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dc.contributor.advisorJohn P. Attanucci.en_US
dc.contributor.authorChow, William, S.M. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Civil and Environmental Engineering.en_US
dc.date.accessioned2014-09-19T19:37:33Z
dc.date.available2014-09-19T19:37:33Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/89853
dc.descriptionThesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2014.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 119-121).en_US
dc.description.abstractPublic transit agencies have traditionally relied on manually collected customer surveys to understand travel behavior and customer satisfaction. With formerly manually collected data such as ridership and running times now being automatically collected, there exists an opportunity to simplify surveys using this automatically collected information. This thesis evaluates an online approach to conduct customer surveys at a public transit agency by linking prior trip history into the survey. It also tests the prompted recall survey approach, where the personalized survey displays a prior trip segment and asks about the journey made by the respondent. The Massachusetts Bay Transportation Authority (MBTA), Boston's public transit agency, was used as a case study to develop a customer panel and test the online survey approach with prompted recall. The research showed that verifying a trip was made in the previous week significantly increased the chances of survey response having an associated trip record. Confirming that a recent trip was made by the respondent increased the rate of matching surveyed journeys to fare transaction data from 26.7% of individuals with no recent trip to 64.2% for individuals with a recent trip. Prompted recall had a slightly higher match rate of 67.3% of individuals, but the rate of partial matches using the prompted recall approach was significantly higher at 88%. Some missed matches may be due to inaccurate or incomplete records in fare transaction records, and solutions to these issues may increase the percentage of matches through the prompted recall approach. This result shows promise for transit agencies that may look to target surveys towards individuals using specific lines or routes. The success of this approach was primarily due to the construction of the survey, which allowed for previous trip records to be analyzed prior to subsequent survey distribution, and therefore should be used as one way to increase the quantity and quality of survey responses.en_US
dc.description.statementofresponsibilityby William Chow.en_US
dc.format.extent121 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.titleEvaluating online surveys for public transit agencies using a prompted recall approachen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Transportationen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.identifier.oclc890140130en_US


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