Using ordered probit modeling to study the effect of ATIS on transit ridership

Abstract A computer-aided telephone interview was conducted in two metropolitan areas in northern California. The survey included an innovative stated preference design to collect data that address the potential of advanced transit information systems. The study’s main objectives are to investigate whether advanced transit information would increase the acceptance of transit, and to determine the types and levels of information that are desired by commuters. The survey included a customized procedure that presents realistic choice sets, including the respondent’s preferred information items and realistic travel times. The ordered probit modeling technique was used. The results indicated a promising potential of advanced transit information in increasing the acceptance of transit as a commute mode. It also showed that the frequency of service, number of transfers, seat availability, walking time to the transit stop and fare information are among the significant information types that commuters desire. Commute time by transit, income, education, and whether the commuter is currently carpooling, were among the factors that contribute to the likelihood of using transit given information was provided.

[1]  Mark Hickman,et al.  Assessment of Information Systems and Technologies at California Transit Agencies , 1996 .

[2]  Peter Jones,et al.  The acquisition of pre-trip information: A stated preference approach , 1993 .

[3]  Asad J. Khattak,et al.  A TAXONOMY FOR ADVANCED PUBLIC TRANSPORTATION SYSTEMS , 1996 .

[4]  F. Koppelman,et al.  Stated preferences for investigating commuters' diversion propensity , 1993 .

[5]  Mohamed Abdel-Aty,et al.  Investigating Effect of Advanced Traveler Information on Commuter Tendency To Use Transit , 1996 .

[6]  Mohamed Abdel-Aty,et al.  INVESTIGATING EFFECT OF TRAVEL TIME VARIABILITY ON ROUTE CHOICE USING REPEATED-MEASUREMENT STATED PREFERENCE DATA , 1995 .

[7]  Jordan J. Louviere,et al.  Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate Data , 1983 .

[8]  Ryuichi Kitamura,et al.  The Impact of Advanced Transit Information on Commuters' mode Changing , 1996, J. Intell. Transp. Syst..

[9]  R. Kitamura,et al.  TRANSIT PRE-TRIP INFORMATION SYSTEMS: AN EXPERIMENTAL ANALYSIS OF INFORMATION ACQUISITION AND ITS IMPACTS ON MODE USE , 1995 .

[10]  Carol L Schweiger EN-ROUTE TRANSIT INFORMATION SYSTEMS: THE STATE OF THE ART IN NORTH AMERICA , 1995 .

[11]  Randolph W. Hall,et al.  EVALUATION OF TRANSIT TELEPHONE INFORMATION AT SCRTD , 1994 .

[12]  Mark Hickman,et al.  PASSENGER TRAVEL TIME AND PATH CHOICE IMPLICATIONS OF REAL-TIME TRANSIT INFORMATION , 1995 .

[13]  Fred L. Mannering,et al.  ANALYSIS OF THE IMPACT OF INTEREST RATES ON AUTOMOBILE DEMAND , 1987 .

[14]  R. McKelvey,et al.  A statistical model for the analysis of ordinal level dependent variables , 1975 .