All Issue

2026 Vol.44, Issue 5

Article

Behavioral Classifications and Latent Attitudinal Car Dependence Typologies among Car Users in Seoul: Focusing on Complementary Perspectives of User Heterogeneity

서울시 승용차 이용자의 행태 기반 유형과 잠재태도 기반 자동차 의존 유형: 이용자 이질성에 대한 상호보완적 설명 중심으로

Youngbeom KIM1
,
Seungjun KIM2
,
Dongmin LEE3*
김 영범1
,
김 승준2
,
이 동민3*
1Researcher, Smart Transportation Research Division, The Seoul Institute, Seoul 06756, Korea
2Senior Research Fellow, Smart Transportation Research Division, The Seoul Institute, Seoul 06756, Korea
3Professor, Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea
1서울연구원 스마트교통연구실 연구원
2서울연구원 스마트교통연구실 선임연구위원
3서울시립대학교 교통공학과 교수
*Corresponding Author
31 October 2026. pp. 737-761
PDF XML Citation
Abstract

This study empirically examines whether classifying car users in Seoul solely by observed car-use behavior can adequately explain their internal heterogeneity, and whether car-related latent attitudes can serve as a complementary dimension to behavior-based classification. Even among car users, frequency of use, purpose of travel (commute, leisure, daily activity), and recent public transport use may differ, while latent attitudes toward cars, such as symbolic meaning, preference/attachment, and driving norms, also vary. Using survey data from 2,000 licensed car users in Seoul with household vehicle access, this study separately derived behavior-based types and latent car-dependence types, and compared the relationship between the two systems. The analysis was conducted sequentially using confirmatory factor analysis, Gaussian mixture modeling, cross-classification analysis, and a multinomial logit model. The results identified four behavior-based types: low-use/recent public transport users (46.45%), leisure and daily-activity car users (36.25%), commute-oriented high-use users (9.65%), and moderate-use/mixed users (7.65%). The latent-attitude-based classification identified two types: low-dependence type (71.10%) and high-dependence type (28.90%). Although the two classification systems were statistically associated (χ2(3)=65.98, p < .001), their direct agreement was very low (ARI = 0.046). In particular, 63.73% of commute-oriented high-use users and 65.10% of leisure and daily-activity car users were classified as low-dependence, indicating that higher observed car-use intensity does not necessarily imply psychological car dependence. The multinomial logit results further show that car-related latent attitudes, parking conditions, and public transport accessibility significantly explain behavior-based type membership. These findings suggest that behavior-based types explain actual patterns of car use, while latent car-dependence types complement them by capturing underlying psychological orientations. Therefore, when identifying target groups for car demand management policies, it is necessary to consider not only car-use intensity but also car-related latent attitudes, car-use environments, and accessibility to alternative transport modes.

Keywords
car dependence
car user heterogeneity
gaussian mixture model
latent attitudes

본 연구는 서울시 승용차 이용자를 관측된 이용행태만으로 분류할 경우 이용자의 내부 이질성을 충분히 설명할 수 있는지를 검토하고, 자동차 관련 잠재태도가 이용행태 기반 분류를 보완할 수 있는지 실증적으로 분석하였다. 승용차를 이용하더라도 이용빈도와 통근･생활･여가 목적, 최근 대중교통 이용 정도가 다를 수 있으며, 자동차에 대한 상징성, 선호･애착, 운전규범 같은 잠재태도도 상이하게 나타난다. 이번 연구에서는 운전면허를 보유하고 가구 내 차량 이용이 가능한 서울시 승용차 이용자 2,000명의 설문자료를 활용하여 행태 기반 유형과 잠재적 자동차 의존 유형을 각각 도출하고 두 분류체계를 비교하였다. 분석은 확인적 요인분석, 가우시안 혼합모형, 교차분석, 다항로짓모형을 순차적으로 적용하였다. 분석 결과, 행태 기반 분류에서는 저이용･대중교통 최근이용형(46.45%), 생활･여가 자동차 활용형(36.25%), 통근중심 고이용형(9.65%), 중간이용･병행형(7.65%)의 유형이 도출되었다. 잠재태도 기반 분류에서는 저의존형(71.10%)과 고의존형(28.90%) 2개 유형이 확인되었다. 두 분류체계는 통계적으로 유의한 관련성을 보였으나(χ2(3) = 65.98, p < .001), 직접 일치도는 매우 낮았다(ARI=0.046). 특히 통근중심 고이용형의 63.73%와 생활･여가 자동차 활용형의 65.10%가 저의존형으로 분류되어, 관측된 이용강도가 높다는 사실이 반드시 심리적 의존을 의미하지 않음을 확인하였다. 또한 다항로짓모형 결과, 자동차 관련 잠재태도와 주차 환경 및 대중교통 접근성은 행태 기반 유형 소속을 유의하게 설명하였다. 이러한 결과는 행태 기반 유형이 실제 승용차 이용특성을 설명한다면, 잠재적 자동차 의존 유형은 심리적 성향을 설명하는 보완적 축임을 보여준다. 따라서 승용차 수요관리 정책에서 대상 집단을 설정할 때에는 단순한 이용강도뿐만 아니라, 자동차 관련 잠재태도와 자동차 이용환경, 대체 교통수단 접근성을 함께 고려할 필요가 있다.

키워드
자동차 의존성
승용차 이용자 이질성
가우시안 혼합모형
잠재 태도
References
1

Abrahamse W., Steg L., Gifford R., Vlek C. (2009), Factors Influencing Car Use for Commuting and the Intention to Reduce It: A Question of Self-Interest or Morality?, Transp. Res. Part F, 12(4), 317-324.

10.1016/j.trf.2009.04.004
2

Ajzen I. (1991), The Theory of Planned Behavior, Organ. Behav. Hum. Decis. Process., 50(2), 179-211.

10.1016/0749-5978(91)90020-T
3

Bae Y. K., Chung J. H., Kim H. J. (2010), Comparative Analysis of Mode Choice Models Using Latent Class Analysis, J. Korean Soc. Transp., 28(3), Korean Society of Transportation, 99-107.

4

Bamberg S., Schmidt P. (2003), Incentives, Morality, or Habit? Predicting Students' Car Use for University Routes With the Models of Ajzen, Schwartz, and Triandis, Environ. Behav., 35(2), 264-285.

10.1177/0013916502250134
5

Banister D. (2008), The Sustainable Mobility Paradigm, Transp. Policy, 15(2), 73-80.

10.1016/j.tranpol.2007.10.005
6

Ben-Akiva M., Lerman S. R. (1985), Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press, Cambridge, MA, USA.

7

Ben-Akiva M., McFadden D., Train K., Walker J., Bhat C., Bierlaire M. et al. (2002), Hybrid Choice Models: Progress and Challenges, Mark. Lett., 13(3), 163-175.

10.1023/A:1020254301302
8

Bhagat-Conway M. W., Mirtich L., Salon D., Harness N., Consalvo A., Hong S. (2024), Subjective Variables in Travel Behavior Models: A Critical Review and Standardized Transport Attitude Measurement Protocol (STAMP), Transportation, 51(1), 155-191.

10.1007/s11116-022-10323-736196062PMC9522447
9

Donald I. J., Cooper S. R., Conchie S. M. (2014), An Extended Theory of Planned Behaviour Model of the Psychological Factors Affecting Commuters' Transport Mode Use, J. Environ. Psychol., 40, 39-48.

10.1016/j.jenvp.2014.03.003
10

Fu X., Juan Z. (2017), Understanding Public Transit Use Behavior: Integration of the Theory of Planned Behavior and the Customer Satisfaction Theory, Transportation, 44(5), 1021-1042.

10.1007/s11116-016-9692-8
11

Fujii S., Kitamura R. (2003), What Does a One-Month Free Bus Ticket Do to Habitual Drivers? An Experimental Analysis of Habit and Attitude Change, Transportation, 30(1), 81-95.

10.1023/A:1021234607980
12

Guerra E. (2022), What the Heck Is a Choice Rider? A Theoretical Framework and Empirical Model, J. Transp. Land Use, 15(1), 165-182.

10.5198/jtlu.2022.2096
13

Haustein S., Hunecke M. (2007), Reduced Use of Environmentally Friendly Modes of Transportation Caused by Perceived Mobility Necessities: An Extension of the Theory of Planned Behavior, J. Appl. Soc. Psychol., 37(8), 1856-1883.

10.1111/j.1559-1816.2007.00241.x
14

Ki H. G., Chang J. S. (2024), Analyzing the Factors Influencing Car Dependency Using the Theory of Planned Behavior, J. Korean Soc. Transp., 42(4), Korean Society of Transportation, 472-493.

10.7470/jkst.2024.42.4.472
15

Kim S. H., Choo S. (2019), Developing a Latent Class Model Considering Heterogeneity in Mode Choice Behavior: A Case of Commuters in Seoul, J. Korea Inst. Intell. Transp. Syst., 18(2), The Korea Institute of Intelligent Transport Systems, 44-57.

10.12815/kits.2019.18.2.44
16

McFadden D. (1974), Conditional Logit Analysis of Qualitative Choice Behavior, in Zarembka P. (ed.), Frontiers in Econometrics, Academic Press, New York, NY, USA, 105-142.

17

Molin E., Mokhtarian P., Kroesen M. (2016), Multimodal Travel Groups and Attitudes: A Latent Class Cluster Analysis of Dutch Travelers, Transp. Res. Part A, 83, 14-29.

10.1016/j.tra.2015.11.001
18

Newman P., Kenworthy J. (1999), Sustainability and Cities: Overcoming Automobile Dependence, Island Press, Washington, D.C., USA.

19

Park S. H., Yi C. (2023), The Intention of Automobile Users to Use Public Transportation: An Application of the Extended Theory of Planned Behavior, J. Korean Soc. Transp., 41(2), Korean Society of Transportation, 166-182.

10.7470/jkst.2023.41.2.166
20

Seoul Institute (2024), Analysis of the Social Impacts of Symbols and Attachments Associated With Cars Among Seoul Citizens.

21

Seoul Metropolitan Government (2025a), Automobile Registration Statistics by Month and District in Seoul, Seoul Open Data Plaza, https://data.seoul.go.kr/, 2026.02.23.

22

Seoul Metropolitan Government (2025b), Daily Travel by Transport Mode and Modal Share Statistics in Seoul, Seoul Open Data Plaza, https://data.seoul.go.kr/, 2026.02.23.

23

Soza-Parra J., Cats O. (2024), Who Is Ready to Live a Car-Independent Lifestyle? A Latent Class Cluster Analysis of Attitudes Towards Car Ownership and Usage, Transp. Res. Part A, 190, 104271.

10.1016/j.tra.2024.104271
24

Steg L. (2005), Car Use: Lust and Must. Instrumental, Symbolic and Affective Motives for Car Use, Transp. Res. Part A, 39(2-3), 147-162.

10.1016/j.tra.2004.07.001
25

Ton D., Zomer L. B., Schneider F., Hoogendoorn-Lanser S., Duives D., Cats O. et al. (2020), Latent Classes of Daily Mobility Patterns: The Relationship With Attitudes Towards Modes, Transportation, 47(4), 1843-1866.

10.1007/s11116-019-09975-9
26

Train K. E. (2009), Discrete Choice Methods With Simulation, 2nd ed., Cambridge University Press, Cambridge, UK.

27

Vij A., Walker J. L. (2016), How, When and Why Integrated Choice and Latent Variable Models Are Latently Useful, Transp. Res. Part B, 90, 192-217.

10.1016/j.trb.2016.04.021
28

von Behren S., Bönisch L., Niklas U., Chlond B. (2020), Revealing Motives for Car Use in Modern Cities—A Case Study From Berlin and San Francisco, Sustainability, 12(13), 5254.

10.3390/su12135254
29

Walker J., Ben-Akiva M. (2002), Generalized Random Utility Model, Math. Soc. Sci., 43(3), 303-343.

10.1016/S0165-4896(02)00023-9
Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 44
  • No :5
  • Pages :737-761
  • Received Date : 2026-03-25
  • Revised Date : 2026-04-23
  • Accepted Date : 2026-06-17
  • DOI :https://doi.org/10.7470/jkst.2026.44.5.737
Journal Informaiton Journal of Korean Society of Transportation Journal of Korean Society of Transportation
Archives
: 2015 Vol.34~
  • scopus
  • NRF
  • KOFST
  • crossref cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close