Memory-Based Judgments: the Roles of Information Typicality and Processing Ability

ABSTRACT - Using the accessibility-diagnosticity framework and the Elaboration Likelihood Model, effects of information typicality on memory-based judgment at different levels of encoding ability were examined. The results showed that atypical information has a recall advantage over typical information in high ability conditions. However, the impact of this atypical information on product evaluations and judgment processes may depend on its attractiveness. The recall-judgment relationship also varied with the level of encoding ability, suggesting that consumers may adjust their processing strategy when encoding ability changes. Future research directions are briefly discussed.


Nai-Hwa Lien and Douglas M. Stayman (1998) ,"Memory-Based Judgments: the Roles of Information Typicality and Processing Ability", in AP - Asia Pacific Advances in Consumer Research Volume 3, eds. Kineta Hung and Kent B. Monroe, Provo, UT : Association for Consumer Research, Pages: 94-99.

Asia Pacific Advances in Consumer Research Volume 3, 1998      Pages 94-99


Nai-Hwa Lien, Cornell University, U.S.A.

Douglas M. Stayman, Cornell University, U.S.A.


Using the accessibility-diagnosticity framework and the Elaboration Likelihood Model, effects of information typicality on memory-based judgment at different levels of encoding ability were examined. The results showed that atypical information has a recall advantage over typical information in high ability conditions. However, the impact of this atypical information on product evaluations and judgment processes may depend on its attractiveness. The recall-judgment relationship also varied with the level of encoding ability, suggesting that consumers may adjust their processing strategy when encoding ability changes. Future research directions are briefly discussed.


Consumers re exposed to large amounts of product-related information every day. Some of the product information contains typical attributes, or attribute information consistent with consumer expectations about the product category (e.g., a sports car that is fast and maneuverable). Some product information is atypical, or expectation-inconsistent (e.g., a sports car with four doors). Conceptually, the degree of consistency between product information and category expectations can influence the manner in which product information is processed and evaluated (Alba and Hutchinson 1987; Cohen and Basu 1987; Loken and Ward 1990). It is not surprising, therefore, that several empirical studies have explored the effects of information typicality on a number of consumer judgment processes (e.g., Meyers-Levy and Tybout 1989; Ozanne, Brucks, and Grewal 1992; Stayman, Alden, and Smith 1992; Sujan 1985).

Empirical studies have examined the effects of information typicality by asking subjects to make an "on-line" judgment. In other words, subjects in these studies were asked to make an evaluative judgment of the product (s) while, or immediately after, examining attribute information. In everyday life, however, many product judgments consumers make are "memory-based". Memory-based judgments occur when consumers acquire product information with no specific objective in mind. Later, when they are asked to make a judgment with none of the information being physically present, they have to rely on information that is stored in memory. Choosing a restaurant before one leaves one’s home is a good example of a memory-based judgment. Given differences between on-line and memory-based judgments, research on information processing in on-line judgments may not have direct implications for memory-based judgments. There has been extensive research on information utilization in memory-based judgments (e.g., Kardes 1986; Lynch, Marmorstein, and Weigold 1988; Park and Hastak 1994). However, relatively few studies have examined the effects of typicality on information use when the judgments are memory-based (for an exception see Schul and Burnstein 1990).

Taken together, research on information processing and typicality has dealt almost exclusively with on-line judgments, while research on information processing in memory-based judgments barely discussed the possible effects of information typicality. The purpose of the present study is to take an initial step to fill this gap. Specifically, this study aims to examine how the typicality of product information influences its utilization in making memory-based judgments.


Memory-Based Judgments

The distinction between on-line versus memory-based judgments has been made to assess the memory-judgment relationship (Hastie and Park 1986; Lichtenstein and Srull 1985, 1987). On-line judgments occur whenever a person acquires brand-related information with the objective of making an evaluation of that brand. When this occurs, a global evaluation of the brand will be made at the time of information encoding and stored in memory. If later asked to make an evaluation, the person can retrieve the stored evaluation from memory and report it.

Memory-based judgments, on the other hand, occur when there is a delay between the time of encoding and the time of judgment. In the simplest situation of memory-based judgment, no global evaluation of the brand is made at the time of infomation acquisition, and no new or partial information is available at the time of judgment. The only information source is the individual product features stored in memory. Judgment outcomes will depend upon the evaluative implications of the particular subset of features retrieved from memory. Such a "pure" memory-based judgment is the focus of the current study.

Feldman and Lynch’s (1988) accessibility-diagnosticity model further suggests that the likelihood with which a particular piece of stored information is used as an input to memory-based judgments depends on the accessibility and diagnosticity of the information. Accessibility refers to the ease with which the information can be retrieved from memory; diagnosticity refers to the degree that consumers believe the information is relevant to accomplish their decision goals. Accessibility is a necessary condition for the utilization of information: only information that can be retrieved from memory has a chance to be used for making judgments. However, accessible information is unlikely to be used as an input to judgment if it is perceived as nondiagnostic or irrelevant with respect to the judgment goal. Information diagnosticity is assessed when it is retrieved from memory. If a single piece of information is perceived sufficient for achieving the judgmental goal, memory search ceases and a judgment is formed solely on the basis of this information (Wyer and Srull 1989). If currently accessible information is not sufficient, memory search continues until enough information for achieving the goal has been accumulated.

Since typical information may differ from atypical information in terms of both accessibility and diagnosticity we address both of these effects below.

Accessibility of Typical vs. Atypical Information

Early studies in social cognition suggested a memory advantage for typical information over atypical information (e.g., Cantor and Mischel 1977; Cohen 1981). These studies claimed that perceivers are more likely to remember information consistent with their expectations (i.e., typical information) than to remember expectation-inconsistent (i.e., atypical) information because 1) typical information may receive more attention than atypical information (Cohen 1981), and 2) typical information may be more easily assimilated and encoded into the cognitive representation (Cantor and Mischel 1977).

Over the past decade, however, most research has shown preferential memory for atypical information, or information that is incongruent with expectation (e.g., Bargh and Thein 1985; Belmore and Hubbard 1987; Srull, Lichtenstein, and Rothbart 1985). According to the model proposed by Wyer and Srull (1989), this recall advantage of atypical information may be a consequence of the "inconsistency-resolution" process undertaken by the perceivers. That is, individuals may attempt to reconcile inconsistent information to the prevailing expectation about the target person or target group by thinking about the atypical information in relation to other relevant information, and thus enhance the cognitive associations between atypical information and the target person or group. These cognitive associations then lead to better recall of atypical information.

The meta-analyses conducted by Stangor and McMillan (1992) and Rojahn and Pettigrew (1992) indicate that atypical information is in general recalled better than typical information, but this recall advantage is moderated by several factors including "processing load". Some studies have found that, when processing load increased because of multiple tasks or external distraction, the recall advantage for atypical information decreased (Macrae, Hewstone, and Griffiths 1993; Stangor and Duan 1991).

The rationale for the moderating effect of processing load can be provided by the Elaboration Likelihood Model (ELM; Petty and Cacioppo 1986). According to ELM, the amount and nature of issue-relevant elaboration are determined by the extent to which people are motivated and able to process a message. When onditions foster people’s motivation and ability to engage in issue-relevant processing, the "elaboration likelihood" is said to be high, and people will thus engage in more comprehension, learning, evaluation, and integration of the information. In contrast, when the elaboration likelihood is low, attitudes and judgments are more likely to be results of relatively simple, less effortful procedures.

As mentioned earlier, the superior recall of atypical information is a consequence of the inconsistency-resolution process, an activity requiring significant cognitive resources and effort. The ELM suggests that people are more likely to engage in this effortful process when they are willing and/or able to do so. If the motivation or ability to process is low, cognitive resources are more likely to be devoted to a relatively easy task, that is, the encoding of typical (or expectation-consistent) information. Therefore, when the motivation and ability to process is high, atypical information will be elaborated to a greater extent and thus be recalled better; but typical information will be recalled better when the elaboration likelihood is low.

Previous arguments and findings can be extended to research on consumer information processing. With low processing load (e.g., no time pressure, only one brand to evaluate, etc.), consumers will have the motivation and ability to elaborate information (Petty, Cacioppo, and Schumann 1983), which suggests they are more likely to pay attention to atypical information and try to resolve the inconsistency. On the other hand, consumers will lack the motivation and ability to elaborate atypical information when the task becomes more demanding (e.g., time pressure, several brands to be evaluated, multiple on-going activities, etc.). In this case, typical information, which is easier to process, will be likely to receive more attention and elaboration. Hence:

H1a:  When elaboration likelihood at encoding is high, atypical information is more accessible than typical information.

H1b:  When elaboration likelihood at encoding is low, typical information is more accessible than atypical information.

Before discussing effects of typicality on diagnosticity it is important to note that positive and negative information can have asymmetric effects on judgment processes, known as the negativity effect (Mizerski 1982). The current study concentrates on positive and neutral information only.

Diagnosticity of Typical vs. Atypical Information and Impact on Judgment

In general, typical attribute information should be perceived as relatively more diagnostic than atypical information to an evaluative judgment of a product for three reasons. First, typical information represents salient beliefs and ideals about the product category (Loken and Ward 1990), so it is relevant to product evaluation by helping consumers assign the brand to one (and only one) cognitive category. Second, typical information supports consumers’ expectation of the product category, and thus increases the perceived validity of the information and consumers’ confidence in using the information as an input. Third, atypical or expectation-inconsistent information is often discounted or attributed to situational factors (Crocker, Hannah, and Weber 1983; Hoch and Deighton 1989), so it will not be viewed as having as important implications for product evaluation as expectation-consistent information. [While a single piece of atypical information may not be diagnostic, we note that when taken together with other information that is recalled, atypical information could be diagnostic in terms of judging the product's "prototypicality," or the level of congruity between the product and its category label. The consequence of the prototypicality or congruity judgment could then affect product evaluations (Sujan 1985; Meyers-Levy and Tybout 1989).]

When elaboration likelihood is low, consumers are expected to remember more typical information (Hypothesis 1b). Since typical information is more relevant to product evaluations, the cumulated diagnosticity of recalled typical features should be able to reach he threshold for a confident product evaluation before consumers begin to search or immediately after searching for the less accessible atypical features. Recalled typical features should thus be the primary basis for the product judgment, and the valence of typical features should determine the valence of the product judgment.

What would happen when the elaboration likelihood at the time of encoding is high? H1a predicts that atypical information has a recall advantage, so they will be retrieved and their diagnosticity will be assessed. However, atypical information is likely to be as less diagnostic (due to low perceived validity or low accountability), so the accumulated diagnosticity of atypical information only may not be sufficient for an evaluative judgment. Consumers may continue searching for other stored information, i.e., typical features. Product judgments should therefore be determined by both typical and atypical information. Since some of the recalled features (especially atypical ones) should not be used as an input for judgment, the correlation between recall and judgment should be lower than when elaboration likelihood is low. Hence:

H2a:  The attractiveness of typical information has a greater effect on product evaluations when the elaboration likelihood at encoding is low than high.

H2b:  The attractiveness of atypical information has a greater effect on product evaluations when elaboration likelihood at encoding is high than low.

H2c:  Recall-judgment correlations are lower when elaboration likelihood at encoding is high than low.

Consumers are expected to rely on both typical and atypical information when elaboration likelihood at the time of encoding is high. Since more product features have to be retrieved and processed, it is likely to take more time to achieve a judgment. Furthermore, the difficulty to retrieve relatively less accessible typical features (H1a) should also lengthen the search process. Thus,

H3a:  Consumers reach product evaluations more slowly when elaboration likelihood at encoding is high than when it’s low.



Typical information is expected to be less accessible under high elaboration conditions (H1a). Consumers should experience difficulty in retrieving typical information, and this difficulty may result in lower confidence in the accuracy of the recalled features ("Did I remember it right?"). Meanwhile, atypical information becomes more accessible, but consumers may be uncertain of their validity or accountability (i.e., consumers perceive atypical attributes as less diagnostic). The uncertainty in both recalled typical and atypical information under high-elaboration condition is likely to reduce consumers’ confidence in their product judgments. Thus,

H3b:  Consumers are less confident with their product evaluations when the elaboration likelihood at the time of encoding is high than when it’s low.



A 2 x 2 x 2 between-subject factorial design was utilized (see Figure 1). The first facto was the ability to process at encoding, one of the determinants of elaboration likelihood.2 The other two factors corresponded to the valence of individual attributes, the attractiveness of typical product features (positive vs. neutral) and the attractiveness of atypical features (positive vs. neutral).

Stimulus and Independent Variables

All subjects performed a computerized judgment task. They first read 10 non-negative, typical and atypical feature statements about a compact car, and later formed an evaluation of the product. Those feature statements consisted of 3 typical, 3 atypical, and 4 filler items, presented in a mixed order. Sample statements and the average typicality and attractiveness of each type of statement are shown in Table 1.

Ability to process at encoding was manipulated by giving half of the subjects (low ability groups) an additional task: to rehearse an 8-digit number while reading the product feature statements. Previous research has demonstrated that this kind of task has a debilitating effect on people’s processing ability (e.g., Macrae, Hewstone, and Griffiths 1993).

Note that in this study, "typicality" was operationalized as the extent to which a piece of product information was consistent with the expectations of the product category. Therefore, a typical feature was not just a value/specification (e.g., high or low) or a dimension/attribute (e.g., price), but a combination of both. "Attractiveness" of a feature was operationalized by asking pretest subjects to indicate "the desirability of the product if it possesses this feature." Thus, attractiveness captured both "valence" and "attribute importance." Pretests showed that typicality and attractiveness were not correlated; Importance was correlated with attractiveness but not with typicality.

Subjects and Procedure

A total of 164 undergraduates participated in this study to receive either extra course credit or a cash payment of seven dollars. They were randomly assigned to one of the eight experimental groups, 18 to 22 per group. Each subject performed the study on a Macintosh computer. The cover story suggested that the focus of the first section of the study was how the wording of product information influenced consumers’ comprehension of the information. Subjects were told that they would be reading product feature statements exerted from Consumer Reports and be giving ratings of the "readability" and "visualizability" of each statement.

The procedure was controlled in several aspects to discourage subjects from forming an on-line overall evaluation of the product (Park and Hastak 1994). First, subjects were told that the feature statements described several brands of small-size sedans. Second, subjects were asked to rate each statement in terms of how easily they can understand it and visualize it. Finally, subjects were given only a limited amount of time (9 seconds) to perform the two ratings of each statement.

Following a short practice session, subjects began to read the feature statements of small-size sedans. Those in the low-ability conditions were given the 8-digit number before they were exposed to the feature statements.

After reading and rating the statements subjects were given a 10-minute filler task. Then subjects were informed that the feature statements they had received earlier were actually about a single brand of small-size sedan. They were asked to evaluate the product based on those information and also to indicate their confidence. This was followed by recall task, demographic questions, and knowledge questions. They were then debriefed and dismissed.



Dependent Measures

Product Evaluations. Three product evaluation questions were asked: "What do you think the performance of this small-size sean would be?" (good/bad), "How do you like this brand of small-size sedan?" (like/dislike), "How would you describe your thoughts about this car?" (favorable/unfavorable). Each question, accompanied by a 7-point scale, was located on its own screen.

These three items yielded a low Cornbach’s alpha (.73). Thus, instead of averaging the three items, we decided to use only the first item for the analyses. The first item asked for a "discrete" judgment (performance), which, according to Kardes (1986), is more likely to rely on individual pieces of attribute information (we note that the results for the other two items were not similar).

Confidence. Right after each product evaluation question subjects indicated their confidence in the evaluation on a 7-point scale, ranging from "Not at all sure" to "Absolutely Sure".

Response Time. The time subjects spent on making product evaluations was recorded in 1/60th second increments, starting at the point at which the question was displayed on the screen and ending at the moment when the participant clicked the browser button to move to the next question.

Recall. Subjects wrote all the feature statements they could remember seeing earlier in the session. Two independent judges coded the recall items into groups of typical, atypical, or filler items. The inter-judge reliability was 88.5%. Disagreements were resolved through discussion.

Judgment-Recall Correlation. Recalled items were weighted by their attractiveness as given by each subject. The summed attractiveness of recalled items was then correlated with the subject’s product evaluation (Chattopadhyay and Alba 1988).

Knowledge. Prior knowledge about automobiles was assessed by 15 multiple choice questions. Based on the distribution of knowledge scores, subjects were divided into high-, medium-, and low-knowledgeable groups. Knowledge level was treated as a blocking factor in data analyses so its main effect and interactions with the independent variables could be investigated.


The effects of encoding ability on recall were assessed via t-tests and ANOVA. High ability groups correctly remembered more atypical items (M=1.76) than typical items (M=1.49; t77=2.11, p=.04), supporting H1a. This recall advantage of atypical items disappeared under low ability conditions (M=1.43 for atypical items, M=1.36 for typical items; t82=.62, p=.53), but was not reversed as H1b predicted. High ability groups, compared to low ability groups, tended to recall more atypical items (F1, 137=5.6, p=.02), but the recall for typical items was not significantly different between the two ability levels (F1, 137=1.51, p=.22). In addition, ANOVA showed that recall of atypical items was also influenced by attractiveness (F1,137=25.82, p=.0001), but recall of typical items did not seem to be influenced by any of the independent variables (no significant main effect or interaction). Cell means of recall and other major dependent measures are reported in Table 2.

Hypotheses on judgment processes were partially supported. Consistent with H3a, high ability groups spent more time to reach a product evaluation (M=12.1 seconds) than low ability groups (M=10.2 seconds; F1,140=4.7, p=.03). However, there were no significant differences in terms of confidence between high and low ability groups (M=3.96 for high ability groups and 3.82 for low ability groups, F1,140=.25, p=.62), failing to support H3b.

A 4-way ANOVA (the 3 dependent variables and knowledge as a blocking factor) was conducted on product evaluation data. H2a predicted an interaction between encoding ability and attractiveness of typical items (T), but no such effects were found (F1,140=1.25, p=.26). H2b predicted an interaction between encoding ability and attractiveness f atypical items (A). The interaction was marginally significant (F1,140=2.69, p=.10), but planned contrasts indicated that effects of atypical items were greater when encoding ability was low than when high. Results from separate analyses at each ability level showed a main effect of A in low ability groups (F1,73=2.85, p=.09), while in high ability groups a main effect of T (F1,67=4.23, p=.04) and a T x A interaction (F1,67=2.77, p=.10) were found. Follow-up examination of the T x A interaction revealed that in the presence of atypical positive items, typical neutral features led to lower product evaluation than typical positive features (4.57 vs. 5.4, p=.01). These results suggested that, although not in the direction we predicted, the effects of atypical items on product evaluations did vary with encoding ability, and were interdependent with the effects of the attractiveness of typical items when encoding ability was high. For completeness, we note that other significant effects in the 4-way ANOVA were T, T x knowledge, and T x ability x knowledge.



Tests of H2c concerned the relationship between recall and product evaluations. Contrary to our predictions, the recall-judgment correlation was greater in high ability conditions (r=.317, p=.004) than in low ability conditions (r=.119, p=.27). Subjects in high ability conditions appeared to base their judgments on memory of the feature statements, while those in low ability conditions did not. Separate correlations were also computed for typical and atypical items. For high ability subjects, the recall-judgment correlation was significant for typical items (r=.22, p=.05), and marginally significant for atypical items (r=.19, p=.09). Low ability subjects also showed a marginally significant correlation for atypical items (r=.16, p=.15), but no significant correlation for typical items (r=.03, p=.81). Both typical and atypical correlations appeared to be lower among low than high ability groups.


Memory for product information can be influenced by processing ability at the time of encoding, and the magnitude of the effect of encoding ability may depend on the typicality of the information. In this study, atypical items were recalled better when encoding ability was high. This recall advantage did not exist when there was distraction at the time of encoding. This is consistent with past research by Stangor and Duan (1991, experiment 1).

This study also found memory-judgment relationship varied with encoding ability. Low ability subjects showed low recall-evaluation correlations, especially for typical items. Although their memory for typical items was not inferior to that of high ability subjects, apparently typical items did not have much impact on their product evaluations. Instead, subjects resorted to the recall of atypical items to help them make product judgments. One potential explanation is that low ability subjects lack confidence in their recall of typical items (Lynch, Marmorstein, and Weigold 1988), so instead of relying on typical items, they may use atypical items in a heuristic manner to make product evaluations. Another explanation for the heuristic use of atypical items is that subjects’ encoding ability might be too low. However, given that low ability subjects recalled almost the same amount of typical information as high ability subjects, it is difficult to claim that distraction at encoding caused such an "extremely low" encoding ability. A second study which tries to replicate the results and directly measures recall confidence is currently underway.

High recall-evaluation correlations for typical and atypical items were found among high ability subjects, suggesting that both types of items were used in their evaluation process. The effect of typical items was most salient among those who received atypical-positive (A/P)information (groups7 & 8). Since this effect was not observed in the low ability-A/P conditions (groups 3 & 4) or high ability-atypical neutral conditions (groups 5 & 6), it may be possible that A/P items could facilitate the processing of typical information only when encoding ability is high. This proposition is consistent with the line of research suggesting that the presence of unusual, positive items may induce elaboration (e.g., Kahn and Isen 1993). Future research on the effects of the attractiveness of atypical items on judgment process is warranted.

In sum, our findings suggested the recall advantage of atypical over typical information decreases if there has been distraction at the time of encoding. When the ability to process at encoding is high, memory for both typical and atypical items is an important input to product evaluations. When the ability is low, however, product evaluations may be more likely to be based on heuristics.


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Nai-Hwa Lien, Cornell University, U.S.A.
Douglas M. Stayman, Cornell University, U.S.A.


AP - Asia Pacific Advances in Consumer Research Volume 3 | 1998

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