Food product development - A consumer-led text analytic approach to generate preference structures
(2007) In British Food Journal 109(2-3). p.246-259- Abstract
- Purpose - This paper aims to illustrate a new method to cluster consumer attribute preferences and to transform spontaneously written texts by consumers about a certain favourite food product (hamburger) into distinct preference clusters of attributes. Design/methodology/approach - A new way of finding significant clusters of consumer attribute preferences is developed by means of a new text analytical approach (Pertex) and a multi-step two-sided cluster analysis procedure. Findings - Clear linkages were ascertained between four respondent and four preference clusters for the two key product dimensions taste and ingredients of the hamburger. Research limitations/implications - Clusters expressed were in close conformity to the conception... (More)
- Purpose - This paper aims to illustrate a new method to cluster consumer attribute preferences and to transform spontaneously written texts by consumers about a certain favourite food product (hamburger) into distinct preference clusters of attributes. Design/methodology/approach - A new way of finding significant clusters of consumer attribute preferences is developed by means of a new text analytical approach (Pertex) and a multi-step two-sided cluster analysis procedure. Findings - Clear linkages were ascertained between four respondent and four preference clusters for the two key product dimensions taste and ingredients of the hamburger. Research limitations/implications - Clusters expressed were in close conformity to the conception of the standard hamburger. Only one student sample (N = 100) was used. Practical implications - A new and practical method to transform written text into distinct consumer preferences (segments) was tested using a multi-step cluster analysis to support food innovation in the food industry. Originality/value - Product dimensions were integrated in a meaningful way into distinct preference clusters that could be used to segment consumers when innovating new food products. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/663201
- author
- Mattsson, Jan and Helmersson, Helge LU
- organization
- publishing date
- 2007
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- consumer behaviour, food industry, food products, fast foods, Sweden
- in
- British Food Journal
- volume
- 109
- issue
- 2-3
- pages
- 246 - 259
- publisher
- Emerald Group Publishing Limited
- external identifiers
-
- wos:000246085600011
- scopus:33847793857
- ISSN
- 0007-070X
- DOI
- 10.1108/00070700710732565
- language
- English
- LU publication?
- yes
- id
- 1af003b0-8409-4dee-934f-b467c461f912 (old id 663201)
- date added to LUP
- 2016-04-01 15:31:32
- date last changed
- 2022-02-12 08:22:06
@article{1af003b0-8409-4dee-934f-b467c461f912,
abstract = {{Purpose - This paper aims to illustrate a new method to cluster consumer attribute preferences and to transform spontaneously written texts by consumers about a certain favourite food product (hamburger) into distinct preference clusters of attributes. Design/methodology/approach - A new way of finding significant clusters of consumer attribute preferences is developed by means of a new text analytical approach (Pertex) and a multi-step two-sided cluster analysis procedure. Findings - Clear linkages were ascertained between four respondent and four preference clusters for the two key product dimensions taste and ingredients of the hamburger. Research limitations/implications - Clusters expressed were in close conformity to the conception of the standard hamburger. Only one student sample (N = 100) was used. Practical implications - A new and practical method to transform written text into distinct consumer preferences (segments) was tested using a multi-step cluster analysis to support food innovation in the food industry. Originality/value - Product dimensions were integrated in a meaningful way into distinct preference clusters that could be used to segment consumers when innovating new food products.}},
author = {{Mattsson, Jan and Helmersson, Helge}},
issn = {{0007-070X}},
keywords = {{consumer behaviour; food industry; food products; fast foods; Sweden}},
language = {{eng}},
number = {{2-3}},
pages = {{246--259}},
publisher = {{Emerald Group Publishing Limited}},
series = {{British Food Journal}},
title = {{Food product development - A consumer-led text analytic approach to generate preference structures}},
url = {{http://dx.doi.org/10.1108/00070700710732565}},
doi = {{10.1108/00070700710732565}},
volume = {{109}},
year = {{2007}},
}