The DOI matches its Crossref record.
The Construction of Preference
Abstract
One of the main themes that has emerged from behavioral decision research during the past three decades is the view that people's preferences are often constructed in the process of elicitation. This idea is derived from studies demonstrating that normatively equivalent methods of elicitation (e.g., choice and pricing) give rise to systematically different responses. These preference reversals violate the principle of procedure invariance that is fundamental to all theories of rational choice. If different elicitation procedures produce different orderings of options, how can preferences be defined and in what sense do they exist? This book shows not only the historical roots of preference construction but also the blossoming of the concept within psychology, law, marketing, philosophy, environmental policy, and economics. Decision making is now understood to be a highly contingent form of information processing, sensitive to task complexity, time pressure, response mode, framing, reference points, and other contextual factors.
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
Towards demand-side solutions for mitigating climate change
Creutzig, F., Roy, J., Lamb, W. F., Azevedo, I. M. L., Bruine de Bruin, W., Dalkmann, H., Edelenbosch, O. Y., Geels, F. W., Grubler, A., Hepburn, C., et al. (2018) · Nature Climate Change · doi:10.1038/s41558-018-0121-1 · Cited by 854
Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation
Fleming, S. M., & Daw, N. D. (2017) · Psychological Review · doi:10.1037/rev0000045 · Cited by 584
Associative processes in intuitive judgment
Morewedge, C. K., & Kahneman, D. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.07.004 · Cited by 492
Baird, A., & Maruping, L. M. (2021) · MIS Quarterly · doi:10.25300/misq/2021/15882 · Cited by 512
West, R. F., Toplak, M. E., & Stanovich, K. E. (2008) · Journal of Educational Psychology · doi:10.1037/a0012842 · Cited by 416
Metadata
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2006-08-28
- OpenAlex
- W891400952
- Cited by
- 785
- References
- 0
- FWCI
- 13.48
- Type
- book
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Construction of Preference. https://app.cochat.ai/papers/10.1017/cbo9780511618031
- The paper
- The Construction of Preference. (2006). Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511618031
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.