Summary Knowing More Than We're Told: Inferences From Advertising Claims
Citation:
Carolyn J. Simmons and Gita Venkataramani Johar (1994) ,"Summary Knowing More Than We're Told: Inferences From Advertising Claims", in NA - Advances in Consumer Research Volume 21, eds. Chris T. Allen and Deborah Roedder John, Provo, UT : Association for Consumer Research, Pages: 96.
KNOWING MORE THAN WE'RE TOLD: INFERENCES FROM ADVERTISING CLAIMS The first paper by Sandra Burke, Sandra Milberg, and Youjae Yi examined the effects of claims about attributes which are inherent to the product category, but which are not emphasized by competitive brands (e.g., Mazola corn oil has no cholesterol). Among those who believed the claimed attribute to be atypical of the product category, such claims increased the probability of brand choice and the perceived importance and typicality of the attribute. These subjects also reported believing that brands not making the claim did not possess the attribute. The second paper by Gita Venkataramani Johar primarily examined claims with incomplete comparisons (e.g.,this brand is better) and inconspicuous qualifications (e.g., qualifications in small print). The inconspicuous qualification was deceptive only under low involvement. Deceptive inferences from incomplete comparisons appeared to be made by some low and high involvement subjects; however, response times revealed that such inferences were made at the time of processing the ad only under high involvement. The third paper by Frank Kardes examined the effects of set size, valence of information, and instruction set (encouraging consideration of unmentioned attributes or not) on consideration of unmentioned attributes, inferences, brand evaluations, and confidence and uncertainty about evaluations. Positive information increased positive inferences, while negative information increased negative inferences, with the greatest number of negative inferences being made when subjects were encouraged to consider unmentioned attributes. No effects were found for set size. Positive inferences had a stronger impact on evaluations than did negative inferences, whereas negative inferences had a stronger impact on confidence than did positive inferences. In his concluding discussion, John Lynch addressed methodological issues relevant to the measurement of deception, including designs for determining whether an inference not made at encoding is made at the time of choice, the tradeoffs in using response times versus closed- and open-ended questions to detect inferences, and the use of baseline control conditions to detect inferences. He also identified a number of questions raised by the papers regarding potential mediators (attribute diagnosticity, inferences versus discounting, etc.) and moderators (sparseness versus denseness of information environment) of observed effects. ----------------------------------------
Authors
Carolyn J. Simmons, Lehigh University
Gita Venkataramani Johar, Columbia University
Volume
NA - Advances in Consumer Research Volume 21 | 1994
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