000206252 001__ 206252
000206252 005__ 20180123001131.0
000206252 0247_ $$2Other$$aISSN 2194-511X
000206252 037__ $$a1023-2016-81885
000206252 041__ $$aen_US
000206252 245__ $$aAttribute Non-Attendance and Satisficing Behavior in Online Choice Experiments
000206252 260__ $$c2015-05
000206252 269__ $$a2015-05
000206252 270__ $$mlahouse@ufl.edu$$pHouse,   Lisa A.
000206252 271__ $$mschiefer@uni-bonn.de$$pSchiefer,   Gerhard
000206252 271__ $$mulb20a@uni-bonn.de$$pRickert,   Ursula
000206252 300__ $$a18
000206252 336__ $$aConference Paper/ Presentation
000206252 520__ $$aWhile a successful survey requires engaged and attentive respondents, careless survey completion remains a great concern in online market research. In this article, we test metrics of engagement in an online willingness-to-pay (WTP) study for fresh blueberry attributes using a major U.S. panel company and evaluate the impact that poorly behaving respondents have on subsequent data quality. In doing so, we investigate in detail the complex joint relationship between attribute non-attendance (ANA) and measures of respondent engagement in web surveying. Using fixed latent classes, an approach known as the Equality Constrained Latent Class procedure, we export individual probabilistic class assignment of all levels of attribute attendance to cross reference with respondents who fail measures of engagement and fraudulence, and analyze their composition and impact on latent classes, indicating non-attendance of individual and combinations of attributes. We also analyze engagement impacts on the tau variance parameter in the scaled mixed logit model and find strong links to unnecessarily increased heterogeneity when not properly filtering poorly behaving respondents. While WTP estimates between respondents passing and failing engagement metrics are similar with the ECLC model, filtering failing respondents in the scaled mixed logit model reduces overall WTP estimates. Results have implications for both WTP researchers and general online market researchers.
000206252 542__ $$fLicense granted by Ursula Rickert (ulb20a@uni-bonn.de) on 2015-06-08T20:03:05Z (GMT):

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000206252 650__ $$aAgribusiness
000206252 700__ $$aJones, Michael S.
000206252 700__ $$aHouse, Lisa A.
000206252 700__ $$aGao, Zhifeng
000206252 720__ $$aSchiefer,   Gerhard$$eeditor
000206252 720__ $$aRickert,   Ursula$$eeditor
000206252 773__ $$d2015$$o432$$q415
000206252 8564_ $$s329062$$uhttp://ageconsearch.umn.edu/record/206252/files/34-House_ANA%20Igls%20paper.pdf
000206252 887__ $$ahttp://purl.umn.edu/206252
000206252 909CO $$ooai:ageconsearch.umn.edu:206252$$pGLOBAL_SET
000206252 912__ $$nSubmitted by Ursula Rickert (ulb20a@uni-bonn.de) on 2015-06-08T20:06:24Z
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000206252 912__ $$nMade available in DSpace on 2015-06-08T20:06:24Z (GMT). No. of bitstreams: 1
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  Previous issue date: 2015-05
000206252 982__ $$gInternational European Forum on System Dynamics and Innovation in Food Networks>2015 International European Forum (144th EAAE Seminar), February 9-13, 2015, Innsbruck-Igls, Austria
000206252 980__ $$a1023