The Attitudinal Implications of a New Brand's Name

ABSTRACT - The research results reported in this paper show that a brand name alone can shift a consumer's attitude away from a neutral or zero level. However, the results also support the conclusion that such a brand name cannot similarly impact consumer purchasing intentions. Further, the results indicate high levels of experience and interest in a product class can lead to high attitudinal levels for a new brand name.


George M. Zinkhan and Claude R. Martin, Jr. (1982) ,"The Attitudinal Implications of a New Brand's Name", in NA - Advances in Consumer Research Volume 09, eds. Andrew Mitchell, Ann Abor, MI : Association for Consumer Research, Pages: 467-471.

Advances in Consumer Research Volume 9, 1982      Pages 467-471


George M. Zinkhan, University of Michigan

Claude R. Martin, Jr., University of Michigan


The research results reported in this paper show that a brand name alone can shift a consumer's attitude away from a neutral or zero level. However, the results also support the conclusion that such a brand name cannot similarly impact consumer purchasing intentions. Further, the results indicate high levels of experience and interest in a product class can lead to high attitudinal levels for a new brand name.

The evidence in this paper supports the hierarchy of effects model for high involvement products. The results also support the notion that there is a relationship between past product experience and attitudes toward a new brand name.


The purpose of this paper is to report on our preliminary research into methods used by consumers in responding to a new previously unknown, brand name. Specifically examined are both the attitudinal implications and behavioral intentions associated with such a new brand name. Coupled with this objective is a review of the way in which the attitudinal responses are influenced by prior experience, familiarity, and interest in the overall product classification.


A key concept underpinning our research is that a brand name is a major product attribute and a part of what the consumer buys (Davis 1981). The importance of the brand name is amplified by a Wall Street Journal report (1981) on "brand personality...defined people feel about a brand rather than what the brand does." Intrinsic to this is that a brand name is something more than a label; it is a complex symbol for the potential consumer. Gardner and Levy (1955) described this as a "public image, a character or personality that may be more important for the overall status (and sales) of the brand than many technical facts about the product." For the sake of this paper, image is defined as a composite of knowledge, beliefs and feelings" attitudes - a person has and takes into account when responding to an object (Meyers 1968). Kinnear and Taylor (1973) have shown that image is related to the brand in at least two ways. First, the brand name contributes to the image; and second, it is through the brand name that image is projected.

In a previous ACR conference (Lastovicka and Gardner 1978) it was proposed that with respect to high involvement products. consumer responses can be categorized in a hierarchy of effects model:

Cognition--> Affect --> Behavior.

A variant of this concept, with respect to product names, can be presented (Palda 1966) as:

Awareness --> Attitude --> Behavioral Intention.

One criterion used to evaluate the appropriateness of a new product name is that of memorability (Rewoldt, Scott and Warshaw 1977). This obviously relates to the first stage of the hierarchy above, awareness. However, our focus in this research is on the other two dimensions: attitude and behavioral intentions as they relate to new brand names.

The very nature of the hierarchy of effects model (Urban and Hauser 1980) suggests the postulate that in the population as a whole, more people would experience an attitudinal effect than would experience a behavioral effect. This leads to our initial two hypotheses:

H1: Attitudes will be shifted away from the neutral level by the product name alone.

H2: Behavioral intentions will not be shifted away from the neutral level by the product name alone.

Perhaps another way of stating the thrust of these hypotheses comes from Richard O'Brien, Executive Vice President of Grey Advertising: "The litmus test is if I took the name out of the commercial, could you tell me the product?" (Wall Street Journal 1981).

We observe that marketers, trying to correct for initial attitude formation, have adopted the first of these hypotheses as operational when attitude change is modelled in communications research. While it may be proper to similarly correct for prior behavioral intentions, it is our a priori notion that this is not necessary for a new brand name choice.

Howard and Sheth (1969) associate limited problem solving (LPS) with moderate attitudes and extensive problem solving (EPS) with low attitudes. High experience, familiarity, number of purchases and interest are representative of an LPS situation. Thus we would expect to find high levels of experience, familiarity, number of purchases and interest to be associated with high attitude levels. The hierarchical model is in agreement when it concerns new products; as customers gain experience with a new product classification they move along a hierarchy beginning with awareness and culminating in purchase. Recall our first hypothesis that a brand name alone can move potential customers along the hierarchy from the awareness to the attitudinal stage. Another way of stating this concept is: "Because the expectancy-value measures (of attitude) elicit relatively specific cognitive and evaluative reactions, it is expected that crystallized attitudinal responses will only occur for those with prior experience with the attitudinal act." (Bagozzi 1981).

In a marketing context, experience with the attitudinal act is equivalent to experience with a particular product classification. This then leads to our remaining hypotheses:

H3: High experience levels Lead to high attitude levels.

H4: High interest levels lead to high attitudinal levels.

H5: A large number of prior purchases (experience) leads to high attitudinal levels.

H6: High familiarity levels lead to high attitudinal levels.

Here, a "high attitude" is equivalent to a favorable attitude toward the product; a "low attitude" is equivalent to an unfavorable attitude toward the product, and a "neutral" or "zero level" attitude is equivalent to a condition of apathy. Experience, interest, familiarity and prior purchases are all measured for the product classification


Essential to this research is a product class that fosters high levels of brand involvement or product interest. At the same tine the product classification has to be one with which many people are familiar and which is relatively inexpensive. Fitting all these criteria are electronic calculators, especially relevant to the eventual, available research subjects - undergraduate college students.

Product interest is measured on an 8 point scale anchored at the two ends by "not at all interested" and "very interested." Number of purchases is measured by having respondents indicate how many times they have purchased a calculator in the last 15 years. Familiarity is operationalized in two stages (Scott 1962, 1963). First, in a free format, respondents list all of the important attributes that they can think of associated with calculators. Second, respondents put these attributes into groups that are similar. A respondent can make as many or as few groups as seem appropriate. A measure of familiarity can be derived according to a formula derived from information theory (Attneave 1959):


where n is the total number of attributes, ni is the number that appears in a particular combination of groups, and pi = ni/n.

H may be treated as an approximate measure of the dimensional complexity of the cognitive domain referring to a particular class of attributes. It is a purely structural property, because it does not depend on the content of the attributes, but on a relations (similarity or dissimilarity) among them (Scott 1962).

An additional measure R, or the index of relative entropy, may be used to correct for varying numbers of attributes initially listed by different subjects:

R = H/log2 (n),

Where" is the number of attributes listed by the subject. While H represents the absolute complexity of the subject's category system, R may be interpreted as the complexity relative to the number of attributes to be comprehended. R thus tends to correct downwards the familiarity scores of subjects who name a large number of calculator attributes, without fully distinguishing among them (Scott 1962). Consequently, a subject's R score is used as a measure of familiarity in this investigation. Notice that the original formulation of this concept - R - required subjects to list and group objects rather than to list and group attributes In other words, a high R score indicates that a subject is able to observe objects within a domain as distinct from one another. Under the procedure employed in this study, subjects place attributes into groups, and thus a high R score indicates that a subject observes product attributes as distinct from one another. The R measure. as formulated here, is akin to Bieri, et al.s (1966) notion of cognitive complexity.

Behavioral intention is operationalized in a manner outlined by Thomas Juster (1966). Probability that a purchase may take place is measured both for the product class and for the individual brand. The behavioral intention measure for the product class of calculators is outlined in Exhibit 1.


Attitude toward the brand is measured using Fishbein's (1967) conceptualization of attitude-toward-the-act (A-act):


Where A-act represents an individual's attitude toward (affect for or against) using a particular brand; Bi is the individual's perceived likelihood (or belief) that using the brand will lead to some consequence i; ai represents the importance of consequence i; and" is the number of salient consequences. Reviewing the attitude measurement equation above, we note that the term "attribute" is often substituted for the term "consequence" in consumer behavior research (Lutz 1975).

It is important that the component of beliefs in the expectancy-value model reflects the factors actually salient in the formation of attitudes. Consequently, pretests were conducted to isolate the important attributes associated with calculators. These attributes are represented in Exhibit Z. Five attributes are used to represent the product category. This is in line with an accepted rule-of-thumb stating that "a person's attitude toward an object is primarily determined by no more than five to nine beliefs about the object" (Fishbein and Ajzen 1975).




Range of Capabilities

Degree of Programmability

Operation Ease

Memory Capacity

In sum, attitude is operationalized here by having subjects indicate how important 5 product attributes are and by having subjects indicate how much of an attribute a particular brand possesses. For example, subjects indicate, on a 7 point scale, how important a calculator's price is; in addition, subjects indicate how satisfactory a fictitious "new" brand's price is on a seven point scale.

Attitude is an important criterion variable here; but, where appropriate, attitude is decomposed into its two components - beliefs and values - to facilitate analysis. A single measure of values is formed by summing the five separate value ratings (price, range of capabilities, etc.) for calculators in general. Similarly, a single belief measure is formed by summing the five separate belief measures. for the "new" brand in particular.


148 undergraduates from a major midwestern university were recruited to participate in the experiment. Students seem to be appropriate for the purposes of the present study since they are especially interested in calculators as a product class.

First, questionnaires designed to gauge the independent variables are administered in the following order: familiarity, interest, experience, and number of purchases. Next, the dependent variables - attitude and behavioral intention - are measured. The value component of attitude is measured for calculators in general; the belief component of attitude is measured for a fictitious brand- the Computron R-55. Behavioral intentions are measured both for the product class as a whole and for the Computron brand in particular. One half of the subjects rated attitudes first and behavioral intentions second; the remaining 74 subjects rated behavioral intentions first and attitude second. Analysis of variance results reveal no difference between these two halves of the sample with respect to attitude and behavioral intention scores.


In order to investigate the first hypothesis, it makes sense to examine the belief component of attitude but it does not make sense to examine the value component. In other words, only the brand specific component of attitude is important when assessing the impact of new product names The beliefs associated with using a Computron are measured on a 7 point scale. The scale is coded with +3 as the most positive rating, -3 as the most negative rating, and O as the midpoint. 95% confidence intervals for these belief scales are shown in Exhibit 3. Notice that these confidence intervals never contain the zero point. In addition, using the Bonferroni method for simultaneous inference, the mean belief ratings are all significantly different than zero. Four belief scales - price, range of capabilities, operating ease, and memory - are all shifted towards the positive end of the scale. Programmability is shifted towards the negative end of the rating scale. In this particular instance, the belief component of a new product attitude is shown to be shifted away from the neutral level. The first hypothesis is supported.

As shown in Exhibit 1, behavioral intention is measured on an 11 point scale; the zero point is equivalent to no chance or almost no chance of purchase, 95% confidence intervals for the behavioral intentions associated with calculators in general and the Computron brand in particular are represented in Exhibit 4. Notice that the confidence intervals do not contain zero. And yet, the brand specific confidence interval is less than one, which indicates a very slight possibility of purchase. For all practical purposes, there is little intention to buy a Computron calculator. This contrasts with the mostly positive beliefs associated with the Computron product and thus provides support for hypothesis two.

Ordinary least squares analysis supplies evidence to support hypotheses 3, 4, and S as shown in Exhibit 5. Hypothesis 5, which relates familiarity with attitude, is not supported. In order to investigate hypotheses 3-5, attitude is broken into its two components as defined here--beliefs and values. Thus, three separate analyses are performed. In the first instance, beliefs about the brand is the dependent variable; in the second instance, importance of brand attributes is the dependent variable; and in the third instance, attitude is the dependent variable. In all 3 instances, the independent variables are interest, number of purchases, experience, and familiarity. Ordinary least squares regression, using standardized coefficients, is the method of analysis.





On first examination, it may seem that multicollinearity may be a problem. The independent variables seem, conceptually, to be highly associated with one another. The main problem associated with multicollinearity is that an independent variable may not share enough unique variance with the dependent variable in order to assess the true impact of the independent variable on the dependent variable. In this particular case, however, the conceptual association between the independent variables does not appear to be a problem. Product experience and number of purchases are significant (p < .05) in all 3 regression equations represented in Exhibit 5. Product interest is significant (p < .05) in two out of the three equations. Familiarity is not significant in any of the regression equations; but this is due to low correlations between familiarity and the 3 criterion variables - not due to a multicollinearity problem.

Notice that the amount of variance explained by the regression equations in Exhibit 5 is fairly substantial. For the criterion variables initial attitude, attribute importance, and brand rating the R2 values equal .273, .419, and .210 respectively. In accordance with the Howard-Sheth model (1969), prior experience within a product class seems to explain a substantial amount of the variance associated with attitude formation. Not only are 3 of the predictor variables investigated here (interest, number of purchases, and experience) effective as a group, but the individual effect of each variable can be sorted out as indicated by the significance levels in Exhibit 5.




Evidence is found which supports the hierarchical model for high involvement products (Lastovicka and Gardner 1978). These findings are also consistent with some of the corollaries of the Howard-Sheth model (1969) concerning extensive problem solving and limited problem solving. In addition, the findings reported here support Bagozzi's (1981) notion concerning the true relationship between prior experience and attitude towards the act.

The naming of a product is a difficult task. Others have pointed out that a new product name should be short, easy to pronounce, potentially memorable; and it should maximize product positioning (K. Feakins 1980). In brief, a new product name should be able to communicate messages that are important to consumers (William R. Doyle 1978). But in addition to this, the naming of a product can have immediate attitudinal implications. Based on a product name alone, customers form instant, non-neutral attitudes about the product that can prove difficult to change through the use of subsequent communications.

For behavioral researchers, the results of this investigation have interesting ramifications. When investigating advertising effects, for example, it seems imperative that attitude be measured before and after exposure to the advertising message. With respect to behavioral intentions, however, such before and after measures may not be necessary when a new product is under investigation. For all practical purposes, prior behavioral intentions are at or near the zero level. The same cannot be said with respect to prior attitude toward a new product.

Future research should examine a wide range of products and should investigate other sections of the hierarchical model. Low involvement products, especially, could be investigated. Or, to speak in the language of the Howard-Sheth model, routine response behavior needs to be investigated. The hierarchy of effects model of communication has come under some recent criticism (Palda 1966; Mindak 1956), but it still holds the promise of providing valuable insights into the nature of consumer behavior


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George M. Zinkhan, University of Michigan
Claude R. Martin, Jr., University of Michigan


NA - Advances in Consumer Research Volume 09 | 1982

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