A NOVEL MEASUREMENT OF JOB ACCESSIBILITY BASED ON MOBILE DEVICE LOCATION DATA

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dc.contributor.advisorZhang, Lei LZen_US
dc.contributor.authorZhao, Guangchenen_US
dc.contributor.departmentCivil Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2022-06-15T05:47:48Z
dc.date.available2022-06-15T05:47:48Z
dc.date.issued2022en_US
dc.description.abstractMobile device location data (MDLD) can offer a new perspective on measuring accessibility. Compared with the traditional accessibility measures, MDLD is capable of capturing people’s preferences with the observed locations. This study proposes a job accessibility measure based on the identified home and work locations from MDLD, evaluating the job accessibility by the proportion of workers identified working in zones within a certain time threshold. In the case study on the Baltimore region, the job accessibility from the MDLD-based measure is compared with the results from a widely-used traditional measure. Then, generalized additive models (GAM) are built to analyze the socio-demographic impact on job accessibility from a MDLD-based measure and a traditional measure, with a feature-to-feature comparison. Finally, the socio-demographic characteristics of regions where there are major disparities between the job accessibility from the traditional measure and the MDLD-based measure are also evaluated from the Student's t-test results.en_US
dc.identifierhttps://doi.org/10.13016/eunk-x2ex
dc.identifier.urihttp://hdl.handle.net/1903/28806
dc.language.isoenen_US
dc.subject.pqcontrolledTransportationen_US
dc.subject.pquncontrolledAccessibilityen_US
dc.subject.pquncontrolledGeneralized Additive Modelen_US
dc.subject.pquncontrolledMobile Device Location Dataen_US
dc.subject.pquncontrolledSocial Equalityen_US
dc.subject.pquncontrolledSocio Demographicsen_US
dc.titleA NOVEL MEASUREMENT OF JOB ACCESSIBILITY BASED ON MOBILE DEVICE LOCATION DATAen_US
dc.typeThesisen_US

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