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Structural Equation Modeling of Relative Desired Travel Amounts

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  • Ory, David T
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    Abstract

    The “derived demand†perspective on daily travel, which has become axiomatic in thetransportation field, holds that travel is derived from the demand to participate in spatiallyseparatedactivities. The act of traveling itself is not considered to offer any positive utility, andminimizing travel time is a primary goal of all travelers in all situations. This dissertationcontinues a recent effort to challenge this paradigm by directly modeling the interrelationshipsamong travel amounts, perceptions, affections (or liking), and desires, and, in doing so, asking:why do some individuals want to travel more, and others less? By modeling quantities such astravel affection and desire, I am, importantly, first acknowledging the existence of these measuresand, second, formally quantifying their relative impact on daily travel amounts and each other.Five short-distance (one-way trips less than 100 miles) and five long-distance categories of travelare examined, specifically: short-distance overall, commute, work/school-related, entertainment/social/recreation, and personal vehicle; long-distance overall, work/school-related, entertainment/social/recreation, personal vehicle, and airplane. The models are estimated using data collected in1998 from more than 1,300 commuting workers in the San Francisco Bay Area. Cross-modelanalysis reveals three robust relationships, namely: (1) myriad measures of actual travel amountswork together to affect qualitative perceptions of those amounts (e.g. “a little†or “a lotâ€); (2)those perceptions are consistently important in shaping desires to reduce or increase one’s travel;and (3) affections for travel have a positive influence on those desires. The second findingsuggests that two individuals who travel the same objective amount may not have the same desireto reduce their travel: how much each individual perceives his or her travel to be is important.The third point argues that the degree to which travel is enjoyed is a key determinant in shapingdesires to reduce travel: the more travel is enjoyed, the less the desire to reduce it. Each of the tenmodels is estimated with the following four estimation techniques: maximum likelihood,asymptotic distribution free, bootstrapping, and the Mplus approach. A cross-model econometriccomparison by estimation technique and sample size is included.The implications of the work are largely theoretical, but the ideas presented can lead to verypractical suggestions. For instance, those promoting travel demand management strategies, suchas telecommuting, should pay attention to the travel perceptions of their target audience. Eventhough someone may be objectively traveling a lot, if the individual does not perceive thoseamounts to be high, he may not embrace a policy aimed at reducing his travel. And the same canbe said for those who enjoy travel: those who see value in travel, perhaps because it provides abuffer between the work and home realms of daily life, will logically be less motivated to reducetheir travel amounts. The survey respondents exhibit a considerable degree of liking for travel ofall kinds studied, and this work unequivocally demonstrates the importance of travel liking totravel behavior.

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    Bibliographic Info

    Paper provided by Institute of Transportation Studies, UC Davis in its series Institute of Transportation Studies, Working Paper Series with number qt8mj659fp.

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    Date of creation: 01 Jul 2007
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    Handle: RePEc:cdl:itsdav:qt8mj659fp

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    Keywords: UCD-ITS-RR-07-09; Engineering;

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    1. Steg, Linda, 2005. "Car use: lust and must. Instrumental, symbolic and affective motives for car use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 147-162.
    2. Redmond, Lothlorien, 2000. "Identifying and Analyzing Travel-Related Attitudinal, Personality, and Lifestyle Clusters in the San Francisco Bay Area," Institute of Transportation Studies, Working Paper Series qt0317h7v4, Institute of Transportation Studies, UC Davis.
    3. Masanori Ichikawa & Sadanori Konishi, 1995. "Application of the bootstrap methods in factor analysis," Psychometrika, Springer, vol. 60(1), pages 77-93, March.
    4. Ory, David T. & Mokhtarian, Patricia L., 2005. "When is getting there half the fun? Modeling the liking for travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 97-123.
    5. David T. Ory & Patricia L. Mokhtarian & Lothlorien S. Redmond & Ilan Salomon & Gustavo O. Collantes & Sangho Choo, 2004. "When is Commuting Desirable to the Individual?," Growth and Change, Gatton College of Business and Economics, University of Kentucky, vol. 35(3), pages 334-359.
    6. Larson, Douglas M. & Lew, Daniel K., 2005. "Measuring the utility of ancillary travel: revealed preferences in recreation site demand and trips taken," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 237-255.
    7. Mokhtarian, Patricia & Salomon, Ilan, 2001. "How Derived is the Demand for Travel? Some Conceptual and Measurement Considerations," Institute of Transportation Studies, Working Paper Series qt1z26n1r8, Institute of Transportation Studies, UC Davis.
    8. Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, December.
    9. Redmond, Lothlorien S. & Mokhtarian, Patricia L., 2001. "The Positive Utility of the Commute: Modeling Ideal Commute Time and Relative Desired Commute Amount," University of California Transportation Center, Working Papers qt4mc291p2, University of California Transportation Center.
    10. Choo, Sangho & Mokhtarian, Patricia L., 2004. "What type of vehicle do people drive? The role of attitude and lifestyle in influencing vehicle type choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(3), pages 201-222, March.
    11. Solomon, Ilan & Mokhtarian, Patricia L., 1998. "What Happens When Mobility-Inclined Market Segments Face Accessibility-Enhancing Policies?," University of California Transportation Center, Working Papers qt0f20d772, University of California Transportation Center.
    12. Muthen, Bengt, 1983. "Latent variable structural equation modeling with categorical data," Journal of Econometrics, Elsevier, vol. 22(1-2), pages 43-65.
    13. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    14. Redmond, Lothlorien S. & Mokhtarian, Patricia L., 2001. "Modeling Objective Mobility: The Impact of Travel-Related Attitudes, Personality and Lifestyle on Distance Traveled," Institute of Transportation Studies, Working Paper Series qt05d352fr, Institute of Transportation Studies, UC Davis.
    15. Tor Andreassen & Bengt Lorentzen & Ulf Olsson, 2006. "The Impact of Non-Normality and Estimation Methods in SEM on Satisfaction Research in Marketing," Quality & Quantity: International Journal of Methodology, Springer, vol. 40(1), pages 39-58, 02.
    16. Myoung-Jae Lee & Ayal Kimhi, 2005. "Simultaneous equations in ordered discrete responses with regressor-dependent thresholds," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 176-196, 07.
    17. Collantes, Gustavo O. & Mokhtarian, Patricia L., 2007. "Subjective assessments of personal mobility: What makes the difference between a little and a lot?," Transport Policy, Elsevier, vol. 14(3), pages 181-192, May.
    18. Tim Schwanen & Patricia L. Mokhtarian, 2007. "Attitudes toward travel and land use and choice of residential neighborhood type: Evidence from the San Francisco bay area," Housing Policy Debate, Taylor & Francis Journals, vol. 18(1), pages 171-207, January.
    19. Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
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