Analysis of the interval difference and spatial effects of Chinese green economic progress

Abstract

A green economy refers to a modern form of harmony between the environment and the economy. China showing the fastest economic growth in the world has entered into a new phase of advance, facing a critical industrial transformation and progression. The paper aims to analyse China's green economic development considering the differences in development of regions. The study applied the ultra-efficient slacks-based measure model to scrutinize China's green economic development efficiency. Dagum Gini coefficient and Kernel density methods are used to estimate spatial characteristics, local adjustments, and dynamic evolution trends. The analysis is based on an annual dataset of 30 Chinese provinces from 2010 to 2019. The findings did not confirm extensive China's green economic development. In contrast, the development efficacy reveals an influential drive over the years. Regional green development is detected as unstable and diverges due to interregional differences. The findings showed that environmental regulation, government investment, industrial structure, education development were 0.0648, 0.00154, 0.0035 and 0.118 (significant at 5% and 1%), respectively. Besides, they stimulate the green economic development in the analysed regions. However, urbanization and openness of economy had the negative value. It confirmed their restriction impact on the green economic development. In addition, the findings showed that ongoing Chines policy on management of environmental development is the priority direction and provoke the declining the environmental pollution. Besides, the modernization and optimization of the Chinese industry structure stimulate the further green economic progress.

The role of environmental risk management in company profitability within sustainable development goals

“…To investigate the impact of the introduction of an environmental risk management system on the profitability of the enterprise, a PLS-SEM (partial least squares structural equation modelling) model was developed in the study. In contrast to the traditional SEM, the PLS-SEM possesses the capability to model and assess intricate causal relationships involving both hidden (latent) and observable variables [126][127][128][129][130][131][132][133][134][135][136][137][138][139][140][141][142][143][144]. Latent variables encapsulate phenomena that are not directly observable and are defined by a set of observable variables.…”

Does Free Compulsory Education Matter for the Green Transformation of Agriculture? Evidence from Rural China

“…There are also studies that investigate environmental education and its effects on farmers' low-carbon practices [29,30]. Additionally, some studies have highlighted the moderating role of educational human capital in investigating the influence of other factors on green production [31,32].…”

Digital Marketing and Sustainable Economic Development Trends in Developed and Underdeveloped Countries: A Bibliometric Analysis

“…Developed countries continue to collaborate and invest in digital marketing through research and innovations, and there has been a growing trend since 2000, while underdeveloped countries invest little and remain underdeveloped. Digital marketing tactics help to advance sustainable development by encouraging sustainable consumption habits through the analysis of customer behavior [25,[66][67][68][69][70][71][72][73][74][75][76]. Contemporary consumers depend on digital platforms for product and service information before patronage, hence the need for both developed and underdeveloped countries to research digital marketing.…”