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The reduction of carbon emissions in the power industry will play a vital role in global decarbonization. The power industry has three main strategies to achieve this reduction in emissions: to implement lean marketing strategies that effectively target users of power and encourage them to adopt decarbonizing technologies and services; to optimize the efficiency of these users of power; and to improve the efficiency of renewable energy sources. This paper establishes a comprehensive evaluation system of indexed data from power industry customers for the development of lean marketing strategies. This system evaluates indexes derived from customer data on renewable energy sources, carbon emissions, energy efficiency, and customer credit. It adopts the DEMATEL–CRITIC combination weight assignment and VIKOR method for system evaluation and conducts simulation experiments on customer data in a region of Northeastern China to give an example of how this method could be applied in practice to lean marketing. The results show that the evaluation system proposed in this paper can govern the lean marketing decision-making of power sales enterprises. [ABSTRACT FROM AUTHOR]

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

Abstract Theses on China's low-carbon economy focus on the driving forces of carbon emissions, energy–carbon efficiency, and the carbon–economy nexus. Meanwhile, comprehensive frameworks that assess China's green economy and also analyze its driving forces are lacking. This paper constructs a green productivity index based on the Global Malmquist–Luenberger productivity index to evaluate the development of the low-carbon economy in China. A panel vector auto-regression model is adopted to further analyze the endogenous interactions and dynamic relationships among aspects of the green economy and its influencing factors. Empirical results show that China has seen a balanced development of green economic growth in 2000–2016, achieved in a series of clear stages. To maintain the sustainable growth of the low-carbon economy in the future, China must rely more on technological progress. This research also makes some important discoveries that have not been found in previous studies: the impact of China's industrial structure and energy consumption structure on the green economy are short term, having a duration of impact of approximately four years. Finally, we provide an assessment of provincial green economy development and describe the corresponding policy implications. Graphical abstract Image Highlights • A comprehensive analysis of China's green economy. • A slack-based Global Malmquist–Luenberger index is adopted to calculate the Green Productivity Index in China. • The stage characteristics of green economic development are identified. • A panel vector autoregressive model is used to analyze the interactions among aspects of the environmental economic system. • The findings that the impact duration of energy structure, industry structure, and urbanization on the green economy is about four years. [ABSTRACT FROM AUTHOR]

This paper mainly investigates the relationship among energy consumption, carbon emissions and economic growth in China from 1952 to 2012. First, we implement unit root and cointegration analysis to test the stationary. Furthermore, we analyze the mutual influence among energy consumption, carbon emissions and economic growth through Granger causality analysis. Next, we also conduct static and dynamic regression analysis on the determinants of carbon emissions and economic growth. Last, we predict the future influence of different energy consumption on carbon emissions and economic growth. We find that coal has dominant impact on economic growth and carbon emissions. GDP (Gross Domestic Product) has bi-directional relationship with CO 2 (carbon dioxide) emission, coal, gas, and electricity consumption. It is imperative to change energy consumption structure in China. We had better decrease coal consumption rate. It is significant to develop hydro and nuclear power in China. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the relationship between renewable energy consumption and economic growth in China for the period 1977–2011. Autoregressive Distributed Lag approach (ARDL) to cointegration and Johansen cointegration techniques are employed by including intermittent variables namely carbon dioxide emissions and labor. We also employed Granger causality test in order to determine the direction of the causality among the variables. The results show that there is a bi-directional long term causality between renewable energy consumption and economic growth. This finding implies that growing economy in China is propitious for the development of renewable energy sector which in turn helps to boost economic growth. We also find that labor influences renewable energy consumption in the short term. However, there is no evidence of long or short run causality between carbon emissions and renewable energy consumption. This implies that actual level of renewable energy in China is still insignificant and not considerably exploited in order to contribute to the mitigation of carbon dioxide emissions. [ABSTRACT FROM AUTHOR]