<?xml version="1.0" encoding="UTF-8"?>
<mods xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.loc.gov/mods/v3" version="3.1" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
  <titleInfo>
    <title>Time extended logit type models based on classical consumer behavior theory</title>
  </titleInfo>
  <name type="personal">
    <namePart>Parajuli, Bishnu Prasad</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Morisugi, Hisa</namePart>
    <role>
      <roleTerm type="text">Chairperson</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Fujiwara, Okitsugu</namePart>
    <role>
      <roleTerm type="text">Examination committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Chen, Jian Shiuh</namePart>
    <role>
      <roleTerm type="text">Examination committee</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>Government of Austria</namePart>
    <role>
      <roleTerm type="text">Scholarship donor</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">th</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Bangkok</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>1996</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>92 leaves</extent>
  </physicalDescription>
  <abstract>Two models for travel demand forecasting are formulated based on consumer behavior  theory and considering value of time saving. Techniques for estimation of model parameters are  also illustrated using social trip data. The first model predicts the demand share of each travel  mode from each origin to each destination simultaneously. Second model is total demand model  which predicts the total number of trips generated in a given origin. Combination of these two  models gives the actual number of trips by each mode from each origin to each destination. All  the demand functions include the policy variables such as travel time and travel cost which  facilitate to assess the effect of policy change on travel demand.  Prediction accuracy of models is checked comparing the predicted and observed  demands. Results show that predictions are fairly accurate with high correlation coefficient  between the predicted and observed demands. Sensitivity analysis is carried out. Results show  that demands are highly sensitive to the variables considered in the model.  Predictions and sensitivity's of the said models were compared with those of  conventional models. Results prevailed that proposed models are better that the conventional  one in terms of accuracy and sensitiveness</abstract>
  <note>A thesis submitted in partial fulfillment of the requirement for the degree of  Master of Engineering, School of Civil Engineering  </note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 1996</note>
  <subject authority="lcsh">
    <topic>Transportation</topic>
    <topic>Planning</topic>
  </subject>
  <relatedItem type="series">
    <titleInfo>
      <title>Thesis ; no. TE-95-07</title>
    </titleInfo>
    <name type="corporate">
      <namePart>Asian Institute of Technology.</namePart>
      <namePart/>
    </name>
  </relatedItem>
  <identifier type="uri">http://203.159.5.9/ait-thesis/detail.php?q=B15011</identifier>
  <location>
    <url displayLabel="Full-Text">http://203.159.5.9/ait-thesis/detail.php?q=B15011</url>
  </location>
  <recordInfo>
    <recordCreationDate encoding="marc">180698</recordCreationDate>
    <recordChangeDate encoding="iso8601">20260819084629.0</recordChangeDate>
  </recordInfo>
</mods>
