
doi: 10.3141/2112-15
This research explores the effect of bus occupancy information on transit users’ choice of a bus by use of a binary logit model. The model predicts the probability of bus choice between the first arriving bus and the second arriving bus. The analysis is based on interview survey data obtained over 1 week (June 19 to June 25, 2008) in the Seoul metropolitan area in South Korea. The data reveal that the need for public transportation information varies by user group (white- or blue-collar workers, students, homemakers, self-employed workers, and older people) and the stage of the trip (before a trip, at a stop, on board, and at a transfer point). The results show that the availability of seats will increase the probability that a bus user will choose to board an arriving bus, with all other things being kept constant, whereas the travel time on board and the crowded-ness on a bus decrease the probability that a public transit user will choose to board an arriving bus. The effects of bus occupancy information are also different among user groups (white- or blue-collar workers, students, homemakers, self-employed workers, and older people) and trip purpose (commute and noncommute).
Travel time, Travel behavior, 330, Real time information, mode - bus, Seoul (Korea), operations - crowding, Passengers, Overcrowding, Bus transit operations, Traveler information and communication systems, Choice models, Commuting, ridership - commuting, Passenger information, Intracity bus transportation, Crowds, planning - signage/information, Bus transit, Crowding, technology - passenger information, Demographics, Journey time, Decision making, land use - impacts
Travel time, Travel behavior, 330, Real time information, mode - bus, Seoul (Korea), operations - crowding, Passengers, Overcrowding, Bus transit operations, Traveler information and communication systems, Choice models, Commuting, ridership - commuting, Passenger information, Intracity bus transportation, Crowds, planning - signage/information, Bus transit, Crowding, technology - passenger information, Demographics, Journey time, Decision making, land use - impacts
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