The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Affective and Cognitive Factors in Preferences
Abstract
Affective factors play an important role in the development and maintenance of preferences. The representation of affect can take a variety of forms, including motor responses and somatic reactions. This explains why cognitive methods of preference change that are directed at only one form of representation have seldom been effective.
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
Feeling and thinking: Preferences need no inferences.
Zajonc, R. B. (1980) · American Psychologist · doi:10.1037/0003-066x.35.2.151 · Cited by 8,094
Self-citationShiffrin, R. M., & Schneider, W. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.127 · Cited by 7,335
Bower, G. H. (1981) · American Psychologist · doi:10.1037/0003-066x.36.2.129 · Cited by 4,154
Cited by
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
The Elaboration Likelihood Model of Persuasion
Petty, R. E., & Cacioppo, J. T. (1986) · Advances in Experimental Social Psychology · doi:10.1016/s0065-2601(08)60214-2 · Cited by 8,822
Dimensions of Consumer Expertise
Alba, J. W., & Hutchinson, J. W. (1987) · Journal of Consumer Research · doi:10.1086/209080 · Cited by 4,375
Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment.
Tversky, A., & Kahneman, D. (1983) · Psychological Review · doi:10.1037/0033-295x.90.4.293 · Cited by 3,991
Representativeness revisited: Attribute substitution in intuitive judgment.
Kahneman, D., & Frederick, S. (2002) · Heuristics and Biases · doi:10.1017/cbo9780511808098.004 · Cited by 3,476
The Role of Emotions in Marketing
Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999) · Journal of the Academy of Marketing Science · doi:10.1177/0092070399272005 · Cited by 3,349
The Elaboration Likelihood Model of Persuasion
Petty, R. E., & Cacioppo, J. T. (1986) · Communication and Persuasion · doi:10.1007/978-1-4612-4964-1_1 · Cited by 3,202
Slovic, P., Finucane, M., Peters, E., & MacGregor, D. G. (2002) · Heuristics and Biases · doi:10.1017/cbo9780511808098.025 · Cited by 2,349
“Clinical versus Actuarial Judgment.”
Dawes, R. M., Faust, D., & Meehl, P. E. (1989) · Science · doi:10.1126/science.2648573 · Cited by 2,298
The Hot Hand in Basketball: On the Misperception of Random Sequences
Gilovich, T., Vallone, R., & Tversky, A. (1985) · Cognitive Psychology · doi:10.1016/0010-0285(85)90010-6 · Cited by 1,649
A Framework for Conceptual Contributions in Marketing
MacInnis, D. J. (2011) · Journal of Marketing · doi:10.1509/jmkg.75.4.136 · Cited by 1,547
How advertising works: what do we really know?
Vakratsas, D., & Ambler, T. (1999) · Journal of Marketing · doi:10.1177/002224299906300103 · Cited by 1,436
Support theory: a nonextensional representation of subjective probability
Tversky, A., & Koehler, D. J. (1994) · Psychological Review · doi:10.1037/0033-295x.101.4.547 · Cited by 1,167
A framework for comparing customer satisfaction across individuals and product categories
Johnson, M. D., & Fornell, C. (1991) · Journal of Economic Psychology · doi:10.1016/0167-4870(91)90016-m · Cited by 898
Cacioppo, J. T., Priester, J. R., & Berntson, G. G. (1993) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.65.1.5 · Cited by 871
Dunning, D., Meyerowitz, J. A., & Holzberg, A. D. (1989) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.57.6.1082 · Cited by 758
Information Processing from Advertisements: Toward an Integrative Framework
MacInnis, D. J., & Jaworski, B. J. (1989) · Journal of Marketing · doi:10.1177/002224298905300401 · Cited by 653
Thompson, C. J., & Tambyah, S. K. (1999) · Journal of Consumer Research · doi:10.1086/209560 · Cited by 559
Chaiken, S., & Stangor, C. (1987) · Annual Review of Psychology · doi:10.1146/annurev.ps.38.020187.003043 · Cited by 518
A Survey-Based Method for Measuring and Understanding Brand Equity and Its Extendibility
Park, C. S., & Srinivasan, V. (1994) · Journal of Marketing Research · doi:10.1177/002224379403100210 · Cited by 446
Arsel, Z., & Thompson, C. J. (2011) · Journal of Consumer Research · doi:10.1086/656389 · Cited by 350
THONG, J. Y. L., HONG, W., & TAM, K.-Y. (2002) · International Journal of Human-Computer Studies · doi:10.1016/s1071-5819(02)91024-4 · Cited by 347
Lee, Y., & Kwon, O. (2011) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2010.11.005 · Cited by 343
Perspectives on consumer decision making: an integrated approach
Hansen, T. (2005) · Journal of Consumer Behaviour · doi:10.1002/cb.33 · Cited by 218
Micro-valences: perceiving affective valence in everyday objects
Lebrecht, S., Bar, M., Barrett, L. F., & Tarr, M. J. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00107 · Cited by 211
Mental Contamination and the Debiasing Problem
Wilson, T. D., Centerbar, D. B., & Brekke, N. (2002) · Heuristics and Biases · doi:10.1017/cbo9780511808098.012 · Cited by 160
The calibration of expert judgment: heuristics and biases beyond the laboratory
Koehler, D. J., Brenner, L., & Griffin, D. (2002) · Heuristics and Biases · doi:10.1017/cbo9780511808098.041 · Cited by 146
The mediation of cognitive attitude for online shopping
Chang, S.-H., Chih, W.-H., Liou, D.-K., & Yang, Y.-T. (2016) · Information Technology & People · doi:10.1108/itp-08-2014-0172 · Cited by 133
Mehta, N., Chen, X. (., & Narasimhan, O. (2008) · Marketing Science · doi:10.1287/mksc.1070.0310 · Cited by 107
Chowdhury, R. M. M. I., Olsen, G. D., & Pracejus, J. W. (2008) · Journal of Advertising · doi:10.2753/joa0091-3367370301 · Cited by 93
Unclarity confusion and expiration date labels in the United States: a consumer perspective
Hall-Phillips, A., & Shah, P. (2017) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2016.12.007 · Cited by 83
The effect of online social network characteristics on consumer purchasing intention of social deals
Park, M.-S., Shin, J.-K., & Ju, Y. (2014) · Global Economic Review · doi:10.1080/1226508x.2014.884047 · Cited by 48
G., R., & Asokan-Ajitha, A. (2021) · Journal of Indian Business Research · doi:10.1108/jibr-04-2018-0132 · Cited by 30
Mir, I. A. (2023) · Journal of Internet Commerce · doi:10.1080/15332861.2021.2021582 · Cited by 26
Metadata
- Authors
- Zajonc, R. B., & Markus, H.
- Venue
- Journal of Consumer Research
- Publisher
- Oxford University Press (OUP)
- Published
- 1982-09
- Volume
- 9
- Issue
- 2
- Pages
- 123
- ISSN
- 0093-5301 (ISSN-L)
- 1537-5277
- OpenAlex
- W2049023573
- Cited by
- 1,066
- References
- 3
- FWCI
- 7.83
- 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.
