dc.contributor.advisor |
Kanfer, F.H.J. (Frans) |
|
dc.contributor.postgraduate |
Cronje, Tanita |
|
dc.date.accessioned |
2021-05-04T11:41:48Z |
|
dc.date.available |
2021-05-04T11:41:48Z |
|
dc.date.created |
2014 |
|
dc.date.issued |
2014-05 |
|
dc.description |
Dissertation (MSc)--University of Pretoria, 2014. |
en_ZA |
dc.description.abstract |
In this decision-driven era, it has become vital for modelers to efficiently model consumer
choices and preferences (from a marketing perspective for instance). Conjoint analysis
is a known method which has been used to perform such analyses. A mixed effects
model is proposed to perform a conjoint analysis with normal responses, illustrated by
an application of modeling respondent’s preferences to different industrial detergents.
The proposed model allows for predicting how observed attributes (which describes a
product in terms of its characteristics and features) of decision makers and choice options,
influence decisions. Inference regarding the parameters of the proposed model with a
normal distribution is discussed in the mixed effect conjoint setting. Extensions of this
model, regarding Bayesian prior selection are also discussed. |
en_ZA |
dc.description.availability |
Unrestricted |
en_ZA |
dc.description.degree |
MSc |
en_ZA |
dc.description.department |
Statistics |
en_ZA |
dc.identifier.citation |
Cronje, T 2014, A mixed model approach to conjoint analysis, MSc Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/79776> |
en_ZA |
dc.identifier.other |
M14/9/149 |
en_ZA |
dc.identifier.uri |
http://hdl.handle.net/2263/79776 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
University of Pretoria |
|
dc.rights |
© 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
|
dc.subject |
UCTD |
en_ZA |
dc.title |
A mixed model approach to conjoint analysis |
en_ZA |
dc.type |
Dissertation |
en_ZA |