Noncognitive Effects on Attitude Formation and Change: Fact or Artifact?

JOURNAL OF CONSUMER PSYCHOLOGY, 4(2), 181 -202 Copyright O 1995, Lawrence Erlbaum Associates, Inc.

PERSPECTIVES AND COMMENTARY

Noncognitive Effects on Attitude Formation and Change: Fact or Artifact? Martin Fishbein University of Illinois at Champaign- Urbana

Susan Middlestadt Academy for Educational Development

Throughout the 1960s and 1970s, there was widespread acceptance of beliefbased models of attitude formation and change. Beginning in the 1980s, a npmber of theories, models, and approaches began to argue for nonbelief-based determinants and to reject the notion of a purely cognitive, expectancy-value or multiattribute basis for attitude. In this article, we empirically demonstrate that many findings that appear to support this latter view may be nothing more than methodological artifacts resulting from the use of inappropriate (i.e., theoretically incorrect, noncorrespondent, or invalid) attitudinal predictors andlor criteria.

Throughout the 1960s and 1970s, the dominant explanations of attitude formation and change were based on cognitive factors. Generally speaking, there was wide acceptance of belief-based models, including numerous versions of expectancy-value and multiattribute utility models. Although there are some important differences among these models (see, e.g., Wilkie & Pessemier, 1973), they all tend to view attitudes as a function of beliefs and the values or utilities associated with those beliefs. For ease of presentation, we focus on one of these models-Fishbein's (1963) expectancy-valuemodel. According to this model, an individual's attitude toward some object is viewed as a function of Requests for reprints should be sent to Martin Fishbein, Department of Psychology, 603 E. Daniel Street, Champaign, IL 61820.

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his or her beliefs about the object (i.e., beliefs linking the object to various characteristics, qualities, and attributes) and the evaluative aspects of those beliefs (i.e., evaluations of those characteristics, qualities, and attributes). Consistent with this viewpoint, it is assumed that changing an attitude toward some object requires a change in this underlying cognitive structure, that is, in one's beliefs about the object and/or in the evaluative aspects of these beliefs. For a review of this literature, see Fishbein and Ajzen (1975) and Ajzen and Fishbein (1980). In the 1980s, belief-based views of attitude formation and change were challenged. As Chaiken and Stangor (1987) pointed out, it became fashionable to distinguish two types of persuasion, one emphasizing and the other deemphasizing detailed cognitive processing. For example, according to Petty and Cacioppo (1981), there are two distinct routes to attitude change: a central route that "emphasizes the information that a person has about the attitude object or issue under consideration" and a peripheral route in which attitude change occurs "without any active thinking about the attributes of the issue or object under consideration" (pp. 255-256). Central processing involves comprehending and learning the arguments in a persuasive message, the generation of cognitive responses while listening to the message, and the combination or integration of this (and other) information into an attitudinal judgment. In contrast, peripheral processing focuses on the rewards or punishments associated with a message and the attractiveness or credibility of the source. The peripheral route also refers to simple affective mechanisms of attitude change, such as classical or operant conditioning. Chaiken (1980, 1987) also differentiated two routes to persuasion which she termed systematic and heuristic processing. Systematic processing is virtually identical to Petty and Cacioppo's (1981) central processing. Heuristic processing, however, is different from peripheral processing. Heuristic processing refers to persuasion that is mediated by simple decision rules, such as "length implies strength," "expert's statements can be trusted," or "consensus implies correctness." Stated in another way, without really absorbing the semantic content of persuasive argumentation or engaging in cognitive elaboration, people may agree more with messages containing many (versus few) arguments, with expert (versus inexpert) communicators, with messages that most (versus few) agree with and so on. (Chaiken & Stangor, 1987, p. 599)

In addition to these theoretical approaches that distinguish two paths to persuasion, one thoughtful and one thoughtfree, there are a number of researchers who postulated a variety of "cognition-free" processes of attitude formation and change. For example, Zajonc (1980,1984) argued for the effects of mere exposure and the primacy of affective responses. Similarly, Abelson,

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Kinder, Peters, and Fiske (1982) claimed that episodic emotional responses to political candidates can account for unique variance in attitudes toward those candidates. Moreover, they argued that these emotional responses surpass semantic beliefs about the candidate as predictors of attitude toward the candidate. Within research on consumer behavior and advertising, Gorn (1982) presented data suggesting a noncognitive transfer of affect via classical conditioning. In addition, several investigators have proposed that attitudes toward advertisements influence brand attitudes without affecting beliefs about the brand or the evaluative aspects of these beliefs (see Brown & Stayman, 1992, for a review and meta-analysis of this literature). What all of these theories, models, or approaches have in common is their rejection of a purely cognitive, expectancy-value basis for attitude. More specifically, there seems to be a growing consensus that factors other than beliefs and their evaluative aspects can make significant and unique contributions to attitude formation and change (see, e.g., Cohen & Areni, 1991; Eagly & Chaiken, 1993; Petty, Unnava, & Strathman, 1991). This is illustrated in Figure 1 which uses exposure to a message as the independent variable. The solid line in this figure represents the traditional cognitive path from exposure to a message (through the mediating variable of cognitive structure operationalized by an expectancy-value model) to change in attitude. At issue here is the question: How do other factors influence attitude? How do a variety of nonr

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FIGURE 1 Paths to attitude change

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cognitive factors, such as peripheral cues, cognitive heuristics, emotional reactions, affective responses, classically conditioned reactions, and attitudes toward messages, exert their influence on attitude? Do these other factors influence attitude only indirectly, through their impact on the cognitive structure, or, as a number of investigators (e.g., Brown & Stayman, 1992; Cohen & Areni, 1991; Petty et al., 1991) argued, is there evidence for a direct link between these other factors and attitude change? In other words, is there evidence for a direct link between other noncognitive factors and attitude change as represented by the dotted line in Figure l? In this article, we examine direct, nonbelief-based determinants of attitude formation and change. First, we discuss a number of conceptual and empirical issues that must be taken into account in any attempt to distinguish between cognitive and noncognitive bases for attitude. Then, we argue that there is little evidence for direct, nonbelief-based effects on attitude when appropriate measures of the underlying cognitive structure are obtained. More specifically, we argue that findings indicating that variables other than beliefs and their evaluative aspects contribute to attitude formation and change can best be viewed as methodological artifacts resulting from the use of inappropriate predictors and 1or criteria. The basic premise and fundamental hypothesis of this article can be stated as follows: When a cognitive variable is an appropriate predictor of a given criterion, this predictor will account for most of the variance in the criterion. Noncognitive variables or other factors will explain little, if any, variance in the criterion. In contrast, if the cognitive predictor is inappropriate, it will account for relatively little of the variance in the criterion; thus, other factors will be able to make an independent, direct contribution to the prediction of the criterion variable over and above the cognitive predictor. Here we discuss three types of problems that can lead to inappropriate cognitive predictors: (a) The predictor may not be the theoretically correct, immediate antecedent of the criterion; (b) the predictor may not correspond (in terms of action, target, context, and time) to the criterion; and (c) the predictor may not be a valid (i.e., theoretically consistent) expectancy-value measure of the cognitive structure underlying an attitudinal criterion.

USING THE THEORETICALLY CORRECT PREDICTOR

As Fishbein and Ajzen (1972, 1975) pointed out, the term attitude has often been used in a general way to refer to beliefs, attitudes, intentions, and behavior. Unfortunately, such a broad use of the term fails to recognize that these four concepts are conceptually and operationally distinguishable from one another. Perhaps even more important, this viewpoint also fails to recognize that these four concepts have theoretically different determinants. Generally

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speaking, behavior is determined by intentions, intentions are determined by attitudes (toward behaviors) and subjective norms, and attitudes are determined by beliefs and their evaluative aspects. Thus, if one is attempting to predict behavior, the most appropriate predictor would be a measure of the person's intention to perform that behavior. Similarly, if one is attempting to predict an intention to perform some behavior, the theoretically correct predictor would be one that included both the attitude toward performing that behavior and the subjective norm concerning that behavior. Thus, using an expectancy-value measure of an underlying cognitive structure to predict intention or behavior would be theoretically incorrect and would lead to a situation in which other factors would appear to contribute to the prediction of intention or behavior. Indeed, the only correct criterion for an expectancyvalue measure of the underlying cognitive structure is a measure of attitude.

ESTABLISHING CORRESPONDENCE BETWEEN PREDICTORS AND CRITERIA

Even when one assesses a theoretically correct predictor, however, the predictor can still be inappropriate. That is, the notion of appropriateness goes beyond merely assessing the theoretically correct determinant of the criterion variable. In addition, there must be correspondence between the predictor and the criterion. As Fishbein and Ajzen (1974) pointed out, there are four elements that define any given behavioral predictor or criterion: target, action, context, and time. Correspondence between a predictor and criterion requires equivalence in all four elements. Thus, if one observes whether shoppers buy Crest toothpaste in the A&P between 8:00 A.M. and 5:00 P.M. on June 6th, the only intention that corresponds exactly to this behavioral observation is a person's intention to "buy Crest toothpaste in the A&P between 8:00 A.M. and 5:00 P.M. on June 6th." Contrarily, if respondents are going to be asked 1 week from now whether they had "bought Crest toothpaste in the past 7 days," the corresponding intentional predictor would be their intention to "buy Crest toothpaste in the next 7 days." Just as intentions and behavioral criteria must correspond, so too must intentions and attitudes and attitudes and beliefs. Thus, for example, if one were interested in predicting male students' intentions to use a condom the next time they have sex with a casual partner, one would have to assess their attitudes toward "my using a condom the next time I have sex with a casual partner," not their attitudes toward "condoms," "using condoms," or even towards "my using a condom the next time I have sex." Similarly, if one wished to predict attitudes toward "my always using a condom with my long-term partner," one would have to assess beliefs about "my always using a condom with my long term partner," not beliefs about "condoms" or "using con-

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doms." However, assessing beliefs about "condoms" would be appropriate if one were trying to predict attitudes toward "condoms." In other words, if one is attempting to predict an attitude toward an object, the appropriate predictor will be based on beliefs about the attributes of that object. In contrast, if one is trying to predict an attitude toward a behavior, one should be assessing beliefs about the consequences of performing that behavior.

OBTAINING VALID EXPECTANCY-VALUE MEASURES According to Fishbein's (1963) expectancy-value theory, a person's attitude toward a given object (or behavior) is a function of his or her salient beliefs about that object (or behavior) and the evaluative aspect of those beliefs. Thus, to arrive at a valid expectancy-value measure of the evaluative implications of an underlying cognitive structure, one must (a) identify the salient attributes (or outcomes) associated with the attitude object (or behavior), (b) assess the strength of one's beliefs that the attributes (or outcomes) are associated with the object (or behavior), (c) assess the evaluation of the attributes (or outcomes), and then (d) create a sum of the products formed by multiplying the strength of each belief by its evaluative aspect. There are at least three ways in which one can arrive at an invalid (and, hence, inappropriate) expectancy-value measure of the underlying cognitive structure. It can be (a) based on something other than a full set of salient attributes, qualities, characteristics, andlor outcomes; (b) based on measures of constructs that are not beliefs andlor their evaluative aspects; and (c) calculated using incorrect scoring andlor using an incorrect combination rule. Identifying Modal Salient Sets of Attributes or Outcomes Standard procedures have been developed for identifying modal salient attributes or outcomes associated with an attitude object or behavior (see Ajzen & Fishbein, 1980). Most important, one cannot simply assume one knows what attributes or outcomes are salient in a given population. One must go to a representative sample of that population in order to identify the modal salient set. Thus, for example, if one were interested in predicting or understanding voters' attitudes toward a candidate, for example, Bill Clinton, one should go to a sample of voters and ask them to describe Bill Clinton. More specifically, this sample should be asked to list what they believe to be the characteristics, qualities, and attributes of Bill Clinton, including such things as his reference group affiliations and his stands on various issues. Similarly, if one were interested in predicting the voters' attitudes toward the behavior of voting for Bill Clinton, the sample should be asked to list what they see as advantages, disadvantages, and other consequences associated with voting for Bill Clinton.

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A content analysis and count of these open-ended responses allows one to identify the modal salient set. More specifically, the set is comprised of those attributes or outcomes that are mentioned most frequently by the population being considered. One rule of thumb is to include all attributes or outcomes mentioned by at least 10% of the sample. Unfortunately, investigators do not always elicit a modal salient set of attributes or outcomes. All too often, investigators rely on their own intuition or knowledge, and they simply make up a set of attributes or outcomes that they believe are relevant for the attitude object under consideration. It is our contention that this practice often leads to invalid expectancy-value measures of the evaluative implications of the underlying cognitive structure. Such arbitrary lists of attributes or outcomes often overlook important salient aspects, and/or they include a number of nonsalient ones. Assessing Beliefs and their Evaluative Aspects Once the set of modal salient attributes or outcomes has been identified, it is necessary to assess (a) the strength of a person's beliefs linking the attitude object (or behavior) to each salient attribute (or outcome) and (b) the person's evaluation of each of the attributes (or outcomes). Typically, in research based on Fishbein's (1963) expectancy-value model, belief strength is measured on a 7-point scale ranging from likely ( + 3) to unlikely ( - 3) and the evaluative aspect is measured on a 7-point scale ranging from good ( + 3) to bad ( - 3). Unfortunately, other variables have sometimes been measured in place of beliefs and/or their evaluative aspects. For example, measures of adequacy have been substituted for belief strength, and measures of attribute importance have been substituted for measures of the evaluative aspects (for a more complete discussion see, e.g., Cohen, Fishbein, & Ahtola, 1972; Fishbein & Ajzen, 1975). Clearly, when one substitutes other variables for either belief strength or evaluation, the obtained measures of the underlying cognitive structure do not constitute valid expectancy-value measures. Using Bipolar Versus Unipolar Scoring Note that the psychology of the double negative is an essential part of an expectancy-value formulation (Ajzen & Fishbein, 1980; Fishbein, 1967; Fishbein & Ajzen, 1975). From the perspective of an expectancy-value theory, and consistent with Heider's (1958) balance theory, believing that an object does not have a negative characteristic or that performing a behavior will prevent a negative outcome should contribute positively (rather than negatively) to the attitude toward that object or behavior. For example, if a student does not believe (i.e., if he or she disbelieves) that "my professor is a capricious grader," this belief should, according to an expectancy-value formulation, contribute

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positively (not negatively) to his or her attitude toward "my professor." Similarly, if a person does not believe that "my wearing a seat belt will increase my chance of injury," this should make the person feel more (rather than less) favorable toward wearing a seat belt. Thus, for an expectancy-value estimate of attitude to be valid (or theoretically consistent), both beliefs and their evaluative aspects must be scored on bipolar (e.g., + 3 to - 3) scales. Use of unipolar scales and/or scoring will often lead to invalid estimates of the evaluative implications of an underlying cognitive structure. In sum, there are a number of reasons why a given belief-based or cognitive measure may be an inappropriate predictor of some criterion. Here, we outline three types of problems: The predictor may not be the theoretically correct determinant of the criterion; it may not correspond to the criterion in target, action, context, and time; and it may not be a valid expectancy-value measure of the evaluative implications of the underlying cognitive structure. As indicated, we argue that support for a direct link between nonbelief-based factors and attitude occurs only when either the predictor or criterion is inappropriate. Indeed, when valid expectancy-valuemeasures are used to predict theoretically correct and correspondent measures of attitude, there is considerable evidence that belief-based expectancy-value measures account for a significant and substantial amount of variance in that attitude (Fishbein & Ajzen, 1972, 1975). If the predictors are appropriate to the criteria, we hypothesize that the variance explained by other noncognitive factors will disappear or be greatly reduced.

METHOD

In the remainder of this article, we present data to support the hypotheses just outlined. The data come from studies conducted primarily to test various hypotheses based on the theory of reasoned action. Two data sets were obtained from an ongoing series of election studies (Fishbein, Middlestadt, & Chung, 1985; Ottati, Fishbein, & Middlestadt, 1988); the third data set was obtained as part of a study investigating the role of music in advertising (Middlestadt, Fishbein, & Chan, 1993). Before discussing specific results, we give a brief description of the method used for each study. The first data set was obtained in a study of the 1980 presidential election between Anderson, Carter, and Reagan. A more complete description of this study can be found in Fishbein et al. (1985). Briefly, an elicitation study was conducted with a sample of 18 students in order to identify the salient qualities, characteristics, and attributes of each of the three Presidential candidates, as well as the salient outcomes or consequences associated with voting for each of the candidates. Based on this elicitation, a fixed alternative questionnaire was developed and administered to an independent sample of 120 university

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students who were eligible to vote in the upcoming election. More specifically, each respondent was asked to indicate, on 7-point bipolar scales, their beliefs about each candidate, their beliefs about voting for each candidate, and their evaluations of each salient attribute of the candidates and of each consequence of voting for the candidates. Each belief was multiplied by its evaluative aspect, and by summing appropriate products, belief-based expectancy-value measures of the evaluative implications of the cognitive structure associated with each candidate (XBoEo) and of the cognitive structure associated with the behavior of voting for each candidate (XBbEb) were computed. Semantic differential measures were used to assess directly attitude toward each candidate (Ao) and attitude toward the behavior of voting for each candidate (Ab). Subjective norms (SN) vis-a-vis voting for each candidate and intentions to vote for each candidate (Ib) were also measured on 7-point semantic differential scales. One week after the election, respondents were called, and a selfreport of actual voting behavior (B) was obtained. During the 1980 election, there were two presidential debates (i.e., Anderson vs. Reagan and Carter vs. Reagan). Each respondent was asked to indicate whom they thought had won each debate. These responses were used to create trichotomous measures (win [ + 11, draw [O], and lose [ - 11) of each candidate's perceived debate performance (Debate). Analogous to a measure of one's attitude toward an ad, these perceptions of debate performance can be viewed as an "other factor" which may or may not have a direct causal influence on attitudes. The second data set was obtained in a study of the 1984 presidential election between Reagan and Mondale. The study is described in Ottati et al. (1988). As with 1980 study, a modal salient set of attributes and issues associated with each candidate were identified in a pilot elicitation study. Then, 2 weeks prior to the election, 140 voting age university students completed a lengthy questionnaire. The questionnaire included 7-point bipolar measures of the respondents' beliefs about each candidate and the evaluative aspects of those beliefs. By summing relevant belief and evaluation products, an expectancy-value measure based on the cognitive structure associated with each candidate was calculated. In addition to providing the data necessary to compute these belief-based measures, the students provided direct, semantic differential measures of their attitudes toward each candidate (Ao) as well as direct semantic differential measures of their attitudes toward paid political advertising on behalf of each candidate (Aad). The final data set was obtained from a study comparing the effectiveness of four television commercials designed to increase attitudes and intentions with respect to "drinking [brand name] apple juice" (Middlestadt et al., 1993). The announcer in the soundtrack linked drinking the brand of apple juice with three positive outcomes. Following exposure to one of the four versions of the commercial, 196 university students were asked to indicate on 7-point bipolar

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scales (a) the strength of their beliefs that "my drinking [brand name] apple juice" would lead to a number of consequences and (b) their evaluation of each consequence. As with the two election studies, the outcomes rated by the respondents were the modal salient consequences of drinking the brand of apple juice identified in a pilot elicitation study. In addition to this salient set, the questionnaire assessed beliefs linking drinking the brand of apple juice to each of the message outcomes, that is, the three outcomes specified in the voice-over of the commercial. Finally, the students provided semantic differential measures of their attitudes toward the behavior of "drinking [brand name] apple juice" (Ab) as well as semantic differential measures of their attitudes toward the advertisement (Aad) they had just seen.

RESULTS AND DISCUSSION

The basic hypothesis of this article is that the contribution of factors other than belief-based expectancy-value measures to the prediction of attitude can be seen as a methodological artifact of using inappropriate measures. That is, if inappropriate predictors are used, other factors may contribute. However, if valid measures of theoretically correct and correspondent cognitive predictors are used, the variance explained by the cognitive predictor (e.g., an expectancyvalue measure) will be large and that of other factors will be small. We illustrate this by reanalyzing data from the three studiesjust described. In each case, we first show results when other factors appear to contribute to the prediction of the criterion. Then, we show how this contribution disappears when appropriate measures are used. A Comparison of Appropriate to Inappropriate Criteria

One way of illustrating the artifactual nature of the contribution of other noncognitive factors is to choose a predictor and compare results obtained using inappropriate criteria to those obtained with the appropriate one. Using data from the 1980 election study, we focus on one predictor-the evaluative implications of the cognitive structure underlying the attitude toward the object-here, a presidential candidate (ZB,E,). The other factor is the perception of whether the candidate won or lost a presidential debate (Debate). As just discussed, given an expectancy-value predictor variable based on modal salient attributes of the candidate (i.e., one based on beliefs about the candidate's personal characteristics, his group affiliations, and his stands on various domestic and foreign issues), the only appropriate criterion would be a valid measure of the person's attitude toward the candidate (Ao). Thus, if our hypothesis is correct, although factors other than the expectancy-value based measure of the evaluative implications of the underlying cognitive structure

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with respect to the candidate may contribute to the prediction of inappropriate attitudinal criteria (e.g., attitude toward the behavior of voting for the candidate [Ab], the intention to vote for the candidate [Ib], or actual voting behavior [B]), these other factors should not contribute to the prediction of the appropriate criterion, here a direct measure of attitude toward the candidate [Ao]. Table 1 provides strong support for our central hypothesis. Column 1 presents the zero-order correlations between the expectancy-value measure of the evaluative implications of the cognitive structure underlying the object, John Anderson, (CB,E,) and each of four criteria: the direct measure of attitude toward John Anderson (Ao), a direct measure of the attitude toward voting for John Anderson (Ab), a measure of the behavioral intention to vote for John Anderson (Ib), and the respondent's self-report of whether he did or did not vote for John Anderson (B). Note that consistent with expectations, although the expectancy-value measure with respect to John Anderson was significantly related to all four criteria, it best predicts Ao, the direct measure of attitude toward John Anderson (r = .68, p < .001). Column 2 of Table 1 presents the zero-order correlations between each criterion and the trichotomous measure of the students' perception of how well Anderson did in his debate with Reagan (debate). Not surprising, the more one perceived that Anderson won the debate, the more one liked Anderson (r with Ao = .35,p < .01); the more favorable was one's attitude toward voting for him (r with Ab = .36, p < .01); the stronger was one's intention to vote for him (r with Ib = .48, p < .01); and the more likely was one to have actually voted for him (r with B = .53,p < .01). The critical question, however, is whether the perception of Anderson's debate performance contributes to the prediction of each criterion over and above the prediction based solely on the TABLE 1 Influence of Perception of Debate Performance in Predicting One Appropriate (Ao) and Three Inappropriate (Ab, Ib, and B) Criteria From the Cognitive Structure Underlying Attitude Toward Anderson (ZB,E,) Correlations*

Beta Weights Multiple

Criteria

Attitude toward object (Ao) Anderson Attitude toward behavior (Ab) Voting for Anderson Intention to behave (Ib) Intend to vote for Anderson Self-reported behavior (B) Voted for Anderson

ZBoEo

Debate

ZBoEo

Debate

R

.68

.35

.63*

.14

.69

.56

.36

.49*

.20*

.59

.60

.48

.SO*

.32*

.67

.50

.53

.32*

.38*

.60

*All zero-order and multiple correlations are statistically significant at or beyond the .05 level. Indications of significance @ < .05) are presented only for beta weights.

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belief-based expectancy-value measure. To test this hypothesis, each criterion was regressed on the two predictor variables. The standardized regression weights are presented in Columns 3 and 4. Column 4 shows that, consistent with expectations, the perception of Anderson's debate performance does make a significant, independent contribution to the prediction of the three inappropriate criteria (Ab, Ib, and B) but does not contribute to the prediction of the appropriate criterion (Ao).'

A Comparison of Appropriate to Inappropriate Predictors

At this point, we can ask whether the significant contribution (shown in Table 1) of the perceived debate performance to the prediction of the last three criteria (Ab, Ib, and B) is real or whether it is only an artifact resulting from the use of an inappropriate predictor. According to our hypothesis, the significant contribution of Anderson's debate performance to the prediction of each of these criteria should be eliminated if one were to use appropriate predictor variables. Thus, for example, if one used an expectancy-value measure based on beliefs about voting for Anderson (CBbEb) rather than on beliefs about Anderson per se to predict attitude toward voting for Anderson, one should find that the perception of Anderson's debate performance no longer makes an independent contribution to the prediction of this attitude. Support for the artifactual nature of the direct contribution of perceived debate performance can be found by the representative results presented in Table 2. Panel A compares appropriate and inappropriate predictors of the criterion, attitude toward the behavior of voting for the candidate (Ab), here Anderson; Panel B compares appropriate and inappropriate predictors of intention to vote for the candidate (Ib), in this case, Carter; and Panel C examines appropriate and inappropriate predictors of the criterion, behavior of voting for the candidate (B), in this example, Reagan.2 First, consider Panel A. For ease of presentation and comparison, the first row in Panel A simply reproduces the second row of Table 1. Thus, it can again be seen that, when the prediction of attitude toward voting for Anderson (Ab) was based on an inappropriate expectancy-value measure (CBoEo) of the cognitive structure underlying the attitude toward Anderson per se, the perception of Anderson's performance in the debate did, in fact, contribute significantly (P = .20, p < .05) to predicting Ab. However, as can be seen in the bottom row of Panel A, when an appropriate expectancy-value measure based 'Analyses with respect to the two other candidates, Carter and Reagan, produced similar results. Some of these data are presented next. lData for Carter and Reagan are presented to demonstrate the generalizability of our findings across candidates. Again, analyses with respect to the two candidates not reported in each panel produce similar results.

--L

0

a

Cognitive Predictor Debate

Cognitive Predictor Debate

Beta Weights

ZBoEo

Debate

ZBoEo

Debate

Beta Weights

ZBoEo

Debate

ZBoEo

.87

.08

*All zero-order and multiple correlations are statistically significant at or beyond the .05 level. Indications of significance @ < .05) are presented only for beta weights.

.59

Multiple R

.75

.61

Multiole R

.71

.59

Multiple R

.23*

Debate

Beta Weights

Panel C: Predicting the Behavior of Voting for Reagan (B) From Inappropriate (ZBoEo)and Appropriate (Ib) Predictors Debate plus expectancy-value measure based on beliefs about the candidate ZBoEo .41 ZBoEo .64 .57* (zBoEo) Debate plus intention to vote for candidate (Ib) IB 1B .87 .41 .84*

Predictors

Correlations

Panel B: Predicting Intention to Vote for Carter (Ib) From Inappropriate (ZBoEo)and Appropriate (Ab and SN) Predictors Debate plus expectancy-value measure based on beliefs about the candidate ZBoEo .34 Z B ~ E ~ .22* .57 .52* (zBoEo) Debate plus attitude toward behavior (Ab) and subjective norm (SN) Ab SN Ab SN .74 .55 .34 .61* .17* .07

Predictors

Correlations

Panel A: Predicting the Attitude Toward the Behavior of Voting for Anderson (Ab) From Inappropriate (ZBoEo)and Appropriate (ZBbEJ Predictors Debate plus expectancy-value measure based on beliefs about the candidate ZBoEo .36 ZBoEo .20* (zBoEo) .56 .49* Debate plus expectancy-value measure based on beliefs about voting for the ZBBEB .36 ZBoEo .09 .71 .67* candidate (ZBbEb)

Predictors

Correlations*

TABLE 2 Influence of Perception of Debate Performance in Predicting Attitudinal Criteria

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on beliefs about voting for Anderson (ZBbEb)is substituted for the inappropriate measure, not only is the zero-order correlation between the expectancyvalue formulation and the direct measure of the attitude toward voting for Anderson greatly improved (r increases from .56 to .71) but, more important, the apparent contribution of Anderson's debate performance disappears completely (P = .09, ns). Thus, as expected, the apparent direct, independent contribution of this other factor (i.e., Debate) is illusory rather than real; its contribution to the prediction of attitude toward voting for John Anderson is best viewed as an artifact rather than as a fact. Next, consider Panel B, which examines intention to vote as the criterion (Ib). Again, the top row of Panel B is similar to Row 3 of Table 1. Here, however, the data presented are vis-a-vis Carter, rather than Anderson. Similar to the findings with respect to Anderson, when beliefs about Carter are used to compute an expectancy-value measure of the evaluative implications of the underlying cognitive structure vis-a-vis Carter (CB, E,), this measure, although inappropriate, does lead to a fairly accurate prediction of the intention to vote for Carter (r = .57, df = 118,p < .01). In addition, the perception of whether Carter won or lost his debate with Reagan, was significantly related to the intention to vote for Carter (r = .34, p < .01). More important, we can again see that, when the intention is regressed on both of these predictors, the perception of Carter's debate performance makes an independent and significant contribution to the prediction of the intention to vote for Carter (P = .22,p < .05). However, when the prediction of intention is based on appropriate measures of Ab and SN vis-a-vis voting for Carter, the prediction of the intention to vote for Carter improves (R increases from .61 to .75) and, more important, the contribution of Carter's perceived debate performance is reduced to nonsignificance (P = .07). Finally, the data in the first row of Panel C are analogous to the data in the last row of Table 1. Here we are concerned with predicting the respondents' self-reported behavior (B), in this case, whether or not they voted for Reagan. The other factor is the perception that Reagan won or lost his debate with Carter. Once again, we can see that the apparent contribution of Reagan's perceived debate performance to the prediction of voting behavior disappears completely when the prediction of whether or not one voted for Reagan is based on an appropriate predictor. That is, the other factor (i.e., Debate) contributes significantly only when an inappropriate predictor (i.e., the expectancy-value measure of the cognitive structure underlying the candidate, Reagan, [CB,E,]) is used, but Debate makes no contribution when the appropriate predictor, the intention to vote for Reagan, (Ib), is used. The Use of Invalid Expectancy-Value Measures The data just reviewed support the hypothesis that the use of inappropriate predictors (i.e., predictors that are either theoretically incorrect or noncorrespondent) can lead to the illusion that other factors contribute independently

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to the prediction of an attitudinal criterion. According to our analysis, we expect that the same illusion will appear if the expectancy-valuemeasure of the underlying cognitive structure is incomplete or otherwise invalid. That is, as already discussed, basing an expectancy-value measure on some arbitrary or incomplete set of attributes or outcomes, rather than on the complete modal salient set, will often result in a situation where the expectancy-value measure accounts for only a small percentage of the variance in an appropriate attitudinal criterion. This can create the illusion that some other factor is contributing independently to the prediction of attitude over and above the measure of underlying cognitive structure. Similarly, computing the expectancy-value measure incorrectly by, for example, using unipolar rather than bipolar scoring of beliefs and/or their evaluative aspects, may also lead to the illusion that other factors are contributing independently to the prediction of a corresponding attitude. To test these hypotheses, we reanalyzed data from (a) a study of the 1984 Presidential election and (b) a study of the effect of music in advertising. In the election study, attitudes toward Mondale and Reagan, (Ao), the Presidential candidates, were selected as criteria. In the music study, the attitude toward the behavior of "drinking [brand name] apple juice" (Ab) was selected as the criterion. In both of these studies, we were concerned with exploring the effects of attitudes toward ads as other noncognitive factors. Within the consumer behavior literature, the attitude toward the ad is frequently used to capture affective, noncognitive change processes (Brown & Stayman, 1992; Cohen & Areni, 1991). Presumably, the attitude toward the ad is directly transferred to the candidate or the brand advertised. Again, the key question concerns the evidence for a direct link (i.e., one that is not mediated by changes in an underlying cognitive structure) between attitude toward the ad and attitude toward the advertised product. Incomplete and incorrectly scored expectancy-value measures about candidates. Data obtained as part of the study of the 1984 Presidential

election were used to compute valid expectancy-value measures (ZB, E,) for Mondale and Reagan. More specifically, the appropriate products of bipolar belief and evaluation items were summed across the complete modal salient set of attributes. In addition, three invalid expectancy-value measures were computed from the same belief and evaluation items. Two of these invalid measures were based on subsets of the attributes rather than on the full set of salient attributes. One measure included only the belief and evaluation products for the candidate's personal characteristics (CB,Ep); e.g., he is intelligent, a strong leader, a moderate, a Republican); the other was based only on beliefs about the candidate's stands on issues (CBiEi); e.g., he is in favor of increased welfare spending, he is opposed to increased military spending, he is in favor of increased spending for education). The third invalid measure used the complete set of salient attributes but an incorrect scoring system (CBo,Eo).

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TABLE 3 Influence of Attitudes Toward Paid Political Advertising (Aad) in Predicting Attitude Toward Mondale (Ao): A Comparison of Appropriate (ZB,E,) to Three Inappropriate Predictors Correlations*

Beta Weights Multiple R

Predictors

ZBE

Aad

ZBE

Aad

Attitude to advertising plus expectancy-value measure complete set scored correctly (ZB,EJ Attitude to advertising plus expectancy-value measure complete set unipolar scoring ("B,"E,) Attitude to advertising plus expectancy-value measure only personal characteristics (ZBpE$ Attitude to advertising plus expectancy-value measure only issue attributes (ZB,E,)

.68

.42

.62*

.10

.68

.56

.42

.46*

.24*

.60

.68

.42

.61*

.17*

.70

.50

.42

.39*

.25*

.55

*All zero-order and multiple correlations are statistically significant at or beyond the .05 level. Indications of significance @ < .05) are presented only for beta weights.

That is, the belief component of each product was scored incorrectly as a unipolar scale (ranging from extremely unlikely [l] to extremely likely [7]) rather than correctly as a bipolar scale. The appropriate (CB,E,) and the three inappropriate (CB,, E, , CB, E, , and XBiEi) measures were used to predict direct, semantic differential measures of attitude toward each candidate (Ao). Semantic differential measures of attitudes toward "paid political advertising on behalf o f ' Reagan and Mondale (Aad) were used to assess other noncognitive factors. Table 3 provides support for the central hypotheses of this article with respect to attitudes toward Mondale. Although not shown, very similar findings were obtained with respect to Reagan. Consistent with expectations, the expectancy-value measure using bipolar scoring (ZB, E,) was more highly correlated with attitude (r = .68 vs. r = .56) than was the measure based on unipolar scoring (CB0,E0).3 In addition, the expectancy-value measure based on the full set of salient attributes predicted the attitude toward Mondale better (r = .68 vs. r = SO) than did the one based on the issue subset (ZBiEi). 'Note that such differences due to scoring will only occur when at least some evaluative aspects take on negative values. More specifically, when all evaluative aspects are positive, ZB,E, and ZB,, E, will correlate perfectly. The political domain is particularly appropriate for demonstrating the effect of scoring differences because voters disagree strongly in their evaluation of issues.

NONCOGNITIVE EFFECTS: FACT OR ARTIFACT?

197

Somewhat surprising, the expectancy-value measure based solely on beliefs about Mondale's personal characteristics (CB,E,) predicted attitude toward Mondale as well as the measure based on the entire set of salient attributes (r = .68 in both case^).^ In addition to the strong correlations between the belief-based expectancyvalue measures and attitudes, Table 3 shows the strong and statistically significant correlation between one's attitude toward Mondale and one's attitude toward "paid political advertisements on behalf of Mondale" (r = .42, p < .001). Although such a correlation could be taken as evidence that at least some of one's attitude toward the ad was transferred to Mondale, it could just as well be viewed as an indication that the more one liked Mondale, the more one liked Mondale ads. The standardized regression weights in Table 3 suggest that the latter interpretation is more likely to be correct. That is, consistent with expectations, it can be seen in Column 4 that the apparent support for a direct effect of Aad on Ao is only obtained when inappropriate, invalid expectancy-value measures (i.e., XB,, E,, CB, E,, and CBiEi) are used as a predictors. For example, when the expectancy-value measure is based on unipolar scoring of the belief component (CBouEo),it appears that the attitude toward Mondale advertising (Aad) has a direct influence on the attitude toward Mondale (P = .24, p < .05). However, when the appropriate expectancy-value measure (CB, E,) is considered, this apparent effect is virtually eliminated (P = .lo, ns): Finally, Table 3 shows that the concept of appropriateness does not simply mean that one should use a belief-based measure that accounts for the most variance in the attitudinal criterion. Recall that the inappropriate expectancyvalue measure based on beliefs about Mondale's personal characteristics (CBpEp)accounted for the same amount of variance in the attitudinal criterion as did the appropriate measure based on the complete salient set (CBoEo). If variance accounted for by the expectancy-value predictor were the main factor determining the potential influence of some other variable on the attitudinal criterion, one would expect that the contribution of Aad to Ao would be about equal in these two cases. However, given that Aad is correlated with the criterion (Ao), it should have more variance in common with an appropriate (XB,E,) than with an inappropriate (CBpEP)measure of the cognitive structure underlying Ao. Thus, the other factor should have a smaller independent effect on the criterion when it is paired with an appropriate than with an inappropriate cognitive predictor. Consistent with our basic hypothesis, it is 'Note that the reverse was true with respect to Reagan. That is, the expectancy-value measure based solely on Reagan's stands on the issues led to better prediction of the attitude toward Reagan (r = .64) than did the measure based solely on Reagan's personal characteristics (r = .56), and both of these measures were somewhat lower than the expectancy-value measure based on the full set of salient attributes (r = .69).

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only when the inappropriate expectancy-value measure (XBpEp)is used that the "other factor" (i.e., Aad) appears to have a direct, independent effect on Ao (p = .17, p < .05). Expectancy-value measures based on an arbitrary set. Although investigators rarely select only a subset of the items they have measured to compute an expectancy-value measure, they do, all too often, fail to identify and measure the set of attributes or outcome beliefs that are salient for a given population. That is, rather than carrying out a pilot elicitation study to identify the modal salient set in the population of interest, many investigators simply select relevant or important beliefs intuitively and/or on the basis of their knowledge of the attitude object. Unfortunately, such arbitrary expectancy-value measures are likely to be incomplete (i.e., they are based only on a subset of salient beliefs) and/or otherwise invalid (i.e., they are based on nonsalient beliefs). Another common error in computing expectancy-value measures of cognitive structures occurs in the context of communication and persuasion and/or advertising effectiveness studies. In this context, investigators have often assessed the effects of a message (or advertisement) only on those beliefs that are contained in the message (or ad) rather than on the entire set of beliefs underlying the attitude toward the object (or behavior) in question. Because it is quite likely that the belief statements in the message are, at best, only a subset of the full set of modal salient beliefs, the resultant expectancy-value measure is likely to be invalid. We would expect that, when such inappropriate measures are considered, one's attitude toward the message (or ad) will appear to have an independent effect on the attitude toward the object (or behavior). However, when an appropriate expectancy-value measure based on all modal salient beliefs is obtained, this apparent effect should be eliminated. Data in Table 4 supports this hypothesis. TABLE 4 Influence of Attitude Toward the Ad (Aad) in Predicting Attitude Toward Drinking [Brand Name] Apple Juice (Ab):A Comparison of Appropriate (XB,E,) to Inappropriate (ZBmEm) Predictors -

-

-

-

-

Beta Weights

Correlations*

Multiple R

Predictors

ZBE

Aad

ZBE

Aad

Attitude to ad plus expectancy-value measure salient set of outcomes (ZBbEb) Attitude to advertising plus expectancy-value measure outcomes in message (ZB,E,)

.66

.41

.59*

.15

.67

.20

.41

.ll

.39*

.43

*All zero-order and multiple correlations are statistically significant at or beyond the .05 level. Indications of significance (p < .05) are presented only for Beta weights.

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199

As already described, following exposure to one of four versions of a commercial for a brand of apple juice, respondents indicated belief strength and outcome evaluation with respect to the modal salient outcomes of "drinking [brand name] apple juice" as well as to the outcomes mentioned in the message. Two expectancy-value measures of the cognitive structure underlying the attitude toward "drinking [brand name] apple juice" were computed: One was based on the full modal salient set of outcomes (CBbEb) and the other solely on an arbitrary set, namely the outcomes mentioned in the message (XB,E,). As in the preceding political behavior study, these expectancy-value measures and the measure of the attitude toward the ad (Aad) were used to predict the direct semantic differential measure of the respondents' attitudes toward the behavior of "drinking [brand name] apple juice" (Ab). Note that, consistent with previous findings in the consumer behavior area, the two direct attitudinal measures (i.e., Ab and Aad) were significantly related. Not surprising, the more one liked the ad, the more positive was one's attitude toward drinking the brand of apple juice (r = .41, p < .01). More important, as can be seen in the second row of Table 4, when only beliefs contained in the message are used to assess the evaluative implications of the underlying cognitive structure, the relation between this arbitrary expectancyand Ab is relatively weak (r = .20). Further, when value measure (CB,E,) Ab is regressed on both this inappropriate, invalid expectancy-value measure and Aad, there appears to be strong support for an independent contribution of Aad on Ab (P = .39, p < .05). In marked contrast, an appropriate expectancy-value measure based on the full set of salient outcomes (XBbEb)leads to a vastly improved prediction of Ab (r = .66, p < .01). Furthermore, and consistent with our hypothesis, use of this appropriate measure in the regression analysis eliminates the apparent direct effect of Aad (P = .15, ns). Thus, once again, it has been possible to create the illusion of a nonbelief-based influence on attitude by using an inappropriate (i.e., invalid) measure of the underlying cognitive structure. However, we have also been able to show that this illusion does, in fact, vanish when an appropriate belief-based measure of the cognitive structure underlying the attitudinal criterion is utilized.

SUMMARY AND CONCLUSION

Throughout the 1960s and 1970s, there was wide acceptance of belief-based models of attitude formation and change. Generally speaking, most investigators accepted the notion that attitudes could best be viewed as a function of beliefs and the values or utilities associated with those beliefs. Beginning in the 1980s, a number of theories, models, and approaches began to reject the notion of a purely cognitive, expectancy-value, or multiattribute basis for attitude. More specifically, this newer viewpoint argued that factors other than beliefs

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and their evaluative aspects make significant and unique contributions to attitude formation and change. In this article, we showed how findings that appear to support such nonbelief based determinants of attitude and attitude change may often be nothing more than methodological artifacts resulting from the use of inappropriate predictors and/or criteria. That is, we showed how the use of theoretically incorrect, noncorrespondent, and/or invalid predictors can lead to findings indicating a direct link between other factors (e.g., attitudes toward an ad) and an attitudinal criterion. We have also tried to show that this apparent direct link disappears when appropriate (i.e., theoretically correct, correspondent, and valid) measures of the underlying cognitive structure are used. Clearly, our analyses and results do not demonstrate that all findings of direct links between nonbelief-based factors and attitudes are artifactual. However, a meta-analysis of the antecedents and consequences of attitude toward the ad (Brown & Stayman, 1992) provides additional support for our position. Brown and Stayrnan tested alternative structural models of the process through which attitudes towards ads are influenced by antecedent variables and, in turn, influence brand attitudes. Consistent with previous findings (e.g., Lutz, McKenzie, & Belch, 1983; McKenzie, Lutz, & Belch, 1986), Brown and Stayman obtained support for a dual mediation model that includes a direct path between attitude toward the ad and brand attitudes. However, as Brown and Stayman pointed out, "the brand cognition and brand attitude relationship is, as in most studies, the weakest in the model" [italics added] (p. 46). Indeed, the standardized path coefficient between brand cognitions and brand attitude was only .20. This low value for the relation between beliefs and attitude must be contrasted with the mean correlation of .53 reported by van den Putte (1991) in a meta-analysis based on 113 articles that provided estimates for 150 groups of respondents (see Eagly & Chaiken, 1993). From our perspective, the low correlations obtained in the studies considered by Brown and Stayman (1992) provide rather compelling evidence for the use of inappropriate expectancyvalue measures of brand cognitions. It is our contention that the dual-mediation model (with its direct path between ad attitude and brand attitude) would not have been supported had the brand cognition-brand attitude correlations reported in the studies reviewed by Brown and Stayman been of average value (i.e., around .5). At the very least, Brown and Stayman's (1992) findings, as well as the analyses reported in this article, strongly suggest that it may be premature to endorse fully nonbelief-based views of attitude. As demonstrated elsewhere (Middlestadt, 1990; Middlestadt et al., 1993), when the cognitive structure underlying a given attitude is appropriately measured, features of an advertisement that appear to contain no brand-relevant information (e.g., color and music) can be shown to influence attitudes toward both the brand per se and

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201

toward buying the brand in a straightforward belief-based manner. Indeed, it appears that belief-based processes are more pervasive than currently assumed, and they deserve both serious consideration and appropriate measurement in tests of models that claim attitude change processes that are not mediated by belief change.

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Accepted jointly by Dipankar Chakravarti, Gerald J. Gorn, and Eric J. Johnson.