引领可再生能源技术创新和绿色供应链管理：构建促进中国生态质量的新框架

IF 14.2 2区经济学 Q1 ECONOMICS

Energy Economics Pub Date : 2025-02-01 DOI:10.1016/j.eneco.2025.108178

Xiaoxi Liu , Yunqiu Zhan , Dingwen Si , Zhen Wang

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引用次数: 0

摘要

绿色供应链管理和可再生技术创新是可持续发展目标9的组成部分。此外，它是生产环保能源的基础，间接有助于实现可持续发展目标9。从化石燃料转向绿色能源对可持续发展和促进生态友好环境至关重要。因此，本研究考察了1990年第一季度至2022Q4年间生态质量的主要驱动力（以承载能力因子为代表）。其他因素，包括天然气消费和能源价格，也被研究。利用最近提出的基于分位数的KRLS和格兰杰因果关系来解决序列的非线性和非正态分布。QQKRLS研究结果表明，可再生能源技术创新提高了各分位数的负荷能力因子，从而改善了生态质量。另一方面，在所有分位数中，天然气消费、能源价格、经济增长、城市化和绿色供应链管理降低了LCF，从而降低了生态质量。QQGC结果表明，所有回归因子（可再生能源技术创新、天然气消费、能源价格、经济增长和绿色供应链管理）都可以显著预测所有分位数的LCF。该研究根据这些发现制定政策。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Navigating renewable technological innovations and green supply chain management: Crafting a novel framework for boosting ecological quality in China

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Navigating renewable technological innovations and green supply chain management: Crafting a novel framework for boosting ecological quality in China

Green supply chain management and renewable technological innovations are integral to sustainable development goal (SDG) 9. Additionally, it serves as the basis for generating eco-friendly energy, indirectly contributing to the achievement of SDG 9. The shift from fossil fuels to green energy sources is crucial for sustainable development and promoting an eco-friendly setting. Therefore, this study examines the major driving forces of ecological quality (proxied by load capacity factor) between 1990Q1 and 2022Q4. Other factors, including natural gas consumption and energy prices, are also studied. The recently proposed quantile-based KRLS and Granger causality are utilized to solve the non-linear and non-normal distribution of the series. The findings of QQKRLS reveal that renewable technological innovations increase load capacity factor (LCF) across all quantiles, thus improving ecological quality. On the other hand, across all quantiles, natural gas consumption, energy prices, economic growth, urbanization, and green supply chain management lessen LCF, thus decreasing ecological quality. The QQGC results show that all the regressors (renewable technological innovations, natural gas consumption, energy prices, economic growth, and green supply chain management) can significantly predict LCF across all quantiles. The study formulates policies in line with these findings.

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来源期刊

Energy Economics ECONOMICS-

CiteScore

18.60

自引率

12.50%

发文量

524

期刊介绍： Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.