The superiority of panel research: a fast food choice modeling case study using online panel research

Fine, B; Menictas, C; Wei, XIN

The superiority of panel research: a fast food choice modeling case study using online panel research

Fine, B Menictas, C Wei, XIN

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Publisher:: ESOMAR
Publication Type:: Conference Proceeding
Citation:: ESOMAR Publications, Panel Research Collection 2007, 2007, pp. 1 - 13
Issue Date:: 2007-01

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Field	Value	Language
dc.contributor.author	Fine, B	en_US
dc.contributor.author	Menictas, C	en_US
dc.contributor.author	Wei, XIN	en_US
dc.contributor.editor	Fellows, D	en_US
dc.date	2007-10-28	en_US
dc.date.issued	2007-01	en_US
dc.identifier.citation	ESOMAR Publications, Panel Research Collection 2007, 2007, pp. 1 - 13	en_US
dc.identifier.isbn	92-831-0211-8	en_US
dc.identifier.uri	http://hdl.handle.net/10453/7655
dc.description.abstract	This paper presents a nationwide price optimisation study for a fast-food company s menu in Australia. * We demonstrate the benefits of combining the practicality of online panels with discrete choice modelling. * As discrete choice models involve trade-offs between alternatives, the full set of alternatives for each choice task is best represented using web-based visual choice tasks. * Data solicitation via online panels is not constrained by geography when compared to CATI or face-to-face methods, hence their unique ability to effortlessly capture nationwide representation. * The amount of information in discrete choice experimental output is oftentimes overwhelming and recently the practice has been to present clients with a decision support system (DSS), to simplify the amount of data the user has to deal with when interpreting the results. * The DSS allows the user to simulate price changes and visually appreciate the impact to market share. * We present a state of the art DSS, which dramatically reduces the amount of information users typically deal with when interpreting the output of discrete choice models.	en_US
dc.publisher	ESOMAR	en_US
dc.relation.ispartof	ESOMAR Publications, Panel Research Collection 2007	en_US
dc.relation.ispartof	ESOMAR Panel Research	en_US
dc.title	The superiority of panel research: a fast food choice modeling case study using online panel research	en_US
dc.type	Conference Proceeding
utslib.location	USA	en_US
utslib.location.activity	Orlando, USA	en_US
utslib.for	150505 Marketing Research Methodology	en_US
dc.location.activity	Orlando, USA	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Arts and Social Sciences
pubs.organisational-group	/University of Technology Sydney/Faculty of Arts and Social Sciences/FASS Faculty Administration
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.place-of-publication	USA	en_US
pubs.start-date	2007-10-28	en_US

Abstract:

This paper presents a nationwide price optimisation study for a fast-food company s menu in Australia. * We demonstrate the benefits of combining the practicality of online panels with discrete choice modelling. * As discrete choice models involve trade-offs between alternatives, the full set of alternatives for each choice task is best represented using web-based visual choice tasks. * Data solicitation via online panels is not constrained by geography when compared to CATI or face-to-face methods, hence their unique ability to effortlessly capture nationwide representation. * The amount of information in discrete choice experimental output is oftentimes overwhelming and recently the practice has been to present clients with a decision support system (DSS), to simplify the amount of data the user has to deal with when interpreting the results. * The DSS allows the user to simulate price changes and visually appreciate the impact to market share. * We present a state of the art DSS, which dramatically reduces the amount of information users typically deal with when interpreting the output of discrete choice models.

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http://hdl.handle.net/10453/7655