Special Session Summary For Better Or For Worse: the Effect of Positive and Negative Disconfirmatory Information in the Marketplace

Rohini Ahluwalia, University of Kansas
Zeynep Gnrhan, University of Michigan
[ to cite ]:
Rohini Ahluwalia and Zeynep Gnrhan (1998) ,"Special Session Summary For Better Or For Worse: the Effect of Positive and Negative Disconfirmatory Information in the Marketplace", in NA - Advances in Consumer Research Volume 25, eds. Joseph W. Alba & J. Wesley Hutchinson, Provo, UT : Association for Consumer Research, Pages: 13.

Advances in Consumer Research Volume 25, 1998      Page 13



Rohini Ahluwalia, University of Kansas

Zeynep Gnrhan, University of Michigan

The potential impact of disconfirmatory information on a target’s subsequent perception and evaluation is of great interest to marketers. Past research has focused on disconfirmation effects either in the context of "product" schemas (e.g., Meyers-Levy and Tybout 1989; Stayman, Alden, and Smith 1992) or customer satisfaction (e.g., Woodruff, Cadotte and Jenkins 1983), with little focus on understanding how disconfirmatory information impacts "brand" name perceptions and preference (Loken and John 1993). Further, little research has attempted to understand the relative impact of negative and positive disconfirmations, even though the dominance of negative information is a robust finding in the literature (e.g., Herr, Kardes and Kim 1991; Mizerski 1982). The three papers in the session identified factors that are likely to enhance or diminish the impact of the disconfirmatory information on process, perceptions and preference outcomes.

Rohini Ahluwalia first presented the results of her research with Bob Burnkrant and Rao Unnava. This study examined the processing differences between high and low commitment consumers when they are exposed to negative (disconfirmatory) as opposed to positive (confirmatory) information about a favorable brand. It was found that low commitment consumers give more weight to the negative disconfirmatory information. In contrast, high commitment consumers resisted negative information not only by discounting it and therefore, weighting it less in their evaluation, but by also distorting its meaning. These consumers misperceived the disconfirmatory information in a biased manner - they perceived it as "less negative" than the low commitment consumers.

Zeynep Gnrhan presented the results of her work with Durairaj Maheswaran. In this research, subjects under high and low motivation were provided disconfirmatory information about a favorableand an unfavorable brand in the context of low typicality (i.e., when disconfirmatory information is condensed in a single product) or high typicality (i.e., when disconfirmatory information is dispersed across several products). Under high motivation, consistent with the bookkeeping model of schema change, consumers revised their evaluations regardless of the level of typicality. Under low motivation, consistent with the subtyping model, evaluations changed more in the context of low typicality.

And finally, Meg Meloy presented her work coauthored with Jay Russo. This study examined the role of positive affect in predecisional distortion. The results confirmed that people who are happy distort nondiagnostic information more than their neutral affect counterparts do and have a greater capacity to discount negative information about their preferred alternative (i.e., they are less likely to switch preferences.) However, when the disconfirmation involves positive information about the trailing alternative, positive affect participants are as likely to reverse preferences as those in the neutral affect condition.

Frank Kardes, as the discussion leader, integrated the findings of the three papers within the context of Brewer’s (1988) and Fiske and Pavelchak’s (1986) dual process models. He suggested that the findings of the session were more consistent with Brewer’s (1988) model since the papers distinguished between schema-based and attribute-based processing depending on the level of commitment, motivation, and affect. Unlike Fiske and Pavelchak’s (1986) model, Brewer’s model identifies the conditions under which schema-based processing takes place in response to disconfirming information. He also suggested that the bias consumers display under high commitment or positive affect can be explained within the framework selective hypothesis testing (Sanbonmatsu et al. 1997).


Brewer, M. B. (1988), "A Dual Process Model of Impression Formation," in Advances in Social Cognition, Vol. 1, eds. T. K. Srull and R. S. Wyer, Jr. Hillsdale, NJ: Lawrence Erlbaum Associates, 1-36.

Fiske, S. T. and M. A. Pavelchak (1986), "Category-Based versus Piecemeal-Based Affective Responses: Developments in Schema Triggered Affect, in Handbook of Motivation and Cognition: Foundations of Social Behavior, eds. R. M. Sorrentino and E. T. Higgins, New York: Guilford, 167-203.

Herr, Paul M., Kardes, Frank R., & Kim, John (1991), "Effects of Word-of-Mouth and Product-Attribute Information on Persuasion: An Accessibility-Diagnosticity Perspective, Journal of Consumer Research, 17, 454-462.

Loken, Barbara and Deborah Roedder John (1993), "Diluting Brand Beliefs: When Do Brand Extensions Have a Negative Impact?" Journal of Marketing, 57 (July), 71-84.

Meyers-Levy, Joan and Alice M. Tybout (1989), "Schema Congruity as a Basis for Product Evaluation," Journal of Consumer Research, 16 (June), 39-54.

Mizerski, Richard W. (1982), "An Attribution Explanation of the Disproportionate Influence of Unfavorable Information", Journal of Consumer Research, 9, 301-310.

Sanbonmatsu, David M, Steven S. Posavac, Frank Kardes, and Susan Mantel (in press),"Selective Hypothesis Testing," Psychonomic Bulletin and Review.

Stayman, Douglas M., Dana L. Alden, and Karen H. Smith (1992), "Some Effects of Schematic Processing on Consumer Expectation and Disconfirmation Judgments," Journal of Consumer Research, 19 (September), 240-255.

Woodruff, Robert B., Cadotte, Ernest R., and Jenkins, Roger L. (1983), "Modeling Cnsumer Satisfaction Processes Using Experience Based Norms," Journal of Marketing Research, (August), 296-304.