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dc.contributor.advisorJoseph Ferreira Jr.en_US
dc.contributor.authorPonce Lopez, Robertoen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Urban Studies and Planning.en_US
dc.coverage.spatiala-si---en_US
dc.date.accessioned2019-02-05T15:59:54Z
dc.date.available2019-02-05T15:59:54Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/120234
dc.descriptionThesis: Ph. D. in Urban and Regional Studies, Massachusetts Institute of Technology, Department of Urban Studies and Planning, 2018.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 245-252).en_US
dc.description.abstractNon-work destinations refer to the locational choices of people regarding where they go for non-work activity. My exploration focuses on the daily trips with a primary purpose of shopping, entertainment, dining and refreshment in Singapore. The uniqueness of non-work trips, compared with home-to-work commuting trips, is that we do not observe the spatial tractability of the alternatives (home and work locations are known). Travelers have flexibility in location and schedule for non-work destination choices, and such selections repeat day after day. The flexibility to choose a non-work destination turns the modeling and forecasting of these trips into a complex task because a combination of factors, including the location of the supply of non-work activities, the activity pattern of the traveler, and the cost of traveling, affects the selection of non-work destination alternatives. This thesis utilizes a spatial-temporal scanning tool on cellphone-locational data to improve the spatial representation of places with high concentration of human activity, and use these places as a proxy of non-work destinations. Then, a clustering algorithm characterizes the spaces at the interior of those previously identified places by the geometry, diversity and density of the commercial establishments that they contain. Finally, the results of two statistical models that estimate housing price and destination choice indicate that the characterization of places capture additional information, which are useful in identifying the characteristics of neighborhoods (or space) and representing the destination alternatives of non-work activity. The model of destination choice shows the potential of the method to construct richer spatial nested structures of destination choice to what is currently in the literature. The main contribution of this thesis is the systematic development of measures that are useful to urban planners in characterizing places. These measures can help us to improve our understanding of non-work destination travel behavior. Another finding is that the spatial organization of the offer of non-work activities in Singapore is reminiscent of Central Place Theory. The spatial structure of non-work activities is highly monocentric, supplemented by additional facilities spread across clearly defined satellite suburban places. Three places in Singapore emerge as the top non-work destinations: Bugis, Orchard Road and Downtown. The distinctive attribute of these three places is that they comprise a diverse and dense number of patches or sub-spaces catering to various audiences.en_US
dc.description.statementofresponsibilityby Roberto Ponce Lopez.en_US
dc.format.extent252 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectUrban Studies and Planning.en_US
dc.titleAn exploration of non-work destinations in Singaporeen_US
dc.typeThesisen_US
dc.description.degreePh. D. in Urban and Regional Studiesen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Urban Studies and Planning.en_US
dc.identifier.oclc1083125015en_US


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