Abstract
The ever-increasing use of cars is a big problem in metropolitan areas. To manage the traffic stream and alleviate air pollution, most metropolitan governments are attempting to discourage the use of cars. Nevertheless, the results have not been satisfactory. It is well known that normal-choice riders choose their travel mode based on utility, which is determined by mode-specific impedances and individual characteristics. On the other hand, this study focuses on identifying car-dependent commuters who tend to keep driving cars regardless of the circumstances they are confronted with. For this study, psychometric factors characterizing car-dependent commuters were investigated. However, the performance of the mode-choice model was not sufficiently enhanced despite incorporation of the psychometric factors. The performance improved considerably when the car-dependent commuters were excluded. Based on psychometric factors, the support vector machine successfully separated the car-dependent commuters from normal-choice riders.
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Abe, M.A., Sinha, K.C.: Pricing in mass transportation. Transp. Eng. J 99(1), 83–91 (1973)
Ben-Akiva, M., Choudhury, C., Toledo, T.: Modeling latent choices: application to driving behavior. Paper presented at the 11th International Conference on Travel Behaviour Research, Kyoto, Japan, 16–20 August 2006
Ben-Akiva, M., Walker, J., Bernardino, A.T., Gopinath, D., Morikawa, T., Polydoropoulou, A.: Integration of choice and latent variable models. In: Mahmassani, H.S. (ed.) Perpetual Motion: Travel Behaviour Research Opportunities and Application Challenges, pp. 431–470. Elsevier, Amsterdam (2002)
Chang, H., Wu, S.: Exploring the vehicle dependence behind mode choice: evidence of motorcycle dependence in Taipei. Transp. Res. Part A 42, 307–320 (2008)
Cortes, C., Vapnik, C.: Support vector networks. Mach. Learn 20, 273–297 (1995)
Davey Smith, G., Shipley, M., Rose, G.: Magnitude and cause of socioeconomic differentials in mortality: further evidence from The Whitehall Study. J. Epidemiol. Community Health 44, 265–270 (1990)
Dittmar, H.: The Social Psychology of Material Possessions: To Have is to be. Havester Wheatsheaf, Hemel Hempstead, UK. St. Martins’s Press, New York (1992)
Ellaway, A., Macintyre, S., Hiscock, R., Kearns, A.: In driving seat: psychosocial benefits from private motor vehicle transport compared to public transport. Transp. Res. Part F 6, 217–231 (2003)
Eriksson, L., Garvill, J., Nordlund, A.M.: Interrupting habitual car use: the importance of car habit strength and motivation for personal car use reduction. Transp. Res. Part F 11, 1–47 (2008)
Gardner, B., Abraham, C.: What drives car use: a ground theory analysis of commuter’s reason’s for driving. Transp. Res. Part F 10, 187–200 (2007)
Glaser, B., Strauss, A.L.: The Discovery of Ground Theory: Strategies for Qualitative Research. Aldine, Chicago (1967)
Johansson, M.V., Heldt, T., Johansson, P.: The effects of attitudes and personality trait on mode choice. Transp. Res. Part A 40, 507–525 (2006)
Kokur, G., Alder, T., Hyman, W., Aunet, B.: Guide to Forcasting Travel Demand with Direct Utility Assesment. United States Department of Transportation, Urban Mass Transportation Administration, Report UMTA-NH-11-001-82-1, Washington DC (1982)
Madanat, S.M., Yang, C.Y.D., Yen, Y.M.: Analysis of stated route diversion intentions under advanced traveler information systems using latent variable modeling. Transp. Res. Rec 1485, 10–17 (1995)
Majumdar, A., Orcheing, W.Y.: Factors affecting air traffic controller workload: multivariate analysis based on simulation modeling of controller workload. Transp. Res. Rec 1788, 58–69 (2004)
Morikawa, T., Ben-Akiva, M., McFadden, D.: Discrete choice models incorporating revealed preferences and psychometric data. In: Franses, P.H., Montgomery, A.L. (eds.) Econometric Models in Marketing, Advances in Econometrics, vol. 16, pp. 29–55. Elsevier, Amsterdam (2002)
Prashker, J.A.: Scaling perceptions of reliability of urban travel modes using Indscal factor analysis methods. Transp. Res. A 13, 203–212 (1979)
Seoul Metropolitan Government: Transportation Survey (2008)
Smith, J., Harding, S.: Mortality of women and men using alternative social classifications. In: Drever, F., Whitehead, M. (eds.) Health Inequalities. Office for National Statistics, London (1997)
Sohn, K.: A systematic decision criterion for the elimination of useless overpasses. Transp. Res. Part A 42(8), 1043–1055 (2008)
Steg, L.: Car use: lust and must. Instrumental, symbolic and affective motives for car use. Transp. Res. Part A 39, 147–162 (2005)
Steg, L., Vlek, C., Slotegraaf, G.: Instrumental-reasoned and symbolic-affective motives for using a motor car. Transp. Res. Part F 4, 151–169 (2001)
Tertoolen, G., Van Kreveld, D., Verstraten, B.: Psychological resistance against attempts to reduce private car use. Transp. Res. Part A 32(3), 187–200 (1998)
Transport Studies Unit, Oxford: Car Dependence. Royal Automobile Club for Motoring and Environment, London (1995)
Tryfos, P.: Methods for Business Analysis and Forecasting: Text & Cases, Chap. 14. Factor Analysis. Wiley, New York (1998)
Vapnik, V.: The Nature of Statistical Learning Theory. Springer, New York (1995)
Willig, C.: Introducing Qualitative Research in Psychology: Adventures in Theory and Method. Open University Press, Milton Keynes (2001)
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Sohn, K., Yun, J. Separation of car-dependent commuters from normal-choice riders in mode-choice analysis. Transportation 36, 423–436 (2009). https://doi.org/10.1007/s11116-009-9209-9
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DOI: https://doi.org/10.1007/s11116-009-9209-9