ScholarWorks@숙명여자대학교

초록

The transport sector plays a dual role—it's essential for economic activity and human well-being, but it is also a major source of greenhouse gas emissions. While electric vehicles are promoted as a key solution for reducing emissions in road transport, their higher upfront costs pose challenges, particularly for lower-income households who face higher implicit discount rates in their purchasing decisions. This study enhances existing bottom-up linear programming transport models by incorporating consumer income characteristics into the analysis of passenger car choices from 2019 to 2050. The study divided driving distances into eight categories based on household income levels and applied income-specific implicit discount rates. It also factored in how gross domestic product growth affects household income levels over time—an aspect previously overlooked. The model results reveal significant differences in electric vehicle adoption patterns across income groups. When income characteristics and varying discount rates are considered, low-income households show lower electric vehicle adoption rates compared to previous model predictions, while high-income households exhibit higher adoption rates. These disparities become even more pronounced under carbon tax policy scenarios. The study concludes that for transport sector carbon neutrality policies to be effective, they must account for various factors influencing vehicle purchase decisions, especially income-related constraints. It specifically recommends developing differentiated subsidy policies for different income groups to promote more equitable adoption of electric vehicles across all economic segments of society.

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