The relationship between land use and automobile travel utility: A Multiple Indicators Multiple Causes approach |
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| Institution: | 1. Centro Interuniversitario de Investigaciones sobre Desarrollo Económico, Territorio e Instituciones (CIDETI), Alma Mater Studiorum-Università di Bologna in the Argentine Republic, Argentina;2. Institut de Statistique, Biostatistique et Sciences Actuarielles (ISBA), UCLouvain, Belgium;3. Center for Operations Research and Econometrics (CORE), UCLouvain, Belgium;1. The University of Texas at Austin, Department of Civil, Architectural and Environmental Engineering, 301 E. Dean Keeton St. Stop C1761, Austin TX 78712, USA;2. The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;3. AECOM, 9400 Amberglen Blvd, Austin, TX 78729, USA;1. Choice Modelling Centre and Institute for Transport Studies, University of Leeds, 36-40 University Road, Leeds LS2 9JT, UK;2. Department of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Bangladesh |
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| Abstract: | The relationship between land use and the utility of automobile travel is examined by refining the utility concept, particularly by combining the microeconomic utility theory, which is concerned with the disutility of travel, and the perspective on the positive utility. A conceptual model is accordingly developed and then adjusted considering different purposes of travel. The purpose-specific models are tested through a Multiple Indicators Multiple Causes approach in Seoul, Korea, using datasets from a sample survey and geographic information systems. The major finding is that land use affects the utility mainly by changing synergy and affective utility rather than instrumental utility, which encompasses disutility variables. Among land use variables, the utility is found to be the most sensitive to the number of transit facilities for commuting and shopping travel and land use balance for leisure travel. |
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| Keywords: | Land use Travel utility Structural equation modeling Multiple Indicators Multiple Causes model |
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