Exploring Memory Processes in Consumer Choice

Gabriel Biehal, University of Houston
Dipankar Chakravarti, University of Florida
ABSTRACT - An experiment examined the effects of task environment structure (different information presentation formats) and learning goal differences (directed versus non-directed learning of product information) on consumers ' retrieval of product information from memory and on choice processing. Analysis of choice and retrieval verbal protocols showed significant processing differences in both memory-retrieval and choice stemming from the manipulations. Implications of the results are discussed, together with directions for further research into memory processes in consumer choice.
[ to cite ]:
Gabriel Biehal and Dipankar Chakravarti (1982) ,"Exploring Memory Processes in Consumer Choice", in NA - Advances in Consumer Research Volume 09, eds. Andrew Mitchell, Ann Abor, MI : Association for Consumer Research, Pages: 65-71.

Advances in Consumer Research Volume 9, 1982      Pages 65-71


Gabriel Biehal, University of Houston

Dipankar Chakravarti, University of Florida


An experiment examined the effects of task environment structure (different information presentation formats) and learning goal differences (directed versus non-directed learning of product information) on consumers ' retrieval of product information from memory and on choice processing. Analysis of choice and retrieval verbal protocols showed significant processing differences in both memory-retrieval and choice stemming from the manipulations. Implications of the results are discussed, together with directions for further research into memory processes in consumer choice.


Memory research in psychology shows that the type of processing that occurs during learning or acquisition of information affects its organization in memory and subsequent retrieval (Tulving 1979; Tulving and Thompson 1971, 1973; Craik and Lockhart 1972). Two types of learning situations are fairly common in consumer information processing (CIP) tasks. First, learning product information may be the primary goal of processing. Consumers may perform this type of "directed learning" either with the intent to make subsequent verbal reports (say to friends or family members), or in anticipation of making future choices. Other CIP situations may involve non-directed learning of product information. For example, product information may be acquired and stored in memory while choosing products in a store or while watching T.V. (Bettman 1979).

Differences in task structure also affect processing at acquisition (Newell and Simon 1972). CIP task environments may differ in the way product information is organized. For example, commercials and product packages present product information by brand, whereas some comparative advertisements provide information by product attribute, and in some instances (e.g., Consumer Reports) information is provided in a matrix of brand-attribute values.

Since learning goals and information presentation formats affect information processing during acquisition, they are likely to affect the organization of product information in memory and subsequent retrieval and choice based on it. This paper examines how learning goals and task structure affect (l) retrieval of product information from memory and (2) choice processes. Learning goals were manipulated by having some subjects learn product information in anticipation of a recall task (directed learning), while others acquired product information incidental to performing a choice task. Task structure was manipulated by presenting product information organized either by attribute, by brand or in a brand-attribute matrix



Consumers may acquire product information either incidental to making a choice or while learning in anticipation of subsequent retrieval from memory. The encoding operations performed during either situation will generate various associations. The nature of these associations will depend on the pattern of prior associations, the learning goals at the time of encoding and the information structure in which the task is pursued. Some of these associations will be stored in long term memory (LTM). Subsequent attempts either to retrieve information or to make a choice based on memory should therefore be a function of the initial learning goal, the structure of the task environment and the nature and extent to which these two factors influence memory content and organization.

Consumer Memory-retrieval Processing

Organization of Product Information. The organization of product information in LTM is not well understood, though it is probably organized by brand. Results showing higher retrieval accuracy (Haber 1964) and faster learning times (Lappin 1967) for object-coded versus dimension-coded information are consistent with this notion. Also, Johnson and Russo (1978a, 1980) argue that, since most consumer experiences with products occur in brand structured environments (e.g., product displays on supermarket shelves and the viewing of brand based advertising), a predominance of brand organized product information may be expected.

H1: Product information in LTM is organized by brand.

Information Format and Memory-retrieval. Information retrieval from LTM should reflect memory organization. If brand organized environments facilitate brand based encoding, retrieval of such information should also be brand based (Tulving 1962). When information is organized in a brand-by-attribute matrix some attribute based associations are likely to be encoded in memory despite the consumer's tendency to encode by brand. In attribute organized environments encoding of attribute based associations is even more likely. Therefore retrieval of information from memory should be predominantly brand-based, most when external information is brand organized, somewhat less when matrix organized and least when organized by attribute.

In contrast with situations where learning is the primary goal, learning may be incidental to other behaviors, e.g., brand choice. Task structure has been shown to influence choice strategy (Newell and Simon 1972; Bettman and Kakkar 1977). Thus environments structured by brand (attribute) should facilitate processing by brand (attribute). Matrix organizations do not explicitly favor processing by brand or by attribute.

Since information format affects how it is processed, format should also affect the organization of product information in memory. Therefore, retrieval processing should reflect memory organization, i.e., attribute processing should be lowest when the external environment at encoding is brand structured, somewhat higher when matrix structured, and highest when organized by attribute.

H2: Under both directed and non-directed learning attribute processing in memory-retrieval will be lowest when the external information is brand organized, highest when it is attribute organized, and at intermediate levels when it is matrix organized.

Learning Goals and Memory-retrieval. When learning is non-directed (e.g., during product choice), choice heuristics may determine how information is processed and thus influence the nature of the associative links stored in memory. Consequently both the choice heuristics used and the existing memory organization will influence the associations made when new information is processed. Since attribute processing should be higher during choice compared with directed learning, retrieval of information stored during choice should show higher levels of attribute processing relative to retrieval of information learned under explicit recall directions

H3: Retrieval of information acquired during choice will exhibit higher levels of attribute processing than information acquired in a directed learning context.

Consumer Information Processing in Choice

Several studies suggest that for choices using external information consumers tend to process by attribute (Russ 1971; Russo and Rosen 1975; Russo and Dosher 1976; Tversky 1969, 1972; Bettman and Jacoby 1976; Bettman and Kakkar 1977). However, the use of attribute based strategies may be moderated by the organization of product information, and whether the information is externally available or drawn from memory.

Thus consumers may make choices using information acquired and stored in LTM in earlier contexts quite different from the present one. It was proposed earlier that the organization of information in LTM is likely to be affected by the structure of the environment at encoding. These organizational effects of the task environment should influence subsequent choice processing based on memory. Hence when choices use memory information,attribute processing should be highest when that information is initially encoded in an attribute structured environment somewhat lower in matrix structured environments and lowest in brand structured environments.

However, the previous discussion suggests that because of a predisposition toward brand organized memory, some brand based reorganization of this information may occur in LTM. Hence, choice processing using memory should show less attribute processing than when external information is used.

H4: Choices based on external information will show most attribute based processing when the information is attribute organized, least when it is brand organized and at intermediate levels for matrix organizations.

H5: Choice based on information in LTM will show most attribute based processing when initial encoding occurs in an attribute organized environment, least when the environment is brand organized and at intermediate levels for matrix organizations.

H6: Choices based on information in LTM will show lower levels of attribute processing than choices based on externally available information.



Subjects performed one of three tasks. Some learned information in anticipation of a recall task and were subsequently given the recall task. Others had the same directed learning task but were then given an unexpected choice task based on information stored in memory. Finally, subjects in the non-directed learning condition made a choice using externally available information and were then unexpectedly asked to recall the information acquired during choice. Product information was presented either by attribute, by brand or in a brand-attribute matrix. Tape-recorded verbal protocols of recall and choice processing were coded to yield an index of percentage attribute based processing operations. The index was analyzed as a function of the three information presentation formats and either (a) recall under directed versus non-directed learning, or (b) choice based on memory versus externally available information.


Subjects were recruited from the University of Florida, Gainesville, campus community by offering a $3 fee for participation in a study "involving human memory." Of the 108 subjects, 80% were undergraduates; the remainder were secretaries or graduate students. By age, 88% were in the 18-25 group; 68% were female.


Product information consisted of four fictitious toothpaste brands named Mast, Foam,Banner and Lark, described on four dimensions: price per 10 ounce tube, flavor, fluorite and mouthwash content (Figure 1). Concern for mundane realism guided the choice of toothpastes as the product category. Fictitious brands were used to eliminate problems arising from prior knowledge. The brand names, selected to be high and similar on concreteness, imagery and meaningfulness, were drawn from a list of nouns measured on these dimensions by Paivio, Yuille and Madigan (1968). Selection of attributes was guided by an exploratory study conducted with a convenience sample of undergraduates. The four attributes consistently rated as most important were chosen.



Experimental Design and Procedures

The study was a 3x3 factorial design with 12 subjects per cell. Three task conditions were crossed with three information formats (brand, attribute and matrix organizations). Each subject was tested individually.

After being randomly assigned to one of the experimental cells, subjects went through seven stages. First, all subjects indicated attribute importances by allocating 100 points among the four toothpaste attributes. Four irrelevant products were included to avoid cueing the subjects on toothpaste as the product category of interest. The second stage was a "warm-up" for the verbal protocol procedure. Subjects described aloud how they chose their present apartments, until the experimenter was satisfied that they were not inhibited by being tape-recorded.

Learning Goal Manipulation. In the third stage Task Groups 1 and 2 were given the product information and asked to learn it "to be able to answer questions about the information later". This constituted the directed learning manipulation. Subjects were told that there was no time pressure for learning, but learning time was surreptitiously recorded. Subjects in Task Group 3 (non-directed learning) were asked instead to choose the most appealing brand based on the information provided. Subjects talked out loud as they made the choice. These protocols were tape-recorded and timed by replaying the tapes later.

Information Format Manipulation. Information presentation during directed learning was controlled. Subjects in the attribute format condition were first given a sheet of information for all four brands on the mouthwash dimension, i.e., the first row of Figure 1. Subjects could take as much time as they wished to learn the information, but once they moved to the next attribute information sheet the previous sheet was no longer available. Information for the four brands on the price, flavor and fluoride content dimension was provided sequentially. Subjects in the brand format condition were given sheets containing information for one brand at a time on all four dimensions, i.e., the columns of Figure 1. The brands were presented in a fixed order (Mast, Foam, Banner and Mark) for all subjects. Subjects il the matrix condition were given all 16 pieces of information organized as in Figure 1.

In Task Group 3 (non-directed learning) the format manipulation was administered through information sheets identical to those used in the directed learning condition. Subjects had access to all the information sheets while they made the choice.

In the fourth stage each group performed a different task. Task Group 1 was given the free recall instruction "tell ml (the experimenter) in your own way all the information you (the subject) just learned". This protocol was tape recorded and timed. In Task Group 2, subjects were unexpectedly asked to "choose the brand that appeals most to you (the subject) based on the information that you just learned". Subjects talked aloud while making their choice. These protocols were tape recorded and timed. Finally, in Task Group 3, subjects were given an unexpected free recall instruction, "tell me (the experimenter) all the information you (the subject) just examined for making your choice". This protocol was also tape recorded and timed.

In the fifth stage of the study, subjects were given a knowledge test using a questionnaire with 16 brand-attribute value questions, such as "What was Mast brand's price?". The questions were in a fixed order but subjects could answer them in any order they wished. A four minute time limit encouraged subjects to move on if they were having trouble answering a particular question. The time taken and the responses for each subject were recorded. The number of correct answers out of 16 was determined later.

Next, subjects completed a task evaluation questionnaire that contained questions on (a) task perceptions (e.g., stimulus realism, task fatigue, care in task performance and clarity of instructions); (b) subjective appraisals of choice or recall performance; (c) manipulation effectiveness and (d) subject demographics. Finally, subjects were debriefed and paid. Typically debriefing took 10 minutes and the experimental task took about 35 minutes.


Protocol Coding

Four types of verbal protocols were collected. Two were free recall protocols, one following directed learning of product information (Task Group 1), the other following non-directed learning during choice (Task Group 3). The other two were for choice tasks, the first using information stored in memory during directed learning (Task Group 2), the second using external information (Task Group 3).

Protocols were transcribed from the tapes and coded by the authors using Bettman and Park's coding scheme (1979, 1980a). The protocols were first edited [Editing involved removing experimenter-subject interact ions in the body of the protocol and clarification statements at the beginning and end of the protocol.] and divided into short, task-related statements. Statements were then coded as either Attribute Comparison Processes (processing within an attribute or set of attributes across brands) or Within Brand Processes (processing within one brand over one or more attributes). [The Bettman-Park coding scheme contains code categories for Use of Prior Information, Statements of Plans and General. Because of the experimental task these categories were rarely used. and thus not used in the dependent measure.]

The coding scheme was pilot-tested on some pre-test protocols. After resolving some basic differences (Biehal and Chakravarti 1982a) the two authors independently coded all 144 protocols without knowledge of the subjects' cell assignments. The recall and choice protocols yielded 1,401 and 1,625 phrases, respectively. The two coders were in agreement on 90% of these 3,026 phrases. [Agreement on the recall protocols was 75-100% (M=95%). It was lower on the choice protocols (43-100%,M=86%) since these were usually longer and more complex. Problematic phrases were discussed until a code was agreed upon.]

Dependent Variables

Hypotheses were stated in terms of attribute based processing as a function of learning goal and presentation format. This dependent variables was operationalized by a "percentage attribute based operations" measure, derived as follows. For each protocol the number of adjusted [The adjustment process is described in Biehal and Chakravarti (1982 a). The procedure involved counting the number of implied retrievals of brand-attribute values in a phrase that was coded as a single Attribute Comparison statement in the Bettman and Park scheme. This helped remove the bias implicit in a simple frequency count of brand and attribute codes.] Attribute Comparison Process statements (Bettman and Park 1979, 1980a) were summed. The result was divided by the total number of Attribute Comparison Process statements and Within Brand Process Statements. The resulting proportion expressed as a percentage yielded the dependent measure.


Manipulation Checks

The learning goal manipulation was checked by assessing the degree to which subjects anticipated a requirement to perform tasks other than the stated task. Most subjects in Task Group 3 reported being surprised by the free recall task following choice. The directed learning manipulation may have been less successful. Task Group 2 subjects reported only moderate surprise when asked to choose a product from information in memory following directed learning, i.e., some of these subjects may have been evaluating the brands while learning. Though most subjects denied having done this, their choice protocols showed some evidence of choice processing prior to the receipt of explicit choice instructions. The debriefing questionnaire indicated that subjects found the study to be realistic and not fatiguing to perform. The stimuli were rated as realistic and easy to learn.

Consumer Memory-retrieval Processing

Brand Based Organization. Hypothesis H1 proposed that product information in memory is predominantly brand based. Consequently retrieval processing following a neutral probe should reflect internal organization and also be predominantly brand based. Table 1 shows the least squares [Since the design was balanced, the analyses without covariates yielded least squares estivates of cell means identical to raw cell means. With covariates the estimates were slightly different from the raw cell means, reflecting small differences between the means of the covariate(s) in the cells. The discrepancies were under one percentage point in all cases. The least square estimates of the cell means are reported throughout, for consistency.] estimates of the mean "percentage attribute based operations" (PABO) for each cell in the free recall protocols. Since by definition the percentage brand based operations equals (100-PABO), these values were 64%, 88% and 77% for the attribute, brand and matrix format conditions, respectively. In one-tailed t tests, these values were significantly greater than 50%. Thus, using the cutoff level of 50% as the basis for predominance, the data support the hypothesis.

Effects of Information Format. Hypothesis HZ stated that brand (attribute) organized external environments should facilitate brand (attribute) based encoding in both directed learning and in non-directed learning during a choice task. Matrix organizations do not explicitly favor either type of processing. This implies a main effect of presentation format in free recall where "percentage attribute based operations" are highest in the attribute format condition, intermediate in the matrix format condition, and lowest in the brand format condition. The ANOVA results in Table 1 showed a statistically significant format effect (p<.05). Further, the format manipulation cell means for both the directed and the non-directed learning conditions followed the predicted ordering. Since the format by learning goal interaction was not statistically significant, the overall means for the three levels of the format manipulation (across both directed and non-directed learning) were compared pairwise using the Tukey multiple comparisons test. Only the difference between the brand and the attribute format conditions was statistically significant (p=.05 for the family of tests).



Effects of Learning Goals. Hypothesis H3 predicted that "percentage attribute based operations" in free recall of information learned during choice should be higher than for information learned under recall directions. Table 1 shows that, as predicted, the percentage attributed based operations in retrieval of information learned during choice was significantly higher (p<.001) than in the directed learning condition.

Consumer Information Processing in Choice

Task Group 2 generated a verbal protocol while choosing a product based on information they had previously learned. Task Group 3 also generated a choice protocol when they selected a product using externally available information. The three-level information presentation format factor and the two-level choice task factor (memory versus external information) and their two-way interactions were used as independent variables in the analysis (Table 2). The variance of the importance weights assigned to the four toothpaste attributes was also included, together with its two- and three-way interactions with the manipulated factors. This was tone to control for the possible effect of individual differences on the dependent variable.



Effect of Information Format. Hypothesis H4 stated that for choice using external information attribute based operations should be highest when information is attribute structured, lowest when it is brand structured, and intermediate for matrix structured information. The cell means in Table 2 show this predicted order for the external information condition. However, the differences were not statistically significant. Only the difference between the brand and attribute conditions was significant at the .10 level.

Processing External versus Memory Information. Hypothesis H5 proposed that attribute processing during choice using memory information will be highest when the information is learned initially in an attribute structured environment, at intermediate levels when the environment is matrix structured and lowest when it is brand structured. The PABO cell means for choice based on information in memory partially violated this prediction. The matrix condition showed the highest level of attribute processing, followed by the attribute and brand conditions, respectively (Table 2). It is interesting to note that brand organized information seemed to lower the level of attribute processing in choice.

Hypothesis H6 stated that choice using memory information will show lower levels of attribute based operations relative to those using external information. A comparison of average cell means across all three format conditions for the two choice task conditions showed that for memory based choice, attribute processing was 16 percentage points lower than for externally based choice (Table 2). This significant (p<.05) difference indicates that the predominantly brand based organization of the memory store generated during directed learning may have attenuated attribute processing in choice.


Limitations of the Study

Interpretation and discussion of these findings must be tempered by the limitations of the study. First, the free recall instructions asked subjects to tell the experimenter the information they had learned. This instruction may have, biased the way subjects reported the retrieved information. If the social context of verbalizing led subjects to assume that brand-organized information was preferred, the format in which the information was reported may not have matched the format in which it was organized in memory. Russo and Johnson (1980) used a similar free recall instruction which, in addition, cued subjects by the product category. Potential biases generated by such "free" recall instructions need investigation.

A second limitation was the degree of experimental control over subjects' processing under directed learning conditions. While subjects learned product information in anticipation of a recall test, some protocols showed that they may have nevertheless engaged in some choice processing. Thus these protocols may have been in part retrospective descriptions rather than concurrent choice protocols. The existence of this problem is significant, since it shows that consumer information acquisition is not passive. Some degree of product evaluation may occur naturally, even when the consumer's primary concern at acquisition is not choice or evaluation. Osgood, Suci and Tannenbaum (1957) have suggested that evaluations are often a primary factor in the search for meaning in stimuli, and may therefore be an important part of the product information encoding process

Third, the results were based on analyses of aggregate counts of attribute based operations over time. Processing differences over various stages of the protocol were not examined. While this limitation is more relevant to choice as opposed to recall processing, the analyses may have masked subjects' phasing behavior.

Finally, the use of undergraduate students as subjects ma) have affected the external validity of the study. Although the task parameters (e.g., the product category and the attributes) were designed with the sample in mint, student may differ systematically from the average consumer in their use of memory-retrieval and choice strategies. In this study the need to minimize between subject variance due to learning and processing ability differentials in response to experimental manipulations dictated the use of a homogeneous subject population. Students were chosen due to cost considerations. However, the caveats noted by Bet man and Zins (1979) about using student samples to apply.

Summary and Implications of Findings

Both information presentation format and learning goal showed fairly consistent effects on retrieval and choice processes. Thus, directed learning of product information led to brand processing in free recall. This effect was moderated by information presentation format. However, even when the external information was attribute structured, and therefore did not facilitate brand based encoding, retrieval processing remained predominantly brand based. To the extent that free recall protocols permit inferences about memory structure, the findings suggest that consumer memory for product information may be primarily brand organized.

While retrieval of information acquired under directed learning conditions was primarily brand based, memory-retrieval of product information learned during choice showed more attribute based processing. This seems to reflect the higher levels of attribute based processing during choice, when information was acquired. Thus the nature of processing at encoding affected the organization of information in memory, and subsequent retrieval behavior reflected this organization. These results demonstrate isomorphism between encoding and retrieval processing and are in agreement with and provide process-based evidence for the "encoding specificity principle" (Tulving and Thompson 1971, 1973).

The structure of the external stimulus also affected processing. Attribute based processing in retrieval, whether initial learning was directed or non-directed, was hi t when the information was learned in an attribute structured environment. This follows logically from the fact that attribute based processing is facilitated most in attribute structured environments. However, even though processing adapted to some degree to the task environment, neither processing activity nor memory organization seem to have been bound by it to the extent suggested by other researchers e.g., Johnson and Russo 1978a, Bettman and Kakkar 1977). Learning goals may dictate that consumers transcend the constraints caused by external information formats. Thus, during choice from external information significant amounts of attribute processing occurred, even in brand structured environments. Also, after directed learning, memory-retrieval behavior remained primarily brand based, indicating that brand based memory organization predominated even when the external environment was attribute structured and presumably did not facilitate brand based processing.

Thus, it may be appropriate to temper an earlier conclusion that "consumers seem to process information in that fashion which is easiest given the display used" (Bettman and Kakkar 1977). Rather, processing may be adaptive, with the nature and extent of adaptation contingent upon the cognitive effort necessary to transcend any constraints imposed by the task environment. This adaptive perspective is consistent with the notion of "constructive processing" (Bettman and Zins 1977, 1979; Bettman and Park 1980a, 1980b) consumers develop or construct choice heuristics from memory contingent upon the properties of the choice task and the phase in the choice process (Wright 1976; Wright and Barbour 1977).

Finally, attribute processing in choice based on memory information was significantly less than when choice was based on external information. Brand based memory organization of information acquired under directed learning did not facilitate attribute processing and lowered its level relative to that observed for choices based on external information.

Future Research

A variety of memory related phenomena warrant further, detailed investigation by CIP researchers. First, individual preferences for different product attributes may affect choice processing and thus both the amount and organization of the information in memory acquired during a choice task. A consumer who attaches extreme significance to one or a few attributes may use more attribute based processing. In contrast, one who values a larger number of attributes more or less equally may use more wholistic evaluation strategies, implying more brand based processing (Biehal and Chakravarti 1982b). Experiments to examine how individual differences affect the choice strategies used ant, in turn, the organization of product information in memory seem to be an important priority.

Second, when choice is the primary task less effort may be directed toward developing well-defined associative links between stimulus elements, or to encoding all the available product information. This implies that less information may be retained relative to directed learning situations, and that what is retained may be subject to greater retrieval error. Since the information that is processed may be Contingent upon the demands of the choice task, it is possible that some brands may be quickly eliminated based on certain attribute values and that information on less important attributes may not be entirely processed. Hence, information on rejected alternatives and less important attributes may be only partially acquired and stored. Therefore, memory for chosen alternatives and key attribute information that receives greater processing attention should be better. Johnson and Russo (1978b, 1981) and Biehal and Chakravarti (1982a) report that recall accuracy is higher for chosen brand information relative to brands that were rejected.

Also, in situations where the choice criteria for subsequent decisions change, difficulties associated with memory retrieval may affect the consumer's ability to perform memory-based choice and thereby influence choice outcomes. For example, when faced with changes in attribute importance weights, a consumer may react in a variety of ways: (1) conduct renewed external search on previously rejected alternatives; (2) use inference processes to assign brand attribute values to alternatives they have difficulty remembering; (3) ignore altogether specific brands and dimensions in the choice process. The strategies consumers use in response to memory retrieval difficulties is another important area for further research.

Third, future research should examine other incidental learning situations, where consumers' information processing goals may be quite different from those in choice. Thus, tasks requiring overall evaluation of product stimuli may generate different processing patterns, as well as the processing of significantly more elements of available information than in a choice task. This suggests that the memory traces resulting from overall evaluations should be stronger than those for incidental learning during a choice task. Some social cognition research has shown better recall performance following a judgment task than under-directed learning (Hamilton, Katz and Leirer 1980). This suggests that in situations where consumers examine all available product information and devote processing attention to developing associative links between stimulus elements in the course of forming an overall judgment about products, memory performance may be better than for either directed learning or non-directed learning during choice.

Another incidental learning situation occurs when product information is acquired under "low involvement" conditions, e.g., viewing a TV commercial. In such instances the amount of processing directed at specific information elements may be less than in choice tasks. Consequently, memory traces for product information acquired under low involvement conditions may be weaker, resulting in differential retrievability and usage of the information in subsequent choices. In summary, future research should explore in more detail different types of incidental learning of product information, and trace their influence on subsequent choice behavior.

Fourth, future research should investigate choice processing and choice outcomes in situations that involve both internal and external information. While past CIP research has focused considerable attention on external search, very little research addresses the interaction between internal and external search processes. Constructive processing implies such an interaction, and propositions about the congruence between external search processes and internal memory organization (Bettman 1979) need empirical investigation. In addition, factors that moderate the relative amounts and sequencing of internal and external search need to be identified, and their effects ascertained. The ways in which consumers resolve potential tradeoffs between memory-retrieval difficulties and the costs associated with external search are also an important CIP research domain.

Finally, the use of verbal protocols as data continues to be of some concern in CIP research. While the validity of verbal protocols has been debated (Nisbett and Wilson 1977) recent papers by Ericsson and Simon (1979, 1980) provide more balanced appraisals, particularly with respect to concurrent verbal protocols. However, there remains concern about how the gathering of protocols affects the choice process. For example, when verbalizing their choices, subjects may feel an implicit need to justify the selection ant/or elimination of certain alternatives. This may result in a greater use of attribute comparison processes than would otherwise occur. Hence the verbal protocol method may cause an artifactual overstatement of the degree of attribute processing in choice.

Even if the choice process itself is unaffected by the gathering of verbal protocols, it is possible that verbalization generates stronger memory traces for information that is processed. Verbalized information may be easier to retrieve in subsequent recall or choice tasks relative to when information is not verbalized, and may affect the results obtained in longitudinal studies of consumer memory and choice processes where subjects perform sequential choice or retrieval tasks for which concurrent protocols are collected. Additional validation of the protocol method needs to be undertaken, perhaps using less intrusive measurement methods, such as response latencies.


Bettman, James R. (1979), An Information Processing Theory of Consumer Choice, Reading, Mass. Addison Wesley.

Bettman, James R. and Jacob Jacoby (1976), "Patterns of Processing in Consumer Information Acquisition". In Beverlee B. Anderson (ed.) Advances in Consumer Research, Vol. 3, Ann Arbor, MI, Association for Consumer Research, 315-320.

Bettman, James R. and Pradeep Kakkar (1977), "Effects of Information Presentation Format on Consumer Information Acquisition Strategies", Journal of Consumer Research, Vol. 3, (March), 233-240.

Bettman, James R. and C. Whan Park (1979), "Descriptions and Examples of a Protocol Coding Scheme for Elements of Choice Processes". Working Paper 276, UCLA Center for Marketing Studies, Los Angeles, CA.

Bettman, James R. and C. Whan Park (1980a), "Implications of a Constructive View of Choice for Analysis of Protocol Data: A Coding Scheme for Elements of Choice Processes". In J.C. Olson (ed.) Advances in Consumer Research, Vol. 7, Ann Arbor, MI, Association for Consumer Research. 148-153.

Bettman, James R. and C. Whan Park (1980b), "Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Processes: A Protocol Analysis", Journal of Consumer Research, Vol. 7 (December), 234-248.

Bettman, James R. and Michel A. Zins (1977), "Constructive Processes in Consumer Choice", Journal of Consumer Research, Vol. 4. (September). 75-85.

Bettman, James R. and Michel A. Zins (1979), "Information Format and Choice Task Effects in Decision Making", Journal of Consumer Research, Vol. 6 (September), 141-153.

Biehal, Gabriel J. and Dipankar Chakravarti (1982a), "Some Experiences with the Bettman-Park Verbal Protocol Coding Scheme", Journal of Consumer Research, Vol. 8 (March). In Press.

Biehal, Gabriel J. and Dipankar Chakravarti (1982b), "Information Presentation Format and Learning Goals as Determinants of Consumers' Memory-retrieval and Choice Processes", Journal of Consumer Research, Vol. 8 (March). In press.

Craik, Fergus I. M. and R.S. Lockhart (1972), "Levels of Processing: A Framework for Memory Research", Journal of Verbal Learning and Verbal Behavior, Vol. 11, 671-684.

Ericsson, K.A. and Herbert Simon (1979), "Thinking-aloud Protocols as Data". CIP Working Paper 8397, Carnegie-Mellon University, Pittsburgh, PA.

Ericsson, K.A. and Herbert Simon (1980), "Verbal Reports as Data", Psychological Review, Vol. 87 (May) ,215-251.

Haber, Ralph N. (1964), "Effects of Coding Strategy on Perceptual Memory", Journal of Experimental Psychology, Vol. 68 (November), 357-362.

Johnson, Eric J. and J. Edward Russo (1978a), "The Organization of Product Information in Memory Identified by Recall Times". In H. Keith Hunt (ed.) Advances in Consumer Research, Vol. 5, Ann Arbor, HI, Association for Consumer Research, 79-86.

Johnson, Eric J. and J. Edward Russo (1978b), "What is Remembered After A Purchase Decision?". Working Paper, Center for Decision Research, Graduate School of Business, University of Chicago, Chicago, IL.

Johnson, Eric J. and J. Edward Russo (1981), "Product Familiarity and Learning New Information". In Kent Monroe (ed.) Advances in Consumer Research, Vol. 8, Ann Arbor, MI, 151-155.

Lappin, Joseph S. (1967), "Attention in the Identification of Stimuli in Complex Visual Displays", Journal of Experimental Psychology, Vol. 75 (November), 321-328.

Newell, Allan and Herbert A. Simon (1972), Human Problem Solving, Engelwood Cliffs, NJ., Prentice-Hall.

Nisbett, Richard E. and Timothy D. Wilson (1977), "Telling More Than We Can Know: Verbal Reports on Mental Processes" Psychological Review, Vol. 84 (May), 321-359.

Osgood, C.E., G.J. Suci and P.H. Tannenbaum (1957), The Measurement of Meaning, Urbana, IL., The University of Illinois Press.

Paivio, A., J.C. Yuille and S. Madigan (1968), "Concreteness, Imagery and Meaningfulness Values for 925 Nouns", Journal of Experimental Psychology Monograph Supplement, Vol. 76, Part 2, 1-25.

Russ, Frederick A. (1971), "Consumer Evaluation of Alternative Product Models". Doctoral Dissertation, Carnegie-Mellon University, Pittsburgh, PA.

Russo, J. Edward and Eric Johnson (1980), "What do Consumers Know about Familiar Products?", In J.C. Olson (ed.), Advances in Consumer Research, Vol. 7, Ann Arbor, MI., Association for Consumer Research, 417-423.

Russo, J. Edward and Larry D. Rosen (1975), "An Eye-Fixation Analysis of Multi-alternative Choice", Memory and Cognition, Vol. 4 (November). 683-689.

Russo, J. Edward and Barbara A. Dosher (1976), "Dimensional Evaluation: A Heuristic for Binary Choice". Unpublished Working Paper, Carnegie-Mellon University, Pittsburgh, PA.

Tulving, Endel (1962), "Subjective Organization of Free Recall of 'Unrelated' Words", Psychological Review, Vol. 69 344-354.

Tulving, Endel (1979), "Relation Between Encoding Specificity and Levels of Processing". In L.C. Cermak and F. I.M. Craik (eds.), Levels of Processing in Human Memory, Hillsdale, NJ., Lawrence Erlbaum Associates.

Tulving, Endel and Donald M. Thompson (1971), "Retrieval Processes in Recognition Memory. Effects of Associative Context", Journal of Experimental Psychology, Vol. 87, 116-124.

Tulving, Endel and Donald M. Thompson (1973), "Encoding Specificity and Retrieval Processes in Episodic Memory", Psychological Review, Vol. 80, 352-373.

Tversky, Amos (1969), "Intransitivity of Preferences", Psychological Review, Vol. 76 (January), 31-48.

Tversky, Amos (1972), "Elimination by Aspects: A Theory of Choice", Psychological Review, Vol. 79, 281-299.

Wright, Peter L. (1976), "The use of Phased, Non-compensatory Strategies in Decisions Between Multi-attribute Products". Working Paper #223, Graduate School of Business, Stanford University, Stanford, CA.

Wright, Peter L. and Frederic Barbour (1977), "Phased Decision Strategies: Sequals to an Initial Screening". In M. Starr and M. Zeleny (eds.) North Holland/TIMS Studies in the Management Sciences, Vol. 6 Multiple Criterion Decision Making. Amsterdam, North Holland, 91-109.