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When Attention‐Getting Advertising Tactics Elicit Consumer Inferences of Manipulative Intent: The Importance of Balancing Benefits and Investments
Abstract
This research examines two attention‐getting tactics commonly used in television advertising and explores how the use of these tactics might sometimes lead consumers to infer that the advertiser is attempting to manipulate the audience. The article explores how inferences of manipulative intent might arise if a consumer's perceptions of personal investments, personal benefits, advertiser's investments, and advertiser's benefits associated with the ad are not in balance. The data show that inferences of manipulative intent are related to measures of personal benefits, personal investments, and advertiser's investments as predicted and that these variables mediate the relationship between the attention‐getting tactics and inferences of manipulative intent. Inferences of manipulative intent are found to lower advertising persuasion as measured by ad attitudes, brand attitudes, and purchase intentions.
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Cites
Adams, J. S. (1965) · Advances in Experimental Social Psychology · doi:10.1016/s0065-2601(08)60108-2 · Cited by 10,818
Availability: A heuristic for judging frequency and probability
Tversky, A., & Kahneman, D. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90033-9 · Cited by 9,984
Cacioppo, J. T., & Petty, R. E. (1982) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.42.1.116 · Cited by 5,359
The Persuasion Knowledge Model: How People Cope with Persuasion Attempts
Friestad, M., & Wright, P. (1994) · Journal of Consumer Research · doi:10.1086/209380 · Cited by 3,811
Process Analysis: Estimating Mediation in Treatment Evaluations
Judd, C. M., & Kenny, D. A. (1981) · Evaluation Review · doi:10.1177/0193841x8100500502 · Cited by 2,442
Are Product Attribute Beliefs the Only Mediator of Advertising Effects on Brand Attitude?
Mitchell, A. A., & Olson, J. C. (1981) · Journal of Marketing Research · doi:10.2307/3150973 · Cited by 1,472
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The Effect of Corporate Social Responsibility (CSR) Activities on Companies With Bad Reputations
Yoon, Y., Gürhan‐Canli, Z., & Schwarz, N. (2006) · Journal of Consumer Psychology · doi:10.1207/s15327663jcp1604_9 · Cited by 1,429
Campbell, M. C., & Kirmani, A. (2000) · Journal of Consumer Research · doi:10.1086/314309 · Cited by 1,342
Self-citationDevelopment of a Scale to Measure Consumer Skepticism Toward Advertising
Obermiller, C., & Spangenberg, E. R. (1998) · Journal of Consumer Psychology · doi:10.1207/s15327663jcp0702_03 · Cited by 1,037
When Is Honesty the Best Policy? The Effect of Stated Company Intent on Consumer Skepticism
Foreh, M. R., & Grier, S. (2003) · Journal of Consumer Psychology · doi:10.1207/s15327663jcp1303_15 · Cited by 1,003
Getting Too Personal: Reactance to Highly Personalized Email Solicitations
White, T. B., Zahay, D. L., Thorbjørnsen, H., & Shavitt, S. (2008) · Marketing Letters · doi:10.1007/s11002-007-9027-9 · Cited by 365
Consequences of “greenwashing”: Consumers’ reactions to hotels’ green initiatives
Rahman, I., Park, J., & Chi, C. G.-Q. (2015) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-04-2014-0202 · Cited by 357
Enhancing or disrupting guilt: the role of ad credibility and perceived manipulative intent
Cotte, J., Coulter, R. A., & Moore, M. (2005) · Journal of Business Research · doi:10.1016/s0148-2963(03)00102-4 · Cited by 324
Guilt appeals: persuasion knowledge and charitable giving
Hibbert, S., Smith, A., Davies, A., & Ireland, F. (2007) · Psychology & Marketing · doi:10.1002/mar.20181 · Cited by 300
Fransen, M. L., Verlegh, P. W. J., Kirmani, A., & Smit, E. G. (2015) · International Journal of Advertising · doi:10.1080/02650487.2014.995284 · Cited by 282
Akpinar, E., & Berger, J. (2017) · Journal of Marketing Research · doi:10.1509/jmr.13.0350 · Cited by 267
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Arango, L., Singaraju, S. P., & Niininen, O. (2023) · Journal of Advertising · doi:10.1080/00913367.2023.2183285 · Cited by 243
Campbell, M. C., Mohr, G. S., & Verlegh, P. W. J. (2013) · Journal of Consumer Psychology · doi:10.1016/j.jcps.2012.10.012 · Cited by 234
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Campbell, C., Mattison Thompson, F., Grimm, P. E., & Robson, K. (2017) · Journal of Advertising · doi:10.1080/00913367.2017.1334249 · Cited by 112
Chen, K., Lin, J. (., & Shan, Y. (2021) · Journal of Consumer Behaviour · doi:10.1002/cb.1945 · Cited by 85
Wortel, C., Vanwesenbeeck, I., & Tomas, F. (2024) · Emerging Media · doi:10.1177/27523543241292096 · Cited by 50
Farman, L., Comello, M. L. (., & Edwards, J. R. (2020) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2020.1767292 · Cited by 48
Janssen, C., Swaen, V., & Du, S. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.07.005 · Cited by 42
Online shopping: How can algorithm performance expectancy enhance impulse buying?
Gallin, S., & Portes, A. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2024.103988 · Cited by 41
KAREKLAS, I., & MUEHLING, D. D. (2014) · Journal of Consumer Affairs · doi:10.1111/joca.12039 · Cited by 24
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“Although individual differences were not directly tested, prior research suggests these processes may vary based on cognitive capacity, motivation (Campbell 1995), privacy literacy, and regulatory awareness.”
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Metadata
- Authors
- Campbell, M. C.
- Venue
- Journal of Consumer Psychology
- Publisher
- Wiley
- Published
- 1995-01
- Volume
- 4
- Issue
- 3
- Pages
- 225-254
- ISSN
- 1057-7408 (ISSN-L)
- 1532-7663
- OpenAlex
- W2000832906
- Cited by
- 554
- References
- 6
- FWCI
- 5.15
- Type
- journal article
- Language
- en
- Open access
- closed
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