See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/233147146
Measuring Attitude Toward the Brand and Purchase Intentions
Article in Journal of Current Issues and Research in Advertising · September 2004
DOI: 10.1080/10641734.2004.10505164
CITATIONS
1,688
READS
176,886
2 authors:
Nancy Spears University of North Texas 51PUBLICATIONS 3,279CITATIONS
SEE PROFILE
Surendra N. Singh University of Kansas 60PUBLICATIONS 5,479CITATIONS
SEE PROFILE
All content following this page was uploaded by Surendra N. Singh on 17 December 2014.
The user has requested enhancement of the downloaded file.
Journal of Current Issues and Research in Advertising, Volume 26, Number 2 (Fall 2004).
and Purchase Intentions
Nancy Spears and Surendra N. Singh
Attitude toward the brand (A
b) and purchase intentions (PI) are two pivotal and popular constructs that have been routinely used by advertising scholars and practitioners. Despite their popularity, standard scales, with known psychometric properties, for measuring A
band PI are not available. Furthermore, these two constructs might not be empirically distinguish- able. On the basis of scales reported in prior studies, the authors develop measures of A
band PI and assess their psychometric validity within a well-established, attitude toward the ad (A
ad) theoretical framework. Implications of their findings are discussed.
Introduction
Attitudes are a popular research topic in advertis- ing/marketing studies for at least two reasons: First, they are useful in predicting consumer behavior (Mitchell and Olson 1981), and second, several theo- retical frameworks for the study of attitudes are avail- able from social psychology researchers (see Eagly and Chaiken 1993), thereby facilitating research on this pivotal construct. The popularity of attitudes is reflected in the annual conference on attitudes spon- sored by the American Marketing Association since 1970 and in the frequent use of the hierarchy of effects models rooted in attitudes. Two attitudinal constructs seem particularly popular: attitude toward the brand, or Ab, and purchase intentions (PI), or personal action tendencies relating to the brand (Bagozzi et al. 1979;
Ostrom 1969). Ab and PI are routinely used in various advertising domains, including copy tests, tracking studies, brand evaluations, and brand extensions (Boush and Loken 1991; Broniarczyk and Alba 1994; Hastak and Olson 1989; Kalwani and Silk 1982; Keller and Aaker 1992; Morwitz, Johnson, and Schmittlein 1993).
During the past two decades, marketing journals have published numerous studies involving Ab and/
or PI constructs across a variety of theoretical para- digms – from country of origin to the Elaboration
Likelihood Model (ELM) to attitude toward the ad.
During the past 24 years, the three marketing journals (Journal of Consumer Research, Journal of Marketing, and Journal of Marketing Research) alone published 76 stud- ies that measured both Ab and PI; of these, an over- whelming majority (55) was conducted within the attitude toward the ad (Aad) framework.
Because of their popularity, considerable research exists about these two constructs. For example, re- search on PI measures has examined their predictive validity (Kalwani and Silk 1982; McNeil 1974; Morrison 1979), discriminant validity (Haley and Case 1979), and vulnerability to response biases (Clancy and Garson 1970), whereas research on Ab has examined the consistency among Ab measures themselves, their ability to discriminate between brands (Haley and Case 1979), and the hedonic and utilitarian aspects of Ab (Batra and Ahtola 1991). Yet, some fundamental issues, including the relationship between Ab and PI, have not been adequately addressed. For example, it is not clear if Ab and/or PI are multidimensional constructs. Moreover, in some studies, Ab and PI have been treated as two separate constructs, whereas oth- ers have treated them as a single construct. Some stud- ies (Leclerc and Little 1997) combine the Ab and PI items simply on the basis of item correlations (>.80), whereas others do so on the basis of factor analyses (Anand and Sternthal 1990; Peracchio and Myers-Levy 1994).
The absence of rigorous evidence of the discrimi- nant validity of Ab and PI and the fact that several studies have found Ab and PI to be highly correlated raise the possibility that these two constructs might not be empirically distinct. If Ab and PI are part of a
Nancy Spears (Ph.D., Oklahoma State University) is an Assistant Professor of Marketing, College of Business Administration, Uni- versity of North Texas, Denton, TX 76203 ([email protected]).
Surendra N. Singh (Ph.D., University of Wisconsin, Madison) is a Professor of Marketing and the Southwestern Bell Chair in Market- ing at the School of Business, University of Kansas, Lawrence, KS 66045 ([email protected]).
The authors thank Richard Bagozzi and John Lastovicka for their valuable suggestions.
54 Journal of Current Issues and Research in Advertising
unidimensional construct, then composite scores, com- puted by summing a person’s scores on individual items relating to Ab and PI, are meaningless, because the composite scores on a scale are meaningful if and only if each of the individual measures is acceptably unidimensional (Anderson and Gerbing 1988). Fur- thermore, anyone who wishes to measure these con- structs is faced with a bewildering array of choices, because no standard, psychometrically validated scales exist for measuring Ab and PI. It seems that just about every study measuring these constructs has utilized a different set of items. For example, in assessing affec- tive responses to advertising, Batra and Ray (1986) mea- sure Ab with a four-item (useful/useless, important/
unimportant, pleasant/unpleasant, and nice/ awful) scale and PI with a single-item, seven-point (definitely would buy/definitely would not buy) scale; MacKenzie, Lutz, and Belch (1986), in contrast, use a three-item, seven-point scale (favorable/unfavorable, good/bad, and wise/foolish) to measure Ab and a three-item, seven- point scale (likely/unlikely, probable/improbable, and possible/impossible) to measure PI.
Because of the importance of Ab and PI in the adver- tising/marketing literature, both problems – the con- fusion over whether the constructs are distinct but correlated or unidimensional in nature and the lack of consistency in the scales used – are significant. The unidimensionality of a construct is of paramount im- portance. Hattie (1985, p. 149), for example, states “that a set of items forming an instrument all measure just one thing in common is a most critical and basic as- sumption of measurement theory.” Lack of consis- tency in measurement, as Dubin (1969, p. 204) observed some three decades ago, also makes valid comparisons across studies difficult:
The problem of several empirical indicators being employed to stand for the same theoretical unit is usually only encountered when two or more stud- ies are being compared. One empirical indicator is used in the first study, but another is made to measure the same theoretical unit in the second study. Each author asserts the propriety of his par- ticular choice. There is no way to test the merits of either claim unless an identical sample population is measured by the several empirical indicators.
This is seldom done.
The questionable nature of Ab and PI measures is disconcerting, especially because we are well aware of the paramount importance of valid measures for the advancement of knowledge (Churchill 1979;
Gerbing and Anderson 1988). We have been repeat- edly exhorted to develop better measure of the vari- ables with which we work (Churchill 1979; Cote and
Buckley 1988). Likewise, we have been urged not to indiscriminately accept measures that “are only mea- sures because someone says they are” but have not been subjected to careful psychometric examination (Jacoby 1978, p. 91).
Thus, the purpose of our study is to develop a set of psychometrically sound measures of Ab and PI and examine the unidimensionability of the two constructs.
We consider the Ab-PI relationship within the well- established attitude toward the ad (Aad) framework, which is a dominant paradigm in the studies that measure both Ab and PI. Our effort will furnish re- searchers with valid measures of Ab and PI, engen- dering meaningful and confident comparisons of findings across studies, for one hallmark of conduct- ing multiple studies to test a theory is the stability of all aspects of the studies, except for subjects and set- tings (Sternthal, Tybout, and Calder 1987). Stability implies the use of consistently measured constructs so that the relationships among the theoretical con- structs can be evaluated in the presence of different subjects and settings. Comparisons using consistently measured constructs are more useful in identifying strengths and weaknesses in theories and models be- cause variations in results are more likely attributable to relationships among constructs than to variations due to differing sets of items measuring the same theoretical construct (Blalock 1982; Dubin 1969).
The measures developed in this study should also be relevant to advertisers who employ Ab and PI mea- sures in various ways, including assessment of cus- tomer perception of brands, tracking trends in brand attitudes and purchase intentions over time, and brand positioning. We begin with a theoretical discussion of why Ab and PI should be distinct but correlated con- structs. We then briefly review the Aad paradigm and the related model, which postulates various struc- tural relationships among the Aad, Ab, and PI con- structs. This is followed by a development of conceptual definitions of Ab and PI. In two studies, we present the details of the initial item selection, purification, and data collection procedures for the Ab and PI measures. (No attempt was made to develop an Aad measure because a psychometrically valid scale to measure this construct already exists [Madden, Allen, and Twible 1988]). We conclude with a discussion of the psychometric properties of the scales, as well as the theoretical and managerial implications of our findings.
A
bAnd PI: Related but Distinct Constructs
As early as 1936, Nixon (p. 16) recognized that “logi- cally, there ought to be some relationship between the
attitude…and the tendency to buy or not to buy the product.” Later scholars expanded our understand- ing by providing a theoretical rationale for the rela- tionship, as well as definitions that helped delineate conceptual distinctions between attitude and behav- ioral intentions. Fishbein and Ajzen (1975), in agree- ment with Thurstone (1931), proposed that attitude is the amount of affect for or against some object. Be- havioral intentions are defined as a person’s intention to perform behaviors. They suggested that attitude be measured with bipolar affective or evaluative dimen- sions relative to an attitudinal object and that behav- ioral intentions be measured by the subjective probability of performing a behavior. Fishbein and Ajzen (1975, p.11) argued that the distinctions between attitude and intentions “not only are justified but … necessary.” They proposed a theoretical framework in which attitude toward some object is based on be- liefs about that object, and attitude, in turn, deter- mines a set of behavioral intentions relative to the object, with specific behavioral intentions leading to specific behaviors with respect to the object.
Other researchers have likewise argued for a con- ceptual distinction between attitude and intention, with intentions being determined by attitude and ex- isting at a lower level of abstraction (i.e., closer to tangible actions) than are more abstracted attitudes (Bagozzi 1981; Bagozzi and Burnkrant 1979; Fishbein and Ajzen 1975; Triandis 1977). Consistent with this reasoning, many studies have treated Ab and PI as distinct constructs both conceptually and empirically (Alpert and Kamins 1995; Anderson and Jolson 1980;
Droge 1989; Machleit, Allen, and Madden 1993;
Mizerski, Allison, and Calvert 1980; Smith 1993).
Although prior research has yielded empirical evi- dence of the distinct but related nature of Ab and PI, there remains a significant body of empirical work that suggests the two constructs may be indistinguish- able. For example, Haley and Case (1979) find that items such as brand liking, brand quality, good/poor brand, and so forth and purchase intent items (e.g., definitely will/not buy) loaded on a single factor. Simi- larly, Anand and Sternthal (1990) measure brand evaluations with four Ab items (bad/good, unpleas- ant/pleasant, dislike/like, and unenjoyable/enjoy- able) and PI with one item (would not buy/buy).
Results of their factor analysis indicated that these items loaded on one factor. Likewise, Shimp, Stuart, and Engle (1991) measure Ab in multiple ways, in- cluding seven items such as good/bad, high quality/
low quality, and pleasant/unpleasant, an overall Ab measure (favorable/unfavorable), and a graphic rat- ing scale (negative/positive). The PI, however, was
measured with one item indicating chances in 10 of making the purchase. Results of confirmatory factor analyses indicated unidimensionality of Ab and PI.
Shimp, Stuart, and Engle (1991) therefore combined all items to form one composite variable.
Further confounding the Ab-PI relationship is the question regarding the dimensionality of Ab. Whereas some (Holbrook and Hirschman 1982; Mittal 1990) have treated Ab as a multidimensional construct—a treatment consistent with attitude theories (see Bagozzi and Burnkrant 1979, 1985; Chaiken and Stangor 1987)—others (Anand and Sternthal 1990) treat Ab as unidimensional. Because a significant number of stud- ies measuring both Ab and PI have combined them into one construct and because of the inconsistency implied in the treatment of Ab and PI, the measure- ment of these items must be reevaluated.
A
band PI: Conceptual Definitions
Attitude Toward the Brand (A
b)
Mitchell and Olson (1981, p. 318) define attitude toward the brand as an “individual’s internal evalua- tion of the brand.” This is an excellent definition, in that it incorporates two characteristics of attitude that, according to Giner-Sorolla (1999), have remained fairly constant across 20th-century definitions: 1) Attitude is centered or directed at an object, in this case a brand, and 2) attitude is evaluative in nature, i.e., there is
“imputation of some degree of goodness or badness”
to the attitudinal object (Eagly and Chaiken 1993, p.
3). The third component of Mitchell and Olson’s defi- nition—internal evaluation—too, is noteworthy. It suggests that an attitude is an internal state. How- ever, following Eagly and Chaiken (1973, p.7), we add that an attitude is an enduring state “that endures for at least a short period of time and presumably ener- gizes and directs behavior.”
Thus, in our conceptualization, attitude toward the brand is a relatively enduring, unidimensional summary evaluation of the brand that presumably energizes behav- ior. In the above definition, following Machleit, Allen, and Madden (1993), we conceive brand attitude as unidimensional, and like Zanna and Rempel (1988), we treat attitude as a “summery evaluation” to distin- guish it from the evaluation which is “implicit in be- liefs, feelings, behaviors and other components and expressions of attitudes” (Giner-Sorolla 1999, p. 443).
For example, attitude toward the brand is not the same thing as feelings elicited by the brand. Feelings are transitory, whereas attitudes are relatively endur- ing. Feelings are self-referent; “they do not provide
56 Journal of Current Issues and Research in Advertising
information about the external world; rather they in- dicate how the external world affects us” (Batra and Ray 1986, p. 235). Furthermore, feelings are qualita- tively different from cognitive or evaluative responses (or appraisals or semantic judgments) that are a respondent’s statements of praise or criticism of the characteristics of the message itself (Breckler and Wiggins 1989). The former is an appraisal, the latter—
a phenomenological property of the person or a state engendered in the respondent (Gardner 1985).
Purchase Intentions (PI)
Purchase intentions are personal action tendencies relating to the brand (Bagozzi et al. 1979; Ostrom 1969).
Intentions are distinct from attitudes. Whereas atti- tudes are summary evaluations, intentions represent
“the person’s motivation in the sense of his or her conscious plan to exert effort to carry out a behavior”
(Eagly and Chaiken 1993, p. 168). Thus, a concise defi- nition of purchase intentions may be as follows:
Purchase intentions are an individual’s conscious plan to make an effort to purchase a brand.
In Fishbein and Ajzen’s (1975) formulation, attitudes influence behavior through behavioral intentions.
(Their theory of reasoned action relates to attitude toward behaviors, not objects, though.) Past studies indicate that the link between attitude toward the ob- ject and behavior is not always clear. In some cases, attitudes have a direct effect on behaviors (Bagozzi and Warshaw 1992; Bagozzi and Yi 1988); in others they do not (see Bagozzi 1981, 1992b).
In this paper, our concern is brand attitude-behav- ioral intention link. The attitude threshold needed for a subject to indicate a favorable intent should be much lower than the threshold needed for behavior. There- fore, following the common practice in marketing lit- erature (for example, MacKenzie, Lutz, and Belch 1986;
Batra and Ray 1986; MacKenzie and Spreng 1992), we hypothesize a link between the attitude and behav- ioral intent.
Attitude Toward the Ad, Attitude Toward the Brand, and Purchase Intentions
As described earlier, an overwhelming majority of studies measuring Ab and PI seem to have done so within the Aad framework, where Aad is a person’s favorable or unfavorable evaluation of an ad. We there- fore chose to explore the nomological validity of the Ab-PI relationship within the Aad framework. Figure 1 presents a model depicting relationships among feel-
ings, Aad, Ab, and PI. The model is based on various advertising studies (Burke and Edell 1989; Edell and Burk 1987; MacKenzie and Lutz 1989; MacKenzie, Lutz, and Belch 1986; see also Brown, Homer, and Inman 1998 and Brown and Stayman 1992 for meta- analyses of Aad studies).
Feelings serve as antecedents to all other variables in this model. Feelings (or moods) are affective re- sponses to a communications message that are per- ceived not as qualities of the message, but as the message recipient’s affective state at the time of expo- sure to the message. Affective responses/feelings/
moods are not emotional responses. Feelings tend to be mild, general, pervasive, and not directed toward any particular object. Emotions, in contrast, tend to be more intense and attention getting and relate to speci- fiable behavior (see Gardner 1985; Petty, DeSteno, and Rucker 2001; Schwarz and Clore 1996). In this paper, we use the terms feelings, moods, and affective re- sponses interchangeably.
It is noteworthy that semantic judgments of a message’s characteristics seem to be treated by re- spondents as summary measures of evaluation (Abelson et al. 1982; Edell and Burke 1987, p. 423).
That is, positive and negative evaluations are treated as polar opposites along a single continuum. Thus, in evaluating an advertisement on the “attractiveness”
criterion, the respondent considers whether the page as a whole was attractive. This is not the case with feelings though. Positive and negative feelings consti- tute separate constructs; that is, they are bidimensional (Brown, Homer, and Inman 1998; Ito and Cacioppo 2001). Our model in Figure 1 reflects this bidimensional nature of feelings.
The model hypothesizes a direct effect (Alpert and Alpert 1986; Burke and Edell 1989; Stayman and Aaker 1988) as well as an indirect effect (Edell and Burke 1987; Holbrook and Batra 1987; MacInnis and Park 1991; Stayman and Aaker 1988) of feelings on Aad and Ab. No direct effect of feelings on PI is envisaged (Batra and Ray 1986). Similarly, Aad is hypothesized to influence Ab directly (Edell and Burke 1987) but influence PI only indirectly (Batra and Ray 1986;
MacKenzie, Lutz, and Belch 1986).
Study 1
Overview
A large pool of items measuring Ab and PI was generated from the marketing literature using an ap- proach suggested by Holbrook and Batra (1987). Next, the items that did not meet the generalizability crite-
Figure 1 Aad Framework
Positive Feelings
Negative Feelings
Aad
Purchase Intent
(PI) Attitude
Toward the Brand
(A )b
ria (i.e., that referred to a specific product class) were eliminated. Using this reduced list of items, subjects evaluated six brands depicted in various print ads and provided their ratings of Ab and PI. We chose advertisements as stimuli instead of actual brands be- cause a majority of marketing studies use ads as stimuli. Half of the observations were used to con- duct an exploratory factor analysis, and the remain- ing were used for confirmatory analysis to check the unidimensionality of the measures and establish their nomological validity.
Initial Item Generation and Selection
Items measuring Ab and PI that were reported in the literature constituted the initial pool of items. We found 52 distinct items for Ab and 15 items for PI.
Only those items that were deemed to be general mea- sures were retained because they are more likely to generalize to a wide assortment of products and ser- vices. Thus, 12 additional items were removed from the Ab list because they were specific to a product, re- ducing the number of Ab items to 40. Of the 15 PI items, two were excised because they were time specific mea- sures and timed intent was not evaluated in this study.
Thirteen PI items remained for further consideration.
The pool of items for Ab and PI was then judged by the first author and an independent researcher who was actively involved with consumer research but unfamiliar with the present study. The judgment cri- teria for Ab was to retain only items that met the con-
ceptual definitions of Ab (“an individual’s internal evaluation of the brand”) and were generalizable to a wide range of products and services. Interjudge reli- ability was 85%, and differences were resolved through discussion. Nine items were removed from the Ab list, reducing the Ab item pool to 31: appeal- ing/unappealing; good/bad; pleasant/unpleasant;
favorable/unfavorable; undesirable/desirable; high quality/low quality; likable/unlikable; interesting/
uninteresting; distinctive/not distinctive; useless/use- ful; expensive/inexpensive; important/unimportant;
exciting/dull; sophisticated/unsophisticated; infe- rior/superior; positive/negative; enjoyable/unenjoy- able; satisfactory/unsatisfactory; agreeable/
disagreeable; not nice/nice; valuable/worthless; best/
worst; fond of/not fond of; attractive/unattractive;
lacks important benefits/offers important benefits;
warm/cold; friendly/unfriendly; advisable to choose/
not advisable to choose; effective/ineffective; no value for money/value for money; expensive/cheap. The judgment criterion for PI items was that items be con- sistent with the conceptual definition of PI (“personal action tendencies relating to the brand”). Interjudge reliability was 85%, and differences were resolved through discussion. The judges removed two redun- dant items, and 11 PI items remained: unlikely/likely;
impossible/possible; never/definitely; certainly not/
certainly yes; extremely favorable/extremely unfavor- able; definitely do not intend to buy/definitely in- tend to buy; very low purchase interest/very high purchase interest; definitely not buy it/definitely buy
58 Journal of Current Issues and Research in Advertising
it; probably not buy it/probably buy it; might buy it/
might not buy it; probability of choosing absolutely certain/absolutely no chance. The retained 31 Ab and 11 PI items represented various nuances of Ab and PI.
Similar to most prior studies, we used a seven-point semantic differential format in our scales, with one exception: one PI item (probability of choosing a brand item) which has been used in several studies (e.g., Hauser and Urban 1986) had a ten-point format.
Additional Measures
Feelings and evaluations of the ads (Aad ) were mea- sured using the Madden, Allen, and Twible (1988) inventory with known psychometric properties. Feel- ings were measured using eight adjective items. Sub- jects were asked to recall how they felt during exposure to the stimulus ad. For each of the eight adjectives, they responded to the prompt, “Did the ad for [stimu- lus brand] make you feel …” on a scale ranging from 7 (very much so) to 1 (not at all). There were five positive and three negative adjectives in the scale, measuring positive feelings and negative feelings, re- spectively. The items were good, cheerful, pleased, stimulated, soothed, insulted, irritated, and repulsed.
Attitude toward the ad measured subjects’ evaluative judgments of the stimulus ads on a six-item, seven- point semantic differential scale. The adjectives were pleasant/unpleasant, likable/unlikable, interesting/
boring, tasteful/tasteless, artful/artless, and good/bad.
Stimuli
Six stimulus ads were selected from magazines from English-speaking countries other than the United States. Unfamiliar ads were used because they are less likely to produce sources of variation in the re- sults not due to the ads themselves. Congruent with the product categories commonly used in prior re- search, the ads were for soft drinks, audiocassettes, household cleanser, athletic shoes, automobiles, and a wristwatch. The ad for the soft drink showed the drink in a bottle, as well as in a glass with ice, with the text describing an exciting and great taste. The audio- cassette ad emphasized the clarity and purity of its recordings. The household cleanser ad promoted its high-foam, multipurpose usage. The athletic shoes ad described many facts about the shoes (e.g., years of research into the materials that constituted the shoes).
The automobile ad described a European sedan with many features that added to comfort, elegance, and performance. The watch ad emphasized its advanced technology and sophistication.
Subjects and Procedure
Ninety-three undergraduate students at a major Midwestern U.S. university participated in the study during regularly scheduled classes. Subjects were in- formed that we were interested in knowing their opin- ions about several advertisements, but the purpose of the study was not disclosed to them. Two booklets were then given to each subject. One booklet con- tained the advertisements, and the other booklet con- tained the corresponding rating scales. The directions instructed the subjects to examine the first ad in the ad booklet and provide their responses to it in the rating scales booklet. Next, they were to examine the second ad and provide responses to it in the rating scales booklet, and so forth. Each subject completed rating scales for each of the six ads.
Results
The analyses were conducted in two phases. The first phase was exploratory and was used to reduce the number of items and to examine the pattern of relationships among these items with the intention of producing a parsimonious and meaningful set of un- derlying factors. The second, confirmatory phase sought to provide a more stringent test of the factor structure generated in the first phase. This phase ex- amined the relationship among feelings, Aad, Ab, and PI to provide evidence of the nomological validity of the Ab and PI measures. The 558 observations (i.e., 93 subjects x 6 ads evaluated by each subject) were ran- domly divided into two groups of 279 each using the SPSS random sample selection option. Thus, both the exploratory and the confirmatory phases had n=279.
Exploratory Analysis
Using N= 279 (the sample size) and 42 items mea- suring Ab and PI (i.e., 31 Ab items and 11 PI items), a parallel analysis (Horn 1965) via principal compo- nents procedure was conducted. This analysis indi- cated that two factors should be retained. The 42 items were then subjected to exploratory factor analysis us- ing the maximum likelihood extraction method and oblimin rotation, restricting the number of factors to 2. The scree plot indeed indicated a two-factor solu- tion, which accounted for 84.5% of the variance in the data set and yielded eigenvalues of 6.73 and 5.95.
Factor 1 (Ab) explained 44.85% of the variance and consisted of items that measured Ab. Factor 2 (PI), which explained 39.67% of the variance, included PI items. Items that measured Ab loaded on the first fac-
tor while items that measured PI loaded on the sec- ond factor.
Two criteria for retaining items from the two fac- tors were employed. The first criterion was factor load- ings greater than .80. The second criterion was simple structure in the factor pattern. Simple structure pro- duces items with high loadings on one factor and loadings near zero on other factors (Hatcher 1994).
Following Bagozzi and Yi (1988) and Lichtenstein, Netemeyer, and Burton (1995), we removed those items that had an extremely high item-to-total corre- lation (.90 or greater). Using these criteria, seven items were retained for Ab (unappealing/appealing, bad/
good, unpleasant/pleasant, unfavorable/favorable, unlikable/likable, unsatisfactory/satisfactory, dis- agreeable/agreeable). The exercise resulted in a re- duced set of eight PI items (unlikely/likely, impossible/possible, never/definitely, certainly not/
certainly yes, definitely do not intend to buy/defi- nitely intend, very low/high purchase interest, defi- nitely not buy it/definitely buy it, probably not/
probably buy it).
Confirmatory Analysis
Confirmatory factor analysis using LISREL VIII (Jöreskog and Sörbom 1993) was employed to evalu- ate and refine the scales generated in the exploratory phase. A two-factor model was estimated using the retained items from the exploratory phase. These in- cluded seven indicators for the Ab factor and eight items for the PI factor. The model fit was not very good (chi-square=508.89, d.f.=89, p<.01, standardized root mean square residual [SRMR]=.16, goodness-of- fit index [GFI]=.78, adjusted goodness-of-fit index [AGFI]=.70, Tucker-Lewis index [TLI]=.92, and con- firmatory fit index [CFI]=.93). Therefore, a refinement of the indicators was undertaken (see Netemeyer, Bur- ton, and Lichtenstein 1995). We examined the pattern of normalized residuals to select items for deletion (Anderson and Gerbing 1988; Gerbing and Anderson 1988; Hunter and Gerbing 1982; Madden, Allen, and Twible 1988). Model fit improved with the deletion of two indicators of Ab and three indicators of the PI factor. The respecified model had 34 degrees of free- dom with a chi-square of 91.17 (p<.01), a SRMR of .022, a GFI of .94, an AGFI of .90, a TLI of .98, and a CFI of .98, which indicate a good fit (Hu and Bentler 1999). Table 1 displays item descriptions and psycho- metric properties for the refined measures, including five Ab items and five PI items.
Internal consistency was investigated by calculat- ing the composite reliability and average variance ex-
tracted (AVE) for each factor. Composite reliability is an alpha equivalent, and AVE provides information about how much variance in the measured variables is captured by the latent constructs (Fornell and Larcker 1981). Composite reliability was .97 for Ab and .97 for PI. The AVE exceeded .50 for all four constructs (see Table 1), which demonstrates that more variance is due to the constructs than to measurement error (Fornell and Larcker 1981). In addition, all items had significant loadings on their respective factors (p<.01). Squared-multiple correlations indicate how much variance in the observed variables is shared with the underlying construct, with .50 often used as a cut- off. All items exceeded this cut-off. In concert, these tests indicate adequate levels of internal consistency.
Discriminant validity was assessed using three tests.
The first test compared a two-factor model to a one- factor model (Anderson and Gerbing 1988). This com- parison yielded a significant chi-square difference, thereby providing support for the superiority of the two-factor specification. The second test determined that the confidence interval (± two standard errors) around the correlation estimate between the two fac- tors did not contain 1.0, thereby providing further evidence of discriminant validity (Anderson and Gerbing 1988). Finally, φ2 was less than the AVE be- tween the factors, furnishing further evidence of ad- ditional discrimination (Fornell and Larcker 1981).
Nomological Validity
The relationship among five distinct but conceptu- ally related constructs—Ab, positive feelings, nega- tive feelings, Aad and PI—was examined using Peter’s (1981) conception of nomological validity. We tested the model shown in Figure 1 using LISREL VIII with the covariance matrix as input. The first three constructs in the model, as mentioned previously, were measured using Madden, Allen, and Twible’s (1988) scale. Coeffi- cient alpha for positive feelings, negative feelings, and Aad (reverse scored for the analysis) were .94, .89, and .94, re- spectively. Figure 2 displays the results of this test.
The measurement model was first established to ensure that the structural estimates and interpreta- tions are not confounded with measurement prob- lems. The measurement model had a chi-square of 586.69 with 242 degrees of freedom (p<.01). With the large sample size, the other indices were considered a better indicator of overall model fit: SRMR =.039, GFI=.85, AGFI=.81, TLI=.95, and CFI=.96. Table 2 shows the correlations among the constructs.
With evidence of an acceptable measurement model, the structural model was then estimated. This model
60Journal of Current Issues and Research in Advertising Table 1
Study 1: Item Descriptions and Psychometric Properties
Completely Coefficient Composite Average
Instruction Standardized Alpha Alpha Variance
Scale and Items* Factor Loadings t- values (Exploratory) (Confirmatory) Extracted
Please describe your overall feelings about the brand described in the ad you just read.
Attitude toward
the brand .97 .97 .86
1. Unappealing/appealing .95 21.01
2. Bad/good .91 19.35
3. Unpleasant/pleasant .91 19.61
4. Unfavorable/favorable .95 21.14
5. Unlikable/likable .90 19.23
Purchase
Intentions .97 .97 .86
1. Never/definitely .90 19.15
2. Definitely do not intend to buy/definitely intend .93 20.31
3. Very low/high purchase interest .92 20.07
4. Definitely not buy it/definitely buy it .96 21.37
5. Probably not/probably buy it .93 20.25
Figure 2 Study 1 Results
Notes: All LISREL estimates are completely standardized. C2=590.48; d.f.=245; p<.01; standardized root mean square
residual=.042; goodness-of-fit index=.85; adjusted goodness-of-fit index=.81; Tucker-Lewis index=.95; and confirmatory fit index=.96.
Positive Feelings
Negative Feelings
Aad
Purchase Intent
(PI) Attitude
Toward the Brand
(A )b -.29
(-5.82) .60 (9.70)
.20 (4.48)
.74 (10.08)
.66 (9.65)
-.05 (-1.51)
produced a significant chi-square result (χ2 =590.48;
d.f.=245; p<.01). However, the other fit indices were adequate, with SRMR=.042, GFI=.85, AGFI=.81, TLI=.95, and CFI=.96. The individual coefficients of determination, which can be interpreted like R2 val- ues, were as follows: Ab .82, Aad-evaluative .48, and PI .43.
To bolster support for the structural model, an al- ternative model was specified and tested against the hypothesized model. This model had a path from Aad-
positive affect, Aad-negative affect, and Aad-evaluative to PI; that is, it posited direct effects of feelings and Aad on PI. A chi- square difference test produced nonsignificant results (χ2=3.79; d.f.=3; p>.05), thereby providing evidence of the superiority of the hypothesized model with paths
from Aad-positive affect, Aad-negative affect, and Aad-evaluative to PI restricted to zero. This finding is expected on the ba- sis of MacKenzie, Lutz, and Belch’s (1986) study, which produced results indicating that Aad influences PI in- directly through Ab.
Study 2: Replication and Further Validation
Despite encouraging results, one may argue that because the same subjects evaluated all six ads, the data do not meet the fundamental assumption of in- dependence. We, therefore, decided to conduct a sec- ond study for further validation of the model. From the six ads, one (the soft drink) was selected at ran- Table 2
Study 1: Standardized Correlations Among the Constructs
Ab PI Aad-positive affect Aad-negative affect Aad-evaluative
Ab 1.00
PI .64* 1.00
Aad-positive affect .68* .52* 1.00
Aad-negative affect -.35* -.23* -.16* 1.00
Aad-evaluative .86* .57* .64* -.35* 1.00
Notes: Construct variances were set to 1.00 for the purpose of identifying the scale of the constructs.
Estimates are from the completely standardized solution.
*p<.05
62Journal of Current Issues and Research in Advertising Table 3
Study 2: Item Descriptions and Psychometric Properties
Completely Coefficient Composite Average
Instruction Standardized Alpha Alpha Variance
Scale and Items* Factor Loadings t- values (Exploratory) (Confirmatory) Extracted
Please describe your overall feelings about the brand described in the ad you just read.
Attitude toward
the brand .95 .94 .77
1. Unappealing/appealing .87 16.68
2. Bad/good .93 18.55
3. Unpleasant/pleasant .89 17.12
4. Unfavorable/favorable .88 16.72
5. Unlikable/likable .84 15.52
Purchase
Intentions .96 .97 .82
1. Never/definitely .89 17.18
2. Definitely do not intend to buy/definitely intend .94 18.82
3. Very low/high purchase interest .87 16.67
4. Definitely not buy it/definitely buy it .94 18.97
5. Probably not/probably buy it .88 16.80
dom. To preserve the independence of the observa- tions, only one ad was used, but doing so necessitated data collection on a number of subjects (n= 232). We followed essentially the same procedure as used in Study 1. We included measures for Aad-positive affect, Aad-
negative affect, Aad-evaluative, and the refined PI and Ab items.
Results
Exploratory Factor Analysis. The 10 items used to measure PI and Ab were factor analyzed using a maxi- mum likelihood extraction method and a Varimax rotation with Kaiser normalization. A two-factor so- lution emerged, accounting for 84.76% of the vari- ance. The five Ab items loaded on one factor, and the five PI items loaded on the second factor.
Confirmatory Factor Analysis. The ten items retained from the exploratory stage were constrained to load on their two respective factors as follows: five items on PI and five items on Ab (see Table 3). The following fit indices were obtained:χ2(34)=148.14, p<.05; goodness- of fit index (GFI)= .88; adjusted-goodness-of-fit index (AGFI)=.81, confirmatory fit index (CFI)= .95; Tucker- Lewis index (TLI)= .94; and a standardized root mean square residual (SRMR)= .034. In concert, these indi- ces indicate acceptable model fit (Hu and Bentler 1999).
Table 3 displays the items and their psychometric properties.
Internal consistency was investigated by calculat- ing the composite reliability and average variance ex- tracted (AVE) for each of the two factors. Composite reliabilities, .94 and .97, and AVEs, .77 and .82, were acceptable. All items had significant loadings on their respective factor (p<.05). Table 3 lists the items and corresponding completely standardized factor loadings and t-values. In sum, clear evidence of internal consis- tency was demonstrated. As in Study 1, discriminant validity was evaluated and was found to be adequate.
(To conserve space, results of this analysis are not pre- sented here, but may be obtained from the authors).
As in Study 1, the nomological validity of the mea- sures was tested with a structural model. (Note: posi- tive feelings had an alpha of .92, negative feelings had an alpha of .90, and Aad had an alpha of .86). The measurement model yielded a χ2=608.51, df=242, p<.05; GFI=.82; adjusted GFI=.78; TLI=.92; CFI=.93, and SRMR=.053. The fit indices for the structural model were as follows: χ2=623.27, df=245, p<.05, GFI=.82, adjusted GFI=.78, TLI=.92, CFI=.93, and SRMR=.067 (see Figure 3). Taken together, these fit indices indicate acceptable model fit (Hu and Bentler 1999). The individual coefficients of determination, which can be interpreted like R2 values, were as fol- lows: Ab .65, Aad-evaluative .50, and PI .54. All estimated structural paths were positive and significant (p<.05).
Table 4 shows the correlations among constructs.
Figure 3 Study 2 Results
Notes: All LISREL estimates are completely standardized. ΧΧΧΧΧ2 =623.27; d.f.=245; p<.01; standardized root mean square
residual=.067; goodness-of-fit index=.82; adjusted goodness-of-fit index=.78; Tucker-Lewis index=.92; and confirmatory fit index=.93.
Positive Feelings
Negative Feelings
Aad
Purchase Intent
(PI) Attitude
Toward the Brand
(A )b -.31
(-4.97) .62 (8.28)
.26 (3.80)
.58 (6.60)
.73 (9.57)
-.10 (-1.97)
64 Journal of Current Issues and Research in Advertising
Discussion and Conclusion
The purpose of our study was to address perceived shortcomings observed in the literature in the mea- surement of Ab and PI by developing valid measures that can be consistently used across studies. To ac- complish this, two comprehensive sets of items that tap the domains of Ab and PI were generated from the literature. Studies 1 and 2 discuss how scales for Ab and PI were developed and how the measurement properties were investigated. In Study 1, the explor- atory phase was used to reduce the number of items and identify a meaningful set of underlying factors that parsimoniously accounted for the observed rela- tionships. The confirmatory phase provided a more rigorous test of the factor structure generated in the first phase. The third phase examined the relation- ship among Aad, Ab, and PI. The refined scales exhib- ited adequate levels of internal consistency and discriminant validity. Study 2 was conducted for fur- ther replication and validation. The extant literature suggested that Ab and PI exist as separate but corre- lated dimensions. This representation was supported here. The refinement of these measures yielded a par- simonious set of items that discriminate between two widely employed constructs in the advertising/mar- keting literature.
Nearly three decades ago, Jacoby (1978, p. 91) noted the impact of poor scaling in the marketing literature in a poignant statement: “More stupefying than the sheer number of our measures is the ease with which they are proposed and the uncritical manner in which they are accepted.” He specifically identified the is- sue of validity as a core problem: “Just how valid are our measures? Little attention seems to be directed toward finding out. Like our theories and models, once proposed, our measures take on an almost sa- cred and inviolate existence all their own. They are rarely, if ever, examined or questioned” (Jacoby 1978,
p. 91). Churchill (1979, p. 64) sought to address “the obvious need for better measures and the lack of such measures” by providing a framework with which mar- keting researchers could strengthen their constructs, and ultimately, the quality of their research. Considerable progress has been made since then. However, validity issues persist (Bagozzi 1992a). Scholarly marketing re- search has tended to say little about dependent vari- ables “other than providing two or three seven-point items as measures,” and while applied researchers di- rect attention to the dependent measures, they are often more concerned about a measure’s predictive abilities than its nature and validity (Bagozzi 1992a).
A typical article these days reports reliability coeffi- cients, and some report results from exploratory fac- tor analysis, too. However, exploratory factor analytic results are subject to ambiguities often inherent in the subjective, post hoc interpretation of factors (Breckler 1984). Thus, there is a great need for refined scales that satisfy standard measurement criteria, namely scales that provide evidence of validity through con- firmatory methods and a nomological network. No- where does this need seem greater than in the case of Ab and PI measures, as illustrated by Bruner and Hensel’s (1996) review of Ab measures. On the basis of a review of more than 70 studies, they conclude,
“Little if any evidence of scale validity was provided in the majority of the studies” (Bruner and Hensel 1996, p. 87).
Our study has sought to address these concerns by developing valid measures for Ab and PI. Our com- parative analyses indicate the efficacy of these mea- sures over competing ones. We believe that use of these scales should facilitate comparison and synthe- sis of findings across studies, which should enhance our theoretical knowledge. The findings of our study have managerial implications, too. Advertisers rou- tinely use Ab and PI scales to assess customer percep- tions of brands for a diverse array of product offerings.
Table 4
Study 2: Standardized Correlations Among the Constructs
Ab PI Aad-positive affect Aad-negative affect Aad-evaluative
Ab 1.00
PI .73* 1.00
Aad-positive affect .63* .46* 1.00
Aad-negative affect -.31* -.23* -.04 1.00
Aad-evaluative .78* .57* .64* -.34* 1.00
Notes: Construct variances were set to 1.00 for the purpose of identifying the scale of the constructs.
Estimates are from the completely standardized solution.
*p<.05
Moreover, scales are used to track trends in brand attitude and PI over time, to compare a company’s brand with competing brands, and to plan position- ing strategies for the brand relative to the competi- tion. The psychometrically valid Ab and PI measures developed in this study should be helpful to advertis- ers in all these domains.
References
Abelson, R. P., Donald Kinder, Mark D. Peters, and Susan T. Fiske (1982), “Affective and Semantic Components in Political Per- son Perception,” Journal of Personality and Social Psychology, 42 (April), 619-30.
Alpert, Frank H. and Michael A. Kamins (1995), “An Empirical Investigation of Consumer Memory, Attitude, and Percep- tions Toward Pioneer and Follower Brands,” Journal of Mar- keting, 59 (October), 34-45.
Alpert, Judy I. and Mark I. Alpert (1986), “The Effects of Music in Advertising on Mood and Purchase Intentions,” Working Pa- per No. 85/86-5-4, Department of Marketing Administration, College of Business Administration, University of Texas, Aus- tin, TX 78712.
Anand, Punam and Brian Sternthal (1990), “Ease of Message Pro- cessing as a Moderator of Repetition Effects in Advertising,”
Journal of Marketing Research, 17 (August), 345-53.
Anderson, James C. and David W. Gerbing (1988), “Structural Equa- tion Modeling in Practice: A Review and Recommended Two- Step Approach,” Psychological Bulletin, 103, 411-23.
Anderson, Rolph E. and Marvin A. Jolson (1980), “Technical Word- ing in Advertising: Implications for Market Segmentation,”
Journal of Marketing, 44 (Winter), 57-66.
Bagozzi, Richard P. (1981), “Attitudes, Intentions, and Behavior: A Test of Some Key Hypotheses,” Journal of Personality and Social Psychology, 41, 607-27.
–––––––––––– (1992a), “Acrimony in the Ivory Tower: Stagnation or Evolution?” Journal of the Academy of Marketing Science, 20 (Fall), 355-59.
–––––––––––– (1992b), “The Self-Regulation of Attitudes, Inten- tions, and Behavior,” Social Psychology Quarterly, 55, 178-204.
–––––––––––– and P. R. Warshaw (1992), “An Examination of the Etiology of the Attitude-behavior Relation for Goal-directed Behaviors,” Multivariate Behavioral Research, 27, 601-634.
–––––––––––– and Robert E. Burnkrant (1979), “Attitude Organi- zation and the Attitude-Behavior Relationship,” Journal of Per- sonality and Social Psychology, 37, 913-29.
–––––––––––– and –––––––– (1985), “Attitude Organization and Attitude-Behavior Relation: A Reply to Dillon and Kumar,”
Journal of Personality and Social Psychology, 49, 47-57.
–––––––––––– , Alice M. Tybout, C. Samuel Craig, and Brian Sternthal (1979), “The Construct Validity of Tripartite Classification of Atti- tudes,” Journal of Marketing Research, 16 (February), 88-95.
–––––––––––– and Youjae Yi (1988), “On the Evaluation of Struc- tural Equation Models,” Journal of the Academy of Marketing Science, 16 (Spring), 74-94.
Batra, Rajeev and O. T. Ahtola (1991), “Measuring the Hedonic and Utilitarian Sources of Consumer Attitudes,” Marketing Letters, 2 (April), 159-70.
–––––––––––– and Michael L. Ray (1986), “Affective Responses Mediating Acceptance of Advertising,” Journal of Consumer Research, 13 (September), 234-49.
Blalock, Jr., Hubert M. (1982), Conceptualization and Measurement in Social Sciences, New York: Sage Publications.
Boush, David M. and Barbara Loken (1991), “A Process-Tracking Study of Brand Extension Evaluation,” Journal of Marketing Research, 28 (February), 16-28.
Breckler, Steven J. (1984), “Empirical Validation of Affect, Behav- ior, and Cognition as Distinct Components of Attitude,” Jour- nal of Personality and Social Psychology, 47, 1191-205.
–––––––––––– and Elizabeth C. Wiggins (1989), “Affect Versus Evaluation in the Structure of Attitudes,” Journal of Experimen- tal Social Psychology, 25, 253-71.
Broniarczyk, Susan M. and Joseph W. Alba (1994), “The Impor- tance of the Brand in Brand Extension,” Journal of Marketing Research, 31 (May), 214-228.
Brown, Steven P., Pamela M. Homer, and J. Jeffrey Inman (1998),
“A Meta-Analysis of Relationships Between Ad-Evoked Feel- ings and Advertising Responses,” Journal of Marketing Research, 35 (February), 114-26.
–––––––––––– and Douglas M. Stayman (1992), “Antecedents and Consequences of Attitude Toward the Ad: A Meta-Analysis,”
Journal of Consumer Research, 19 (June), 35-51.
Bruner, Gordon C. II and Paul J. Hensel (1996), Marketing Scales Handbook, Chicago: American Marketing Association.
Burke, Marian C. and Julie A. Edell (1989), “The Impact of Feelings on Ad-Based Affect and Cognition,” Journal of Marketing Re- search, 26 (February), 69-83.
Chaiken, Shelly and Charles Stangor (1987), “Attitude and Atti- tude Change,” Annual Review of Psychology, 38, 575-630.
Churchill, Gilbert A., Jr. (1979), “A Paradigm for Developing Better Measures of Marketing Constructs,” Journal of Marketing Re- search, 16 (February), 64-73.
Clancy, Kevin J. and Robert Garson (1970), “Why Some Scales Pre- dict Better,” Journal of Advertising Research, 10 (October), 33-8.
Cote, Joseph A. and M. Ronald Buckley (1988), “Measurement Er- ror and Theory Testing in Consumer Research: An Illustra- tion of the Importance of Construct Validation,” Journal of Consumer Research, 14 (March), 579-82.
Droge, Cornelia (1989), “Shaping the Route to Attitude Change:
Central Versus Peripheral Processing Through Comparative Versus Noncomparative Advertising,” Journal of Marketing Research, 26 (May), 193-204.
Dubin, Robert (1969), Theory Building, New York: The Free Press.
Eagly, Alice H. and Shelly Chaiken (1993), The Psychology of Atti- tudes, New York: Harcourt Brace College Publishers.
Edell, Julie A. and Marian C. Burke (1987), “The Power of Feelings in Understanding Advertising Effects,” Journal of Consumer Research, 14 (December), 421-33.
Fishbein, Martin and Icek Ajzen (1975), Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research, Reading, MA:
Addison-Wesley.
Fornell, Claes and David F. Larcker (1981), “Evaluating Structural Equation Models with Unobservable Variables and Measure- ment Error,” Journal of Marketing Research, 18 (February), 39-50.
Gardner, Meryl Paula (1985), “Does Attitude Toward the Ad Effect Brand Attitude Under a Brand Evaluation Set?” Journal of Mar- keting Research, 22 (May), 192-198.
Gerbing, David W. and James C. Anderson (1988), “An Updated Para- digm for Scale Development Incorporating Unidimensionality and Its Assessment,” Journal of Marketing Research, 25 (May), 186-92.
Giner-Sorolla, Roger (1999), “Affect in Attitude: Immediate and Deliberative Perspectives,” in Dual-Process Theories in Social Psychology, Shelley Chaiken and Yaacov Trope, eds., The Guilford Press: New York, 441-61.
Haley, Russell I. and Peter B. Case (1979), “Testing Thirteen Atti- tude Scales for Agreement and Brand Discrimination,” Journal of Marketing, 43 (Fall), 20-32.
66 Journal of Current Issues and Research in Advertising
Hastak, Manoj and Jerry C. Olson (1989), “Assessing the Role of Brand-Related Cognitive Responses as Meditors of Commu- nication Effects on Cognitive Structure,” Journal of Consumer Research, 15 (March), 444-56.
Hatcher, Larry (1994), A Step-by-Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling, Cary, NC: SAS Institute Inc.
Hattie, J. (1985), “Methodology Review: Assessing Unidimension- ality of Tests and Items,” Applied Psychological Measurement, 9 (June), 139-64.
Hauser, John R. and Glen L. Urban (1986), “The Value of Priority Hypotheses for Consumer Budget Plans,” Journal of Consumer Research, 12 (March), 446-62.
Holbrook, Morris and Rajeev Batra (1987), “Assessing the Role of Emotions as Mediataors of Consumer Responses to Advertis- ing,” Journal of Consumer Research, 14 (December), 404-20.
–––––––––––– and E. C. Hirschman (1982), “The Experiential As- pects of Consumption: Consumer Fantasies, Feelings, and Fun,” Journal of Consumer Research, 9 (September), 132-40.
Horn, J. L. (1965), “A Rationale and Test for the Number of Factors in Factor Analysis,” Psychometrika, 30, 179-85.
Hu, Li-tze and Peter M. Bentler (1999), “Cutoff Criteria for Fit In- dexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives,” Structure Equation Modeling, 6, 1-55.
Hunter, John E. and David W. Gerbing (1982), “Unidimensional Measurement, Second Order Factor Analysis and Causal Mod- els,” in Research in Organizational Behavior, 4, Barry M. Staw and L. L. Cummings, eds., Greenwich, CT: JAI Press, Inc., 267-320.
Ito, Tiffany A. and John T. Cacioppo (2001), “Affect and Attitudes:
A Social Neuroscience Approach,” in Handbook of Affect and Social Cognition, Joseph P. Forgas, ed., Hillsdale, NJ: Lawrence Erlbaum Associates, 51-74.
Jacoby, Jacob (1978), “Consumer Research: A State of the Art Re- view,” Journal of Marketing, 42 (April), 87-96.
Jöreskog, K. G. and Dag Sörbom (1993), LISREL VIII: Users Refer- ence Guide, Chicago: Scientific Software.
Kalwani, Manohar and Alvin J. Silk (1982), “On the Reliability and Predictive Validity of Purchase Intention Measures,” Market- ing Science, 1 (Summer), 243-86.
Keller, Kevin Lane and David A. Aaker (1992), “The Effect of Se- quential Introduction on Brand Extensions,” Journal of Market- ing Research, 29 (February), 35-50.
Leclerc, France and John D. Little (1997), “Can Advertising Copy Make FSI Coupons More Effective?” Journal of Marketing Re- search, 34 (November), 473-84.
Lichtenstein, Donald R., Richard G. Netemeyer, and Scott Burton (1995),
“Accessing the Domain Specificity of Deal Proneness: A Field Study,” Journal of Consumer Research, 22 (December), 314-26.
Machleit, Karen A., Chris T. Allen, and Thomas J. Madden (1993), “The Mature Brand and Brand Interest: An Alternative Consequence of Ad-Evoked Affect,” Journal of Marketing, 57 (October), 72-82.
MacInnis, Deborah J. and C. Whan Park (1991), “The Differential Role of Characteristics of Music on High- and Low-Involve- ment Consumers’ Processing of Ads,” Journal of Consumer Re- search, 18 (September), 161-73.
MacKenzie, Scott B. and Richard J. Lutz (1989), “An Empirical Examination of the Structural Antecendents of Attitude To- ward the Ad in an Advertising Pretesting Context,” Journal of Marketing, 53 (April), 48-65.
–––––––––––– , ––––––––––– , and George E. Belch (1986), “The Role of Ad as a Mediator of Advertising Effectiveness: A Test of Competing Explanations,” Journal of Marketing Research, 23 (May), 130-43.
–––––––––––– and Richard A. Spreng (1992), “How Does Motiva- tion Moderate the Impact of Central and Peripheral Process- ing on Brand Attitudes and Intentions?” Journal of Consumer Research, 18 (March), 519-29.
Madden, Thomas J., Chris T. Allen, and Jacquelyn L. Twible (1988),
“Attitude Toward the Ad: An Assessment of Diverse Mea- surement Indices Under Different Processing ‘Sets’,” Journal of Marketing Research, 25 (August), 242-52.
McNeil, J. (1974), “Federal Programs to Measure Consumer Pur- chase Expectations, 1946-73: A Post-Mortem,” Journal of Con- sumer Research, 1 (December), 1-10.
Mitchell, Andrew A. and Jerry C. Olson (1981), “Are Product Be- liefs the Only Mediator of Advertising Effect on Brand Atti- tude?” Journal of Marketing Research, 18 (August), 318-32.
Mittal, Banwari (1990), “The Relative Roles of Brand Beliefs and Attitude Toward the Ad as Mediators of Brand Attitude: A Second Look,” Journal of Marketing Research, 27 (May), 209-19.
Mizerski, Richard W., Neil A. Allison, and Stephen Calvert (1980),
“A Controlled Field Study of Corrective Advertising Using Multiple Exposures and a Commercial Medium,” Journal of Marketing Research, 17 (August), 341-80.
Morrison, Donald G. (1979), “Purchase Intentions and Purchase Behavior,” Journal of Marketing, 43 (Spring), 63-74.
Morwitz, Vicki G., Eric Johnson, and David Schmittlein (1993),
“Does Measuring Intent Change Behavior,” Journal of Con- sumer Research, 20 (June), 46-61.
Netemeyer, Richard G., Scot Burton, and Donald R. Lichtenstein, (1995), “Trait Aspects of Vanity: Measurement and Relevance to Consumer Behavior,” Journal of Consumer Research, 21 (March), 612-26.
Nixon, H.K. (1936), “Notes on the Measurement of Consumers’
Attitudes,” Journal of Marketing, 1 (July), 13-19.
Ostrom, Thomas M. (1969), “The Relationship Between the Affec- tive, Behavioral, and Cognitive Components of Attitude,” Jour- nal of Experimental Social Psychology, 5, 12-30.
Peracchio, Laura A. and Joan Meyers-Levy (1994), “How Ambigu- ous Cropped Objects in Ad Photos Can Affect Product Evalu- ations,” Journal of Consumer Research, 21 (June), 190-204.
Peter, J. Paul (1981), “Construct Validity: A Review of Basic Issues and Marketing Practices,” Journal of Marketing Research, 18 (May), 133-45.
Petty, Richard E., David DeSteno, and Derek D. Rucker (2001),
“The Role of Affect in Attitude Change,” in Handbook of Affect and Social Cognition, Joseph P. Forgas, ed. Hillsdale, NJ:
Lawrence Erlbaum Associates, 213-33.
Schwarz, N. and G.L. Clore (1996), “Feelings and Phenomenal Ex- periences,” in Social Psychology: Handbook of Basic Principles, E.
T. Higgins and A. W. Kruglanski, eds. New York: Guilford Press, 433-65.
Shimp, Terence A., Elnora W. Stuart, and Randall W. Engle (1991),
“A Program of Classical Conditioning Experiments Testing Variations in the Conditioned Stimulus Context,” Journal of Consumer Research, 18 (June), 1-12.
Smith, Robert E. (1993), “Integrating Information from Advertising and Trial: Processes and Effects on Consumer Response to Product Information,” Journal of Marketing Research, 30 (May), 204-19.
Stayman, Douglas M. and David A. Aaker (1988), “Are All Effects of Ad-Induced Feelings Mediated by Aad?” Journal of Con- sumer Research, 15 (December), 368-73.
Sternthal, Brian, Alice M. Tybout, and Bobby J. Calder (1987), “Con- firmatory Versus Comparative Approaches to Judging Theory Tests,” Journal of Consumer Research, 14 (June), 114-25.
Thurstone, L. L. (1931), “The Measurement of Attitudes,” Journal of Adnormal and Social Psychology, 26, 249-69.
Triandis, H. C. (1977), Interpersonal Behavior, Monterey, CA: Brooks/
Cole.
Zanna, M. P. and J. K. Rempel (1988), “Attitudes: A New Look at an Old Concept,” in The Social Psychology of Knowledge, D. Bar- Tal and A. W. Kruglanski, eds., Cambridge University Press:
Cambridge, 315-34.