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2026 Vol.17, Issue 1 Preview Page

General Article

Examining the nonlinear relationship between urban built environment and commuting distance in Seoul, South Korea
Sangyeon Nam1
,
Tai-Jin Song2
,
Sungjo Hong3*
1Ph.D. Student, Department of Urban Engineering, Chungbuk National University, Cheongju, South Korea
2Associate Professor, Department of Urban Engineering, Chungbuk National University, Cheongju, South Korea
3Professor, Department of Urban Engineering, Chungbuk National University, Cheongju, South Korea
*Corresponding Author
31 March 2026. pp. 75-94
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Abstract

Substantial empirical evidence has been presented regarding the relationship between built environments and commuting distance; however, conflicting conclusions still exist for certain variables. Therefore, our study aims to identify the relationship between built environments and commuting distance by leveraging mobile phone data, providing a large commuting sample, and explainable machine learning techniques capable of capturing complex relationships between variables. Initially, we constructed a commuting distance prediction model using the XGBoost algorithm. Subsequently, we used explainable machine learning techniques, namely SHapley Additive exPlanations (SHAP) and Partial Dependence Plot (PDP), to identify the built environment factors that influence commuting distance. The results highlighted the distance from the residence to the employment center as the most crucial built environment factor. Additionally, the land use mix and job-population balance at the residence were found to have nonlinear relationships with commuting distance. Contrary to the empirical evidence from Western cities, population density was found to have a positive relationship with commuting distance. Our findings emphasize the need for customized urban and transportation planning strategies in various urban contexts.

Keywords
built environment
commuting distance
explainable machine learning
Seoul
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Information
  • Publisher :Sustainable Building Research Center (ERC) Innovative Durable Building and Infrastructure Research Center
  • Publisher(Ko) :건설구조물 내구성혁신 연구센터
  • Journal Title :International Journal of Sustainable Building Technology and Urban Development
  • Volume : 17
  • No :1
  • Pages :75-94
  • Received Date : 2025-11-11
  • Accepted Date : 2026-03-07
  • DOI :https://doi.org/10.22712/susb.20260006
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