Carbon Reduction Effects in Transport Infrastructure: The Mediating Roles of Collusive Behavior and Digital Control Technologies

Abstract

Many countries have committed to carbon reductions and carbon neutrality targets in response to the Paris Agreement and Sustainable Development Goals (SDGs). With economic development, the transportation sector has become a major source of carbon emissions. In China, transport infrastructure—as an important carrier of the transportation sector—is important for controlling carbon emissions from this sector and achieving carbon neutrality and the targets of the SDGs. However, most studies have focused on transport vehicles and neglected transport infrastructure. Furthermore, the influences of collusive behavior and digital control technologies on the carbon reduction process have not yet been examined. This study aimed to analyze the influencing factors in the carbon reduction process in transport infrastructure. This study uses partial least squares structural equation modeling (PLS-SEM) to analyze the factors influencing carbon reductions in transport infrastructure and the mediating roles of collusive behavior and digital control technologies in the carbon reduction process. Low-carbon technologies, digital control technologies, and collusive behavior have positive direct and indirect effects on the carbon reduction effect. Digital control technologies have a positive effect on low-carbon regimes. Low-carbon technologies influence carbon reduction effects. Collusive behavior plays a mediating role in low-carbon regimes. Finally, the industrial structure influences carbon reduction effects. This study extends China’s carbon emission research in the transportation sector by focusing on infrastructure rather than vehicles. Additionally, this is the first study to incorporate collusive behavior and digital control technologies into the framework to analyze the impact of carbon reductions. The study also employs PLS-SEM to explore effective carbon reduction paths. The findings provide decision-making support for controlling carbon reductions in transport infrastructure.

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