Can we get more out of Net-Promoter Data?

dc.contributor.authorMecredy, Pen_US
dc.contributor.authorFeetham, PMen_US
dc.contributor.authorWright, MJen_US
dc.contributor.editorSinha, Aen_US
dc.contributor.editorCadeaux, Jen_US
dc.contributor.editorBucic, Ten_US
dc.coverage.spatialSydneyen_US
dc.date.accessioned2016-04-17T23:17:29Z
dc.date.accessioned2016-04-19T23:43:25Z
dc.date.available19/02/2016en_US
dc.date.finish-date2015-12-02en_US
dc.date.finish-date2015-12-02en_US
dc.date.finish-date2015-12-02en_US
dc.date.finish-date2015-12-02en_US
dc.date.finish-date2015-12-02en_US
dc.date.issued19/02/2016en_US
dc.date.start-date2015-11-30en_US
dc.date.start-date2015-11-30en_US
dc.date.start-date2015-11-30en_US
dc.date.start-date2015-11-30en_US
dc.date.start-date2015-11-30en_US
dc.description.abstractNet-Promoter Score (NPS), a loyalty measure, is used extensively in commercial market research due to its simplicity of use and ease of understanding, despite criticism of the metric. Given the widespread use of NPS commercially, it is important to understand whether applying alternative loyalty measures has any advantages over Net-Promoter. This paper aims to demonstrate whether a likelihood mean and Polarization Index, φ, provide different results to Net-Promoter. These three measures were applied to data collected from an on-line survey of 1,818 participants who evaluated brands in a service industry. The findings show that all three measures provided similar variations in loyalty across brands and regions. The likelihood mean and NPS are strongly correlated, indicating that no one measure is more superior to the other at measuring loyalty within a service industry in New Zealand. However, the Polarization Index appears to assess loyalty differently to the likelihood mean and NPS.en_US
dc.description.confidentialfalseen_US
dc.description.confidentialfalseen_US
dc.description.confidentialfalseen_US
dc.description.confidentialfalseen_US
dc.description.confidentialfalseen_US
dc.description.place-of-publicationSydneyen_US
dc.description.place-of-publicationSydneyen_US
dc.description.place-of-publicationSydneyen_US
dc.description.place-of-publicationSydneyen_US
dc.description.place-of-publicationSydneyen_US
dc.format.extent333 - 338 (6)en_US
dc.identifierhttp://www.anzmac.org/_resourceitems/14558601192015-ANZMAC-Conference-Proceedings.pdfen_US
dc.identifier.citation2016, pp. 333 - 338 (6)en_US
dc.identifier.elements-id259667
dc.identifier.harvestedMassey_Dark
dc.identifier.issn1441-3582en_US
dc.identifier.urihttps://hdl.handle.net/10179/7746
dc.publisherANZMACen_US
dc.relation.replaceshttp://hdl.handle.net/123456789/2578
dc.relation.replaces123456789/2578
dc.sourceAustrailian and New Zealand Marketing Academy Conferenceen_US
dc.subjectNet-Promoter, polarization index, brand loyalty measuresen_US
dc.titleCan we get more out of Net-Promoter Data?en_US
dc.typeConference Paper
pubs.notesNot knownen_US
pubs.organisational-group/MU
pubs.organisational-group/MU/College of Business
pubs.organisational-group/MU/College of Business/School of Communication, Journalism and Marketing
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