KSCE Journal of Civil Engineering

, Volume 23, Issue 2, pp 788–799 | Cite as

Evaluation of Transfer Efficiency between Bus and Subway based on Data Envelopment Analysis using Smart Card Data

  • Eun Hak Lee
  • Hoyoung Lee
  • Seung-Young Kho
  • Dong-Kyu KimEmail author
Transportation Engineering


The government of Seoul has been operating the automatic fare collection system based on the smart card since 2004. The smart card data in Seoul consist of 15 million instances of individual transit information per day, providing 99% of transit users’ trips. This study provides information about the efficiency of transfer stations in Seoul. The purpose of this study was to estimate the relative efficiency of the transfer stations between bus and subway using smart card data and suggest the improvement strategies for achieving the optimal efficiency. The transfer efficiency was estimated by using the Data Envelopment Analysis (DEA) model, and Tobit regression analysis was conducted to identify the factors that influence transfer efficiency. The DEA model showed that the efficiency scores of 32 major stations were estimated to be 0.557 on average. The transfer efficiency scores of these stations were analyzed to be proportional to the number of transfer trips and the transfer rate of the station. In the external factor analysis, we selected two socioeconomic variables, i.e., population and the number of companies. The external factor analysis indicated that the DEA model produced reasonable results for evaluating transfer efficiency.


public transportation smart card data Data Envelopment Analysis (DEA) model Tobit regression analysis transfer station 


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  1. Banker, R. D., Charnes, A., and Cooper, W. W. (1984). “Some models for estimating technical and scale inefficiencies in data envelopment analysis.” Management Science, Vol. 30, No. 9, pp. 1078–1092, DOI: 10.1287/mnsc.30.9.1078.CrossRefzbMATHGoogle Scholar
  2. Barnum, D. T., McNeil, S., and Hart, J. (2007). “Comparing the efficiency of public transportation subunits using data envelopment analysis.” Journal of Public Transportation, Vol. 10, No. 2, pp. 1–16, DOI: 10.5038/2375-0901.10.2.1.CrossRefGoogle Scholar
  3. Charnes, A., Cooper, W. W., and Rhodes, E. (1978). “Measuring the efficiency of decision making units.” European Journal of Operational Research, Vol. 2, No. 4, pp. 429–444, DOI: 10.1016/0377-2217(78) 90138–8.MathSciNetCrossRefzbMATHGoogle Scholar
  4. Choi, J., Lee, Y. J., Kim, T., and Sohn, K. (2012). “An analysis of Metro ridership at the station-to-station level in Seoul.” Transportation, Vol. 39, No. 3, pp.705–722, DOI: 10.1007/s11116-011-9368-3.CrossRefGoogle Scholar
  5. Eom, J. K., Song, J. Y., and Moon, D. S. (2015). “Efficiency analysis on bus companies in Seoul city using a network DEA model.” KSCE Journal of Civil Engineering, Vol. 19, No. 5, pp. 1530–1537, DOI: 10.1007/s12205-015-0013-0.CrossRefGoogle Scholar
  6. Farrell, M. J. and Fieldhouse, M. (1962). “Estimating efficient production functions under increasing returns to scale.” Journal of the Royal Statistical Society, Series A (General), 252–267, DOI: 10.2307/2982329.Google Scholar
  7. Golani, H. (2007). “Use of archived bus location, dispatch, and ridership data for transit analysis.” Transportation Research Record: Journal of the Transportation Research Board, pp. 101–112, DOI: 10.3141/1992-12.Google Scholar
  8. Guo, Z. and Wilson, N. (2007). “Modeling effects of transit system transfers on travel behavior: Case of commuter rail and subway in Downtown Boston, Massachusetts.” Transportation Research Record: Journal of the Transportation Research Board, pp. 11–20, DOI: 10.3141/2006-02.Google Scholar
  9. Hahn, J. S., Kho, S. Y., Choi, K., and Kim, D. (2017). “Sustainability evaluation of rapid routes for buses with a network DEA model.” International Journal of Sustainable Transportation, Vol. 11 No. 9, pp. 659–669, DOI: 10.1080/15568318.2017.1302022.CrossRefGoogle Scholar
  10. Hahn, J., Kim, D., Kim, H. C., and Lee, C. (2013). “Efficiency analysis on bus companies in Seoul city using a network DEA model.” KSCE Journal of Civil Engineering, Vol. 17, No. 6, pp. 1480–1488, DOI: 10.1007/s12205-013-0467-x.CrossRefGoogle Scholar
  11. Hahn, J., Sung, H. M., Park, M. C., Kho, S., and Kim, D. (2015) “Empirical evaluation on the efficiency of the trucking industry in Korea.” KSCE Journal of Civil Engineering, Vol. 19, No. 4, pp. 1088–1096, DOI: 10.1007/212205-012-1009-7.CrossRefGoogle Scholar
  12. Jang, W. (2010). “Travel time and transfer analysis using transit smart card data.” Transportation Research Record: Journal of the Transportation Research Board, Vol. 2144, pp. 142–149, DOI: 10.3141/2144-16.CrossRefGoogle Scholar
  13. Metropolitan Transportation Authority. (2015). Joint business of current O/D in the metropolitan area in 2014,
  14. Nishiuchi, H., Todoroki, T., and Kishi, Y. (2015). “A fundamental study on evaluation of public transport transfer nodes by data envelop analysis approach using smart card data.” Transportation Research Procedia, Vol. 6, 391–401, DOI: 10.1016/j.trpro.2015.03.029.CrossRefGoogle Scholar
  15. Park, J., Kim, D. J., and Lim, Y. (2008). “Use of smart card data to define public transit use in Seoul, South Korea.” Transportation Research Record: Journal of the Transportation Research Board, pp. 3–9, DOI: 10.3141/2063-01.Google Scholar
  16. Rezaee, M. J., Izadbakhsh, H., and Yousefi, S. (2016). “An improvement approach based on DEA-game theory for comparison of operational and spatial efficiencies in urban transportation systems.” KSCE Journal of Civil Engineering, Vol. 20, No.4, pp. 1526–1531, DOI: 10.1007/s12205-015-0345-9.CrossRefGoogle Scholar
  17. Sohn, K. and Shim, H. (2010). “Factors generating boardings at metro stations in the Seoul metropolitan area.” Cities, Vol. 27, No. 5, pp. 358–368, DOI: 10.1016/j.cities.2010.05.001.CrossRefGoogle Scholar
  18. Song, J. Y., Eom, J. K., Lee, K. S., Min, J. H., and Yang, K. Y. (2015). “Public transportation service evaluations utilizing seoul transportation card data.” Procedia Computer Science, Vol. 52, pp. 178–185, DOI: 10.1016/j.procs.2015.05.053.CrossRefGoogle Scholar
  19. Sun, L., Rong, J., and Yao, L. (2010). “Measuring transfer efficiency of urban public transportation terminals by data envelopment analysis.” Journal of Urban Planning and Development, Vol. 136, No. 4, 314–319, DOI: 10.1061/(ASCE) UP.1943-5444.0000028.CrossRefGoogle Scholar
  20. Sung, H. and Oh, J. T. (2011). “Transit-oriented development in a highdensity city: Identifying its association with transit ridership in Seoul, Korea.” Cities, Vol. 28, No. 1, pp. 70–82, DOI: 10.1016/j.cities.2010.09.004.CrossRefGoogle Scholar
  21. Transportation Safety Authority (2015). Survey of public transport in 2015,
  22. Transportation Safety Authority (2016). Public transportation transfer satisfaction survey,
  23. Utsunomiya, M., Attanucci, J., and Wilson, N. (2006). “Potential uses of transit smart card registration and transaction data to improve transit planning.” Transportation Research Record: Journal of the Transportation Research Board, Vol. 1971, pp. 119–126, DOI: 10.3141/1971-16.CrossRefGoogle Scholar
  24. Zhao, J., Jiang, Y., and Zhang, X. (2015). “Research on transportation efficiency evaluation based on DEA model.” In 15 th COTA International Conference of Transportation Professionals, pp. 2364–2375, DOI: 10.1061/9780784479292.219.Google Scholar

Copyright information

© Korean Society of Civil Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Eun Hak Lee
    • 1
  • Hoyoung Lee
    • 1
  • Seung-Young Kho
    • 1
  • Dong-Kyu Kim
    • 1
    • 2
    Email author
  1. 1.Dept. of Civil and Environmental EngineeringSeoul National UniversitySeoulKorea
  2. 2.Institute of Construction and Environmental EngineeringSeoul National UniversitySeoulKorea

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