Avatar Appearance and Cognitive Load Effects on Attitudes

Home , Avatar (computing), There (virtual world)

Jorge Pen˜ a* Under Pressure: Avatar University of California, Davis Appearance and Cognitive Seung-Chul Yoo Load Effects on Attitudes, Loyola University Chicago Trustworthiness, Bidding, and Interpersonal Distance in a Virtual Store

Abstract

This study investigated how avatar appearance and cognitive load affect virtual interactions. Avatar salespeople dressed in black were perceived as unpersuasive and untrust- worthy, and were offered less money compared to avatars in white clothes. Moreover, participants stood closer to avatars in white clothes compared to avatars dressed in black. Contrary to the traditional prediction (i.e., cognitively busy participants would trust avatars in white clothes the most but avatars in dark clothes the least), cognitively nonbusy participants expressed less trust towards avatar salespeople dressed in black instead of white clothes, while cognitively busy participants trusted both characters equally. The ﬁndings expanded current research on virtual social inﬂuence by considering the effects of the clothing color of virtual characters, along with how cognitive load and avatar appearance can modify perceived avatar trustworthiness when combined.

1 Introduction

Empirical studies have unveiled fascinating persuasive processes in virtual settings. For instance, participants who see their own avatar endorsing a virtual product show higher brand attitudes and purchase intentions relative to those who see other avatars endorsing a product (Ahn & Bailenson, 2011). In addition, people recall fewer ads and develop more negative brand attitudes after playing a game containing violent cues (e.g., blood, guns) in comparison to playing a game with no violent cues (Yoo & Pen˜a, 2011). Overall, brand recall, purchase intention, and brand attitude are reliably affected by contextual cues in virtual settings. It appears that people are mindlessly persuaded by categorical and stereotypical visual cues integrated into interfaces, avatars, and computer-controlled agents. Computer interface avatars depicted as male are more persuasive than female avatar interfaces, particularly when users experience attentional demands or cognitive load (Lee, 2008). In addition, participants show more attitude change when the virtual partners are of the same gender as themselves (Guadagno, Blascovich, Presence, Vol. 23, No. 1, Winter 2014, 18–32 doi:10.1162/PRES_a_00166 ª 2014 by the Massachusetts Institute of Technology *Correspondence to [email protected].

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Bailenson, & McCall, 2007). Avatar race also influences (Lee, 2008). The effects of cognitive load on avatar per- virtual social interactions (Groom, Bailenson, & Nass, suasive and perceptual outcomes deserve more attention 2009). For instance, participants experience greater learn- as, to the best of our knowledge, there is only one previ- ing gains after interacting with computer-controlled ous study addressing this question (e.g., Lee, 2008). tutors depicted as ‘‘experts’’ when the character’s race is Consider also that cognitive load has multilayered effects nontraditional (i.e., African-American versus Caucasian), and may lead not only to increased avatar stereotyping, as perhaps this is unexpected and, thus, makes participants but also to decreased reliance on stereotypes as docu- pay more attention (Baylor & Kim, 2004). In addition, mented in offline settings (Gilbert & Hixon, 1991; Sher- adults and children prefer physically attractive avatars as man & Frost, 2000). Thus, cognitive load effects on ava- partners (Principe & Langlois, 2013), and attractive avatar perception need to be replicated and different tars are more persuasive (Holzwarth, Janiszewski, & Neu- outcomes remain to be documented. mann, 2006). In general, realistic virtual characters influence social behavior more reliably than less realistic 2 Priming Effects in Virtual Environments characters (Guadagno et al., 2007). Though these studies have expanded our knowledge To understand the effects of avatar appearance, we about the effects of avatar gender, ethnicity, physical turn to priming mechanisms. Priming research focuses attractiveness, and realism on perceivers’ reactions, we on the temporary activation of individuals’ mental con- know less about how visual traits such as avatar clothing cepts on perception, memory, motivation, and behavior color affect perceptions and persuasive outcomes in vir- (Bargh & Chartrand, 2000; Tulving & Schacter, 1990). tual settings. Avatar clothing choices are central to how For instance, the activation of a concept, social group, people express and decode social identity in virtual set- stereotype, or the mere presence of a member of that tings (Martey & Consalvo, 2011). When customizing group (e.g., elderly people) can influence ongoing and avatars for a romantic date, people select elegant clothes subsequent perceptions, emotions, and behaviors including dresses, suits, and accessories for their avatars (Bargh, Chen, & Burrows, 1996). For example, expo- (Vasalou, Joinson, Banziger, Goldie, & Pitt, 2008). In sure to the color black stimulates spontaneous negative addition, the desire to project online identity when peo- thoughts and emotions (Sherman & Clore, 2009). In ple use avatars is linked to intentions to purchase virtual addition, after virtual group discussions, participants items (Kim & Que, 2007). To address this gap, we study using avatars dressed in black developed more aggressive how wearing dark clothes can lead to decreased persua- attitudes compared to those using avatars in white (Penã, sion and more negative perceptions, especially in con- Hancock, & Merola, 2009). texts involving trust, lying, and persuasion (Vrij, 1997). Priming is an umbrella term for phenomena defined as In addition, we examine the effects of cognitive load not conscious (Bargh & Chartrand, 2000). For example, on avatar perceptions. People can experience intense conceptual priming refers to the activation of mental rep- attentional demands as they keep track of targets and resentations in one context so as to observe unconscious objectives when playing video games. Moreover, cogni- influence in unrelated subsequent contexts (Bargh & tive load is a key factor to consider when designing edu- Chartrand, 2000). Participants exposed to concepts such cational video games (Plass, Moreno, & Bru¨nken, as ‘‘reckless’’ and ‘‘adventurous’’ were more likely to use 2010), and it also affects the way people interact with those notions when later forming an impression of a avatar-based computer interfaces (Lee, 2008). Congru- stranger (Higgins, Rholes, & Jones, 1977). Conceptual ent with the traditional prediction that cognitive load priming studies keep tasks as different from outcome leads to increased stereotyping (Fiske & Neuberg, variables to avoid contamination stemming from per- 1990), participants attribute greater competence and sonal goals, awareness, etc. show increased conformity to male instead of female car- Mindset priming captures carryover effects that con- toon avatars only when experiencing cognitive load ceptual priming research overlooks (Bargh & Chartrand,

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2000). These studies have participants engage in goal- comes. Consider the case of dark uniforms and clothes. oriented thought in one context to show how this goal Across many cultures, the color black is linked to death, or mindset then affected ensuing situations. For evil, and anger while the color white is associated with instance, participants read a ‘‘boy meets girl’’ story. Sub- goodness and helpfulness (Adams & Osgood, 1973). sequently, male participants flirted more at female con- Also, people automatically assume that bright objects are federates (Wilson & Capitman, 1982). good and dark objects are bad (Meier, Robinson, & Additionally, sequential priming studies examine the Clore, 2004). For example, color-naming speed in a associative connections between mental representations Stroop task was faster when words in black were linked by varying the time delay between the presentation of to immorality rather than morality, and when words in stimuli to examine whether an effect is unconscious or white concerned morality instead of immorality conscious (Bargh & Chartrand, 2000). If priming effects (Sherman & Clore, 2009). Preference for cleaning prod- occur at short time gaps, then the effect is likely linked ucts moderated the Stroop effect, implying that those to associated concepts stored in memory (Bargh & Char- who value cleanliness were more likely to think that trand). For example, responses to the concept ‘‘nurse’’ immorality is dirty and black and, conversely, that moral- were faster when ‘‘doctor’’ was primed earlier (Meyer & ity is clean and white (Sherman & Clore). Additionally, Schvaneveldt, 1971). suspects wearing dark clothes were perceived as guiltier Studies exploring virtual priming effects borrow ele- and more aggressive compared to those in light clothes ments from conceptual and mindset priming studies in ambiguous legal situations (Vrij, 1997). Sports teams because participants operate avatars with features that in dark uniforms also behaved more aggressively and also can potentially activate mental representations (Penã, were perceived as more aggressive, especially compared 2011). Virtual priming research also adopts supraliminal to teams in white uniforms (Frank & Gilovich, 1988). In instead of subliminal priming assumptions. Unlike par- addition, hockey teams in black jerseys were penalized ticipants in subliminal priming studies, subjects in supra- more frequently, and home teams in white jerseys were liminal priming research are conscious of the presence of penalized less than home teams in colored jerseys (Web- a stimulus (e.g., avatar appearance), but their alertness to ster, Urland, & Correll, 2012). the influence of the stimuli is assessed with awareness The main implications of this research are clear. Ava- checks (Penã, 2011). For instance, participants control- tars in dark clothes will prime more negative mental rep- ling avatars in uniforms with aggressive connotations resentations and will be less influential than avatars in (e.g., dark gowns and KKK-looking robes) developed light clothes: more negative cognitions than those who used avatars H1 Participants who converse with avatar salespeople in with more positive uniforms (e.g., light gowns and doc- black clothes will show (a) lower brand attitudes and pur- tor outfit) (Penã et al., 2009). In addition, participants chase intentions, (b) keep larger distances, (c) lower trust- kept larger interpersonal distances and experienced more worthiness, (d) and bid less money compared to those who arousal when interacting with an avatar of Moroccan interact with avatars in white clothes. instead of Caucasian facial features, implying that avatar Preceding social influence studies inspired the out- faces activate impulsive biased responses (Dotsch & Wig- comes considered in the hypotheses. Social influence boldus, 2008). refers to changes in attitudes, behaviors, or beliefs due to As noted earlier, there is ample research on how avatar real or perceived external factors, while persuasion means visual traits including gender, ethnicity, and attractive- variations in attitudes, opinions, and behaviors based on ness activate involuntary attitudes and behaviors on per- persuasive messages (Guadagno & Cialdini, 2005). Ear- ceivers (Baylor & Kim, 2004; Dotsch & Wigboldus, lier research has operationalized these constructs as 2008; Guadagno et al., 2007; Lee, 2008). However, changes in brand attitudes and purchase intentions based there are fewer studies documenting how avatar clothing on exposure to virtual cues (Ahn & Bailenson, 2011; color affects partner perception and persuasive out- Guadagno et al., 2007; Yoo & Penã, 2011). In addition,

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trustworthiness plays a key role in virtual collaborations (Bargh & Chartrand, 2000). One traditional axiom (Bente, Ru¨ggenberg, Kra¨mer, & Eschenburg, 2008). states that mentally busy people rely more on available Establishing how media properties (e.g., avatar visual re- stereotypical information to form partner impressions solution, interface gender) influence trust by adding (Fiske & Neuberg, 1990). Stereotypical information fits back in the visual cues lost in other technologies is a cen- prior expectations and, thus, it might be easier to grasp tral research question (Bente et al., 2008). Interpersonal and apply, especially when facing cognitive demands distance is also an established factor of interest in non- (Sherman, Conrey, & Groom, 2004). In addition, peo- verbal communication research (Hall, 1966). According ple may exert as little effort as needed when forming to Hall (1966), proxemics is the study of how people partner impressions and, hence, may not attend to infor- unconsciously manage microspace in the conduct of mation that defies prior beliefs (Sherman et al., 2004). everyday transactions. For example, individuals’ use of For example, individual participants viewed a record- space can be classified according to intimate (0–18 ing depicting two women (Macrae, Hewstone, & Grif- inches), personal (1.5–4 feet), social (4–12 feet), and fiths, 1993). Participants were asked to pay attention to public distance (12–25 feet). People using avatars com- one of the women in the conversation, who was labeled pensate for intimacy by regulating distance, as predicted as a doctor or a hairdresser. In addition to the occupa- by equilibrium theory (Argyle & Dean, 1965). For tional prime, half of the participants observed the target example, avatars looked away when virtual characters woman behave in stereotype consistent (e.g., smart and stood closer, perhaps to regulate intimacy (Yee, Bailen- cultured doctors) or inconsistent ways (e.g., intelligent son, Urbanek, Chang, & Merget, 2007). Also, the and cultured hairdresser). Macrae and associates manipu- greater the distance, the less intimacy between avatars lated cognitive load by having participants learn a long (Krikorian, Lee, Chock, & Harms, 2000). As noted ear- or a short number. Cognitively busy participants recalled lier, visual traits, including avatar race and height, can more stereotype consistent information and made more influence virtual interpersonal distances (Dotsch & Wig- stereotypic judgments about the target woman than boldus, 2008; Yee & Bailenson, 2007), but the effects of nonbusy participants (Macrae et al.). In a related study, the partner avatar’s clothing color on proxemics remain participants played a trivia game with a computer (Lee, uncharted. Finally, money bids and offers as a function 2008). A male or female avatar represented the com- of avatar clothing color are worth examining to gauge puter, and half of the participants were made cognitively social influence. For instance, people using taller avatars busy after studying a long number. Participants per- split fictional money more in their favor in negotiations ceived the male interface as more trustworthy and com- compared to those using shorter avatars (Yee & Bailen- petent than the female interface only when cognitively son, 2007). When playing EverQuest, female avatars ask- busy (Lee). Congruent with traditional findings, cogni- ing for aid received more spare change compared to male tive load led to increased gender stereotyping of com- avatars (Yee, 2001). The next section outlines the effects puter interfaces (Lee). of cognitive load. Though cognitive load has reliable Though people under high cognitive load are pre- effects on impression–formation and stereotyping proc- dicted to likely encode and apply stereotypes when esses, the effect of increased attentional demands has not forming impressions, there are exceptions to this rule been fully studied in avatar-based interactions. (Sherman et al., 2004). For example, instead of paying more attention to stereotype consistent information, 3 The Effects of Cognitive Load on cognitively busy participants attended to stereotype Impression–Formation in Virtual inconsistent information (Allen, Sherman, Conrey, & Environments Strossner, 2009; Sherman & Frost, 2000). This effect is reliable but less prevalent than the traditional predic- Cognitive load regulates priming effects on impres- tion (Sherman et al.,). Reduced stereotyping under sion–formation, stereotyping, and social influence cognitiveloadislikelyrelatedtoflexibleinformation

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processing, as cognitive load requires people to reallo- and, thus, the study’s sample was N ¼ 83. Participants cate attention in order to process both stereotypical and were between the ages of 18 and 23 (M ¼ 20.83, SD ¼ counterstereotypical information. Once stereotypical 2.86). Twenty-six participants were men and fifty-seven information is understood, attention may shift away to were women. The participants were given same-gender inconsistent, unique, or intricate information (Sherman avatars. To balance avatar assignment by gender, an et al.,). equal number of participants of each gender was In addition, contrary to traditional predictions, cogni- assigned to the avatar clothing color conditions. Among tively busy perceivers were less likely than nonbusy per- male participants, 14 subjects conversed with avatars ceivers to form stereotypical impressions (Gilbert & dressed in black and 12 subjects communicated with ava- Hixon, 1991). After meeting Asian or Caucasian targets, tars in white. Among female participants, 27 participants cognitively nonbusy participants ended unfinished words communicated with avatars in black and the rest con- more stereotypically (e.g., answering ‘‘rice’’ in the frag- versed with avatars in white. Fifty-four participants were ment RI_E) than cognitively busy participants. One ex- Caucasian, 12 Hispanic, 10 Asian, 3 African-American, 3 planation for this effect is that there are clear activation Native American, and 1 came from another ethnic back- and application phases when forming stereotypical ground. impressions, and that cognitive load can disrupt both phases (Gilbert & Hixon). In sum, cognitive load should affect partner avatar perceptions. One possibility is that 4.2 Pretest and Materials people experiencing cognitive load will generate more stereotypical avatar perceptions (e.g., Lee, 2008). 4.2.1 Avatars. A game designer created the vir- Another possibility is that cognitive load disrupts stereo- tual store along with male and female salespeople avatars type processing and application in avatar-based interac- dressed in black or white clothes (see Figure 1). All ava- tions (Gilbert & Hixon). Thus: tar salespeople were Caucasian. The experimental avatars H2 Cognitively busy participants will generate (a) were pretested using a different sample to establish the more negative impressions of avatars dressed in black and perceptions raised by the characters (N ¼ 60, with equal (b) more positive perceptions of avatars in white compared numbers of men and women). Individual participants to cognitively nonbusy participants. evaluated a single avatar that matched the judge’s gen- H3 Cognitively nonbusy participants will generate (a) der. For example, female participants evaluated the same more negative impressions of avatars dressed in black com- female avatar dressed in black or white clothes. The par- pared to white clothes and (b) cognitively busy participants ticipants rated the avatars using four 7-point semantic will not differentiate between the avatars due to mental load. differential items taken from Muehling and Laczniak’s (1988) study. The semantic differential items were nega- 4 Method tive/positive, bad/good, harmful/beneficial, and unpleasant/pleasant. The scale was reliable (a ¼ .89). 4.1 Participants Participants’ responses were averaged to create an avatar Ninety-three undergraduate students were perception scale. Participants developed significantly recruited from communication courses at a large public more negative attitudes toward avatars dressed in black university in the U.S. in exchange for extra course credit. (M ¼ 3.80, SD ¼ .58) compared to avatars in white They partook in an experiment employing a 2 (avatar (M ¼ 5.25, SD ¼ 1.32), F(1, 58) ¼ 30.21, p < .001, salesperson appearance: black vs. white clothes) by 2 Z2 ¼ .34. No gender differences were found, F < 1. (cognitive load induction: high vs. low load) between- Thus, the pretest showed that avatar salespeople dressed subjects factorial design. Ten participants did not fulfill in dark clothes were perceived as more negative than the the parameters of the cognitive load manipulation same avatar dressed in white. This effect operated equally described next. They were excluded from the analysis on both male and female participants.

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Figure 1. Avatar salespeople in black or white clothes.

4.2.2 Virtual Store. The experiment’s store was (see Figure 3). The participants could move freely similar to a typical 3D virtual store in PlayStation Home around the store but salespeople avatars remained static or Second Life to increase engagement with the study behind a desk. and to augment its realism and generalizability. The virtual store consisted of two separate rooms with a corri- 4.2.3 Computer System. The virtual environ- dor connecting each room. The first room was used to ments and the avatars were presented to the participants train participants to move their avatar and communicate using Dell Precision M6300 laptops connected to 23-inch with text messages and to manipulate participants’ cog- LCD screens. The participants navigated the virtual envi- nitive load (see Figure 2). The second room contained ronment with keyboard and mouse in first-person perspec- the virtual store where interactions with salespeople ava- tive and, thus, they could not see their own avatar. tars took place. Note that the floor of the virtual store was designed as a Likert-type scale measuring the dis- 4.3 Procedure tance between the participants’ avatar and the virtual salespeople. Seven rectangular tiles separated the en- After granting informed consent, individual partici- trance of the virtual store from the salesperson avatar pants were randomly assigned to the experimental condi-

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Figure 2. High and low cognitive load manipulations.

conditions. Participants could text-message back their comments. The salesperson avatar pitched an online music pass similar to an iTunes gift card. The music pass had a fictitious name (i.e., T1000) to avoid biases based on familiarity with the product. The conversation was scripted using the Wizard of Oz technique (Brennan, 1990), which allows simulating natural con- versations between people and machines. The experi- menter was trained on how to text-message the sales script at similar rates, answer questions, and redirect the conversation back to the script if needed (Brennan, Figure 3. The virtual store (floor tiles were used to measure distance in a 1 to 7 scale). 1990). The participants were not told whether the salesperson avatar was an AI or a real person to prevent tions. Cognitive load was manipulated while in the train- that belief from affecting the results (Guadagno et al., ing room and prior to interacting with a randomly 2007; Guadagno, Swinth, & Blascovich, 2011). Inter- assigned salesperson avatar (see Figure 2). After learning actions with the salesperson avatar took 5–8 minutes. how to move and communicate using text messages, the All interactions were stored with a video recording participants were asked to memorize a randomly program. assigned number. In the low cognitive load condition Participants were then asked to fill out an online sur- this was a single digit (‘‘6’’), while in the high cognitive vey. The questionnaire asked the participants to evaluate load condition this was a seven-digit number the salesperson avatar that they had interacted with. The (‘‘3612685’’). The participants were given 30 seconds to participants also stated their brand attitude and purchase memorize the assigned number. This procedure has intention about the online music pass depicted in the been employed in several studies examining how cogni- sales pitch. The survey also measured participants’ per- tive load affects stereotyping and impression-formation ceived trustworthiness toward the salesperson avatar. (Gilbert & Hixon, 1991; Lee, 2008; Macrae et al., Next, the participants shared their demographic infor- 1993). mation, experience with video games and online com- Following the cognitive load manipulation, the par- merce, and their music consumption habits. In addition, ticipants walked into the virtual store and met the ran- the participants reproduced the number that they mem- domly assigned salesperson avatar dressed in black or orized for the cognitive load manipulation. Participants white clothes. Salespeople avatars text-messaged the also stated the color of the avatar salesperson’s garments. same short script to the participant in all experimental Lastly, participants responded to an awareness check and

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then were fully debriefed. The survey also collected 4.4.4 Bidding. To measure the effect of the avatar mood and interpersonal attraction data that will appear and cognitive load manipulations on virtual bids and in a different study. Survey responses were recorded in money offers, the participants were asked to name a price an online database for statistical analysis. for the online pass (i.e., ‘‘The regular price for the T1000 music pass is $14.99 per month in the virtual store. How much would you pay for the T1000 music 4.4 Dependent Measures pass?’’). 4.4.1 Brand Attitude and Purchase Intention. Purchase intention and brand attitude to- 5 Results ward the online pass pitched by the avatar salespeople was measured with items inspired by Ajzen (2002). Pur- 5.1 Awareness and Manipulation chase intention was assessed with three questions (e.g., Checks ‘‘I intend to purchase the ‘T1000 music pass’ between 5.1.1 Awareness Check. The participants were now and the holiday season’’). The items were arrayed in asked to answer awareness check items to determine 7-point Likert-type scales (1 ¼ extremely unlikely, 7 ¼ whether they knew the objective of the experiment. The extremely likely). The participants stated their attitudes questions were based on Bargh and Chartrand’s (2000) using 7-point semantic differential scales pleasant/ recommendations on how to measure awareness in pri- unpleasant, good/bad, and worthless/valuable. The ming research using funneled debriefing forms. The scales were reliable (a ¼ .81). Participants’ responses awareness check asked participants what they thought were averaged to create attitude and purchase intention the experiment was trying to study. No participant indices. showed awareness of the purpose of the avatar appearance and cognitive load manipulations. 4.4.2 Interpersonal Distance. The floor tiles of the virtual store were designed as a 7-point Likert-type 5.1.2 Avatar Appearance. The participants were scale (see Figure 3). Seven tiles separated participants asked to identify the clothing color of the avatar salesper- from the salespeople avatars’ sales desk. Distance in tiles son. All of the participants correctly identified the cloth- was recorded at the end of the interactions. This proce- ing color of the avatar. dure was inspired by a stereotype rebound study that showed that participants trying to suppress stereotypical 5.1.3 Cognitive Load. The participants were beliefs held larger social distances from a target (as meas- asked to reproduce the number they learned for the cog- ured in chairs) than those who did not suppress stereo- nitive load manipulation. As noted earlier, 10 partici- typical beliefs (Macrae, Bodenhausen, Milne, & Jetten, pants were excluded from the study because they failed 1994, Experiment 2). When scaled up to real-world dis- to memorize their assigned number (see Gilbert & tances, each tile was 62 inches, and the total distance Hixon, 1991). from the entrance of the virtual store to the salespeople avatars’ desk was 434 inches (36.2 feet). 5.2 The Effects of Avatar Appearance and Cognitive Load on Avatar 4.4.3 Perceived Trustworthiness. Trustwor- Perceptions thiness was measured using a five-item scale developed by McAllister (1995). Participants expressed their per- The analyses initially employed participants’ previ- ceived trustworthiness toward the salesperson avatar ous gaming experience and music consumption habits as with statements such as: ‘‘If I shared my problems with covariates in an attempt to isolate the effect of these fac- this person, I know (s)he would respond constructively tors. The covariates were not statistically significant and, and caringly.’’ The scale was reliable (a ¼ .80). therefore, we employed ANOVAs to test for the hypoth-

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eses. H1a–d predicted that partner avatars dressed in black would be less persuasive than the same avatars dressed in white. The main effects of the cognitive load manipulation appear in a footnote1 because they were not central to the study. Participants’ gender had no effects. Did avatar salespeoples’ clothing color affect participants’ perceptions of the avatar and the persuasiveness of the sales pitch? The ANOVA test revealed that avatar clothing color affected participants’ attitudes about the product sold by the avatars: F(1, 83) ¼ 6.52, p < .01, Z2 ¼ .08. Attitudes toward the item presented in the virtual store were significantly lower after interacting with Figure 4. Interaction effects of avatar appearance and cognitive load salespeople avatars dressed in black (M ¼ 3.45, SD ¼ on perceived trust. .86) compared to participants who interacted with avatars dressed in white (M ¼ 4.11, SD ¼1.38). In addition, ing with avatar salespeople dressed in black (M ¼ 2.60, participants’ intentions to purchase the item were signifi- SD ¼ 1.18) relative to participants who met avatars cantly lower for participants who met avatars dressed in dressed in white (M ¼ 1.45, SD ¼ .86), F(1, 83) ¼ black clothes (M ¼ 2.30, SD ¼ 1.27) relative to those 25.61, p < .001, Z2 ¼ .18. This result supported H1c. who interacted with avatars dressed in white (M ¼ 3.18, In real-world distances, participants communicating with SD ¼ 1.50), F(1, 83) ¼ 7.98, p ¼ .006, Z2 ¼ .09. These avatar salespeople dressed in black stood at 161.2 inches findings supported H1a. No interaction effects were (13.43 feet), while those who interacted with avatars in found. white stood at 89.9 inches (7.49 feet). No interaction Furthermore, participants offered less money for the effects between avatar appearance and cognitive load product after interacting with avatar salespeople dressed were found. in black (M ¼ 6.25, SD ¼ 2.72) compared to those who Did avatar clothing color and cognitive load affect par- conversed with avatar salespeople dressed in white (M ¼ ticipants’ trust toward the salesperson avatar? An 8.56, SD ¼ 2.31), F(1, 83) ¼ 17.75, p < .001, Z2 ¼ ANOVA revealed that participants expressed less trust .18. This finding supported H1b. No interaction effects toward avatar salespeople dressed in black (M ¼ 3.12, with cognitive load were found. SD ¼ .89) compared to avatars dressed in white (M ¼ The analysis also uncovered that participants main- 4.22, SD ¼ 1.25), F(1, 83) ¼ 23.31, p < .001, Z2 ¼ tained larger interpersonal distances when communicat- .23. This result supported H1d. The effect of avatar appearance on perceived trustworthiness was qualified by a statistically significant interaction effect: F(1, 83) ¼ 1. An ANCOVA found that cognitive load affected participants’ atti- 5.84, p < .05, Z2 ¼ .07. The interaction appears in Fig- tudes regarding the virtual item: F(1, 83) ¼ 4.06, p < .05, Z2 ¼ .04. Attitudes toward the product presented in the virtual store were signifi- ure 4. Cognitively nonbusy participants expressed less cantly lower for participants assigned to the high cognitive load condi- trust toward avatar salespeople dressed in black (M ¼ tion (M ¼ 3.52, SD ¼ 1.11) compared to those in the low cognitive load condition (M ¼ 4.04, SD ¼1.23). Participants’ trust toward the 3.23, SD ¼ .77) compared to avatar salespeople in white avatar was significantly lower for participants in the high cognitive load clothes (M ¼ 4.84, SD ¼ 1.05), t(41) ¼ 5.67, p < .001. condition (M ¼ 3.28, SD ¼ 1.08) compared to participants in the low This replicated the pattern in H1d for cognitively non- cognitive load condition (M ¼ 4.06, SD ¼1.23), F(1, 83) ¼ 11.09, p < .01, Z2 ¼ .12. Lastly, participants in the high cognitive load condition busy participants. However, when cognitive load was (M ¼ 6.64, SD ¼ 2.32) offered less money for the product than those high, there was no perceived trustworthiness differences who were in the low cognitive load condition (M ¼ 8.28, SD ¼2.97), F(1, 83) ¼ 7.40, p < .01, Z2 ¼ .08. There were no significant effects of between avatars in black (M ¼ 3.04, SD ¼ .94) and cognitive load on purchase intentions and interpersonal distance. white clothes (M ¼ 3.33, SD ¼ 1.13), t(48) ¼ .93, ns.

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In addition, cognitively nonbusy participants rated ava- distances were affected by avatars’ ethnicity and physical tars in white as more trustworthy (M ¼ 4.84, SD ¼ attractiveness (Dotsch & Wigboldus, 2008; Yee & Bai- 1.05) compared to cognitively busy participants (M ¼ lenson, 2007), this is the first study showing that avatar 3.33, SD ¼ .77), t(44) ¼ 4.49, p < .001. The results dis- clothing colors also affect virtual proxemics. Considering confirmed H2a–b but confirmed H3a–b, as cognitively Hall’s (1966) personal distance classification system, par- nonbusy participants rated avatars dressed in black as less ticipants conversed with avatars dressed in white at social trustworthy compared to avatars in white but cognitively distances usually reserved for business and social dis- busy participants did not differentiate between the ava- course (7.49 feet), while those who communicated with tars in terms of perceived trustworthiness. avatars in black maintained public distances usually reserved for acquaintances or strangers (13.43 feet). 6 Discussion According to Hall (1966, p. 123), ‘‘At twelve feet an alert subject can take defensive action if threatened. The This study investigated how avatar clothing color distance might be a vestigial but subliminal form of flight influenced attitudes and intentions, trustworthiness, bid- reaction.’’ This resonates with the assumption that pri- ding, and interpersonal distance. While previous studies ming has a noticeable influence on behavioral measures examined how avatar race, gender, attractiveness, and re- because social behavior is automatically affected by con- alism affect users’ cognition and behavior, fewer studies text (Bargh et al., 1996). The results can also inform the had explored the social influence effects of partners’ ava- design of games and virtual shopping experiences based tar clothing color. In addition, to the best of our knowl- on how avatar salespeople’s clothing color can make visi- edge, there was only one preceding study examining tors keep virtual salespeople near or at arm’s length. how cognitive load influenced avatar perceptions (i.e., Additionally, salesperson avatar clothing color affected Lee, 2008). Earlier research suggested that cognitive participant’s bids for a virtual product. For example, par- load frequently leads to increased stereotyping, but there ticipants offered $2.31 more for the same virtual product are exceptions to this rule (Sherman et al., 2004). This when avatars in light instead of dark clothes introduced it. study observed one such exception in relation to avatar These findings add to mounting evidence of how avatar trustworthiness perceptions. visual cues unconsciously influenced virtual social interac- Interacting with an avatar salesperson dressed in dark tions. As noted, computer interfaces represented by a clothes diminished participants’ brand attitude and pur- male character were more persuasive when playing trivia chase intention of a fictitious product compared to avatar games than interfaces represented by female characters, salespeople in white clothes. This effect is congruent particularly when participants were cognitively busy (Lee, with studies showing that, in real-life contexts, wearing 2008). Nowak and Rauh (2005) found that anthropo- dark clothes prompted negative perceptions in situations morphic avatars were more trustworthy than less human- involving suspiciousness and trustworthiness (Vrij, like avatars. This result may inform the design of virtual 1997). This effect has also been replicated in virtual envi- shopping experiences based on how avatar clothing color ronments in relation to how avatar appearance primed socially influenced money bids in online transactions. negative mental representations on people controlling Though it is commonly expected that cognitive load avatars in dark uniforms (Penã et al., 2009). The aware- increases stereotyping of people (Fiske & Neuberg, ness check showed that participants were not conscious 1990) and, more recently, gendered avatars (Lee, 2008), of the intended effect of avatar salespeople’s appearance. there are important caveats to this rule (Sherman et al., This implies that these effects were unconscious in na- 2004). In the present study, cognitively nonbusy partici- ture as suggested by priming mechanisms. pants expressed less trust towards avatar salespeople In addition, communicating with salespeople avatars dressed in black instead of white clothes, while cogni- in dark clothes triggered larger interpersonal distances tively busy participants trusted both characters equally. relative to avatars in white. Though virtual interpersonal Congruent with Gilbert and Hixon (1991), it is likely

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that cognitively nonbusy participants rated avatars in the trustworthiness interaction effect, cognitive load in black as less trustworthy because they had more mental itself decreased attitudes, intentions, trustworthiness, resources to evaluate the avatars. Following Gilbert etc., thus indicating that mental load differences were and Hixon’s reasoning, it is likely that cognitively busy fully operating (see footnote 1). A more likely explana- participants had fewer attentional resources to devote tion is that virtual experiences’ activation effects were to the avatars and, thus, found them similarly trustwor- restricted by the strength of the link between a real- thy. world concept and its virtual counterpart (Williams, Though the results are informative, several issues need 2006). Consider that the connection between wearing to be considered. First, the findings contradict the tradi- dark clothes and reduced trustworthiness is well estab- tional notion that cognitive load leads to increased ster- lished (Vrij, 1997), and this possibly restricted avatar eotyping of people, computer interface avatars, etc. clothing color and cognitive load effects to affect factors Though increased partner stereotyping when perceivers that were more strongly linked to the study’s context experience cognitive load has been well documented (see Williams). Another likely explanation as to why ava- (e.g., Lee, 2008; Macrae et al., 1993), cognitive load can tar clothing color and cognitive load affected only per- also disrupt the activation and application of stereotypes ceived trust is that the scale we implemented measured (Gilbert & Hixon, 1991) and direct attention to stereo- the affective dimension of trust by focusing on sharing type inconsistent information (Sherman & Frost, 2000). emotions, competence, and whether a person was uncar- In this regard, it is likely that the cognitive load manipu- ing and unconstructive (see McAllister, 1995). Future lation affected the application but not the activation of studies should investigate whether the priming effects stereotypical avatar perceptions. Manipulation checks of avatar appearance combined with cognitive load are revealed that all of the participants correctly identified the more successful at influencing affective responses clothing color of salespeople avatars, and clothing color compared to attitudes and behaviors. had the main intended effects (see H1). This suggests that stereotypical perceptions of characters dressed in 6.1 Limitations dark or light clothes were successfully activated. How- ever, cognitively busy participants found avatars in dark One limitation of this study was using a rather con- and white clothes equally trustworthy, perhaps suggest- trived manipulation of cognitive load. Though having ing that they did not apply the black ¼ bad and white ¼ participants memorize a long or short number has been good heuristic to the virtual characters. Future studies widely used in previous research (Gilbert & Hixon, should clarify how exactly cognitive load affects the acti- 1991; Lee, 2008; Macrae et al., 1993), educational vation and application of stereotypes when forming ava- researchers have examined cognitive load by adding or tar impression. According to Gilbert and Hixon, the subtracting factors connected to the experience of being timing of the onset of cognitive busyness may determine online, such as visual and aural information, interface whether cognitive load will increase or impair avatar ster- design, and player control, among others (Huang & eotyping. Stereotyping is more likely to occur when social Tettegah, 2010). Players need to have sufficient cogni- labels are activated prior to an episode of cognitive load. tive capacity to develop empathy for other characters in Avatar appearance may lead to more stereotypical impres- educational ‘‘serious games’’ teaching about humanitar- sions if people see the virtual characters before experienc- ian issues (Huang & Tettegah). Future research should ing cognitive load. employ cognitive load manipulations that make more Second, it is not clear why only perceived trustworthi- sense in context. For example, manipulating attentional ness was affected by avatar appearance and cognitive load demands by altering the amount of visual and aural while the rest of the outcome variables remained unaf- cues (Plass et al., 2010) makes more sense in video fected. The results cannot be attributed to ineffective- games and educational technologies than memorizing a ness of the cognitive load manipulation. In addition to digit. Nevertheless, the choice of the cognitive load

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manipulation is not a fatal flaw. This manipulation has Strathman, and Priester (2005, p. 116), the ELM is a been extensively validated in previous research (Gilbert theory of persuasion that explains attitude change based & Hixon; Lee; Macrae et al.). on the amount and nature of thinking people do about Another limitation was not specifying to participants persuasive messages (see also Petty & Cacioppo, 1986). whether they were interacting with human or computer- Following this definition, the ELM could potentially controlled avatar salespeople. The belief that one is inter- account for the product attitude and purchase intention acting with a computer or human-controlled avatar can findings based on peripheral route processes. Instead of influence user responses (e.g., Guadagno, Blascovich, effortful and motivated elaboration of persuasive mes- Bailenson, & McCall, 2007). Though this is an impor- sages represented by the central route, it is likely that par- tant consideration, it may not annul our findings because ticipants simply were swayed by peripheral cues including unless avatar–agent agency was theorized and manipu- source attributes, heuristics, and mental shortcuts (i.e., lated (Guadagno et al., 2007, 2011), previous studies good people wear light clothes; bad people wear dark did not specify human or computer-controlled avatar outfits). Priming refers to temporary and unconscious agency to participants. For example, Dotsch and Wig- activation of thoughts, affect, and behavioral tendencies boldus (2008) did not detail whether Moroccan or Cau- based on exposure to concepts, individuals, and stereo- casian avatars were human or computer-controlled. In types (Bargh & Chartrand, 2000). Priming mechanisms addition, studies examining the effects of computer-con- have accounted for an array of unconscious social influ- trolled tutoring agents did not specify whether the char- ence phenomena (Bargh & Chartrand). Considering acter was human or computer-controlled (Baylor & these definitions, priming was a more parsimonious ex- Kim, 2004). Yee and Bailenson (2007) trained confeder- planation than the ELM because the former theory ates with conversation scripts but did not detail to partic- explains broader social influence phenomena, while the ipants whether the confederate avatar was a human or latter theory restricts itself to explaining attitudes. The not. In another study, Groom and associates (2009) also ELM is bounded to attitudinal processes (Petty et al., did not specify whether Caucasian or nonwhite confed- 2005), while priming has been associated with trustwor- erate avatars were human or computer-controlled. In thiness, interpersonal distance, and attitude formation general, studies that manipulate virtual character agency and change. For example, subtly using words such as tend to specify this information to participants, while ‘‘partner’’ or ‘‘opponent’’ when giving experimental studies centering on different outcome variables may or instructions affected subsequent trustworthiness when may not disclose such information. Future research playing bargaining games (Burnham, McCabe, & Smith, should examine the combined effects of avatar clothing, 2000). In addition, participants primed with independent cognitive load, and human or computer-controlled ava- self-construals sat further away from a person in a waiting tar agency. Human avatar agency should augment the room compared to a control group, while those primed effects of avatar appearance and cognitive load, as it is with interdependent self-construals sat closer to the other expected that more realistic, anthropomorphic, and sen- person than those primed with an independent self (Hol- tient virtual characters should be more influential. land, Roeder, van Baaren, Brandt, & Hannover, 2004). In addition, though we rationalized avatar appearance Priming mechanisms also have been linked to attitude effects based on priming mechanisms, alternative frame- change. Media exposure can make certain issues more ac- works could explain the results. For example, the Elabo- cessible or easily recalled for people, thus influencing ration Likelihood Model (ELM) can potentially explain their standards when forming attitudes about candidates our findings based on peripheral persuasion effects. How- and political issues (Scheufele & Tewksbury, 2007). ever, some issues to consider are the boundary conditions Considering these issues, priming is the more inclusive and object of study of priming and ELM research, and explanation for the findings. While ELM concerns itself the substantial overlap between peripheral processes and with attitudes, priming accounts for broader social influ- priming mechanisms. According to Petty, Cacioppo, ence processes.

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