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Transit market research using structural equation modeling and attitudinal market segmentation

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  • Shiftan, Yoram
  • Outwater, Maren L.
  • Zhou, Yushuang
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    Abstract

    This paper presents a comprehensive approach for identifying potential transit markets and for developing strategies to increase public transport ridership. The approach uses structural equation modeling (SEM) to identify simultaneously travelers' attitudes, travel behavior, and the causal relationships between a traveler's socioeconomic profile and his/her attitude toward travel. Travel attitudes are also used to identify distinct market segments and to develop plans that best serve the needs of each segment and increase transit ridership. The approach is demonstrated with a case study from the Utah Transit Authority.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transport Policy.

    Volume (Year): 15 (2008)
    Issue (Month): 3 (May)
    Pages: 186-195

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    Handle: RePEc:eee:trapol:v:15:y:2008:i:3:p:186-195

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    1. Fujii, Satoshi & Kitamura, Ryuichi, 2000. "Evaluation of trip-inducing effects of new freeways using a structural equations model system of commuters' time use and travel," Transportation Research Part B: Methodological, Elsevier, Elsevier, vol. 34(5), pages 339-354, June.
    2. Choo, Sangho & Mokhtarian, Patricia L., 2007. "Telecommunications and travel demand and supply: Aggregate structural equation models for the US," Transportation Research Part A: Policy and Practice, Elsevier, Elsevier, vol. 41(1), pages 4-18, January.
    3. Anable, Jillian & Gatersleben, Birgitta, 2005. "All work and no play? The role of instrumental and affective factors in work and leisure journeys by different travel modes," Transportation Research Part A: Policy and Practice, Elsevier, Elsevier, vol. 39(2-3), pages 163-181.
    4. Steg, Linda, 2005. "Car use: lust and must. Instrumental, symbolic and affective motives for car use," Transportation Research Part A: Policy and Practice, Elsevier, Elsevier, vol. 39(2-3), pages 147-162.
    5. Steg, Linda & Geurs, Karst & Ras, Michiel, 2001. "The effects of motivational factors on car use: a multidisciplinary modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, Elsevier, vol. 35(9), pages 789-806, November.
    6. Anable, Jillian, 2005. "'Complacent Car Addicts' or 'Aspiring Environmentalists'? Identifying travel behaviour segments using attitude theory," Transport Policy, Elsevier, Elsevier, vol. 12(1), pages 65-78, January.
    7. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, Elsevier, vol. 37(1), pages 1-25, January.
    8. W.F. Lythgoe & M. Wardman, 2002. "Demand for rail travel to and from airports," Transportation, Springer, Springer, vol. 29(2), pages 125-143, May.
    9. Golob, Thomas F., 2001. "Joint models of attitudes and behavior in evaluation of the San Diego I-15 congestion pricing project," Transportation Research Part A: Policy and Practice, Elsevier, Elsevier, vol. 35(6), pages 495-514, July.
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    Cited by:
    1. Hickman, Robin & Ashiru, Olu & Banister, David, 2010. "Transport and climate change: Simulating the options for carbon reduction in London," Transport Policy, Elsevier, Elsevier, vol. 17(2), pages 110-125, March.
    2. Elias, Wafa & Shiftan, Yoram, 2012. "The influence of individual’s risk perception and attitudes on travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, Elsevier, vol. 46(8), pages 1241-1251.
    3. Elias, Wafa & Albert, Gila & Shiftan, Yoram, 2013. "Travel behavior in the face of surface transportation terror threats," Transport Policy, Elsevier, Elsevier, vol. 28(C), pages 114-122.
    4. Diana, Marco & Pronello, Cristina, 2010. "Traveler segmentation strategy with nominal variables through correspondence analysis," Transport Policy, Elsevier, Elsevier, vol. 17(3), pages 183-190, May.
    5. Wen, Chieh-Hua & Wang, Wei-Chung & Fu, Chiang, 2012. "Latent class nested logit model for analyzing high-speed rail access mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, Elsevier, vol. 48(2), pages 545-554.

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