare services in China. METHODS: A three-stage super-efficient slack-based measure (SBM) model with undesirable outputs was used to measure the efficiency of healthcae services in 31 Chinese provinces from 2009 to 2021, and a global Malmquist-Luenberger (GML) index was used to assess their spatiotemporal evolution characteristics and internal influencing mechanisms of healthcare services efficiency. RESULTS: The empirical results showed that the efficiency of China's healthcare services changed significantly from 2009-2014 and then remained stable. During the study period, the efficiency of healthcare services in the eastern region was higher than the national level, while it was lower in the western region. The results of the analysis of environmental factors indicated that an increase in population density reduced the redundancy of healthcare input resources and that economic development as well as an increase in government subsidies, contributed to an increase in the redundancy of healthcare input resources. The main contribution to the growth of healthcare sercices efficiency in China came from the technological innovation effect, and the growth was most significant in the western region. CONCLUSION: From 2009 to 2021, the efficiency of national healthcare services generally showed a slow upward trend, and the efficiency of healthcare services varied widely among regions. Under the existing environmental constraints, relevant departments in each region should strengthen technological innovation in healthcare services, completely focus on the regional catch-up effect, and promote the balanced development of regional health.

Spatio-temporal evolution characteristics of eco-efficiency in the Yellow River Basin of China based on the super-efficient SBM model.

It is of great significance to study the trends and internal differences of eco-efficiency in the Yellow River Basin for ecological protection and high-quality development of the Yellow River Basin. According to the characteristics of the Yellow River Basin in China, the eco-efficiency evaluation system was constructed, and the super-efficiency slack-based measure (SBM) model and the super-efficiency SBM model of undesired output were used to calculate the eco-efficiency levels of provinces in the Yellow River Basin from 2005 to 2020, and the variation trend and internal differences were analyzed. The results show that when only the expected output was considered, the eco-efficiency of the Yellow River Basin as a whole and each province showed a fluctuating upward trend, but there were obvious differences. Qinghai Province, Sichuan Province, and Ningxia Autonomous Region had high eco-efficiency, while Shaanxi Province, Shanxi Province, and Inner Mongolia Autonomous Region had low eco-efficiency. Compared with only considering the expected outputs, eco-efficiency of Qinghai Province had improved significantly when considering non-expected outputs. The eco-efficiency of Shandong Province and Henan Province had improved significantly after 2016, while the eco-efficiency of the two provinces had decreased significantly before 2016. The eco-efficiency of Shaanxi, Shanxi, Inner Mongolia, Ningxia, and Gansu had declined to varying degrees. Finally, the reasons for the differences in eco-efficiency in various provinces in the Yellow River Basin were analyzed, and suggestions for improving the eco-efficiency of the Yellow River Basin were put forward.

Research on the ecological efficiency of the Yangtze River Delta region in China from the perspective of sustainable development of the economy-energy-environment (3E) system.

Balancing the relationship between economic development, energy utilization, and environmental protection has become an important task in China's Strip Planning and Construction. This article takes the annual panel data from 2005 to 2015 as the research object firmly grasps the research basis of the Economy-Energy-Environment (3E) System, and focuses on building a new research framework from both internal and external perspectives of the eco-efficiency index to achieve the exploratory research on regional ecological efficiency changes and influencing factors. First of all, it uses super-efficient slacks-based measure (SBM) model which introduces undesired outputs to measure eco-efficiency at different levels. Then, it applies Malmquist index to calculate total factor productivity and structural efficiencies. Finally, it selects six indicators and uses the STIRPAT regression model to analyze external factors. The results indicate that (1) the overall ecological efficiency is effective and maintaining a good momentum of development. Among all the cities and provinces, Shanghai and Zhejiang provinces play the role of "stabilizers," while Jiangsu and Anhui provinces act as "accelerators." (2) All 41 prefecture-level cities can be divided into four different types, i.e., "high-high", "low-high", "low-low," and "high-low" cities, and there is an obvious phenomenon of spatial clustering; (3) pure technical efficiency and scale efficiency is the core driving force for the improvement of ecological efficiency. (4) Anhui and Jiangsu provinces show a U-shaped relationship, while Zhejiang province shows an inverted U-shaped relationship. Graphical abstract The structure of introduction-body paragraphs-conclusion carbon.