Riding the green rails: Exploring the nexus between high-speed trains, green innovation, and carbon emissions
Yu Chen,
Changyi Zhao,
Shan Chen,
Wenqing Chen,
Kunyang Wan and
Jia Wei
Energy, 2023, vol. 282, issue C
Abstract:
Carbon management holds increasing significance in today's global economy, particularly in the pursuit of sustainable development and carbon neutrality for nations like China. Given that energy consumption plays a central role in driving carbon emissions, a comprehensive exploration of strategies to enhance energy efficiency becomes imperative. While existing research has scrutinized the direct impacts of eco-friendly transportation modes like high-speed trains on energy usage and carbon emissions, limited attention has been directed towards investigating their indirect implications. This study posits that the introduction of high-speed train systems facilitates swift flows of resources, expertise, and funding, thereby fostering an environment conducive to green innovation. Thus, this research probes the hypothesis that the establishment of high-speed train networks can trigger green innovation, ultimately bolstering energy efficiency and mitigating carbon emissions. Utilizing data spanning 2008 to 2018 of the prefecture-level cities, this study employs mediation, moderation, and robustness tests to validate the notion that the integration of high-speed train cultivates a setting favorable to green innovation, leading to improved energy efficiency and reduced carbon emissions. Furthermore, this effect is notably accentuated in cities engaged in intellectual property pilot cities and low-carbon pilot cities.
Keywords: Carbon emissions; HST; Green innovation; Intellectual property pilot cities; Low-carbon pilot cities (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:282:y:2023:i:c:s0360544223023496
DOI: 10.1016/j.energy.2023.128955
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