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 <datafield tag="088" ind1="" ind2="">
  <subfield code="a">Glerum_STRC_12</subfield> 
  </datafield>
<datafield tag="909" ind1="C" ind2="0">
<subfield code="p">TRANSP-OR</subfield>
</datafield>
<datafield tag="980" ind1="" ind2="">
<subfield code="a">TALK</subfield>
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 <datafield tag="700" ind1="" ind2="">
  <subfield code="a">Glerum, Aurélie</subfield> 
  </datafield>
 <datafield tag="700" ind1="" ind2="">
  <subfield code="a">Bierlaire, Michel</subfield> 
  </datafield>
<datafield tag="245" ind1="" ind2="">
<subfield code="a">
Accounting for response behavior heterogeneity in the measurement of attitudes: an application to demand for electric vehicles</subfield>
</datafield>
<datafield tag="260" ind1="" ind2="">
<subfield code="c">2012</subfield>
</datafield>
<datafield tag="711" ind1="2" ind2="">
<subfield code="a">
Swiss Transport Research Conference</subfield>
<subfield code="c">
Ascona</subfield>
<subfield code="d">May 04, 2012</subfield>
</datafield>
<datafield tag="520" ind1="" ind2="">
<subfield code="a">
Hybrid choice models have proved to be a powerful framework that integrates attitudinal and perceptional data into discrete choice models. However the measurement component of such a framework often fails to exploit individual-specific information that might affect the way subjects answer to indicators of opinion. In this paper we propose an HCM with a measurement model that takes into account heterogeneity in the response behavior. Precisely, we capture effects of exaggeration in answers to psychometrics. We moreover provide an application of this model to the evaluation of the future demand for electric vehicles.</subfield>
</datafield>
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