The San Francisco Bay Area Water Transit Authority is evaluating expanded ferry service, as required by the California legislature. Predicting ferry ridership has historically been difficult because water-transit riders often choose their travel mode based on factors other than travel time and cost. Most forecast models place a premium on time and cost and ignore other traveler attitudes. Structural equation modeling was used to identify simultaneously travel behavior and the causal relationships between a traveler's socioeconomic profile and travel attitudes. These market segments were used to estimate stated-preference (SP) mode choice models for 14 alternative modes, which separated the traveler's reaction to time savings by market segment and recognized that modal choices were different for market segments that were sensitive to travel stress or a desire to help the environment. The focus was on the application of the model to evaluate three future-year alternatives and to test the sensitivity of pricing policies, service changes, and alternative transit modes. These sensitivity runs included increased tolls on bridges, parking charges for Bay Area Rapid Transit stations, reduced ferry headways, alternative transit investments (express buses) in ferry corridors, and combinations of these assumptions. The results from these model runs were used to support the environmental impact statement and implementation and operations plan and were used to prioritize routes for further consideration based on the ridership potential in the corridor. Preliminary work to competitively position a ferry system that maximizes ferry mode share based on the market segments in the corridor was undertaken for a few routes.


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    Titel :

    Market Segmentation Approach to Mode Choice and Ferry Ridership Forecasting


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    01.01.2004




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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