Market Segmentation Approach to Mode Choice and Ferry Ridership Forecasting

Abstract

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.

A Psychological Investigation on Public-transport Users’ Intention to Use Routes with Transfers

“…Travel behavior studies [10,[48][49][50] have shown that PT users' socio-demographics and trip characteristics have an effect on their travel behavior. Guo and Wilson [7] discussed that frequent riders tend to be more familiar with the PT network and services and therefore perceive transfers to be less onerous than infrequent riders.…”

Identifying key risk factors in air traffic control by exploratory and confirmatory factor analysis

“…The structural equation modeling (SEM) approach is one of the most appropriate techniques for identifying latent variables and analyzing the correlational relationship among them, since it combines the advantages of confirmatory factor analysis and path analysis (multiple regression), which can test the linear causal relationship among variables and assess the hypothetical model with both manifest and latent variables. SEM has been widely applied in various transportation fields, including travel behavior and demand (e.g., [20][21][22][23][24][25][26][27][28][29]), mode choice (e.g., [30][31][32][33]), service quality (e.g., [34][35][36]), and transport safety (e.g., [37,38]) during recent decades. The SEM approach possesses several technologic advantages over other statistical methods.…”

An Environmental Decision Framework Applied to Marine Engine Control Technologies

“…Some literature suggest that where customers are informed about environmental stewardship implications, ridership or cargo volume on a cleaner vessel could be positively affected; these factors are being considered in marketing efforts for expanded ferry service. 39 If the physical attributes of an alternative reduce vessel capacity, then there may be some negative revenue impacts.…”