The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
An Integrated Approach toward the Spatial Modeling of Perceived Customer Value
Abstract
The authors present a new measurement methodology of perceived value, based on latent structure multidimensional scaling, that derives simultaneously the underlying dimensions of the perceived value of various brands and market segment heterogeneity in terms of how such value evaluations are made. This latent structure, ordered probit, multidimensional scaling (MDS) based methodology improves on existing industry techniques of illustrating perceived customer value because it enables researchers to infer the underlying dimensions of perceived value from the data without specifying these a priori, as is common in existing methods. The authors compare the proposed model against more traditional MDS approaches in an empirical illustration involving the perceived value of compact cars. Finally, the authors discuss managerial implications of this technique and provide directions for further research.
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
Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Bozdogan, H. (1987) · Psychometrika · doi:10.1007/bf02294361 · Cited by 4,468
Modeling Loss Aversion and Reference Dependence Effects on Brand Choice
Hardie, B. G. S., Johnson, E. J., & Fader, P. S. (1993) · Marketing Science · doi:10.1287/mksc.12.4.378 · Cited by 903
Cited by
The concept of perceived value: a systematic review of the research
Sánchez-Fernández, R., & Iniesta-Bonillo, M. Á. (2007) · Marketing Theory · doi:10.1177/1470593107083165 · Cited by 1,269
Creating Enduring Customer Value
Kumar, V., & Reinartz, W. (2016) · Journal of Marketing · doi:10.1509/jm.15.0414 · Cited by 829
The customer value proposition: evolution, development, and application in marketing
Payne, A., Frow, P., & Eggert, A. (2017) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-017-0523-z · Cited by 440
The moderating effect of customer perceived value on online shopping behaviour
Hsin Chang, H., & Wang, H. (2011) · Online Information Review · doi:10.1108/14684521111151414 · Cited by 398
The value proposition of food delivery apps from the perspective of theory of consumption value
Kaur, P., Dhir, A., Talwar, S., & Ghuman, K. (2021) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-05-2020-0477 · Cited by 377
Metadata
- Authors
- Sinha, I., & DeSarbo, W. S.
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 1998-05
- Volume
- 35
- Issue
- 2
- Pages
- 236-249
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W3121529737
- Cited by
- 317
- References
- 3
- FWCI
- 13.51
- Type
- journal article
- Language
- en
- Open access
- closed
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.