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Individual Susceptibility to Priming Effects
STACY WOOD*
University of South Carolina
CAIT POYNOR
University of Pittsburgh
TANYA L. CHARTRAND
Duke University
*Stacy Wood is Moore Research Fellow and Associate Professor of Marketing at the
Moore School of Business, University of South Carolina, Columbia, SC 29208, [email protected]. Cait Poynor is an assistant professor of marketing at the Katz
Graduate School of Business, University of Pittsburgh, Pittsburgh, PA 15260, [email protected]. Tanya L. Chartrand is professor of marketing and psychology at the Fuqua School of Business, Duke University, Durham, NC 27708, [email protected].
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Do individuals differ in their susceptibility to priming effects? If so, who is most vulnerable to priming influences? Conventional wisdom suggests that priming influences
(especially those embedded in persuasive messages or advertisements) are most likely to exploit vulnerable individuals, such as those with low literacy levels or cognitive ability.
However, an examination of the theoretical basis for priming suggests the opposite: individuals with high cognitive capacities in attention and associative thinking may be more strongly influenced by primes. Here, we propose a simple 6-item Susceptibility to
Priming (STP) index. We demonstrate the efficacy of this index in explaining magnitude of priming effects in three experimental studies. By identifying a generalized individual difference in STP, this research contributes theoretical insight into the priming mechanism, policy-relevant insight regarding the use of priming stimuli in marketing messages, and an empirical tool for identifying stronger effect sizes in priming research.
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“However, the very ubiquity, and relative ease of obtaining these [priming] effects, as well as the rather surprising and dramatic effects that ‘mere’ priming can have raises many important ‘second-generation’ questions, for instance:…Are there individual differences in priming effectiveness...”
John Bargh, 2006
Priming research demonstrates the widespread ability of incidental exposure to stimuli to influence how individuals set goals, evaluate objects, report attitudes, and engage in behavioral responses (for reviews, see Dijksterhuis, Chartrand and Aarts 2006;
Bargh and Chartrand 1999). It is not surprising that priming has been widely investigated as a form of influence in marketplace persuasion, especially in advertisements (e.g.,
Forehand and Deshpande 2001; Mandel 2003; Pechmann and Knight 2002). The consumer behavior literature has traditionally supported the belief that “subliminal advertising” does not work, but this belief has been brought into question by recent and robust demonstrations of nonconscious priming effects (Bargh 2002).
If priming effects may indeed be effectively employed in persuasive media, then are some individuals more impacted by that imperceptible influence? We seek to answer this question by systematically exploring a broad array of individual difference factors to determine what may lead some individuals to exhibit an increased susceptibility to priming (STP). Variance in prime efficacy has often been reported both across studies and within studies, leading researchers to wonder if priming efficacy depends, in part, on specific characteristics of the individual (e.g., Ansorge 2004; Cheng and Chartrand 2000; van Baaren et al. 2003). This question becomes increasingly interesting in light of potential applications of priming within persuasive messages. Consumer behavior research has often identified consumers who are vulnerable to persuasive influence— especially unethical or “under the radar” persuasion tactics—to be those who are at risk
4 because of deficits in age, experience, or cognitive ability (e.g., Morgan, Schuler, and
Stoltman 1995). This is congruent with a long-standing societal perception of the vulnerable—those who need external protection and support—as weak, infirm, or unintelligent (Bremner 1994).
We propose that the mechanism by which semantic primes operate creates a unique situation where those most susceptible to priming effects are those we would consider most invulnerable according to conventional marketplace wisdom—decision-makers who are, broadly speaking, engaged and highly associative. We posit, first, that some individuals are more engaged with their surroundings, paying greater levels of attention to environmental cues which would enhance the likelihood or quality of their exposure to primes. Second, we argue that individuals may differ in their cognitive abilities— specifically, their innate tendency to engage in associative cognitive processing, thus impacting the magnitude a given prime may exert via spreading activation. Based on supporting evidence within the extant priming literature, we develop a simple index measure of STP that is based on an individual’s combined attentional and associational cognitive tendencies. We then test the STP index in three studies to assess whether it reliably explains differential priming magnitude across individuals.
These findings offer important insights to both theory and practice. For theory, the identification of individuals with increased susceptibility to primes provides further evidence of the cognitive processes and necessary individual factors that underlie priming effects. The STP index also provides a practical tool for future priming research as its use as a covariate can help uncover priming effects that may otherwise be obscured by individual differences in the research population. This is increasingly important as the
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“next generation” of priming research will look outside the lab in investigations of real world marketplace influence where individual variance is most likely to exist (Bargh
2006). For practice, these findings have important consequences for marketers and public policy makers who wish to identify those consumers most likely to be influenced by subtle cues in decision environments. For example, imagine the use of visual cues in a high school cafeteria that are designed to prompt students to make healthy lunch choices; our findings suggest that such cues might be least effective for “at risk” students.
Conversely, firms that target products to highly educated and involved consumers (e.g.,
Apple, Volvo) may be most encouraged to use primes as cues within marketing messages because of the cue’s efficacy in this population. In order to explore this issue, we first turn to a discussion of individual factors that may contribute to priming susceptibility.
PRIMING AND INDIVIDUAL SUSCEPTIBILITY
In one of the first notable demonstrations of priming, Higgins, Rholes, and Jones
(1977) found that participants exposed to personality concepts in an earlier task, later interpreted the ambiguous actions of an unknown individual (Donald) in line with the primed trait. Not long after, Herr (1989) used the priming paradigm to investigate pricing and product judgments. Since then, much work has investigated priming influence within persuasive domains. The great interest in priming research within consumer behavior has been driven by the broad range of responses that primes may influence. A prime may make particular elements of the environment more salient and thus more influential in later evaluations or may activate goal-states that are subsequently pursued until
6 completion (Bargh et al. 2001; Chartrand and Bargh 1996), may activate semantic schemas (e.g., Aarts and Dijksterhuis 2000; Bargh, Chen and Burrows 1996; Macrae and
Johnston 1998), or may encourage behaviors, evaluations, emotions and even processing styles which are consistent with a given prime (e.g., Meyers-Levy 1989; Winkielman,
Berridge and Wilbarger 2005).
In his agenda for future priming research and theory building, Bargh (2006) explicitly ponders the potential for individual differences in priming effectiveness. Extant priming research illustrates that the efficacy of a given prime relies on two basic requirements—first, that physical (perceptual) exposure to the prime occurs and, second, that this leads to a spreading activation of associated concepts. This conceptualization guides our index generation process in that it suggests that individual differences in attention to the environment may impact the former requirement and differences in associative thinking may impact the latter. Thus, we begin with the idea that individual susceptibility to priming may be viewed as an aggregation of both attentional and associational differences.
Individual Tendencies to Attention
Priming most obviously requires that a cue be perceived by the primed individual.
Conscious awareness of perception is not necessary; in fact, some evidence suggests that increasing consciousness of exposure can reduce priming efficacy (Bornstein and
D’Agostino 1992). Yet, weak or non-existent priming effects can be due to a failure of
7 sufficient physical exposure. Ansorge (2004) has demonstrated this “collicular contribution” to priming by showing that primes presented in weak visual fields have less impact than those presented in strong visual fields. Similarly, increasing prime strength, which may increase physical exposure, can lead to stronger priming effects (Srull and
Wyer 1979).
We posit that individuals who more closely attend to their environments will demonstrate stronger priming effects. In examining priming efficacy variance within the literature, there are some examples where one may infer that differing efficacy is influenced by a broader attentional proclivity (i.e., the extent to which an individual attends to his/her environment). First, greater task involvement is associated with greater prime efficacy in that priming effects are stronger for participants than for observers
(Monahan and Zuckerman 1999). Participants are likely to have more attention deployed with the source of the prime than are observers. Second, increased attention to the environment is often evident in patterns of proactive social interaction. This has been demonstrated in a number of related ways with recent research showing that high levels of self-monitoring (Cheng and Chartrand 2003), self-consciousness (Hull et al. 2002), context-dependence (van Baaren et al 2004), and need for affiliation (Lakin et al 2003) correspond to stronger responses to primes. Such socially-aware individuals (e.g., those with a tendency to self-monitor, be interdependent, or value conformity) often pay a great deal of attention to their environment. Finally, support for an attentional influence can also be seen in evidence that attention to specific information within the environment, namely affective cues, may also lead to increased STP: Individuals’ increased attention to
8 affect-laden information may explain the role that affect plays in prime efficacy (Rottveel and Phaf 2004).
Individual Tendencies to Association
Priming processes have been shown to begin with the direction of attentional resources (Soto et al. 2005), but Davenport and Potter (2005) show that semantic priming impacts lexical identification processes as well – processes which rely on the associative network an individual possesses. Building on these findings, we argue that individual susceptibility to priming may also be a function of individuals’ tendencies or abilities with regard to activating associative thought patterns.
Primes direct thought to associated stimuli via spreading activation (Soto et al.
2005). Thus, the inhibitionless (e.g., Posner and Snyder 1975) and automatic (Bargh
1996) spreading activation of associated thought is a fundamental aspect of priming mechanisms. The idea that individuals differ in their tendency to associational thought patterns and that thought styles characterized by rich associational connections are a hallmark of creative thinking has a long history in psychology (see Barron and
Harrington 1981). If creative people utilize more fluid associational patterns, creativity may increase priming efficacy by providing a more “fertile ground” for cue activation.
Interestingly, then, we see that Shaw and Conway (1990) provide some support for this idea; they show that highly creative participants used more nonconscious cues that did those who had lower levels of creativity. Additionally, individuals differ in their tendencies to truncate associational elaboration, such as in their tendency to see situations
9 as ambiguous or multifaceted (e.g., closed mindsets) and in their tolerance for ambiguous situations (e.g., need for closure; Kruglanski, Webster, and Klem 1993; Webster and
Kruglanski 1994). Primes often show greater effects in ambiguous situations (Kay,
Wheeler and Bargh 2004; Shaw and Conway 1990), and of especial interest, Fiedler et al.
(2005) found that closed mindsets in individuals led to weakened priming effects. These findings suggest that, because priming influence depends on the activation of associational schemas, priming effects are likely to be enhanced for individuals whose natural tendency facilitates rather than inhibits associative thoughts.
The Susceptibility to Priming (STP) Index
Taking this evidence together, we propose that the quality of individual attention
(Ansorge 2004) and potential for spreading activation of associational schemas (Aarts and Dijksterhuis 2005; Bargh, Chen and Burrows 1996) are foundational for priming efficacy. Importantly, we recognize that while the attentional and associative facets of
STP are likely correlated within individuals, they need not be. Thus, we use an index measure where the individual’s tendencies to each facet may contribute independently to
STP. However, this said, attentional and associational components of cognition are closely related and most likely to show strong positive correlation at the individual level.
We build on this conceptual development to generate a simple 6-item reflective
STP measure. We first describe the measurement development process undertaken to create this index and then apply it in three studies. Most central to our research question, the three studies demonstrate that our index of STP does predict the magnitude of an
10 individual’s response to a prime with more susceptible individuals showing stronger priming effects than less susceptible individuals. Study 1 demonstrates that priming individuals with concepts of the elderly (akin to the “walking to the elevator” study by
Bargh, Chen, and Burrows [1996]) can influence susceptible consumers to “move slowly” in consumer domain, specifically in adversely affecting their attitude toward the speed of high tech product innovations. Study 2 demonstrates that a subtle work-oriented prime can alter prime-susceptible college students to report increased intentions to study.
Importantly, we also test these effects in a marketplace environment. Study 3 demonstrates that priming the concept of promotion versus prevention (Aaker and Lee
2006) within an advertisement can increase susceptible consumers’ valuation of a promotion-congruent product attribute (personal customization). These studies provide insight both into susceptibility to primes and to the nature of the prime itself: In some cases, the use of the index provides more nuanced interpretation of an apparently robust prime, showing that its overall effect is actually localized to only a subset of the population. In other cases, the use of the index allows a weak or marginally-significant aggregate effect of a prime to be understood as quite strong if only among a section of the sample. Before describing these studies, we first provide an abbreviated description of the development of the STP index.
MEASUREMENT DEVELOPMENT
We first conducted a simple measurement development process to construct a susceptibility to priming (STP) measure. Based on past evidence reflected in the literature
11 regarding the attentional and associational mechanisms driving priming effects, we began by generating six items expected to reflect STP – three related to attention and three related to association. We then used two separate samples (samples a and b) to explore the validity and reliability of this six-item index. We finally collected a number of other individual difference measures in order to test their relationship to STP and establish its uniqueness from other potentially related personality traits.
Method
Participants. Participants were 41 (57% female) undergraduate business students who participated in two research sessions conducted two weeks apart. All participated for course credit.
Method. During the first data collection session, participants completed the 6- item STP scale. The items were: (attention) “I am very attentive to my surroundings,” “I often notice when someone I know has a new haircut or outfit,” and “I like to pay attention to the environment around me,” and (association) “I tend to find lots of connections between different ideas,” “When someone tells me something new, I tend to find myself thinking about it long after the conversation is over,” and “Things I hear often trigger me to think about a lot of related issues.” All items were answered on a 7- point scale, where 1 was labeled “Strongly Agree” and 7 “Strongly Disagree.”
Two weeks later, all participants completed the same STP items again. After this, a
10-minute distracter task was followed by five unrelated tasks, among which were interspersed the Susceptibility to Interpersonal Influence scale (Bearden et al. 1999), the
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Verbalizer-Visualizer Style of Processing Scale (Childers et al. 1985), and a self-report of grade point average (GPA). We also collected an ad-hoc Need for Achievement Scale, which contained the items “I consider myself highly achievement-oriented,” “I am a person who has clearly-defined goals,” “A major part of my self-esteem comes from my achievements,” “I get bored if I’m not given new challenges regularly,” and “Feeling like
I’m making progress on things is extremely important to me,” all answered from 1
(strongly disagree) to 7 (strongly agree).
These scales were chosen in order to establish both convergence with conceptually- related traits and to establish that STP captures a distinct characteristic not completely associated with other more general measures. Specifically, it was expected that
Susceptibility to Interpersonal Influence (SII) might show a significant relationship with
STP. SII is defined as “The need to identify with or enhance one’s image in the opinion of significant others through the acquisition and use of products and brands, the willingness to conform to the expectations of others regarding purchase decisions, and/or the tendency to learn about products and services by observing others or seeking information from others” (Bearden et al. 1989, p. 474). Thus, high SII implies the importance of attention to one’s surrounds as well as the use of such information in subsequent decisions. Responses from the two data collection sessions were matched through the use of the last four digits of either the participant’s student ID or telephone number. We collected the Verbalizer-Visualizer scale in order to establish that STP taps into an underlying personality trait rather than simply into verbal or visual tendencies, since many primes used in empirical research are delivered visually and contain a verbal component. Our Need for Achievement scale was collected in order to see if STP simple
13 reflects a high degree of response to any task, or if it truly taps into a construct specific to the priming manipulations. GPA was collected in order to observe whether the attentional and associative aspects we expect to relate to STP could simply be captured as well by general academic performance – that is, is it simply the case that lower or higher achieving individuals possess more or less of these capacities and therefore, respond more strongly to primes?
Analysis and Results. In both datasets, the STP index showed acceptably high and similar levels of reliability. The six items were averaged (sample 1: α = .78, sample 2: α =
.74) to create an STP index at time 1 and time 2. When analyzed with all other items collected, we note that the STP items load together, and that no other items load on the
STP factor.
Test-Retest Reliability. Data was analyzed for evidence of test-retest reliability. The correlation in responses across the two collection periods was strong and significant (r =
.74, p < .0001), satisfying guidelines for acceptable test-retest reliability.
Convergent and Discriminant validity. The Susceptibility to Interpersonal
Influence (α = .82), Verbalizer-Visualizer (α = .80), and GPA measures were analyzed for their correlation with the STP measure taken two weeks earlier. The correlation between STP and Susceptibility to Interpersonal Influence was positive and marginally significant, consistent with expectations. However, this correlation does not indicate excessive overlap between the two constructs (r = .25, p = .09). The correlation between
STP and Need for Achievement was also positive, but not significant (r = .20, p = .20).
Finally, we observed that there was no tendency for high STP individuals to be particularly strongly verbal or strongly visual in their style of processing (r = -.18, p =
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.23), and that STP was not significantly associated with general academic performance (r
= .05, p = .73).
Discussion
These analyses suggest that the STP index is internally reliable and taps into a stable individual difference. In addition, these data suggest that the measure captures a tendency which is, as expected, somewhat correlated with but conceptually distinct from
Susceptibility to Interpersonal Influence, another individual difference which would be expected to involve both associative and attentional capacities. Additionally, STP was not correlated with Visualizer/Verbalizer tendencies or general academic performance.
Therefore, if indeed the STP scale captures differential responsiveness to priming, we do not expect that such differences will be isolated only among individuals either very high or very low in cognitive ability, or that performance on post-prime tasks is primarily driven by a general desire to exhibit high achievement or optimum performance.
Thus, these data provide some validation of the STP measure as conceptualized and lay the groundwork for application of the index to different priming protocols, where empirical validation can be assessed. Therefore, in studies 1 - 3, we test whether the STP index can explain observed differences in priming effects. We use three very different priming manipulations and focal dependent measures. These different approaches provide a more compelling picture of the robustness and generalizability of the STP index across diverse choice/judgment environments.
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We also test new priming situations that have a marketplace focus. In the following studies, we examine the influence of the classic “elderly prime” (Bargh, Chen, and
Burrows 1996) on attitudes toward product innovation speed, the use of a work-related prime to increase intentions to study, and the influence of a promotion- versus prevention-oriented prime to increase the valuation of a promotion-oriented product attribute. While these priming effects are new demonstrations rather than replications of existing effects, and therefore have some interest as they stand, our primary focus is on the ability of the STP index to moderate the prime’s effect strength.
STUDY 1: THE ELDERLY PRIME
In one of the most well-cited and provocative demonstrations of priming, Bargh,
Chen, and Burrows (1996) demonstrated that study participants primed with the concept of the elderly subsequently walked more slowly down the hall when leaving the experiment. In this study we test whether the primed tendency to physical slowness can similarly impact other types of slowness—in this case, one’s attitudes toward the speed of high tech innovation. In study 1, we expose participants to a modified version of an
“elderly prime” (Bargh, Chen and Burrows 1996) and test the impact of this prime on responses to a survey about attitudes toward the speed of technological change; specifically, we predict that an elderly prime will serve to decrease reported attitudes toward speedy innovation. We anticipate that the STP index will moderate the effect of this prime, such that priming effects are strongest for those with higher STP.
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Method
Participants. 156 university undergraduates (62% female) participated for course credit.
Procedure. Participants came to a testing facility where they were seated at individual carrels. Study sessions lasted approximately one hour and consisted of several unrelated tasks. Early in the session, the participants engaged in two ostensibly unrelated tasks that were, together, the focal task. In the first part of this task, participants filled out a survey that asked them to look at a list of brand names for products (e.g., Dasani water,
Kleenex tissues) and to identify which brands they thought were American brands and which brands were Canadian brands. In the elderly prime condition, six fictional brand names were words associated with the elderly similar to the sentence scramble task used by Bargh et al (e.g., Bingo cookies, Gray Walk paper, Slow-Pour syrup, Old Town kayaks). In the neutral condition, these words were replaced with unrelated neutral words (e.g., Bell cookies, Sweet-Pour syrup). After this, participants moved on to another separate survey about their attitudes about high tech products. This attitude survey included two items intended to tap into participants’ attitude toward the pace of technological change: “The rate at which technology changes is:” and “The rate at which new updates or versions of products come out is:” completed by a seven-point scale where 1 was labeled “too slow,” 4 was labeled “just right,” and 7 was labeled “too fast.”
Results
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We first created an STP index for each participant by averaging across the 6 STP items (α = 0.76, M = 5.57, SD = .74). We also indexed the two items described above (α
= 0.71) to form a measure of participants’ attitudes toward technological change.
We then analyzed the data using the STP index and the prime condition of the participant as predictors of attitudes towards technological change. The main effect of the prime (F(1, 151) = .14, p = .71) was not significant. However, there was a significant overall interaction of priming condition and STP scale score (F(1, 151) = 4.08, p = .04).
We then probed the nature of this interaction by plotting the effect of prime condition at one standard deviation above the mean STP score, at the mean STP score, and one standard deviation below the mean STP score and conducting regression analyses as suggested by Aiken and West (1991). This analysis indicates that the prime was ineffective for low and moderate STP individuals, who did not rate technology differently than did their unprimed counterparts (moderate: Mprime = 4.92, Mno prime = 4.85, F(1,151)
= .14, p = .71; low: Mprime = 4.77, Mno prime = 5.09, F(1,151) = 1.41, p = .49). However, among high STP individuals, the prime did have an effect. Higher STP individuals exposed to the elderly prime were significantly more likely to describe the pace of technological change as too fast (M = 5.08) than those not exposed to the prime (M =
4.61, F(1,151) = 3.46, p = .05).
Discussion
In study 1, we observe that priming effects emerge primarily for individuals who score higher on the STP index, but are virtually undetectable than for those who score
18 lower. Importantly, in this data, the absence of a main effect of the prime might have led researchers to conclude that the elderly prime had no impact on individuals’ reactions to high-tech products. In fact, application of the STP index allows us to see that the prime did, in fact, have interesting effects on individuals at high levels of STP. This suggests that experimental or real-world use of primes that at first blush appear to yield a null effect may, in fact, only be observed for some individuals within the population.
In our study 1 protocol, however, we used a traditional priming manipulation that took place before the measurement of the focal evaluation. For marketers, it is important to see whether incidental cues embedded directly in the marketing message itself, may show similar prime-consistent evaluations. Thus, in study 2, we embed the prime directly in the stimuli used for the focal dependent variable (in this case, a measure of intention rather than evaluation). In study 1, we also used only a prime as compared to a no-prime condition, which allows us to see the effect of a prime in one direction from the baseline.
In study 2 we use two opposing primes, in order to see if high STP individuals can respond to opposing primes in opposite ways, that is, if opposite primes can create inverse outcomes for higher STP consumers, but still do little to change the behavior of those lower in STP.
STUDY 2: THE WORK-STUDY PRIME
Can people be primed to engage in beneficial activities such as studying, exercising, or healthy eating? Research by Geyskens et al. (2007) showed that health primes increased the consumption of low-fat potato chips, although, ironically, this effect
19 could lead to overeating. Here, we test the influence of work-related and fun-related primes on college students’ intentions to study. We expect that those individuals who are primed with concepts surrounding work will be likely to report greater intentions to study than those who are primed with concepts related to fun. However, we expect that the nature of the prime to which they are exposed (work v. fun) will be more important for those with higher as opposed to lower scores on the STP index.
Method
Participants in study 2 were 211 university undergraduate students, who took part in the experiment for course credit. Participants first completed the STP scale as previously described. After competing approximately 30 minutes of unrelated tasks, they then completed a questionnaire which began with one of two sets of directions, which contained the priming manipulation. The priming manipulation was included in the instructions for the survey as a way to test the influence of subtle cues embedded in the task itself rather than as a separate task completed prior to the target dependent variables.
The purpose of this procedure was to better match the types of cues that marketers might be able to employ in real decision contexts (e.g., the wording of ad text). The use of a between-subjects design greatly minimizes demand artifact as a possible alternative explanation in this procedure. The tenor and meaning of both sets of instructions were kept constant, but the words employed were either more work- or fun-oriented. In the work prime condition, they read the following (prime-related words are bolded for reporting, but not in stimuli):
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This is a short survey about your average study habits. Don’t worry! It’s not a challenge on which you’ll be graded! But, we are only interested in your personal responses, so please don’t discuss it with your colleagues while you are filling this out. When you have finished, please fold the paper in half. Thanks for your participation – you are helping us achieve an understanding of how student life works best.
In the fun/friends prime condition, participants read:
This is a short survey about your average study habits. Relax! It’s just for fun and we won’t tell your friends! But, we are only interested in your personal responses, so please don’t chat with your friends while you are filling this out. When you have finished, please fold the paper in half. Thanks for your participation – you are helping us keep up with what’s happening in young adult life.
After reading these instructions, participants completed a number of measures that assessed the individual’s intentions to study in the future. The primary dependent measure was an opened-ended question which asked, “How many hours do you plan to study this weekend?” We anticipated that participants primed with the work-related words would report more hours dedicated to studying than would participants primed with the fun-related prime and that this priming effect would be stronger for participants who scored high on the STP index. In order to control for individual differences in general study habits, we also collected the average number of hours each student said they would study on a normal week. In addition, we collected participants’ attitude toward studying in general, captured on a 1 (strongly agree) to 9 (strongly disagree) statement which read, “I think it’s extremely important to study hard.”
Analysis and Results
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As in study 1, we first created a summed STP score for each participant (α = .80,
M = 5.55, SD = .86). We then used the mean-centered STP score and participants’ prime condition (contrast coded at -1 and 1) and their interaction as predictors of their intended studying behavior during the upcoming weekend. Each participant’s feeling that studying was important(M = 7.18, SD = 6.35) and average hours spent studying (M = 5.21 hours,
SD = 1.97) did not interact with either STP or prime condition and were also included in the model as covariates.
Not surprisingly, participants who felt that studying was important showed a likelihood to study more during the upcoming weekend (b = .53, F(1, 203) = 4.45, p =
.03). Each participant’s average studying time also had an independent effect on planned studying (b = 1.14, F(1, 203) = 26.50, p < .0001). Beyond these effects, the prime itself had a marginally-significant effect on planned weekend studying (b = .60, F(1, 203) =
2.44, p = .10). The STP index had no significant main effect on planned weekend studying (F(1, 203) = 0.01, p > .93), but there was a significant interaction between prime condition and participants’ STP index scores (b = 1.23, F(1, 203) = 7.14, p = .008).
In order to more fully understand the data, we again plotted planned studying responses at one standard deviation above the mean STP (high STP), at the mean STP
(moderate STP), and one standard deviation below the mean STP (low STP). As hypothesized, we find that the difference between the work and fun prime conditions is significant when STP is high (b = 1.76, t(1, 203) = 1.67, p = .003), such that high STP participants primed with “work” showed a significant increase in their studying likelihood compared to high STP individuals primed with “fun.” We also found that the work prime increased likelihood of studying at moderate levels of STP (b = 5.36, t(1,
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203) = 2.35, p = .02) relative to the fun prime. However, whether they saw the work or fun prime was of no significant difference for participants at low levels of STP (b = -.45, t(1, 203) = -.80, p > .42).
In this study, we also expected that the effect of the different primes might vary depending on participants’ STP. To test this prediction, we conducted regression analyses within each prime condition using STP and the two control measures to predict planned studying. In the work prime condition (n = 107), we found that as STP increased, planned studying time also increased marginally (F(1, 103) = 2.67, p = .09). In the fun prime condition (n = 102), we see that higher STP is consistently associated with lower amounts of planned studying than is lower STP (F(1, 98) = 5.62, p = .02).
Discussion
In study 2, we examine the use of a work and fun prime to influence students’ choices about time consumption—in this case, the intention to spend time studying. We use a prime that is embedded within the task to better match real-world marketing messages. The results show that, in this situation, the nature of the prime has a weak effect across the sample as a whole – whether one is exposed to “work” or “fun” related terms generally could be said to have a slight effect on behavior. ‘
However, use of the STP index again provides a better understanding of the actual effectiveness of the primes. Closer analysis reveals that showing that the effects that are weak in the aggregate are in fact quite strong among high and moderate STP individuals, for whom the nature of the prime does in fact change behavioral intentions. Further, this
23 study demonstrates that STP can explain variance in a prime’s efficacy when considered alone, as behavior within each prime group could generally be predicted by STP.
However, we do acknowledge that the relationship between STP and planned studying was marginal in the work prime condition, suggesting that some primes may vary in their
STP-dependence. Some primes may simply reflect default behaviors, and be relatively effective regardless of STP, while other primes may be so weak that they have little effect on a consumer’s state tendencies regardless of their trait STP. In our case, the stronger relationship between STP and the magnitude of the priming effect in the “fun” condition may have been stronger because the desire to have fun is inherent in our population; they more readily accept even nonconsciously processed cues to refrain from work. Thus higher STP individuals were willing to change their behavior more than when faced with a work prime. By contrast, the work prime may have met with some unconscious resistance and thus created a slightly smaller effect—but, importantly, still a significant effect.
Finally, study 2 provides further evidence for the existence of individual level susceptibility to priming based on attentional and associative tendencies. In study 3, we replicate this effect once again, this time using a context that more directly resembles a real-world advertising message and evaluation task and a dependent measure which should only be impacted by one type of the two used: the value of a customization package, which should be increased among high STP, promotion-primed individuals, but which should not show the same increase in value among either lower STP individuals or those who are primed with a prevention focus.
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STUDY 3: THE PROMOTION-PREVENTION PRIME
Regulatory focus theory describes two modes of self-regulation, promotion and prevention, that predict behavioral differences based on when individuals may be oriented toward achieving gains versus avoiding losses (see Pham and Higgins 2004 for a review). While individuals may have chronic promotion or prevention orientations (e.g.,
Shah, Higgins, and Friedman 1998), temporary instantiations of either a promotion or prevention mindset can have a strong influence on choice behavior (e.g., Aaker and Lee
2006; Mogilner, Aaker, and Pennington 2008). In study 3, some participants are given a prime intended to create a promotion mindset (versus a prevention mindset), which should increase the desirability of product customization (Aaker and Lee 2006; Chitturi,
Raghunathan, and Mahajan 2008). We then measure the extent to which promotion- primed participants value an add-on customization package for a new product. This protocol also allows us to analyze preliminary evidence to see if differential effects of a promotion prime explained by varying levels of STP will bleed over to more global product evaluations and thus, may have important, larger-scale managerial consequences.
Method
One hundred and twenty-one undergraduate students took part in the experiment for extra credit. Participants were randomly assigned to either a promotion prime or prevention prime condition, and the same 6-item STP scale was collected as before.
25
All participants read an advertisement entitled “A Palm for Real Life,” describing a new PDA. In the prevention prime condition, the ad copy read:
The new Palm 3100 handheld wireless PDA ought to fit your life. You have a duty to look for durability. You are responsible for staying stylish. The 3100 has it all in interchangeable features that prevent this from being just any PDA. You choose the upgrades that fit your needs. So responsible!
In the promotion prime condition, the ad copy read:
The new Palm 3100 handheld wireless PDA aspires to fit your life. You dream of durability. You strive to stay stylish. The 3100 has it all in interchangeable features that prevent this from being just any PDA. You choose the upgrades that fit your needs. So ideal!
Bolded words indicate alterations made between the conditions as part of the priming manipulation, but were not bold in the original ad. All other graphical elements were identical. Participants than read about an option to customize this PDA through the addition of a customization (called the “unforgettable” package) add-on. We used a customization feature as our focal attribute because past research has shown that promotion-orientations are more compatible with independent and unique self-views
(Aaker and Lee 2006) and also lead to enhanced valuation of hedonic attributes (Chitturi,
Raghunathan, and Mahajan 2008); thus, we chose an optional customization package as an attribute that would appeal to promotion-focused individuals as a hedonic feature that promoted independent self expression. The customization attribute was described in the following manner:
Interested in style? Upgrade with our UNFORGETTABLE package. For only $75 at purchase, this package allows you to customize the look of your palm with over 150 shapes, styles, and casings that allow you to express your unique perspective. You’ll be unforgettable whether you choose distressed black leather with industrial rivets or sleek brushed pewter or sexy pink champagne.
26
After reading about this option, participants were asked to complete a number of dependent measures. After completing approximately 40 minutes of unrelated tasks, participants completed the same 6-item STP scale as used in studies 1 and 2.
Measures
We collected two sets of focal dependent measures. First, we collected three items intended to capture participants’ value of the customization package using three questions. Each question started with the same stem: “The ‘Unforgettable’ package is,” and asked participants to complete the sentence by expressing their opinion concerning whether it was “Very unappealing” (1) to “Very appealing” (9), “Very unfavorable,” (1) to “Very favorable,”, and “Something that I don’t like,” (1) to “Something that I like a lot” (9). Our second set of focal dependent measures related to the product as a whole.
We used these measures to test for downstream consequences of changes in attitude toward a specific promotion-related feature to the product or brand in general. The two questions were: “What is your overall evaluation of the Palm 3100,” and “What is your overall evaluation of the Palm brand, both anchored at Very Poor (1) or Very Good (9).
Finally, we also collected perceptions of the ad by asking participants to what extent they disagreed (1) or agreed (9) with two questions: “I found the information in this ad manipulative,” and “I found the information in this ad to be just a sales pitch.”
Analysis and Results
27
Perceptions of Ad. We first checked to make sure that neither STP, the manipulation in the advertisement, or their interaction impacted the baseline perception of the ad or raised suspicion about the purpose of the ad. There were no significant differences in the extent to which the ad was seen as manipulative (all p’s > .3) or that participants felt the ad was just a sales pitch (all p’s > .1).
Promotion Prime and STP. As before, the STP index was created for each participant by averaging across the 6-item STP index (α = .80, M = 5.47, SD = .74). Each individual’s STP score, their prime condition and the interaction of the two factors were then used to predict their value for the customization package offered in the promotion.
As observed in study 1, the prime manipulation seemed, at first blush, to have a weak or non-significant impact across all participants, only marginally increasing the evaluation of the promotion-oriented customization package (F(1, 117) = 2.53, p = .1).
Interestingly, in this data, STP also had a significant main effect on baseline valuation of the customization package, such that individuals higher in STP generally found the customization package more valuable than did those lower in STP (F(1, 117) = 12.27, p =
.0007). Again, though, these main effects were qualified by a significant interaction of the two factors (F(1, 117) = 5.02, p = .03), as depicted in figure 2. Once again, the promotion prime increased perceptions of the customization package significantly among high STP individuals relative to the prevention prime (F(1, 117) = 6.45, p = .01) but the nature of the prime had no significant effect at moderate (F(1, 117) = .40, p = .52), or low
(F(1, 117) = .79, p = .38) levels of STP. Regression analyses as conducted in study 2 suggest that within the promotion prime condition (n = 54), higher STP individuals reliably valued the customization package more than did lower STP individuals (F(1, 52)
28
= 16.56, p = .0002). However, the level of STP did not have any effect on the extent to which prevention-primed individuals (n = 67) valued the customization package (F(1, 65)
= .79, p = .37).
Perception of Product as a Whole. Will the increased evaluation of the customization package have downstream consequences for overall product evaluation?
We find that the pattern of results observed for the evaluation of the customization package is reflected, albeit more weakly, in the overall evaluation of the product. We indexed the two product evaluation questions (α = .74) and conducted an ANOVA where
STP and the prime condition as well as their interaction were used to predict participants’ scores on this index.
As might be expected, we see that individuals primed with a promotion focus tended to rate the product more highly (Mpromotion = 7.20, Mprevention = 6.75, F(1, 118) =
3.91, p = .05). Further, we see a marginally-significant interaction of the prime condition and STP score (F(1, 118) = 3.27, p = .07). The form of this interaction mirrors that seen for the evaluation of the customization package. In addition to the above-reported analyses, regression analysis demonstrates that perceptions of the customization package reliably predict the value of the product as a whole (t(1, 121) = 4.09, p < . 001). Analysis of a model where the customization package as well as STP, prime condition, and their interaction are used to predict overall product perceptions shows that the effect of the customization package remains significant (F(1, 116) = 9.09, p < .01), but that the interaction of STP and prime condition now drop from significance altogether (F(1, 116)
= 1.43, p = .23). The Sobel test for this mediation is marginally significant (p = .1). We note that in this case, reversing the order of the mediator and the DV does not yield a
29 similar pattern of analyses, suggesting that the mediation in this case is not simply an artifact of self-generated validity. Though measures were taken simultaneously, and therefore we hesitate to overstate the degree to which a mediation analysis can be conclusive, there is however some evidence to suggest that varying effects of the promotion prime on perception of the customization package mediate overall product perceptions.
Discussion
Study 3 provides further evidence that the STP index can significantly predict the observed strength of priming effects. As in study 2, this priming task used a procedure that more closely matched marketing messaging in the real-world and further demonstrates the broad and influential scope of priming effects in marketplace contexts.
Individuals who score high on STP show and are put in a promotion mindset show more affinity for the customization package than those who score lower or those who are primed with prevention. Again, this test shows how an initial analysis of overall priming influence may have appeared to indicate no significant effect, but that the consideration of susceptibility to priming allows for the observance of the effect in a subset of individuals.
Therefore, study 3 provides further theoretical insight into priming in general, suggesting once again that the effect of a prime depends on an individual’s associative and attentional capacity. It also provides new insights into promotion and prevention focuses, suggesting that prevention-primed consumers may not respond by devaluing a
30 promotion-related option, rather they may simply fail to ascribe it a higher value as would a high STP, promotion primed individual. However, these results also provide important managerial insights. Specifically, when we want consumers to think about improving their lives, we may initially rely on the use of encouraging, promotion-focused language to prompt the activation of proactive pathways. However, for some consumers, such subtle approaches may not be effective – for some consumers, more direct persuasion attempts may be required to lead a consumer to take actions consistent with a promotion focus. One may also consider this insight in light of less consumer-friendly messages: while high STP individuals may benefit more from priming “nudges” toward positive behavior embedded in messages from benevolent sources, these individuals may also be more likely to be influenced against their best interests by primes embedded in advertising messages for unnecessary or unhealthy products.
GENERAL DISCUSSION
Theoretical and Practical Implications
This research examines the potential for individual differences in susceptibility to priming and develops a scale to measure STP. In reviewing occurrences of priming efficacy differences in the literature, we observe that many fall into two broad categories—traits or situations that indicate greater attention to the environment and traits that indicate a more general tendency to associative thought patterns. These two categories coincide with the priming process itself—priming effects occur when
31 individuals physically (if nonconsciously) perceive a prime that subsequently triggers associated schemas through quick spreading activation. From this relationship, we develop the hypothesis that individuals who are inherently prone to attention and associative thought will be more susceptible to priming influence. We subsequently develop a 6-item index which captures these traits, show that it taps into individual differences which are stable over time, and conforms with our expectations regarding its modest relationships to related concepts.
Here, evidence from three studies suggests that increased attention and associative thought do lead to enhanced priming effects in that an individual’s score on the STP index can predict the strength of observed priming effects. Important to consumers and marketers alike, these findings suggest that consumers who are attuned to their environments and quickly connect ideas to one another may be more susceptible to priming effects embedded in marketing messages than other consumers who are more traditionally perceived as vulnerable to persuasion attempts.
These findings contribute to theory development by speaking to one of the important questions currently facing priming research (Bargh 2006). Other individual differences may exist that further enhance one’s susceptibility to priming, however this identification of attentional and associative cognitive tendencies provides the first, and potentially most foundational, traits that characterize enhanced STP. A better understanding of who is most prone to priming influence is important for both marketplace practitioners and for priming researchers. First, for marketers, the ability to predict which consumers are likely to be influenced by subtle cues in marketing messages
(e.g., advertisements) or decision environments (e.g., retail space design) can indicate
32 when the inclusion of such cues are worthwhile. For example, firms whose customer base is largely well-educated may have a stronger incentive to design and integrate small cues in their ads or stores. Second, for researchers, the STP index provides a valuable tool for capturing priming effects “in the wild.” Increasingly, future priming research will explore the impact of priming outside the laboratory. In such situations, the use of the
STP index may help determine the true impact of cues within subsets of the general population where, without the use of an individual difference factor, the overall effect across the population may appear very small. Conversely, while the STP index may also provide a good covariate in laboratory demonstrations of priming, the use of a college student population and “captive audience” protocols that facilitate high levels of attention to target stimuli suggest that finding priming effects in the lab may already be more likely because a disproportionately high level of individual STP. However, we note that our studies here were conducted in the laboratory with a student population and still found significant differences in measured STP and its effect on priming efficacy. So, while this index may be most useful outside the lab, its usefulness in the lab may not be immaterial as it stands.
Limitations and Future Directions
Both our method and results suggest ample room for future research in this areas.
First, our results in study 2 and 3 show that different primes may be more or less dependent on STP to determine the magnitude of their effect. For example, while STP had a significant effect on play-primed individuals’ planned studying, it had only a
33 marginal effect on work-primed individuals’ planned studying. And while STP reliably predicted the promotion-focused individuals’ valuation of a customization package, consistent with past research it did little when consumers had a prevention mindset.
These differences in the importance of STP may be theoretically justified, for example, in the latter case, when a prevention-focus may flatten consumers’ response to an option which is not designed to appeal to them. However, future research may attempt to explore when primes are so strong that STP doesn’t matter or so weak that even the highest STP individual remains unaffected.
Other research also suggests there may be differences in STP which we do not explore here. When Bargh (2006) first suggested that individuals might be differentially susceptible to priming, he wondered if the effect might be culturally derived. In this supposition, he was guided by research by Nisbett (2003) that demonstrates robust differences in the way that Westerners and Asians process perceptual information.
Notably, Nisbett shows that Asians pay more attention to context in figure-ground processing than do Westerners. While we go down a different path by exploring an individual trait-based tendency to STP here, we don’t rule out other potentially additive effects of culture on generalized susceptibility. In fact, we note the similarity of our treatment of attentional factors to Nisbett and colleagues’ figure-ground findings.
Whether inherent or situationally determined, the findings here and elsewhere suggest that attention is likely to have a significant influence on priming efficacy. The examination of cultural differences remains a promising avenue for future research.
Additionally, we believe that future research may find something other than a linear relationship between measured STP and prime efficacy. For example, at extremely high
34 levels of attentional faculty, higher perceptual vigilance may result in the emergence of a curvilinear relationship between attention and priming, such that the effects of priming decrease akin to discounting effects observed in mere exposure paradigms (e.g.,
Bornstein and D’Agostino). Though we did not find these results in our sample, it is possible that they could emerge when more extreme STP scores are observed. Further, we tested the STP index with an age-homogenous (college student) population. Greater variance in scores might be observed when populations that differ in age, educational level, and other factors.
Taken together, the development of the STP index and its application in three diverse priming tasks provides compelling evidence that individuals do indeed differ in their inherent susceptibility to incidental cues. The combination of attentional and associative elements that contribute to our STP measure suggest that those individuals most vulnerable to priming effects are those who are both engaged in the environment and have strong cognitive skills in associative thinking. These characteristics paint a picture of a person who is attentive and intelligent—an image that diverges from our common assumptions of “at-risk” consumers. Contrary to other situations of consumer vulnerability, it may be the engaged and cognitively-advantaged consumer who is most prone to be influenced by subtle primes embedded in marketing messages. If
“subliminal” advertising is more effective than previously thought (Bargh 2004), then the dangers of it may be greatest for those who we least expect.
35
REFERENCES
Aaker, Jennifer L. and Angela Y. Lee (2006), “Understanding Regulatory Fit,” Journal of
Marketing Research, 86 (February), 15 -19.
Aarts, Henk and Ap Dijksterhuis (2000), “Habits as Knowledge Structures: Automaticity
in Goal-Directed Behavior,” Journal of Personality and Social Psychology, 78
(January), 53-63.
Aiken, Leona S. and Stephen G. West (1991), Multiple Regression: Testing and
Interpreting Interactions, Sage: Thousand Oaks.
Ansorge, Ulrich (2003), “Asymmetric Influences of Temporally vs. Nasally Presented
Masked Visual Information: Evidence for Collicular Contributions to
Nonconscious Priming Effects,” Brain & Cognition, 51(3), 317-325.
Ansorge, Ulrich (2004), “Top Down Contingencies of Non-Conscious Priming Revealed
by Dual-Task Interference,” Quarterly Journal of Experimental Psychology:
Human Experimental Psychology, 57A(6), 1123-1148.
Bargh, John A. (2006), “Agenda 2006: What Have we been Priming all these Years? On
the Development, Mechanisms, and Ecology of Nonconscious Social Behavior,”
European Journal of Social Psychology, 36 (2), 147-168.
Bargh, John A. (1996) Principles of Automaticity. In E. Tory Higgins and Arie
Kruglanski (Eds.), Social Psychology: Handbook of Basic Principles, (p. 169-
183). New York: Guilford
36
Bargh, John A. (2002), “Losing Consciousness: Automatic Influences on Consumer
Judgment, Behavior and Motivation,” Journal of Consumer Research, 29(2), 280-
285.
Bargh, John A. and Tanya L. Chartrand (1999), “The Unbearable Automaticity of
Being,” American Psychologist, 54 (July), 462-479.
Bargh, John A., M. Chen and L. Burrows (1996), “Automaticity of Social Behavior:
Direct Effects of Trait Construct and Stereotype Activation on Action,” Journal of
Personality and Social Psychology, 71, 230-244.
Bargh, John A., Peter M. Gollwitzer, Annette Lee-Chai, Kimberly Barndollar, and
Roman Trostchel (2001), “The Automated Will: Nonconscious Activation and
Pursuit of Behavioral Goals,” (2001), Journal of Personality & Social
Psychology, 81(6), 1014-1027.
Barron, Frank and David M. Harrington (1981), “Creativity, Intelligence, and
Personality,” Annual Review of Psychology, 32 (January), 439-476.
Bearden, William O., Richard G. Netemeyer, and Jesse E. Teel (1989), “Measurement of
Consumer Susceptibility to Interpersonal Influence,” Journal of Consumer
Research, 15 (4), 473-482.
Bornstein, Robert F. and Paul R. D’Agostino (1992), “Stimulus Recognition and the
Mere Exposure Effect,” Journal of Personality & Social Psychology, 63(4), 545-
552.
Boush, David M., Marian Friestad and Gregory M. Rose (1994), “Adolescent Skepticism
toward TV Advertising and Knowledge of Advertiser Tactics,” Journal of
Consumer Research, 21(1), 165-175.
37
Bremner, Robert Hamlett (1994), Giving: Charity and Philanthropy in History,
Transaction Publishers: Edison, New Jersey.
Chartrand, Tanya L. and John A. Bargh (1996), “Automatic Activation of Impression
Formation and Memorization Goals: Nonconscious Goal Priming Reproduces
Effects of Explicit Task Instructions,” Journal of Personality and Social
Psychology, 76, 893-910.
Chen, Serena, Annette Y. Lee-Chai and John A. Bargh (2001), “Relationship Orientation
as a Moderator of the Effects of Social Power,” Journal of Personality & Social
Psychology, 80(2), 173-187.
Cheng, Clara Michelle and Tanya L. Chartrand (2003), “Self-Monitoring Without
Awareness: Using Mimicry as a Nonconscious Affiliation Strategy,” Journal of
Personality & Social Psychology, 85(6), 1170-1179.
Childers, Terry L., Michael J. Houston, and Susan E. Heckler (1985), “Measurement of
Individual Differences in Visual Versus Verbal Information Processing,” Journal
of Consumer Research, 12(2), 125-135.
Chitturi, Ravindra, Rajagopal Raghunathan, and Vijay Mahajan (2008), “Delight by
Design: The Role of Hedonic versus Utilitarian Benefits,” Journal of Marketing,
72 (May), 48-63.
Davenport, Jodi L. and Mary C. Potter (2005), “The Locus of Semantic Priming in RSVP
Target Search,” Memory & Cognition, 241-248.
Dijksterhuis, Ap, Tanya L. Chartrand, and Henk Aarts (2006), “Effects of Priming and
Perception on Social Psychology and Goal Pursuit,” in Social Psychology and the
38
Unconscious: The Automaticity of Higher mental Processes, ed. John A. Bargh,
Philadelphia: Psychology, 51-131.
Fiedler, Klaus, Wolfram Schenck, and Marlin Watling (2005), “Priming Trait Inferences
Through Pictures and Moving Pictures: The Impact of Open and Closed
Mindsets,” Journal of Personality and Social Psychology, 88(2), 229-244.
Forehand, Mark R. and Rohit Deshpandé (2001), “What We See Makes us Who We Are:
Priming Ethnic Self-Awareness and Advertising Response,” Journal of Marketing
Research, 38(3), 336-348.
Geyskens, Kelly, Mario Pandalaere, Siegfried Dewitte, and Luk Warlop (2007), “The
Backdoor to Overconsumption: The Effect of Associating “Low Fat” Food with
Health References,” Journal of Public Policy & Marketing, 26 (Spring), 118-125.
Herr, Paul (1989), “Priming Price: Prior Knowledge and Context Effects,” Journal of
Consumer Research, 16(1) 67-75.
Higgins, E. Tory, William S. Rholes, and Carl R. Jones (1977), “Category Accessibility
and Impression Formation,” Journal of Experimental Social Psychology, 13(2),
141-154.
Hull, Jay G., Laurie B. Slone, Karen B. Meteyer, and Amanda R. Matthews (2002), “The
Nonconsciousness of Self-Consciousness,” Journal of Personality and Social
Psychology, 83(2), 406-424.
Kay, Aaron C., S. Christian Wheeler, John A. Bargh and Lee Ross (2004), “Material
Priming: The Influence of Mundane Physical Objects on Situational Construal
and Competitive Behavioral Choice,” Organizational Behavior & Human
Decision Processes, 95(1), 83-96.
39
Kruglanski, Arie W., Donna M. Webster, and Adena Klem (1993), “Motivated
Resistance and Openness to Persuasion in the Presence or Absence of Prior
Information,” Journal of Personality and Social Psychology, 65 (5), 861-876.
Lakin, Jessica L., Valerie E. Jefferis, Clara Michelle Cheng, and Tanya L. Chartrand
(2003), “The Chameleon Effect as Social Glue: Evidence for the Evolutionary
Significance of Nonconscious Mimicry,” Journal of Nonverbal Behavior, 27(3),
145-162.
Macrae, C. Neil and Lucy Johnston (1998), “Help, I Need Somebody: Automatic Action
and Inaction,” Social Cognition, 16(4), 400-417.
Mandel, Naomi (2003), “Shifting Selves and Decision Making: The Effects of Self-
Construal Priming on Consumer Risk-Taking,” Journal of Consumer Research,
30(1), 30-40.
Monahan, Jennifer L. and Cynthia E. Zuckerman (1999), “Intensifying the Dominant
Response: Participant-Observer Differences and Nonconscious Effects,”
Communication Research, 26(1), 81-110.
Morgan, Fred W., Drue K. Schuler, and Jeffrey J. Stoltman (1995), “A Framework for
Examining the Legal Status of Vulnerable Consumers,” Journal of Public Policy
and Marketing, 14 (Fall), 267-277.
Meyers-Levy, Joan (1989), “Priming Effects on Product Judgments: A Hemispheric
Interpretation,” Journal of Consumer Research, 16(1), 76-86.
Nisbett, Richard E. (2003), The Geography of Thought: How Asians and Westerners
Think Differently…and Why, New York: Free Press.
40
Pechmann, Cornelia and Susan Knight (2002), “An Experimental Investigation of the
Joint Effects of Advertising and Peers on Adolescents’ Beliefs and Intentions
about Cigarette Consumption,” Journal of Consumer Research, 29(1), 5-19.
Pham, Michel Tuan and E. Tory Higgins (2004), “Promotion and Prevention in
Consumer Decision Making: State of the Art and Theoretical Propositions,” In
Srinivasan Ratneshwar and David Mick, Ed., Inside Consumption: Frontiers of
Research on Consumer Motives, Goals, and Desires, Routledge.
Posner, Michael L. and Nyder, C.R.R. (1975), “Attention and Cognitive Control.” In R.
L. Solso, Ed., Information Processing and Cognition: The Loyola Symposium, p.
55-85. Hillsdale, NJ: Erlbaum.
Rottveel, Mark and R. Hans Phaf (2004), “Loading Working Memory Enhances
Affective Priming,” Psychonomic Bulletin and Review, 11(2), 326-331.
Shah, James, E. Tory Higgins, and Ronald S. Friedman (1998), “Performance Incentives
and Means: How Regulatory Focus Influences Goal Attainment,” Journal of
Personality and Social Psychology, 74 (February), 285-293.
Shaw, Geraldine A. and Martin Conway (1990), “Individual Differences in
Nonsconscious Processing: The Role of Creativity,” Personality & Individual
Differences, 407-418
Soto, David and Dietmar Heinke (2005), “Early, Involuntary Top-Down Guidance of
Attention from Working Memory,” Journal of Experimental Psychology: Human
Perception and Performance, 31(2), 248-261.
41
Srull, Thomas K. and Robert S. Wyer (1979), “The Role of Category Accessibility in the
Interpretation of Information about Persons: Some Determinants and
Implications,” Journal of Personality and Social Psychology,1660-1672. van Baaren, Rick B, William W. Maddux, Tanya L. Chartrand, Cris DeBouter, and Ad
van Knippenberg (2003), “It Takes Two to Mimic: Behavioral Consequences of
Self-Construals,” Journal of Personality and Social Psychology, 84(5), 1093-
1102. van Baaren, Rick B., Terry G. Horgan, Tanya L. Chartrand, and Marit Dijkmans (2004),
“The Forest, The Trees and the Chameleon: Context Dependence and Mimicry,”
Journal of Personality & Social Psychology, 86(3), 453-459.
Webster, Donna M. and Arie W. Kruglanski (1994), “Individual Differences in Need for
Cognitive Closure,” Journal of Personality & Social Psychology, 67(6), 1049-
1062.
Winkielman, Piotr, Kent C. Berridge and Julia L. Wilbarger (2005), “Emotion, Behavior
and Conscious Experience: One More without Feeling,” in Emotion and
Consciousness, Lisa Feldman Barrett, Paula M. Niedenthal and Piotr Winkielman,
editors. New York, NY, US: Guilford Press, 2005. pp. 335-362
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FIGURE 1
Study 2 Interaction of Work/Fun Prime and STP on Hours of Planned Studying
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FIGURE 2
Study 3 Interaction of Promotion Prime and STP on Value of the Customization Attribute