Deakin University
Browse
mcdonald-testingthecircumplex-2006.pdf (88.56 kB)

Testing the circumplex model of emotions in a consumer setting

Download (88.56 kB)
conference contribution
posted on 2006-01-01, 00:00 authored by P Darbyshire, R Bell, H McDonald
There is widespread belief that more positive emotional reactions to consumption situations will lead to positive business outcomes such as increased market share through the combination of increased loyalty, repeat purchase and strengthened reputation. However, most of the psychological work on emotions has not dealt directly with consumption experiences, but rather broader everyday experiences. In this study, psychological models of emotion were tested using magazine subscribers, specifically looking at their emotional responses to the magazine and the overall subscription package. The aim was to determine whether one of the major theories on emotional structure, the circumplex model, is relevant and consistent when applied specifically to a consumption experience. The results are positive, with the model being supported, and they provide insight into the structure and relations of different emotional responses (e.g., satisfaction, delight) consumers might have to a consumption experience.

History

Event

Australian & New Zealand Marketing Academy Conference (2006 : Brisbane, Queensland)

Publisher

Queensland University of Technology, School of Advertising, Marketing and Public Relations

Location

Queensland University of Technology, Gardens Point Campus, Brisbane

Place of publication

Brisbane, Qld.

Start date

2006-12-04

End date

2006-12-06

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2006, The authors

Editor/Contributor(s)

Y Ali, M van Dessel

Title of proceedings

ANZMAC 2006 : Advancing theory, maintaining relevance, proceedings

Usage metrics

    Research Publications

    Categories

    No categories selected

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC