The DOI matches its Crossref record.
Value-System Segmentation: Exploring the Meaning of LOV
Open accessAbstract
Human values have been increasingly used as a basis for market segmentation. The list of values (LOV) is one common approach to segmentation: typically, marketers use the top-ranked value to assign consumers to segments. Although it is simple to implement, the top-rank approach to values segmentation conflicts with Rokeach's concept of an ordered value system, in which individual values are organized in the context of an overall hierarchy. This study uses a new measurement model that identifies latent (unobserved) value-system segments derived from a ranking of the LOV items. Higher-order value-system segments reflect the reality that multiple values will affect an individual's behavior. A values map is also constructed, which allows dimensions underlying the value-system segments to be identified. Data from a national survey show that the resulting value-system segments and values map have face validity consistent with the psychological structure of human values recently hypothesized by S. H. Schwartz and W. Bilsky.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Yoo, B., Donthu, N., & Lenartowicz, T. (2011) · Journal of International Consumer Marketing · doi:10.1080/08961530.2011.578059 · Cited by 916
Trying to prosume: toward a theory of consumers as co-creators of value
Xie, C., Bagozzi, R. P., & Troye, S. V. (2008) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-007-0060-2 · Cited by 668
Factors underlying the inclination to donate to particular types of charity
Bennett, R. (2003) · International Journal of Nonprofit and Voluntary Sector Marketing · doi:10.1002/nvsm.198 · Cited by 295
Impact of cultural values on technology acceptance and technology readiness
Sunny, S., Patrick, L., & Rob, L. (2019) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2018.06.017 · Cited by 197
Kraus, A. (2015) · International Journal of Consumer Studies · doi:10.1111/ijcs.12144 · Cited by 112
A Concept of Location-Based Social Network Marketing
Tussyadiah, I. P. (2012) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2012.666168 · Cited by 76
Krystallis, A., Vassallo, M., & Chryssohoidis, G. (2012) · Journal of Marketing Management · doi:10.1080/0267257x.2012.715091 · Cited by 63
Zhang, Q., Wang, Y., & Ariffin, S. K. (2024) · PLoS ONE · doi:10.1371/journal.pone.0296339 · Cited by 50
Metadata
- Authors
- Kamakura, W. A., & Novak, T. P.
- Venue
- Journal of Consumer Research
- Publisher
- Oxford University Press (OUP)
- Published
- 1992-06
- Volume
- 19
- Issue
- 1
- Pages
- 119
- ISSN
- 0093-5301 (ISSN-L)
- 1537-5277
- OpenAlex
- W2094870275
- Cited by
- 443
- References
- 0
- FWCI
- 10.00
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.