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Effects of Land-Use Characteristics on Transport Mode Choices by Purpose of Travel in Seoul, South Korea, Based on Spatial Regression Analysis

Author

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  • Byunghak Min

    (Department of Architecture, Korea University, 145, Anam-ro, Seungbuk-gu, Seoul 02841, Korea)

  • Gunwon Lee

    (Division of Architecture, Civil and Environmental Engineering, Hoseo University, 20, Hoseo-ro 79 beon-gil, Baebang-eup, Asan-si 31499, Korea)

  • Seiyong Kim

    (Department of Architecture, Korea University, 145, Anam-ro, Seungbuk-gu, Seoul 02841, Korea)

Abstract

The objective of this study was to identify the effects of land-use characteristics on the transport mode choices of people according to their purpose of travel. Land-use characteristics consisting of variables associated with density, diversity and accessibility were selected as independent variables. The volume of traffic entering each administrative neighborhood was extracted to establish travel data as the dependent variable. We compared and analyzed the results derived from ordinary least squares (OLS) analysis and spatial regression (SR) analysis. The results showed that the explanatory power of the SR model was higher than that of the OLS model. The results in this study reveal that the effects of land-use characteristics on travel show clear differences according to the transport mode, more so than according to the purpose of travel. Moreover, the results showed that an increase in the level of variables associated with density does not always facilitate the use of non-motorized or public transit modes, nor does it always deter the use of personal motorized modes. The findings in this study are significant in a knowledge-sharing context, as they present the effects of land-use characteristics on the volume of traffic in high-density cities, using Seoul as a case study.

Suggested Citation

  • Byunghak Min & Gunwon Lee & Seiyong Kim, 2021. "Effects of Land-Use Characteristics on Transport Mode Choices by Purpose of Travel in Seoul, South Korea, Based on Spatial Regression Analysis," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1767-:d:494773
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