In order to investigate the impact of green energy technology on the environmental sustainability of China, take the Beijing-Tianjin-Hebei region as an example, this paper first calculates the per capita ecological footprint (ef), ecological carrying capacity (ec) and ecological deficit (ed) of China and Beijing-Tianjin-Hebei region from 1990 to 2019 by using the ecological footprint (EF) model, and then uses an expanded STIRPAT model and Partial Least Squares (PLS) regression to explore the impact and importance of green energy technology on EF in China and Beijing-Tianjin-Hebei region. It is found that the ec of China and Beijing-Tianjin-Hebei region is much lower than that of the ef from 1990 to 2019. It is always in the state of ecological deficit, and the sustainable development is faced with severe challenges. Progress in green energy technology can significantly reduce the EF of China and Beijing-Tianjin-Hebei region. The importance of each factor on the EF of China and Beijing-Tianjin-Hebei region is different. The degree of dependence on foreign trade and urbanization rate are important influencing factors of Beijing’s EF. Urbanization rate, per capita GDP, population size, energy consumption per unit GDP and built-up area are the important influencing factors of EF in Tianjin and Hebei. Therefore, to reduce the EF of Beijing, Tianjin and Hebei, it is necessary to accelerate the progress of green energy technology, develop compact ecological city and change people’s consumption patterns.
In order to examine the key determinants of carbon dioxide emissions and judge whether China’s carbon dioxide emissions can reach their peak value before 2030, this study first uses the extended STIRPAT model to analyze the determinants of China’s carbon dioxide emissions from 1995 to 2019 and then uses the model regression result to forecast the carbon dioxide emissions from 2020 to 2040 under six scenarios to investigate their prospect. It is found that population size, GDP per capita, energy intensity, the share of coal consumption, urbanization level, the share of secondary industry, and investment have significant positive effects on carbon dioxide emissions. Among them, the influence of population size is the biggest and energy intensity is the weakest. China’s carbon dioxide emissions can reach their peak in 2029 under the baseline scenario. Increasing the rate of population growth, energy intensity, and share of coal consumption will push back the peak year. A lower rate of economic growth and share of the secondary industry will bring the peak year forward. Therefore, it is necessary to optimize the industrial structure and energy consumption structure, reduce the energy intensity, and control the population size in order to achieve the goal of peaking carbon dioxide emissions as soon as possible.
The growth of green-oriented businesses for sustainable development (SD) is no longer optional in the current dynamic world, especially for manufacturing businesses in general. Accordingly, the present study investigates the interlinkages between green organizational strategy (GOS), environmental corporate social responsibility (ECSR), and organizational sustainable performance (OSP) by exploring the key mediating role of green technology innovation (GTI). This study uses a quantitative method to gather data from Chinese manufacturing industries, employing a well-structured questionnaire. Senior and middle-level managers were the intended respondents. From the primary survey, 264 valid responses were gathered. The final data were analyzed using SmartPLS (version 3.3.9) by adopting structural equation modeling (SEM) to examine the associations between the targeted constructs, and the results add to the recent literature by offering a cohesive model of GOS, ECSR, GTI, and OSP. The findings revealed that GOS has a strong positive effect on ECSR, GTI, and OSP. Further, ECSR has a strong positive impact on GTI and OSP. Meanwhile, GTI is a key mediating variable in these relationships, which previous studies have not explored. This study innovatively integrates the three green traits, namely, GOS, ECSR, and GTI, into a comprehensive model that is understudied in existing literature in order to help businesses improve their sustainable competitive advantage. The ultimate aim is to help businesses improve their environmental performance and achieve solid sustainability over the long term.
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