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Cited by 24Marketing and Advertising StrategiesAdvertising and Communication StudiesDigital Marketing and Social Media

Using Quasi-Experimental Data To Develop Empirical Generalizations For Persuasive Advertising

Open access
Armstrong, J. Scott, Patnaik, Sandeep·2009·Journal of Advertising Research
DOI 10.2501/s0021849909090230
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Abstract

ABSTRACT “Quasi-experimental data” provide a valid and relatively low-cost approach toward developing empirical generalizations (EGs). These data are obtained from studies in which some key variables have been controlled in the design. We describe our EGs as normative statements, i.e., “evidence-based principles.” Using data from 240 pairs of print advertisements from five editions of the Which Ad Pulled Best series, we analyzed 56 of the advertising principles from Persuasive Advertising by J. Scott Armstrong (New York: Palgrave Macmillan, forthcoming). These data controlled for target market, product, size of the advertisement, media, and in half the cases, for the brand. Aspects of the advertisements differed, however, as in illustrations, headlines, and text. The findings from quasi-experimental analyses were consistent with field experiments for all seven principles where such comparisons were possible. Furthermore, for 26 principles they unanimously corroborated the available laboratory experiments as well as the meta-analyses for seven principles. In short, quasi-experimental findings always agreed with experimental findings. This is impressive given that the quasi-experimental analyses—and some of the experimental analyses—involved small samples, and often used different criteria.

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  • In one study comparing findings from experiments with analyses of non-experimental data for 24 causal statements, the directional effects differed for 8 of the 24 comparisons.

    “In one study, we had an opportunity to compare findings from experiments with those from analyses of nonexperimental data for 24 causal statements. The directional effects differed for 8 of the 24 comparisons (Armstrong and Patnaik 2009).”

    From Illusions in Regression Analysis (2011) · cites this paper as Armstrong and Patnaik 2009

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Research works printed but not linked: 1

  1. Zinkhan, George M., and Betsy D. Gelb. "What Starch Scores Predict." Journal of Adver- tising Research 26, 4 (1986): 45-50.

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Related

Authors
Armstrong, J. S., & Patnaik, S.
Affiliations
  • University of Pennsylvania (US)
  • Gallup and Robinson
ORCID
Armstrong, J. Scott
Venue
Journal of Advertising Research
Publisher
Informa UK Limited
Published
2009-06
Volume
49
Issue
2
Pages
170-175
ISSN
  • 0021-8499 (ISSN-L)
  • 1740-1909
DOI
10.2501/s0021849909090230
OpenAlex
W2023683912
Cited by
24
References
2
Citations by year
2024: 1 · 2020: 1 · 2019: 3 · 2018: 1 · 2017: 2 · 2016: 7 · 2015: 1 · 2014: 3 · 2012: 3
FWCI
5.18
Type
journal article
Language
en
Open access
Locations
  • Journal of Advertising Research (publishedVersion)
  • Scholarly Commons (University of Pennsylvania) (submittedVersion)
  • ScholarlyCommons (University of Pennsylvania) (submittedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
  • Social Sciences › Communication › Advertising and Communication Studies
  • Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
Keywords
empirical generalization, persuasive advertising, advertising principles, print advertising, field experiments, advertising effectiveness, normative statements

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