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Implicit Measures ofConsumer Cognition:

A Review

Claudiu V. DimofteGeorgetown University

ABSTRACT

In line with recent methodological advances from the cognitive andsocial psychology literature, consumer researchers have shownstrong interest in addressing the nonconscious nature of consumer

information processing, attitude formation, and behavioral response.The related use of implicit measures in the study of a variety of mar-keting effects has offered novel insights into consumer perceptionof, and response to, marketing stimuli. This paper highlights concep-tual issues and empirical findings on the topic of implicit consumercognition and examines the incremental value that implicit meas-ures may bring to the field. The review suggests that while the use ofimplicit measures in consumer research is still in its infancy, itshows significant promise as a methodological tool. 2010 WileyPeriodicals, Inc.

The recent development and use of a variety of measures designed to captureindividuals implicit social cognitions has naturally spilled over into the con-

sumer psychology field. Yet with every novel methodological development, ques-tions arise about the proper understanding of the conceptual issues underlying

the new measures and implications regarding their practical application.Theseconcerns are all the more relevant to the marketing area, which has only cau-tiously begun to adopt some of these measures in the hope of achieving a bet-

ter understanding of the way consumers process and respond to marketing

stimuli. This is indeed new territory. For example, the Simonson et al. (2001)review of the state of the consumer research field was virtually silent on the topic

Psychology & Marketing, Vol. 27(10): 921937 (October 2010)

View this article online at wileyonlinelibrary.com

2010 Wiley Periodicals, Inc. DOI: 10.1002/mar.20366

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of implicit social cognition. In 2002, Bargh made a passionate plea for new work

that was needed concerning automatic influences on consumer judgment, behav-ior, and motivation.

Proposing that consumer contexts are indeed conducive to automatic pro-

cessing effects, Fitzsimons et al. (2002) reviewed accumulating evidence for theenhanced role of nonconscious influences on consumer responses ranging from

perception and memory to affect and choice. Dijksterhuis et al. (2005) furtherargued for the role of the unconscious in the routine behavior of consumers andproposed that much of it involves automatic goal pursuit. According to theseauthors, conceptual accounts emphasizing conscious and thorough information

processing are unable to account for a large part of consumer choices, and in factthe vast majority of choices are not the result of much information processingat all (Dijksterhuis et al., 2005). Instead, they involve decisions that are contex-

tually or environmentally cue-induced and either engage automatically activatedattitudes or are completely devoid of deliberate attitude processing.These aspects

are critical because the validity of explicit measures is negatively affected by

respondents lack of a particular attitude, their inability to access it, or theirunwillingness to share information about it with researchers (Perkins et al., 2008).

In a consumption landscape largely determined by nonconscious influences,implicit measures would seem to be potentially useful tools for detecting con-sumers true responses. In assessing this conjecture, this paper provides a

brief summary of the evolution of academic marketing thought on implicit socialcognition in the last decade. To this end, the conceptual underpinnings of thisarea of study from cognitive/social psychology are first reviewed.Then the par-

ticular relevance of implicit measures to the study of consumption topics isintroduced, with specific examples from more recent marketing literature.

Finally, several conclusions are offered regarding the current state of implicitsocial cognition in consumer research and directions for future research.

BACKGROUND

The ImplicitExplicit Construct Distinction

Many constructs of interest in cognitive and social psychology (and by extensionin consumer psychology) are presumed to involve stable mental representations

(e.g., relatively consistent, valenced evaluations in the case of attitudes) that arestored in memory and activated by contextual cues, leading to immediate changesin behavior.1 For example, if consumers have positive attitudes toward globalbrands,being exposed to globality information associated with a well-known brand

like McDonalds may improve attitudes toward the brand and purchase likeli-hood (Dimofte, Johansson, & Ronkainen, 2008). However, an alternative, con-

structionist view of attitudes argues that consumers may in fact create attitudestoward global brands on the spot in a particular context (in other words, con-sumers may infer their attitudes from observing the ambient stimuli in a salient

context and recalling their past behavior in such contexts; see Wilson & Hodges,

1992).

1 Although implicit social cognition is a naturally broad topic and involves a variety of constructs,the focus of this article is on attitudes because of their immediate theoretical and practical rel-evance to the consumer psychology field.

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To accommodate these two accounts, Wilson, Lindsey, and Schooler (2000)

proposed that when an individual is exposed to an object, the persons initial atti-tude toward it is automatically retrieved, although salient aspects of the contextare also brought to bear in producing a response. Whether the initial attitude

or the novel information is given more weight can vary, as described by severalclassic models of attitude formation and change, such as Chaikens heuristic-

systematic model (Chaiken, 1980) and Petty and Cacioppos Elaboration Likeli-hood Model (Petty & Cacioppo, 1986).At the end of the process, a novel attitudeis created and the old one is generally overwritten. However, when both the ini-tial attitude and a newly formed one toward the same object are stored in memory,

a dual attitude can result (Wilson, Lindsey, & Schooler, 2000; also see Cohen &Reed, 2006; Petty, 2006).The classic case of vice behaviors illustrates a situationin which the implicitexplicit discrepancy comes into play. In this example,

explicit attitudes may involve an individuals conscious acknowledgment thatengaging in a vice behavior is bad, whereas implicit attitudes point to a more

positive underlying valence (see Fitzsimons, Nunes, & Williams, 2007). For a

McDonalds customer, recently acquired knowledge of the negative aspects offast food consumption (e.g., increased obesity levels or risk of heart disease)

may lead to a downward adjustment of explicit attitudes toward the brand andperhaps (but not necessarily, as we will see below) reduced patronage of thechain. However, it is likely that the individual will continue to show a positive

predisposition toward the brand and perhaps exhibit a smile when passing bythe restaurant and absorbing the enticing smell of the golden french fries.In short, whereas a consumers explicit, conscious attitudes toward a brand may

become more negative, implicit or nonconscious attitudes may yet retain theirhighly positive automatic brand associations.

Petty, Briol, and DeMarrees (2007) Meta-Cognitive Model proposes that atti-tudes consist of stored evaluative associations (positive and/or negative) along withaccompanying true/false validity tags. Unlike the dual attitudes approach of

Wilson, Lindsey, and Schooler (2000), this model argues for one integrated atti-tude representation and accommodates the potential discrepancy betweenimplicit and explicit attitudes via the conscious consideration of the validity tag

in the latter case (Petty, Briol, & DeMarree, 2007). In our example, McDonaldsmay well elicit positive automatic thoughts, but they are largely tempered by anegative cognitive tag that our consumer retrieves when creating an explicit

attitude toward the brand.

Whether speaking about attitudes, goals, or even self-esteem, it is possible thata certain level of dissociation exists between constructs at the conscious, effort-

ful processing level and their nonconscious, implicit variants. Wilson, Lindsey,and Schooler (2000) reviewed such disparities between implicit and explicit con-structs as varied as memory, attachment, dependency, and explanatory style.

Importantly, these differences have direct relevance for the specific type of behav-ior that follows,and therefore an accurate understanding of the implicitexplicit

construct distinction is conceptually critical. Once this dichotomy is acknowl-edged, the next step will necessarily involve a similar dichotomy in terms of theappropriate measurement instruments.

The ImplicitExplicit Measure Distinction

Explicit measures rely on individuals self-reported assessments of the specificattributes or their intentions regarding potential behaviors and choices they

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face. Responses are often registered on Likert scales, by means of which indi-

viduals select numerical values to express the degree to which they possess anattribute or plan to engage in a particular behavior. This approach naturallyassumes that individuals have conscious access to the relevant constructs in

memory and that responses are not determined on the spot, as the construc-tionist model of attitudes suggests (cf.Wilson & Hodges, 1992). If either of these

assumptions is not satisfied, the validity of the respective item or scale sufferssignificantly.

Other problems plaguing explicit measures have been widely acknowledged.For example, they may induce poor comprehension (due to complex or unclear

wording), social desirability (due to perceived pressure to provide socially accept-able answers), acquiescence (due to a misplaced propensity to indiscriminatelyagree to items regardless of content), or extremity of response (for a more com-

prehensive review, see Oskamp & Schultz, 2005). On the other hand, implicitmeasures are arguably free of such methodological shortcomings and hold the

advantage that individuals may not realize what is being measured or be able

to consciously correct their answers within the allotted time constraints.According to De Houwer and Moors (2010), a measures implicit character is

determined by whether the processes involved in measuring the attribute areautomatic. For example, automatic processing occurs in the absence of particu-lar processing goals on the part of the individual or operates even when the

person is unaware of the object prompting the process. Different implicit meas-ures can thus be implicit (i.e., automatic) in different ways, and one shouldspecify the automaticity feature that characterizes the respective measure

(De Houwer & Moors, 2010).Implicit measures of attitudes are often structured to assess whether infor-

mation processing is facilitated (i.e., shorter latencies) or hindered (i.e., longerlatencies) by the presentation of an attitude object (Gawronski & Bodenhausen,2007). Facilitation or impairment reflects the (lack of) compatibility between

the process engaged by the activation of the attitude and some other process-ing demand. De Houwer (2003) dichotomized this difference into two processes,response compatibility (driven by the match between the tendencies associated

with two different tasks, as in the Stroop paradigm) and stimulus compatibil-ity (driven by semantic similarity, as in lexical decision tasks). Both of theseprocesses make responses to implicit measures, unlike those to explicit meas-

ures, difficult to control.

Despite the general enthusiasm associated with the emergence and use ofthese novel methodological tools, several researchers have argued that more

rigorous study is needed to better understand the value of implicit measures.For example, the fact that a particular construct is assessed via an implicitmeasure does not necessarily imply that the construct is an implicit or non-

conscious one, but instead may simply suggest that motivational influences thatoccur downstream from attitude elicitation play a key role (as suggested by the

MODE dual process model of Fazio & Towles-Schwen, 1999). At the same time,the finding that different implicit measures of the same construct often do notcorrelate very highly is not encouraging and begs for more inquiry into this

problem (Fazio & Olson, 2003; Payne, Burkley, & Stokes, 2008).In general, implicit and explicit constructs in a consumption context are

well aligned and correlate highly. However, this is not always the case.

In fact, it is in the very instance when this alignment is lacking that research

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findings have shown extremely interesting results. Here we turn to consumer

research involving the most popular of the measures of implicit attitudes, theImplicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998).

IMPLICIT MEASURES IN CONSUMER RESEARCH

The psychology literature has been prolific of late in introducing a variety ofimplicit measures of cognition (see De Houwer & Moors, 2010, for a list of as manyas 17 examples). The most commonly employed (and debated) measure has been

the IAT (Greenwald, McGhee, & Schwartz,1998); as its popularity has expanded,specific applications have emerged in the consumer research literature. Othersuch measures have also found their place in consumer applications, as dis-

cussed next.The IAT assesses automatic associations between a bipolar target (e.g., com-

peting brands such asNikevs. Reebok in a marketing context) and a bipolarattribute concept (e.g., fastvs. slow) through a series of categorization tasksthat require quick responses (see Schnabel, Asendorpf, & Greenwald, 2008).

Shorter response latencies are expected to emerge when strongly associatedconcept pairings are elicited (e.g.,Nike and fast, based on perception that Nikeshoes provide better athletic performance) and share a common response key as

compared to when they do not. In a typical IAT, the first block instructs partic-ipants to press the D key when a Nike logo appears on the screen and the Kkey when a Reebok logo pops up. In the following block, participants are trained

to press D forfast words (e.g., speedy, quick) and K for slow words (e.g., slug-

gish, lethargic).The next, critical block combines the two discrimination tasks,such that participants are instructed to press D forNike or fast and K for

Reebok or slow. Naturally, there are also single and combined discriminationblocks that reverse the key assignment (i.e., such that Reebok logos are responded

to with a press of the D key and thatNike and slow share a response key). Theorder of the combined blocks is usually counterbalanced across participantsin order to control for the fact that IAT scores show stronger associations for cat-

egories that are paired (and learned) first. Recorded latencies in the combinedtasks are then used for calculation of IAT scores, which are generally computedas the difference between mean response latencies to the second combined task

and to the first combined task (Greenwald, McGhee, & Schwartz, 1998). Ifresponse management is attempted (say by a Reebok employee who is a closetfan of Nike or vice versa), response latencies and error rates increase notably.

Detailing the specific scoring algorithms that can be used to measure the IATeffect is beyond the scope of this review, but analysis of reliability and validitysuggests that the measure has good psychometric properties (Greenwald et al.,

2009a; Maison, Greenwald, & Bruin, 2004).According to Schnabel,Aspendorpf, and Greenwald (2008), much of the strength

of the IAT comes from the fact that many social objects seem to have natural coun-terparts (e.g., males vs. females, whites vs. blacks, or even McDonalds vs. BurgerKing and Microsoft vs. Apple). Yet that is perhaps one of its weaknesses as well,

since as a relative measure the IAT effect always involves a dual explanation.Thus, it is not necessarily clear whether the IAT effect described in the exampleabove stems from an automatic association ofNike and fast or, alternatively, one

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between Reebok and slow.2Although this may not be a major problem in a mar-keting context (i.e., the relative implicit preference for the two brands is clearly

established), in cases where associations with unipolar concepts are of interest,other implicit measures may be more appropriate. Along these lines, the SingleCategory IAT (SC-IAT; Karpinski & Steinman, 2006; Steinman & Karpinski,

2008) employs a single unipolar element (e.g., Exxon) and one bipolar concept

(e.g.,goodvs. bad) but otherwise features a procedure similar to the IAT.The Go/No-Go Association Task (GNAT; Nosek & Banaji, 2001) is another

example of an implicit measure. Like the IAT, it works by presenting various stim-uli for brief periods of time that require prompt responses. However, unlike theIAT, the GNAT requires the same response (i.e., gopress the space bar) to

items that belong to a category (e.g., insects) and an evaluative attribute (e.g.,good). No response (i.e., no-godo not press any key) is expected when items do

not belong to the target category and attribute (i.e., are distractors; see Nosek &Banaji, 2001). In a consumer context, Bassett and Dabbs (2005) employed theGNAT to show that smokers had less negative implicit attitudes toward smok-

ing than nonsmokers, although for both groups the GNAT correlated positivelywith explicit self-reports.

Finally, the Breadth-based Adjective Rating Task (BART; Karpinski et al.,

2007) is an indirect paper-and-pencil measure of consumer attitudes that isbased on the premise that individuals tend to describe expectancy-consistentinformation with more abstract and generic traits, whereas expectancy-

inconsistent information is captured via more concrete and specific traits. Thisabstraction bias is captured in the BART by having participants rate howwell trait adjectives of varying breadth and valence describe an attitude object

(Karpinski et al., 2007). Initially developed in the context of information describ-

ing the self and interpreted as an indirect expression of a persons level of self-esteem, the measure has found use in consumer contexts as well (e.g., Steinman &Karpinski, 2009).

There are two general situations that warrant researcher recourse to implicit

measures in order to reliably and validly capture consumer processing of, andresponse to, marketing stimuli. The first is the case of self-presentation biasesthat often plague marketing research data. To the extent that survey or exper-

imental response items create consumer discomfort or entail the risk of therespondent coming across as less sophisticated, open-minded, or knowledgeablethan is socially acceptable or expected (Kihlstrom, 2004), conscious adjustments

may be undertaken that alter or even hide objectively true responses.The second instance that may produce biased feedback is one of consumers

lacking conscious access to their own cognitive processes or information stored

in memory. Explicit measures may simply be inadequate to capture these typesof data. In these situations, a theoretically interesting dissociation of explicit and

implicit responses may occur, and the immediate question of whether explicitor implicit measures of cognition are more predictive of actual behavior becomesdirectly relevant. The self-presentation bias and the lack of awareness cases

are each explored next.

2 Others have also noted that what the IAT picks up is not an implicit attitude, but in fact extra-personal associations created by exposure to widely disseminated social knowledge (see Olson& Fazio, 2004; Schwarz & Bohner, 2001). Thus, an effect on the NikeReebok IAT favoring theformer brand may in fact emerge even for consumers who explicitly prefer Reebok,merely becauseof Nikes marketplace dominance.

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Consumer Conscious Adjustment of Explicit Responses

In a consumption environment that features ever-changing social trends andnorms, deviant attitudes and behaviors are often not readily admitted. Con-sider the case of consumers queried about their recycling behaviors and attitudes

toward recycling. It is likely that because of the enhanced pressure to think and

act in an environmentally conscious manner in todays society, many respon-dents may be reluctant to express unfavorable attitudes toward recycling or

admit that they routinely fail to recycle.Accordingly, they may engage in responsemanagement strategies to conceal their true attitudes and instead provide

socially desirable answers (see Meneses, 2010), which can lead to invalid infer-ences regarding their attitudes and behavior. A recent illustration of this effectwas provided during the 2008 presidential electoral season. The American vot-

ing public was polled by a variety of national media outlets,but a significant num-ber of individuals also took IAT tests that measured their implicit preferencesfor the two main candidates on an Internet Web site sponsored by an academic

institution. Notably, whereas the electoral polls varied widely in their predictionsand many were unable to clearly predict a winner given their margins of error,the IAT proved highly reliable in predicting the winning candidate (Greenwald

et al., 2009b). It appears that revealing preferences to a pollster (or a marketer,for that matter) is less honesty-inducing than responding to an implicit measure.

In the same vein, Brunel, Tietje, and Greenwald (2004) assessed consumers

behavioral and attitudinal responses to spokesperson race in print advertising.Social psychology research had uncovered relatively low correlations between

explicit and implicit measures of racial attitudes, which is in line with the expec-tation that respondents consciously adjust their answers due to a self-presentation

bias (Greenwald, McGhee, & Schwartz, 1998). Brunel, Tietje, and Greenwald(2004) exposed subjects to advertisements featuring celebrity spokespeople ofeither Caucasian or African American ethnicity. An interesting interactionoccurred between viewer ethnicity and type of measurement of respondents

attitudes toward the advertisement. Explicit self-report measures administeredto Caucasian consumers were unable to detect any preference for a same-ethnicity spokesperson advertisement, whereas the IAT identified a significant

pro-Caucasian preference among the same respondents. Alternatively, AfricanAmerican consumers self-reported an explicit preference for ads featuring same-

ethnicity endorsers, but this effect was absent in the IAT. These results suggestthat response management strategies may have been employed by both ethnicgroups, driven by the perceived pressure to provide socially desirable or group-

consistent responses.Individuals are generally adept at engaging in a variety of cognitive defen-

sive mechanisms in order to detect and protect the self from threatening incom-

ing information. For example, in the domain of romantic relationships,researchers find evidence for a specific risk regulation system designed to dealwith risky relationship situations (e.g., Murray, Holmes, & Collins, 2006). In

this context of romantic relationships, Dimofte and Yalch (2010a) exposed sub-jects to information according to which a recent survey in the studys geographiclocation had uncovered a 3:1 ratio of females to males in the population.

The immediate implication that it is much easier to date someone as a malewas immediately salient to all respondents, including females for whom this

novel information (factually true and therefore highly credible) was directlythreatening. However, in line with classic findings on self-enhancement, these

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female respondents claimed that future dating in the respective location would

not be a more difficult task when asked about it on explicit measures.This con-scious, self-protective adjustment in self-reports was not possible on the IAT,which revealed stronger automatic associations between dating and difficult

(than between single and difficult) for the threatened female respondents, includ-ing those in committed romantic relationships at the time of the study (Dimofte &

Yalch, 2010a).Finally, recent research by Dimofte, Brumbaugh, and Goodstein (2010) on

the topic of consumer response to target marketing is germane to the point thatindividuals may choose to conceal their true responses in explicit self-reports.

Over time, many product categories develop associations with particular userprototypes in the consumers mind regarding who it is that tends to buy theparticular products (e.g., environmentally conscious, progressive urban dwellers

are hybrid car buyers). Yet some of these prototypes may not always fit withthose brand managers had considered when developing their targeting strate-

gies. In these cases, it could be argued that the marketplace has in effect cre-

ated an undesirable product association (i.e., because the prototype is overlynarrow or perhaps even completely off the mark relative to the firms initial

positioning). When firms create target advertising for such products, the userprototype knowledge is automatically activated and the response to advertisingis often driven by the way the consumer compares to the prototype (and not to

the ad-suggested target customer). In this case, if the user prototype is a mem-ber of an out-group relative to the consumers in-group, a social comparisonprocess is engaged. If this group comparison is unfavorable to the consumer

(say for a Caucasian male exposed to advertising for basketball shoes associatedwith an athletic African American product user prototype), a decline in collec-

tive self-esteem may ensue, leading to unfavorable advertisement and productattitudes (Dimofte, Brumbaugh, & Goodstein, 2010). These declines are notreadily observed in explicit self-reports, as subjects may guess the reason why

ethnic collective self-esteem questions are being explicitly asked after exposureto the ad and may choose to artificially inflate their estimates. However, theseself-esteemenhancing adjustments are not as likely to occur with implicit meas-

ures, as these authors observed. In fact, results suggested that individualsimplicit self-esteem (captured via their IAT effect size) fully mediates theresponse of consumers to target advertising that elicits threatening user pro-

totype knowledge (Dimofte, Brumbaugh, & Goodstein, 2010).

Consumer Lack of Awareness of Implicit Responses

It has been argued that the nonconscious nature of some consumer cognition

resides in individuals lack of awareness for a variety of processing-related ele-ments. For example,Chartrand (2005) suggested that consumers may be unawareof the external cues that prompt the engagement of an automatic cognitive

process, of this process itself, or of its outcomes. In other words, a TV viewerexposed to a commercial for Jackson Hewitts tax preparation service may beunaware that the ads slogan (Get more in return) has triggered an automatic

processing of its multiple meanings, that the secondary meaning has beenaccessed and comprehended, or that an ad hoc perception has emerged accord-

ing to which this tax service is simultaneously perceived as more affordableand better at getting deductions. In fact, that is precisely what Dimofte and

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Yalch (2007a) found in their research on polysemous (i.e., multiple-meaning)

brand slogans. For a cellular phone provider that employed the slogan Raisingthe Bar to effectively convey two brand-favorable information cues (i.e., supe-rior service relative to competitors and more signal bars when using the com-

panys network), many consumers unexpectedly had more negative attitudinalresponses to the brand than did those in a control group exposed to the slogan

Redefining the Best. Yet the reason for the negative attitudes was not appar-ent when exploring participants elicited thoughts, suggesting that self-reportmeasures may be inadequate when it comes to fully capturing the languageprocessing effects involved in consumer response to polysemous slogans. How-

ever, an IAT juxtaposing the respective cellular provider with a direct competi-tor using the evaluative categories affordable and expensive uncovered novelautomatic associations between the advertised brand and perceptions of expen-

siveness.While certainly inadvertent and unintended on the part of the marketer,consumers apparently implicitly accessed a negative secondary meaning of the

brand slogan, according to which they perceived that the firm raised the bar in

terms of jacking up the prices it charged for its high-end service (Dimofte &Yalch, 2007a).

In a similar fashion, the expression going down fast in Aspen, employed tosuggest the quality of the mountain resorts ski slopes, was instead implicitly (butnot explicitly) construed by study respondents to imply the deteriorating qual-

ity of the resorts services over time, an effect certainly opposite to that intendedby the advertiser (Dimofte & Yalch, 2007b). Importantly, in both cases consumersfailed to mention the negative slogan aspects in self-reports, but demonstrated

the implied negative associations via the IAT.Forehand and Perkins (2005) used self-report and the IAT to assess consumer

response to advertising using celebrity voices.They found that liking a celebrityproduced a positive response to advertising featuring the celebritys voice, butonly for consumers who were unable to recognize the celebrity. However, con-

sumers who recognized the celebrity, were motivated to eliminate irrelevantinfluences on their advertising response, and were able to consciously adjusttheir explicit response did not exhibit the same effect. The authors argued

that the explicit measure adjustment involved a correction of the perceivedinfluence of the celebrity (i.e., resetting) because of its actual irrelevance. Thisresetting implied a conscious evaluation that the IAT did not allow for, leading

to the emergence of dissociation between the explicit and implicit results. This

work (as well as that of Dimofte & Yalch reviewed above) shows the value ofthe IAT as a methodological tool for capturing cognitive processes that under-

lie effects observable on explicit measures of attitudes but not easily explainablefrom consumer self-reports (see Perkins et al., 2008 for a similar argument).

In evaluating consumer attitudes toward genetically modified foods, Spence

and Townsend (2006) employed the GNAT to show that context-free implicitattitudes were in fact relatively positive, although corresponding explicit self-

reports were neutral. At the same time, a downshift was observed when GNATmeasurement occurred in the context of organic foods, as implicit attitudestoward genetically modified products were found to be neutral but not negative

(Spence & Townsend, 2006). These results suggest that consumers have auto-matic approach tendencies toward these foods despite indifferent explicitattitudes. Since self-report measures did not show a reported preference

for non-modified products (as self-presentation bias might have suggested),

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it appears the positive implicit effects are driven by consumers lack of aware-

ness of the actual favorable attitudes they show toward these products at non-conscious levels.

The largely positive behavioral response that American consumers have

toward global brands was the focus of research by Dimofte, Johansson, andRonkainen (2008). Unlike respondents in developing nations, who display an

explicit preference for these brands due to their aspirational nature, U.S. con-sumers reported seeing no particular benefit or value associated with globalbrands (be they American or foreign). In a study employing a nationally repre-sentative panel of respondents recruited via the Internet, who presumably had

no self-presentation motives, the only explanation for the favorable behavioraleffect that global brands engendered (i.e., higher purchase levels thanattitudebehavior consistency models would predict) was that U.S. consumers

harbor positive implicit attitudes toward global brands. Indeed, an indirect testshowed that an individual described along several attributes was liked better

if presented as a global (vs. local) beer drinker, whereas an IAT uncovered

implicit associations favoring global over local brands (Dimofte, Johansson, &Ronkainen, 2008).

Psychological research introduced a shifting standards model of evaluations(Biernat, Manis, & Nelson, 1991) according to which individuals routinely adjusttheir subjective (but not objective) judgment standards as they evaluate mem-

bers of stereotyped social groups. For example, women are stereotypicallyexpected to earn less than men if judged in annualized dollar amounts, but theyare at the same time not expected to be less financially successful than men.

(In fact, Biernat, Manis, & Nelson, 1991, found that the very same women earningless than men were perceived to be more financially successful than those men;

thus, for a woman, such financial performance was quite impressive). Alongthese lines, Dimofte and Johansson (2009) uncovered the existence of a similarshifting standards effect in marketing with respect to consumer brand evalua-

tions. They found that for inferior brands that engender strong expectations,consumers unconsciously lower their evaluative standards and cut them slackwhen responding to word-based, subjective scales (but not to number-based,

objective scales). In other words, a Hyundai engine that puts out 150 hp is objec-tively unimpressive,but in subjective terms (i.e., on a scale anchored by not pow-erful at all and extremely powerful), a horsepower rating at that level sounds

pretty goodfor a Hyundai. The automatic nature of this adjustment was cap-

tured via the IAT and further demonstrated by consumers lack of acknowl-edgment that they had engaged in the evaluative shift when informed about it

on a post hoc basis (Dimofte & Johansson, 2009).Priluck and Till (2009) examined consumer brand perception with a stan-

dard, explicit brand equity scale as well as the IAT in order to spot instances

when the two may diverge. Their findings suggest that for clearly distinguish-able brands such as those of high versus low equity, both the IAT and the explicit

brand equity scale were successful in capturing differences in perceptions. How-ever, when two brands were less distinguishable in explicit terms, the IAT uncov-ered an implicit consumer preference for the pioneering brand that was not

apparent from explicit brand equity measurement (Priluck & Till, 2009).Early work on rumor processing and acceptance by Tybout, Calder, and

Sternthal (1981) found that strategies other than refutation are more useful for

quelling unfavorable brand rumors (such as the actual marketplace report at

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the time according to which McDonalds burger meat contained red worms).

This is an important issue because despite explicit disbelief in the story, sub-sequent brand attitudes and purchase intent measures displayed significantdeclines. Astorage rumor quelling strategy, for example, involved exposing con-

sumers (simultaneously with the rumor) to novel information cues about the neg-ative contaminant (e.g., red worms are used in high-end French cuisine).The strat-

egy proved successful, although explaining the precise mechanism throughwhich it operated was left unaddressed. For example, it could have been that theextra information cues interfered with the creation of a brandcontaminantassociation or that the positive valence of this information made the contami-

nant less objectionable (Tybout, Calder, & Sternthal, 1981). To disentangle thesealternative explanations, Dimofte and Yalch (2010a) employed the IAT to demon-strate that the brandcontaminant automatic association is quick to emerge

and cannot be suppressed, but the positive nature of the new information aboutthe contaminant significantly improves implicit attitudes toward it (thus, worms

are somehow not that bad after all and therefore the rumor is less damaging to

the brand).Finally, Dimofte and Yalch (2010b) introduced a mere association effect in

the context of consumer information processing, which was driven by an inabil-ity to suppress automatically activated but irrelevant brand associations.In one of their studies, participants were asked to rate 20 academic institutions in

terms of reputation as party or work-intensive schools, respectively. The twofocal institutions were USC and UCLA, with the latter perceived to be more ofa party school at statistically significant levels. Subsequent exposure to a series

of brand logos that included that for Trojan condoms (vs. a control condom brand)was conducive to the emergence of an implicit association between USC and

play (captured on the IAT), which in effect reversed prior explicit perceptions.Thus, the mere fact that the Trojan construct is associated with both condomsand the athletic teams of an academic institution produced an automatic trans-

fer of attributes between the two that logically should not have occurred. Theeffect was also observed on evaluative judgments. In a different study, con-sumers exposed to the wordfrog were more likely to choose a wine bottle fea-

turing a frog on its label, but the word warts (as a negative associate of toadsand frogs) produced avoidance behavior for the same label instead (Dimofte &

Yalch, 2010b). This research is informative regarding the unexpected and poten-

tially damaging effects that may occur when specific primes are paired with

brand names, despite the fact that the mere association effect should be con-sciously suppressed. Importantly, implicit measures are critical in demonstrat-

ing and explaining their underlying associative mechanisms.

The Predictive Power of Implicit Measures forConsumption Behavior

Fazio and Olson (2003) reviewed evidence for the predictive validity of implicit asso-

ciations, in particular studies examining priming, the IAT, and other implicitmeasures (e.g., the word fragment completion task). They argued that individ-

ually these measures seem to predict subsequent behaviors. However, they alsocautioned that implicit measures show surprisingly low correlations with eachother, largely due to their low reliability and large measurement error (Fazio &

Olson, 2003).

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and added to the specificity of prediction above and beyond explicit attitude

(Steinman & Karpinski, 2009). Similarly, Maison, Greenwald, and Bruins (2004)limited meta-analysis of several studies employing both the IAT and explicitmeasures of consumer attitudes confirmed that the use of implicit measures

enhances the predictive ability of consumption behavior relative to that of explicitmeasures alone.

Finally, Chan and Sengupta (2010) further qualify the correspondence betweenimplicit/explicit attitudes and implicit/explicit behaviors. In their work on con-sumer flattery, individuals who were complimented by marketers in targeted com-munications reported awareness of the firms ulterior motive but had difficulty

adjusting for it (Chan & Sengupta, 2010). Instead of being replaced by a dis-counted explicit judgment, an implicit favorable reaction to flattery continuedto exist along with it, which is in line with the dual attitude theory reviewed above

(e.g., Wilson,Lindsey, & Schooler, 2000). Importantly, the attitudebehavior cor-respondence account was found to operate for immediate measurement, but a

reversal occurred after a delay, such that implicit attitudes (measured similarly

to explicit attitudes but with significantly longer time to respond) were in factmore predictive of behavior (store coupon choice from the ingratiating marketer

or a competitor).

DISCUSSION

Research evidence reviewed in this paper highlights recent methodologicaladvances in the area of implicit social cognition and their relevance to consumerpsychology. Rooted in the conceptual distinction between implicit and explicit

facets describing a variety of psychological constructs, a parallel dichotomy hasbeen proposed relative to the specific measurement instruments to capturethese constructs. The implicitexplicit distinction is of particular concern in two

instances of consumer response to marketing stimuli. First is the case in whichresponse management strategies are engaged and socially desirable or self-

enhancing responses are provided in self-reports. In this case, individuals maybe unwilling to provide the researcher with their true appraisals of the measuredconstruct, rendering their explicit feedback invalid for purposes of assessing their

underlying sentiments or intentions. Second is the case in which the implicitnature of the construct being measured or other related psychological processes

makes these true ratings inaccessible for respondent introspection. When thisoccurs, the individuals bona fide efforts to provide accurate representations ofthese constructs or processes simply fall short on grounds of inaccessibility.

The value of implicit measures thus resides in their potentially superior abil-

ity to gather accurate construct measurement data despite consumers reluctanceor inability to provide them. In some of the work cited here, implicit measureswere differentially qualified to capture cognitive processing effects that would

otherwise be unobservable and left open to theoretical interpretation and debatein a manner reminiscent of behaviorisms black box paradigm. In other cases,

implicit and explicit measures displayed unexpectedly low correlations,prompting

consideration of more comprehensive theoretical frameworks that feature richerconceptual understandings.Finally, the fact that implicit measures were shown to

display relatively high levels of predictive validity is an important considerationin a field concerned with understanding and predicting consumer behavior.

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It also seems apparent that the IAT has emerged as the most preferred meas-

ure of implicit attitudes.The reasons for the IATs attractiveness to researchersmay have to do with its relatively good fit with the consumer research enterprise.The dual-category design is a great match for marketplace scenarios that jux-

tapose two direct competitors, while its general use in between-subjects designsavoids some methodological and interpretation issues raised in psychological

research based on within-subject responses. It is also useful in situations fea-turing attitudinal ambivalence toward specific brands, as it allows for the emer-gence of more clearly defined automatic preferences once the burden of cognitiveelaboration across a multitude of attributes is lifted.

Much of the research involving the IAT has been squarely focused on meas-uring implicit attitudes, at the expense of richer contexts, such as those involv-ing assessment of memory or self-esteem, where the measure has significant

potential as well. Moreover, future consumer research should expand the use ofimplicit measures beyond the IAT to perhaps the GNAT (uniquely suited to

address single-brand implicit effects), the BART, or other, less common, method-

ological tools from social psychology (see Schellekens, Verlegh, & Smidts, 2010,on consumer use of language abstraction in word of mouth).

Other areas of great potential involve the application of classic effects frompsychological research to the consumer domain in which implicit measures canbe used to assess specific underlying mechanisms. For example, Dijksterhuis

et al. (2006) have proposed that making optimal choices in complex situationsentails nonconscious rather than conscious deliberation (e.g., deliberating inter-nally in the absence of attention and effortful processing).The implications that

this effect carries for consumer research are significant, and understanding whythese choices produce better results and greater satisfaction provides a research

opportunity that is both intriguing and appealing. If specific product attributesare perhaps erroneously overemphasized during explicit choice consideration,their reduced salience and importance in nonconscious deliberation invites

researchers to consider other avenues of research, such as measurement ofimplicit responses.

In the end, the increasing popularity of implicit measures in mainstream

consumer psychology and the emergence of findings based on their use thatshed new light on a variety of consumer phenomena are encouraging. Morework is needed, though, in order to demonstrate their usefulness to a wider con-

stituency and highlight their incremental contributions in the field of market-

ing and advertising research. As the knowledge base on the topic widens,replication work, meta-analyses, and more comprehensive reviews will con-

tribute to a better assessment of their future place in the fields methodologicalarsenal.

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