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  <titleInfo>
    <title>An analysis of travel mode transfer and first-and last-mile trips of public transport users in Bangkok</title>
  </titleInfo>
  <name type="personal">
    <namePart>Rattanan Hempholchom</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  </name>
  <name type="personal">
    <namePart>Kunnawee Kanitpong</namePart>
    <role>
      <roleTerm type="text">Chairperson</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Ampol Karoonsoontawong</namePart>
    <role>
      <roleTerm type="text">Co-Chairperson</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Bhatt, Ayushman</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Hadikusumo, Bonaventura H.W.</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>Royal Thai Government Fellowship</namePart>
    <role>
      <roleTerm type="text">Scholarship Donor</roleTerm>
    </role>
  </name>
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  <genre authority="marc">technical report</genre>
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    <place>
      <placeTerm type="text">Pathum Thani, Thailand</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>2025</dateIssued>
    <issuance>continuing</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
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    <extent>119 leaves : ill.+ 1 online resource</extent>
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  <abstract>This study focuses on identifying the key factors that influence individuals{u2019} mode  choices for First and Last Mile (FLM) travel connected to BTS stations in Bangkok. It  also looks at how household situations, like family size or vehicle ownership, influence  these travel decisions. The study also offers suggestions to encourage people to use  more environmentally friendly ways of getting to the BTS, like walking or using public  transport.  Data were gathered through a questionnaire survey involving 1,216 BTS passengers,  resulting in a total of 2,293 recorded FLM trips. The analysis was conducted using three  different models: the Multinomial Logit (MNL), Nested Logit (NL), and Latent Class  (LC) models. However, the NL model did not perform well due to invalid nesting, and  the LC model could not produce reliable results. As a result, the MNL model was used  as the main tool for analysis.  Among all versions of the MNL model tested, Model 19 showed the best performance.  It included variables related to travel time, cost, distance, demographic characteristics,  household structure, and built environment factors. The results show that cost and time  sensitivity, accessibility, vehicle ownership, and household size all significantly affect  FLM mode choice.  Based on these findings, several recommendations were made. These include  improving pedestrian access and cycling paths near BTS stations, enhancing bus  services, and encouraging the use of shared electric vehicles. The study also suggests  that future research could expand the study area or explore other rail systems, such as  the MRT Blue Line. </abstract>
  <note>A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Transportation Engineering</note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 2025</note>
  <subject authority="lcsh">
    <topic>Urban transportation</topic>
    <geographic>Thailand</geographic>
    <geographic>Bangkok</geographic>
  </subject>
  <subject authority="lcsh">
    <topic>Choice of transportation</topic>
    <geographic>Thailand</geographic>
    <geographic>Bangkok</geographic>
  </subject>
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    <titleInfo>
      <title>Thesis;  no. TE-24-03</title>
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      <namePart>Asian Institute of Technology.</namePart>
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  <identifier type="uri">http://203.159.5.9/ait-thesis/detail.php?q=B23368</identifier>
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