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2025 Vol.43, Issue 2 Preview Page

Article

Analysis of Commuting Mode Choice by Residential Group: Focusing on Central Business Districts in Seoul

거주지 그룹에 따른 통근 수단 선택 분석: 서울시 중심업무지구를 중심으로

Ryujeong LEE1
,
Juho LEE1
,
Juhyeon KWAK2
,
Seungjae LEE3*
이 류정1
,
이 주호1
,
곽 주현2
,
이 승재3*
1Master Course, Department of Transportation Engineering / Department of Smart Cities, University of Seoul, Seoul 02504, Korea
2Ph.D. Candidate, Department of Transportation Engineering / Department of Smart Cities, University of Seoul, Seoul 02504, Korea
3Professor, Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea
1서울시립대학교 교통공학과/스마트시티학과 석사과정
2서울시립대학교 교통공학과/스마트시티학과 박사수료
3서울시립대학교 교통공학과 교수
*Corresponding Author
30 April 2025. pp. 222-236
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Abstract

도시 교통 시스템은 주민들의 일상생활과 삶의 질에 큰 영향을 미치며, 특히 대도시에서는 통근 패턴이 거주지 위치와 중심 업무 지구(CBD)와의 근접성 등 다양한 요인에 의해 좌우된다. 또한, 개인의 통행 수단 선택을 이해하는 것은 도시 이동성 및 교통 계획에 있어 매우 중요한 통찰력을 제공한다. 본 연구는 건축 환경이 통행 행태에 미치는 영향을 탐구하며, 특히 서울시의 중심 업무 지구와 거주지 간의 거리 및 대중교통 인프라 발달 정도가 교통수단 선택에 미치는 영향을 분석한다. 서울시의 예를 통해 대중교통 의존도가 높은 환경에서 개인의 통근 패턴을 이해하고, 공간적 그룹화를 통해 거주지 위치가 교통수단 선택에 미치는 영향을 분석한다. 2021년 대한민국의 개인통행실태조사 데이터를 기반으로 하여, 성향 점수 매칭(PSM) 방법을 사용함으로써 거주지 선택의 자기 선호 효과를 제어하고, 이를 통해 보다 정확한 통찰을 도출한다. 분석 결과는 도시 교통 시스템의 효율성 증대와 정책 결정 과정에서 실질적인 근거를 제공할 것으로 기대되며, 도시 계획 및 교통 정책의 효과적인 개선을 위한 기초 자료로 활용될 수 있을 것으로 판단된다.

Keywords
built environment
central business distirct (CBD)
commute
mode choice
propensity score matching (PSM)

The urban transportation system exerts a profound influence on the daily lives and quality of life of residents. In metropolises in particular, the commuting patterns of individuals are shaped by a multitude of factors, including the location of residences and proximity to central business district (CBD). Furthermore, an understanding of individual travel choices provides valuable insights into urban mobility and transportation planning. This study examines the influence of the built environment on travel behavior, with a particular focus on the impact of the distance between Seoul's central business district and residential areas and the extent of public transportation infrastructure development on transportation mode choice. The case of Seoul is employed as a point of reference to gain insight into individual commuting patterns in an environment where public transportation plays a significant role, and to examine the influence of residential location on transportation mode choice through spatial grouping. The 2021 Personal Travel Survey in South Korea is used as a basis for this study, with the propensity score matching (PSM) method employed to control for the self-selection effect of residential choice, thereby deriving more accurate insights. It is anticipated that the analysis results will provide practical evidence for increasing the efficiency of urban transportation systems and for policy-making, and will be used as basic data for effective improvement of urban planning and transportation policies.

키워드
건축 환경
중심 업무 지구
통근
수단 선택
성향 점수 매칭
References
1

Al-Rashid M. A., Goh H. C., Harumain Y. A. S., Ali Z., Campisi T., Mahmood T. (2021), Psychosocial Barriers of Public Transport Use and Social Exclusion Among Older Adults: Empirical Evidence From Lahore, Pakistan, International Journal of Environmental Research and Public Health, 18(1), MDPI, 185.

10.3390/ijerph1801018533383763PMC7794845
2

Bhat C. R., Guo J. Y. (2007), A Comprehensive Analysis of Built Environment Characteristics on Household Residential Choice and Auto Ownership Levels, Transportation Research Part B: Methodological, 41(5), Elsevier, 506-526.

10.1016/j.trb.2005.12.005
3

Cao X. J., Ettema D. F. (2014), Satisfaction With Travel and Residential Self-Selection: How Do Preferences Moderate the Impact of the Hiawatha Light Rail Transit Line?, Journal of Transport and Land Use, 7(3), JSTOR, 93-108.

10.5198/jtlu.v7i3.485
4

Cao X. J., Mokhtarian P. L., Handy S. L. (2009a), The Relationship Between the Built Environment and Nonwork Travel: A Case Study of Northern California, Transportation Research Part A: Policy and Practice, 43(5), Elsevier, 548-559.

10.1016/j.tra.2009.02.001
5

Cao X. J., Mokhtarian P. L., Handy S. L. (2009b), Examining the Impacts of Residential Self-Selection on Travel Behaviour: A Focus on Empirical Findings, Transport Reviews, 29(3), Taylor & Francis, 359-395.

10.1080/01441640802539195
6

Cao X. J., Xu Z., Fan Y. (2010), Exploring the Connections Among Residential Location, Self-Selection, and Driving: Propensity Score Matching With Multiple Treatments, Transportation Research Part A: Policy and Practice, 44(10), Elsevier, 797-805.

10.1016/j.tra.2010.07.010
7

Chen F., Wu J., Chen X., Nielsen C. P. (2021), Disentangling the Impacts of the Built Environment and Residential Self-Selection on Travel Behavior: An Empirical Study in the Context of Diversified Housing Types, Cities, 116, Elsevier, 103285.

10.1016/j.cities.2021.103285
8

Cirella G. T., Bąk M., Kozlak A., Pawłowska B., Borkowski P. (2019), Transport Innovations for Elderly People, Research in Transportation Business & Management, 30, Elsevier, 100381.

10.1016/j.rtbm.2019.100381
9

Convery S., Williams B. (2019), Determinants of Transport Mode Choice for Non-Commuting Trips: The Roles of Transport, Land Use and Socio-Demographic Characteristics, Urban Science, 3(3), MDPI, 82.

10.3390/urbansci3030082
10

De Vos J., Ettema D., Witlox F. (2018), Changing Travel Behaviour and Attitudes Following a Residential Relocation, Journal of Transport Geography, 73, Elsevier, 131-147.

10.1016/j.jtrangeo.2018.10.013
11

Deng Y., Zhao P. (2022), Quantifying Residential Self-Selection Effects on Commuting Mode Choice: A Natural Experiment, Transportation Research Part D: Transport and Environment, 104, Elsevier, 103197.

10.1016/j.trd.2022.103197
12

Ewing R., Cervero R. (2010), Travel and the Built Environment: A Meta-Analysis, Journal of the American Planning Association, 76(3), Taylor & Francis, 265-294.

10.1080/01944361003766766
13

Handy S., Cao X., Mokhtarian P. L. (2005), Correlation or Causality Between the Built Environment and Travel Behavior? Evidence from Northern California, Transportation Research Part D: Transport and Environment, 10(6), Elsevier, 427-444.

10.1016/j.trd.2005.05.002
14

Jang S., An Y., Yi C., Lee S. (2017), Assessing the Spatial Equity of Seoul's Public Transportation Using the Gini Coefficient Based on Its Accessibility, International Journal of Urban Sciences, 21(1), Taylor & Francis, 91-107.

10.1080/12265934.2016.1235487
15

Kim D. J., Kim H. J., Jang W. J., Sung H. G. (2006), A Comparison of Public Transportation Competitiveness in World Major Cities, J. Korean Soc. Transp., 24(4), Korean Society of Transportation, 81-91.

16

Ko J., Lee S., Byun M. (2019), Exploring Factors Associated with Commute Mode Choice: An Application of City-Level General Social Survey Data, Transport Policy, 75, Elsevier, 36-46.

10.1016/j.tranpol.2018.12.007
17

Kwak J., Jeong I., Lee D., Ku D., Lee S. (2024), Lessons Learned from Spatiotemporal Effect of COVID on the Population Density in the CBD, Proceedings of the Institution of Civil Engineers - Municipal Engineer, 177(4), Emerald Publishing Limited, 169-179.

10.1680/jmuen.24.00012
18

Lee K., Kim C., Lee S. (2021), Does the Transportation SOC Investment Plan Conform With the TOD-Oriented Policy? Analysis and Prediction of Mode Choices for Commuters in Seoul Metropolitan Area, 2005-2030, Journal of the Korean Official Statistics, 27(1), KOS, 56-89.

19

Lee K., Kim I., Shim J., Kim J. (2020), Improvement of Zone-Based Regional Transportation Mode Choice Model Reflecting Behavioral Difference by Travel Distance, J. Korean Soc. Transp., 38(5), Korean Society of Transportation, 346-360.

10.7470/jkst.2020.38.5.346
20

Li S., Zhao P. (2015), The Determinants of Commuting Mode Choice Among School Children in Beijing, Journal of Transport Geography, 46, Elsevier, 112-121.

10.1016/j.jtrangeo.2015.06.010
21

Lim J., Le D. (2023), Estimation of the Effect of Commercial Vehicle Driving Safety Training Using the Propensity Score Matching Method, J. Korean Soc. Transp., 41(2), Korean Society of Transportation, 254-265.

10.7470/jkst.2023.41.2.254
22

Ma G. R., Kim D. H., Chu S. H. (2007), The Impact of the Position of City Boundaries on the Estimation of Excess Commuting, The 55th Conference of KST, Korean Society of Transportation, 228-235.

23

Munshi T. (2016), Built Environment and Mode Choice Relationship for Commute Travel in the City of Rajkot, India, Transportation Research Part D: Transport and Environment, 44, Elsevier, 239-253.

10.1016/j.trd.2015.12.005
24

Nasri A., Carrion C., Zhang L., Baghaei B. (2020), Using Propensity Score Matching Technique to Address Self-Selection in Transit-Oriented Development (TOD) Areas, Transportation, 47, Springer, 359-371.

10.1007/s11116-018-9887-2
25

Özkazanç S., Sönmez F. N. Ö. (2017), Spatial analysis of social exclusion from a transportation perspective: A case study of Ankara metropolitan area, Cities, 67, 74-84.

10.1016/j.cities.2017.04.013
26

Prashker J., Shiftan Y., Hershkovitch-Sarusi P. (2008), Residential Choice Location, Gender and the Commute Trip to Work in Tel Aviv, Journal of Transport Geography, 16(5), Elsevier, 332-341.

10.1016/j.jtrangeo.2008.02.001
27

Rasca S., Saeed N. (2022), Exploring the Factors Influencing the Use of Public Transport by Commuters Living in Networks of Small Cities and Towns, Travel Behaviour and Society, 28, Elsevier, 249-263.

10.1016/j.tbs.2022.03.007
28

Rubin D. B. (2001), Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation, Health Services and Outcomes Research Methodology, 2, Springer, 169-188.

29

Schwanen T., Mokhtarian P. L. (2005), What Affects Commute Mode Choice: Neighborhood Physical Structure or Preferences Toward Neighborhoods?, Journal of Transport Geography, 13(1), Elsevier, 83-99.

10.1016/j.jtrangeo.2004.11.001
30

Seoul Metropolitan Government (2014), 2030 Seoul Plan, 1-217.

31

Shin H. C., Woo M. (2020), Study on the Reverse Commuting Phenomena Considering Spatial Mismatch: In the Non-Seoul Metropolitan Area, Journal of the Korean Regional Science Association, 36(2), KRSA, 3-12.

32

Šťastná M., Vaishar A. (2017), The relationship between public transport and the progressive development of rural areas, Land use policy, 67, 107-114.

10.1016/j.landusepol.2017.05.022
33

Sung H. (2012), Impacts of the Structural Relationship for Transit Accessibility and Jobs-Housing Balance in Residential Location Choice on Travel Behavior at the Household Level, Journal of the Korean Planners Association, 47(4), KPA, 265-282.

34

Sung H. (2020), Identification on the Differentiating Characteristics of Determinant Factors on Commuting Mode Choice for the Single-Person Household Compared to the Multi-Person Household, LHI Journal of Land, Housing, and Urban Affairs, 11(2), LHI, 1-14.

35

Sung H., Lee S., Cheon S. (2014), Empirical Analysis on the Inequality Factors of Housing Type and Transit Accessibility Influencing Walking Activity by Travel Purpose, Journal of Korea Planners Association, 49(10), KPA, 65-82.

10.17208/jkpa.2014.10.49.6.65
36

Sung H., Sohn D. (2020), Private-Car Mode Choice in Commuting and Its Hidden Impacts on the Travel Time: Focused on the Multilevel Determinant Measures of Individual, Household, and Residential Area, J. Korea Plan. Assoc., 55, KPA, 54-68.

10.17208/jkpa.2020.02.55.1.54
37

Van Wee B. (2009), Self‐Selection: A Key to a Better Understanding of Location Choices, Travel Behaviour and Transport Externalities?, Transport Reviews, 29(3), Taylor & Francis, 279-292.

10.1080/01441640902752961
38

Wong R. C. P., Szeto W. Y., Yang L., Li Y. C., Wong S. C. (2018), Public transport policy measures for improving elderly mobility, Transport policy, 63, 73-79.

10.1016/j.tranpol.2017.12.015
Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 43
  • No :2
  • Pages :222-236
  • Received Date : 2024-12-09
  • Revised Date : 2024-12-30
  • Accepted Date : 2025-02-04
  • DOI :https://doi.org/10.7470/jkst.2025.43.2.222
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