Cognitive and Affective Responses in Attribute-Based Versus End-Benefit Oriented Advertising

ABSTRACT - The question of cognitive and affective responses in attribute-based versus end-benefit oriented advertising is explored. The two types of advertising are shown to differ both in motivating purchase intent and, more fundamentally, in the type of underlying response mechanisms generated. Product users and non-users predisposed toward purchase are shown to be reacting primarily to the cognitive aspects of the advertising; nonusers not predisposed toward purchase were shown to be reacting primarily to the affective elements of the campaigns. The results were interpreted in terms of low involvement theory.


Martin R. Lautman and Larry Percy (1984) ,"Cognitive and Affective Responses in Attribute-Based Versus End-Benefit Oriented Advertising", in NA - Advances in Consumer Research Volume 11, eds. Thomas C. Kinnear, Provo, UT : Association for Consumer Research, Pages: 11-17.

Advances in Consumer Research Volume 11, 1984      Pages 11-17


Martin R. Lautman, ARBOR, Inc.

Larry Percy, CREAMER, Inc.

[The authors would like to acknowledge the efforts of Ms. Ann Miksovic of ARBOR, Inc. in assisting in the design and for conducting the data analysis. The technical assistance of Dr. Shel Feldman of ARBOR, Inc. is also gratefully acknowledged.]


The question of cognitive and affective responses in attribute-based versus end-benefit oriented advertising is explored. The two types of advertising are shown to differ both in motivating purchase intent and, more fundamentally, in the type of underlying response mechanisms generated. Product users and non-users predisposed toward purchase are shown to be reacting primarily to the cognitive aspects of the advertising; nonusers not predisposed toward purchase were shown to be reacting primarily to the affective elements of the campaigns. The results were interpreted in terms of low involvement theory.

For many people and for many products, the commercial is the product. People structure their expectations on the basis of the commercial copy and visual images and evaluate product performance against these expectations. The commercial may be the consumer's only link between product expectations and their basic needs and preferences.

Two types of commercial tactics address this linkage in very different ways. In one, the product feature/ characteristic/ attribute approach, a specific product-based attribute is highlighted. For example, an advertised product may be described as convenient, nutritional, reliable or expensive. In the second approach, a consumer end-benefit is highlighted and, for example, the advertised product may be described as "keeping you slim," whelping your dog to live longer," or preserving your memories (film)."

Which of these two types of tactics will be more effective? Specifically, in the case of a low calorie food product is it more advantageous to advertise that the product will "taste good" or that the product will "help YOU look beautiful?"

A more fundamental issue related to this question is the nature of the executional format used in these two different approaches. While there is no creative mandate, in many product categories attribute-based advertising has tended to be of the factual type involving "cognitive-type" thinking (Learn-Feel-Do) and executional formats with the product as "hero". End-benefit advertising has tended to be more image and mood oriented (Feel-Learn-Do) and to emphasize affective responses with the consumer's reaction the focus. For example, Kodak's commercials have been described by their agency as not intending to offer rational reasons for buying film, under the assumption that emotion and not rationality motivates a consumer's purchase of film. Thus, which of these two executional formats would be most effective, "mind-directed" or "stomach-oriented," is a key concern in developing and implementing advertising strategy consistent with a brand's strategic framework.


Given this distinction between affective and cognitive oriented advertising formats, the question of appropriate measures to evaluate the difference arises. A review of the literature yields a surprising lack of either empirical research or theoretical approaches to this subject. The most similar research thrust seems to be the literature on attitude toward the ad (Aad) versus attitude toward the brand (Ab). Here, the assumption is explored that affective attitudes toward the advertising itself and not just toward the product may have an impact upon product purchase. This idea has stimulated a great deal of recent consumer research interest. After all, should not someone respond more favorably to a message that is more favorably received than one less favorably received?

In fact, advertising researchers have drawn from a large body of research in the psychology literature that would seemingly support this idea. For example, Bower and his colleagues (Bower, 1981; Bower, Monteiro, and Gilligan, 1978) have studied the relationship between memory and a person's mood during learning tasks. In the earlier study, it was reported that emotional moot served as a distinctive learning-and-recall context primarily when the subject had to keep separate several interfering sets of material. Would this be a reasonable description of advertising in a clutter environment? Perhaps, but the involvement required in their experiments seems quite beyond what one might expect when presented with most advertising communications.

Bower's 1981 study proposed an associative network theory where emotion serves as a memory unit that can enter into associations with coincident events. But, here again something must trigger the emotion unit. Should we expect this to occur in the consumer's mind at the point-of-purchase, or when otherwise confronted with a brand stimulus?

Srull (1983) has attempted to deal with this question of mood and its relationship to affective reactions to advertising. His preliminary findings suggest that initial evaluations are strongly influenced by subjective mood states at the time of information acquisition. Importantly, however, he also notes that there were significant interactions between mood state at the time of retrieval and the type of information provided. We would offer that this could also tend to mediate relationships between types of message and the impact of affective reactions to the source of that message: that is, the attitude toward the advertising.

The seemingly common sense notion that one's reaction to an advertisement will be generalized to the subject of the advertising has been appealing to many advertising researchers as well as practitioners (Bartos, 1980; Light, 1980) despite zany well-known examples to the contrary; among them, the consumer-hated 'White Tornado campaign for Ajax, and "ring around the collar" campaign for Wisk.

The explanation for the success of these "contrary" campaigns has been attributed to another body of communication theory -- cue discounting -- where the receiver was felt to simply forget or disassociate the source of the information from the information itself. However, an alternative hypothesis has been offered by Silk and Vavra (1974). They have suggested that, contrary to a straight linear relationship, a J-shaped relationship exists between positive reaction to an advertisement and its effectiveness; and, that the most effective advertising will be that which is either liked very much or disliked very much. This could account for the effectiveness of disliked advertising, while still maintaining a mediating role for attitudes toward the ad. Moore and Hutchinson (1983), also found a similar 3-shaped response function after one week, but noted that immediate response tended to be more linear.

Most of the attempts to relate attitude toward the advertising and attitude toward the advertised brand seem to be following information processing theory lines. Lutz, MacKenzie, and Belch (1983), for example, have taken such a view in reporting a study aimed at uncovering the possible causal mediating role of affective reactions to advertising. While finding a significant mediating role for attitudes toward advertising, they seem less certain as to why, offering several possible explanations (among them the idea of "mood").

Shimp (1981) also postulated a mediating role for attitude toward the ad, proposing that it is linearly related to attitudes toward the advertised brand, such that the more positive a receiver's reactions are to specific advertising, the more positive will be his reactions to the advertised product.

Some of the most ambitious empirical work to date on this question comes from Mitchell and his associates (Edell, 1982; Gardner, 1981; Mitchell, 1980, 1982a, 1982b, 1983; Mitchell and Olson, 1981). The Mitchell and Olson (1981) study looked at the effect of manipulating the content of advertising. An analysis of brand attitude (following Fishbein's expectancy-value formulation) suggested that something other than the observed beliefs about the brand mediated the effect exposure to advertising had upon brand attitude. Factor analysis of the scales used uncovered a clear evaluative dimension in the measures used; and this, along with the brand attitude results from the expectancy-value model, reliably accounted for the observed difference in brand attitude. Mitchell and Olson concluded from these findings that attitudes toward an advertisement could mediate the effects of emotional and visual advertising in the formation of brand attitude.

A methodological problem with the Mitchell and Olson study, however, mitigates its generality. They used a latin square design for stimulus presentation such that each respondent saw all four advertisements. Thus, consumer reactions to the ads seen earlier in this study probably influenced later reactions. Specifically, seeing the verbal claim of softness may have sensitized respondents to it in other ads, and in particular, the ad portraying a kitten. Mitchell and Olson, apparently aware of this potential confounding problem, had two other groups of respondents provide cognitive response protocols immediately after exposure to each of the ads. They showed that, "When the verbal claim preceded the kitten advertisement, about as many subJects mentioned softness in their protocols for the kitten advertisement as when the kitten advertisement preceded the verbal claim." They concluded that ... the kitten picture independently connoted the semantic concept of softness." While this may be true, the effects on consumer beliefs relative to softness, the focus of the analysis, remains undetermined. It is reasonable to suspect that their findings were the result of contrast effects on beliefs; that is, exposure to all of the advertisements had a strong and significant effect on consumer beliefs relative to the softness of the alternative products.

Mitchell (1980) has suggested that attitude toward the brand and attitude toward the advertisement, way, in fact, represent two different channels in the information acquisition process attitude toward the brand a verbal reaction to the product and attitude toward the advertisement a process that generates a node in memory that attaches to the memory trace of the advertising. Building upon this idea, he now suggests (1983) that attitudes toward the ad mediate visual and emotional effects, and may represent primarily a nonverbal channel.

Ray and Batra (Batra and Ray, 1982; Ray and Batra, 1983) have addressed the question of affect by combining information processing theory with the concept of involvement (Krugman, 1965). They suggest that high and low involvement advertising initiate different types of affective response. In the case of high involvement, affect is the result of extensive cognitive activity; in the case of low involvement advertising, affect is coupled with awareness (Zajonc's (1968) "mere exposure effects") since few cognitive responses, if any, are created.

All of these prior studies have tended to avoid directly manipulating the type of advertising tactic being employed and, therefore, identifying the underlying response mechanisms which might apply with different executional formats. Yet there is a strong possibility that the type of execution will significantly influence both cognitive and affective evaluations of the brand as well as the advertising itself. For example, does the execution itself have specific influence over and above the beliefs associated with the product as a result of the advertising? Furthermore, no attempt has been made as of yet to simultaneously investigate alternative advertising tactics along with differences in receiver response as might be present in users and non-users of the product.

Thus, the primary purpose of this study will be to explore the underlying affective and cognitive mechanisms involved in end-benefit oriented versus product attribute-based advertising. As a rationale for current practice, it would seem that in end-benefit type advertising, affective reactions would have a greater impact in motivating purchase while in product attribute-based advertising, cognitive reactions would have the greater role. A secondary purpose of this study will be to explore the effects of these alternative advertising tactics on different consumer segments.

Analytic Plan

The analysis will be conducted in two phases. First, we will identify which campaigns did best and worst by usage segment and by diet behavior. In our second phase, we will probe the cognitive and affective response mechanisms underlying the performance of the different campaigns. This will be done by developing a series or scales to quantity different underlying response mechanisms and then applying those scales to explain the differential responses to the various campaigns by different product usage segments.


Study Design

Four finished 30-second commercials for a recently introduced a food product with lower than the typical number of calories were created. The product has been positioned as an appetizing product for weight conscious women. The four commercials varied in their content ranging on a continuum from what was judged to be attribute-based to end-benefit oriented in their promotional content. Specifically, the commercials can be described as follows.

1. Commercial A. Significant emphasis on product appearance and attributes with eight close-up product beauty shots, and no presenter.

2. Commercial B. Some emphasis on product appearance and attributes with three close-up product beauty shots and formal female presenter.

3. Commercial C. Minimal product emphasis with some emphasis on benefit to the consumer with four close-ups of eyes and mouth of actress and three product beauty shots.

4. Commercial D. Significant emphasis on appearance of consumer with five close-ups of beautiful body of actress, two involving an admiring male, and three product beauty shots.

In addition to the commercials, print ads which mirrored the commercial copy were created. Five print ads were generated since it was of interest whether Commercial C might be more effective with an end-benefit oriented print ad campaign or an attribute - based print campaign, both of which were present to some degree in the commercial. Thus, two ads, compatible with the commercial content, were created as companion print ads. These campaigns were identified as the product attribute-based print ad (C-PA) and the end-benefit oriented print ad (C-EB). Each of the five campaigns was evaluated monadically.


Respondents were intercepted and interviewed in central location test facilities in five cities. An equal number of respondents were assigned to each of the five treatment groups in each city. A total of 500 respondents were interviewed, 100 in each of the five treatment cells.

Along with standard security questions, respondents were screened for being female heads of households between the ages of 18 to 65 who had used products in that category in the past month. Quotas were set so that no more than 20% of the respondents were between the ages of 45 to 65 and one-half of the respondents in each cell had bought the test product in the past and were positively disposed towards buying it again.


After screening, respondents were given a pre-exposure constant sum question and asked to identify the brand(s) of products in the category an,l quantity of each they will buy in their next 10 purchases (packages). They were then shown a test commercial, told to watch it carefully, and, after exposure, asked to rate it on an adjective checklist. Following this they were shown the print ad and asked to read it carefully. This was followed by a five point purchase intent scale,

"Based only on both the commercial and print ad you just saw how likely would you be to buy (test brand)?"

an interest question,

"After having seen this advertising campaign, would you say that your interest in buying (test brand) has increased, decreased, or remained the same?'

a post-exposure constant sue, and questions about new information learned, consistency of the advertising campaign with personal experience, perceptions of any major advantages of the advertised brand, and belief in overall superiority of the test brand over competition. Additional substantive questions followed these, but since they are not relevant to our discussion they will not be presented here. Along with standard demographic questions, respondents were asked if they were currently on a diet or watching their weight.


Treatment Cell Respondent Homogeneity Tests

Two chi-square tests were conducted to insure that the treatment cells for the five campaigns did not differ on the key demographic factors of age or diet behavior. A chi-square test of Age x Campaign was observed to be non-statistically significant (X2 = 17.43, d.f. = 16, p > .05). Similarly, a chi-square test of Diet Behavior (on a diet, watching weight, not on a diet) x Campaign was not statistically significant (X2 = 9.09, d.f. = 8, p > .05).

In order to test whether the five treatment cells were equivalent in terms of pre-experimental usage of the test product, a Campaign x Diet Behavior x (test) Product Usage (user, non-user) three way ANOVA was conducted with the dependent variable the pre-exposure number of test packages intending to purchase. Other than the expected main effect for Product Usage (p < .001) with users reporting significantly greater purchase interest than non-users, no other main effects or interactions were statistically significant. While the mean scores for the Diet Behavior cells were in the expected direction (on a diet > watching weight > not on a diet), a significant main effect for Diet Behavior was observed only when the Product Usage variable was deleted from the analYsis.

Campaign Performance

A series of six three-way .,NOVAs were conducted with the independent variables Product Usage, Diet Behavior and Campaign and the dependent variables new information learned, consistency with personal experience, major advantage citations for the advertised product, belief in the overall superiority of the advertised product, purchase intent and the difference in post and pre "purchases" in the constant sum question. All post-hoc tests were conducted using the Tukey HSD procedure. The purpose of these tests were to determine if the five campaigns varied in their ability to generate different responses relating to information acquisition, perceptions of personal experiences and motivation (major advantage citations, overall superiority belief, and intended purchases) among the different market segments.

Learn New Information. Statistically significant main effects were observed for Product Usage (p < 001) and Campaign (p < .001). More information was learned by non-users than by users (p < .05) and by respondents in the two most extreme product attribute-based campaigns, A and B than in the two most end-benefit oriented campaigns, C-EB and D (p < .05). The intermediate product attribute-based campaign, C-PA, also scored significantly higher than its complementary end-benefit oriented campaign, C-EB (p < .05).

Consistency with Personal Experience. A statistically Significant main effect for product usage (p < .001) and a product usage by campaign interaction (p < .02) were observed. The source of the interaction was that while on an overall basis users reported significantly greater consistency than non-users (p < .05), users found campaign A consistent with their experience and nonusers found it inconsistent with their experience at levels far greater than any other campaign; and, in campaign C-EB, users and non-users did not differ at statistically significant levels.

Major Advantage. Statistically significant main effects were observed for Product usage (p< .001) and for Campaign (p < .05). significantly more users than non-users cited major advantages for the test product (p < .01). With respect to the campaigns, more major advantages were cited in the most product attribute-based Campaign A than in either of the two most end-benefit oriented campaigns, C-EB and D.

Overall Superiority. Statistically significant main effects were observed for product usage (p < .001). Diet behavior (p < .05) and, (marginally) for Campaign (p < .06). Users rated the test brand higher in overall superiority, and those on a diet rated it significantly better than respondents either watching their weight or not dieting (p < .05). As in the case of major advantage citation, the product attribute-based campaign A, out performed either of the two most end-benefit oriented campaigns, C-EB and D (p < .05).

Purchase Intent. All three variables had statistically significant main effects. Predictably, users were significantly higher in purchase intent than non-users (p < .001) and respondents on a diet or watching their weight had significantly higher purchase intent than non-dieters (p < .05). Higher purchase interest was observed for all three product attribute-based campaigns, A, B and C-PA than for the two end-benefit oriented campaigns, C-EB, and D (p < .05).

Pre-Post Constant Sum. As is often the case with Constant Sum measures because of "ceiling effects" with users, significantly more intended purchases were stated by non-users than by users (p < .002). A statistically significant campaign main effect (p < .03) was the result of the two most extreme product attribute-based campaigns, A and B, having significantly greater shifts in intended purchases than the two most extreme end-benefit oriented campaigns (p < .05). A (marginally) statistically significant Product Usage by Diet Behavior interaction (p < .06) was the result of non-dieters showing no statistically significant difference between users and non-users (p > .05) while among those respondents watching their weight, non-users showed a significantly greater shift than users (p < .05). In fact, respondents who were watching their weight and were test brand users allowed a significantly smaller shift than any non-user segment (p < .05).

Scale Development

While it has just been demonstrated that the product attribute-based campaign clearly outperformed the end-benefit oriented campaigns and that diet behavior significantly affected consumer reactions to all of the campaigns, the different ,mechanisms which might be underlying consumer response to the four commercials has yet to be identified. As such, one way ANOVAs were conducted on all 22 adjectives of the adjective checklist. In each case, the independent variable was the four commercials and the dependent variable was purchase intent. Fifteen (15) adjectives were selected as showing discrimination among the four commercials (p < .10). A principle components factor analysis with a varimax rotation of these adjectives was conducted. Three factors were identified, using as a criterion an eigenvalue cutoff of 1.0 or higher. Inclusion of a fourth factor did not seem defensible on either statistical (there was a sharp dropoff between three and four factors in variance accounted for) or logical grounds. Table 1 shows the three factors. Each factor was considered a scale and a reliability analysis indicated alpha levels of .82, .78 and .76 for the three scales, respectively.



The three scales seemed to reflect three types of response structures - affective positive, cognitive negative and cognitive positive. It remains to be determined how the commercials differed in terms of these response mechanisms. Our prediction is that the product attribute-based campaigns would significantly outperform the end-benefit oriented campaigns on the cognitive positive measure with the reverse true for the cognitive negative and affective positive measures.

Campaign Differentiation in Terms of Response Mechanisms

Three ANOVA's were conducted. In each, one of the three response scales was the dependent variable and the independent variables were, as before, Product Usage, Diet Behavior and Campaign.

In the three way ANOVA on the affective positive scale, the only statistically significant effect was the main effect for Campaign (p < .01). The strongest end-benefit oriented Campaign D was rated higher than the product attribute-based Campaign B (p< .05). Although not quite statistically significant, as would be predicted, Campaign D also was rated higher than Campaign

In the ANOVA on the cognitive negative scale, there were two statistically significant effects, the main effects for Product Usage, where non-users had more cognitive negative responses than users (p < .01), and for Campaign. In the case of the latter effect, Campaign D had significantly more cognitive negative ratings than Campaigns A or B. Campaign C, it might be noted, was positioned right where predicted, between D and Campaigns A and B.

The ANOVA on the cognitive positive scale produced two statistically significant effects, a Product Usage main effect and a Campaign main effect, and one marginally significant main effect for Diet Behavior. Users were observed to rate the commercials higher than non-users (p < .01) and the most product oriented Campaign A produced more positive associations than the most end-benefit oriented Campaign D (p < .01). It might be noted once again that the intermediate Campaigns, B and C, fell in the predicted order; that is B had the most cognitive positive associations after A.

Regression Modeling of Advertising Response

Up until now we have demonstrated that the campaigns had different impacts upon the target market and that these effects seemed to relate to the underlying cognitive and affective responses to the advertising stimuli. We now turn to the questions of 1) whether these cognitive and affective responses make an independent contribution to the overall purchase motivation over and above that accounted for by "background" variables (age, income, product usage and diet behavior), and 2) whether the nature of the mechanisms underlying these responses differ bs usage category

Table 2 shows the results of a series of multiple regression models. These models are tied together by a conceptual framework which suggests that cognitive responses are more important in determining purchase interest to current product users and the most susceptible non-users while affective responses are of primary importance to "hard core" non-users. Models I and II are based on the total sample. Model II includes Model I and demonstrates that inclusion of the affective and cognitive responses greatly increases the amount of variance accounted for by the models. An F test showed that Model II is a significant improvement over the strictly background Model I (F = 56.59, d.f. = 3,373, p < .001). It might be also noted that in terms of magnitude, each of the beta weights for the two cognitive measures accounts for more than four times the explained variance than does the affective measure.



The high beta value for the number of pre-packages and our prior ANOVA results suggested to us that users and non-users might be responding differentially to the different campaigns. A Chow test (see Appendix A) clearly demonstrated this to be true (F = 6.71, d.f. = 7,374, p < .001). The user and non-user models are shown as models III and IV, respectively. Interestingly, only cognitive response levels were statistically significant among users while both cognitive and affective responses were statistically significant among non-users. In fact, for non-users, the beta weights for both cognitive response and the affective response levels were now about equal, suggesting that all three contribute about equally in motivating purchase intent.

One further segmentation of the data is of interest, although sample size limitations prevent conducting conclusive tests. We divided the non-user sample (Base = 199) on the basis of their diet behavior. One group was defined as "susceptibles" (Base = 135) and included respondents categorized as on a diet or watching their weight. The second group was defined as "non-susceptibles" (Base = 64) on the basis of their not being on a diet or watching their weight. Models V (Susceptibles) and VI (Non-Susceptibles) suggest that the underlying response mechanisms of these two groups differ. Susceptibles seem to be motivated by cognitive response mechanisms while non-susceptibles are motivated by the affective mechanisms. Figure 1 summarizes these effects.



Lastly, additional multiple regression analyses, not reported here tue to space limitations, incorporated a dummy variable in order to determine the impact of the print ad and any of the other non-response mechanism based "background" variance in the different cells. The underlying cognitive and affective response scales were found to maintain their statistical significance even with this additional "background" variable.


Our results showed that the attribute-based campaigns outperformed the end-benefit oriented campaigns and that diet behavior predisposed the respondents towards more positive reactions to all of the campaigns. Pursuing our interest in the process underlying these findings, we developed a series of scales which showed that the campaigns did, in fact, vary on the hypothesized cognitive and affective dimensions. The better performing product attribute-based campaign commercials scored higher on the cognitive positive dimension and the lower scoring end-benefit commercials scored higher on the cognitive negative and affective positive dimensions.

Our final analysis explored the nature of the relationship between these underlying response dimensions and purchase interest. It was shown that these cognitive and affective reactions contributed toward purchase interest in the test product over and above the effects attributable to demographic, current product usage, and predispositional (diet behavior) variables. Furthermore, it was found that users and non-users differed in the relationship of their cognitive and affective responses to purchase interest. Non-users relied more zn affective reactions. A further segmentation of the non-user group identified two subgroups which differed in their responses: (1) a "susceptibles" non-user subgroup, those with a positive predisposition toward product purchase as evidenced by their engaging in some form of diet behavior who showed significant relationships with purchase interest only for cognitive responses; and (2) a "non-susceptibles" non-user subgroup who showed significant relationships with purchase interest only for affective responses.

Two conclusions seem to be suggested by these findings. First, advertising campaign tactics can be differentiated along underlying consumer response dimensions and these can be expected to include both cognitive and affective reactions to the advertising itself. Second, cognitive responses, as defined in Table 1, appear to be more important in motivating current product users or :hose non-users predisposed to usage while affective responses are more important among the least predisposed non-users. It is tempting to describe this differentia:ion as suggesting that rational arguments are needed to persuade those respondents predisposed toward purchase while affective reactions are needed to motivate those lot predisposed.

If non-usage (but responsiveness to the advertising message) is viewed as low (product) involvement, then the results of this study are consistent with that body of literature. Low involvement is theorized to result in few cognitive responses and unchanged attitudes. It is perceived as creating advertising awareness and pre-cognitive affect. Here, however, awareness was con:rolled in the sense of the advertising being presented in a forced exposure format; and, even in this environment, cognitive responses were minimized. Thus, affective responses may be more important in low involvement advertising, independent of "mere exposure" driven awareness. High involvement is theorized as generating significant cognitive activity, corresponding to the responses observed here among users and those predisposed toward Purchase.

It was found that the product attribute-based campaign outperformed the end-benefit oriented campaign. This may have been the result of high consumer familiarity with the end benefit of the tested product. With a new product, one where product attributes are not often advertised or a different product class/category, the end-benefit oriented approach might prove to be superior. In any case, the confounding effects of end-benefit campaigns tending to be affect oriented and product-based attribute campaigns tending to rely on cognitive mechanisms would require separation in future studies in order to provide a clear understanding of what "works best" in any given situation.




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Martin R. Lautman, ARBOR, Inc.
Larry Percy, CREAMER, Inc.


NA - Advances in Consumer Research Volume 11 | 1984

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