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Abstract

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

Consumer discrimination occurs when sales clerks and other store employees, including security personnel, treat customers differently because of their race or ethnicity. The goal of the present research was to examine how participants perceived a case of consumer discrimination and what actions they felt the victim should take. Based on Robinson's theory of perceptual segregation, we examined whether the perceptions and responses of white participants differed from those of people of color. We also drew on the liberation psychology tenets of conscientization and de-ideologization with particular emphasis on taking the perspective of the oppressed, by measuring participants’ level of perceived societal discrimination. These two individual difference variables (participant race and perceived societal discrimination) significantly predicted participants’ perceptions of the situation and their emotional responses, which, in turn, mediated how they thought the customer should respond.

When New Yorker Denise Simon goes shopping, she is always on guard. She carries a small bag, keeps her hands visible whenever possible, and makes an effort to be overly friendly to sales clerks. She doesn't have any reason to be wary except for one thing—she happens to be Black. And if she doesn't take these precautions, she fears she will once again fall victim to racial profiling. (Norman, 2009)

Perceptual Segregation

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

Perceiving discrimination is more difficult today given that its expression is rarely overt. Because modern racism is subtle, potential incidents of discrimination can be attributed to other factors. Robinson (2008) argues that the phenomenon of perceptual segregation inhibits people of different races from reaching a common understanding of incidents that are not clearly race-based. He defines perceptual segregation as a social construct that results in people of color and Whites interpreting potential incidents of discrimination through fundamentally different psychological frameworks. Due to informational and incentive disparities, Robinson believes that Blacks and Whites are likely to disagree on the very definition of “racial discrimination” with many Whites expecting it to be explicit while many Blacks perceive it to be primarily implicit (see also Sommers & Norton, 2006). Although perceptual segregation theory suggests that an individual's race is a predictor of his or her attitudes toward an ambiguous event, race may not be the only determinant.1

Racial differences in interpretations of discrimination may be due to the fact that Black Americans tend to have more extensive and accurate knowledge of racism in U.S. history than White Americans. Studies show that individuals with a greater awareness of the oppression faced by members of a particular racial or ethnic group are more likely to interpret ambiguous behavior as discrimination regardless of their own race (Adams, O'Brien, & Nelson, 2006; Nelson, 2010; Nelson, Adams, Branscombe, & Schmitt, 2010). These findings can be interpreted within the framework of liberation psychology.

Liberation Psychology

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

Liberation psychology was introduced by Martín-Baró (1994) during the 1970s to address the social issues and societal problems in existence under the oppressive and authoritarian regimes of many Latin American countries. The notion of liberation was introduced by Freire whose work strongly influenced Latin American social sciences (Flores Osorio, 2009). Recently, several social psychologists have recognized the relevance of this theoretical approach to research in other cultural contexts (Adams et al., 2006; Burton & Kagan, 2009). Adams et al. (2006) and Nelson (2010) used this framework in order to more fully understand the racial differences in perceptions of the U.S. government's response to Hurricane Katrina.

Generally, researchers studying intergroup relations attempt to understand why members of minority/nondominant groups think, behave, or perceive events differently than Whites. In contrast, the tenet of de-ideologization cautions academics that mainstream thinking and cultural contexts narrow our perspectives (Martín-Baró, 1994). For example, in explaining perceptions of racism during the Hurricane Katrina tragedy, Adams et al. (2006) argued that the perceptions of Whites should be examined critically rather than serving as the normative standard against which the perceptions of people of color were evaluated.

Another essential—and related—component of liberation psychology requires considering the perspective of the targets of social injustice. Martín-Baró used Friere's concept of “conscientization” to explain the dynamic relationship between the activists, academics, or external catalytic agents and the oppressed people themselves. The oppressed racial minorities provide insight and essential information to fully understand the complex systems at work. The external agents bring knowledge and tools for change. Through this relationship, social justice can be achieved (Burton & Kagan, 2009).

De-ideologization and conscientization promote system-challenging perceptions and behaviors. In contrast, mainstream and traditional perspectives are system-reproducing in that they result in perceptions and behaviors that perpetuate racism. When people are more aware of the systematic forces that oppress racial minorities, they are more likely to view inequalities as being due to racism (Adams et al., 2006; Nelson et al., 2010). For example, Nelson et al. (2010) found that Whites characterized current incidents of anti-Black conspiracies as implausible. But, with more knowledge of actual anti-Black conspiracies in U.S. history, through conscientization, they were more open to the plausibility of the current anti-Black incidents.

Just as many White Americans are unfamiliar with some episodes of racism in U.S. history, they are also less aware of the microaggressions that people of color continue to face today. Defined as “brief everyday exchanges that send denigrating messages to people of color because they belong to a racial minority group…, [m]icro-aggressions are often unconsciously delivered in the form of subtle snubs or dismissive looks, gestures, and tones” (Sue et al., 2007b, p. 273). These daily incidents have a cumulative debilitating effect over the course of a person's lifetime resulting in an erosion of self-confidence as well as physical consequences such as stress-related illnesses (Barksdale, Farrug, & Harkness, 2009).

Consumer Discrimination

Our introductory quote illustrates one type of microaggression that people of color encounter while shopping in retail stores. They report being followed, accused of shoplifting, detained and searched while shopping (Crockett, Grier, & Williams, 2003; Gabbidon, 2003; Lee, 2000; Schreer, Smith, & Thomas, 2009). The subtle discrimination they face includes being required to prepay for goods or services and receiving slow or rude service (Brewster, 2012; Harris, 2003; Rusche & Brewster, 2008; Sue, Bucceri, Lin, Nadal, & Torino, 2007a). These types of incidents in which sales clerks, security personnel, and other store employees treat shoppers differently because of their race or ethnicity constitute “consumer discrimination” (Williams, Hakstian, & Henderson, 2009).

Prevalence

While reliable data to confirm the regularity of consumer discrimination are limited, a few studies provide some insight into its frequency. In 1998, economist Peter Siegelman estimated that the probability of discrimination in any given restaurant visit or shopping trip is approximately 1–5% (Siegelman, 1998). In a study of restaurants in which servers were questioned about the treatment of patrons, over 50% of respondents reported that they sometimes observed their coworkers providing inferior service to African American customers. In addition, 38.5% of respondents admitted that, at least sometimes, the quality of their own service varied according to the customers’ race (Brewster & Rusche, 2012). Two studies of consumer racial profiling (CRP), a form of consumer discrimination in which people are suspected of criminal activity due to their race, showed that Black respondents were much more likely than Whites to report having experienced CRP (Gabbidon & Higgins, 2007; Gabbidon, Craig, Okafo, Marzette, & Peterson, 2008).

Perceptions

Like discrimination that arises in other contexts, it is not always clear whether poor treatment in retail settings is due to racial bias of store personnel. Consistent with the theory of perceptual segregation, Baker, Meyer, and Johnson (2008) found that African American participants were more likely to attribute a service failure to racism. White participants’ attribution of poor service to racism occurred only when it was unambiguous, that is, when they had explicit information that White customers received better service than customers of color. Similarly, a survey of 1,000 households revealed that most African Americans (86%) believe that racial discrimination exists in the marketplace compared to only 34% of Whites (Williams & Snuggs, 1996). More recently, Jordan, Gabbidon, and Higgins (2009) found that Blacks were significantly more likely than Whites to believe that the profiling of customers based on their race is widespread. Similarly, a 2004 Gallup poll revealed that other non-Whites’ perceptions differ from those of Whites with 65% of Blacks, 56% of Hispanics, and only 45% of Whites reporting that racial profiling in malls and stores is widespread (Carlson, 2004).

Emotional reactions to consumer discrimination

The emotions of customers who experience poor treatment in retail stores have been described as mirroring those of crime victims. Among those feelings are anger, anxiety, confusion, helplessness, and shame (Chebat & Slusarczyk, 2005; Friend, Costley, & Brown, 2009; Gabbidon et al., 2008; Higgins & Gabbidon, 2009). In addition, the experience of CRP can negatively affect an individual's self-worth (Gabbidon et al., 2008). In measuring emotional responses to discrimination in a sample of Black Americans, Barksdale et al. (2009) found that the most common emotional responses were feelings of anger and frustration, but they also felt strengthened. Baker et al. (2008) examined people's emotional reactions to service failures and found that Black participants were angrier about an incident of consumer discrimination than were White participants. Interestingly, Baker and Meyer (2011) found that White participants with high levels of empathy reacted similarly to Blacks in terms of their emotional responses to service failure in stores. Some studies have documented the importance of emotions in mediating responses to discrimination. For example, Chebat and Slusarczyk (2005) examined the effect of a bank's efforts to recover from a service failure on customer loyalty. Importantly, the customer's own emotional responses to the recovery attempts significantly mediated this relationship with positive emotions (joy and hope) predicting customer loyalty and negative emotions (anxiety and disgust) associated with switching to another bank.

Behavioral responses

Because they are microaggressions, each incident of consumer discrimination may seem relatively small making it difficult to determine the appropriate response. A customer's choice of actions may range from responses that challenge the racism of the system, to addressing the mistreatment at an individual level, to taking no action at all thus allowing the racism to persist. Gabbidon et al. (2008) found that only 18% of the students they surveyed reported the CRP incident to a representative of the company (system-challenging), whereas 84% of the students shared the details with friends. Moreover, a sizeable number of them still made a purchase (49%) and later returned to the store (system-reproducing). Other research has shown that very few people of color have actually sued retailers for discriminating against them while they shopped (system-challenging; Harris, 2003; Harris, Henderson, & Williams, 2005; Williams, Harris, & Henderson, 2006). Therefore, it is important to understand how people characterize and respond to episodes of consumer discrimination and the extent to which they support system-challenging versus system-reproducing responses.

Overview of this Study

The present research examines people's perceptual, emotional, and behavioral responses to an incident of consumer discrimination as well as the role of their race and their awareness of societal discrimination in shaping their responses. It provides insight into their reactions to a scenario in which a person of color receives poor treatment in a department store.

Our key independent variables are participants’ race and level of perceived societal discrimination against the target group (PSD). These two variables allow us to explore the perspective of the “oppressed” and the extent of our participants’ awareness of the oppression (conscientization) that exists in society. The dependent variables are the behavioral responses to the incident of consumer discrimination, that is, the extent to which participants agree that the customer should exit the store and return later, complain to store personnel, and complain to others outside the store. Furthermore, we examine the mediating effects of participants’ perceptions of the incident (general disapproval of the sales clerk and race attribution) and their emotional responses to the incident (anger, anxiety, and empowerment).

We hypothesize that people of color will have more system-challenging responses to the incident of consumer discrimination than Whites. However, the participants’ race alone will not explain their responses. Based on liberation psychology, we predict that participants with higher levels of PSD (i.e. conscientization) will have more system-challenging responses to the incident than those with lower levels. Finally, we hypothesize that these effects will be mediated by the participants’ perceptions of and emotional responses to the consumer discrimination incident. Specifically, general disapproval and anxiety will lead to a system-reproducing response whereas race attribution, anger, and empowerment will lead to a system-challenging one.

Methods

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

Participants

Two online survey panels were used to collect data for the study. The first panel was an opt-in privacy-protected subject pool recruited for Web-based research. It was established and is operated by a public university in the southwest. The second panel was recruited through an “invitation only” model by a full-service commercial market research firm with profiles of over 22 million online users. All panelists were compensated through incentives including cash and other prizes. The survey was administered online using Qualtrics survey software. Invitations were sent via email with a Web link to initiate the study. The response rates were similar across both panels, about 16%. The sample consisted of 1,206 participants, 322 males (26.7%) and 884 females (73.3%). Participants were between 17 and 83 years of age (M = 43.88). Although they represented all geographic regions of the country, the participants were predominantly from the Northeast (21.0%), Southwest (20.8%), and Midwest (18.1%). Because a primary focus of our study was to understand differences among racial/ethnic groups and because the first panel skewed heavily toward non-Hispanic Whites, the second panel matched the demographics of the first panel but over-sampled African Americans. The overall sample consisted of 53.5% Whites, 35.1% Blacks, 2.6% Latino, 3.7% mixed, and 5.1% others.

Scenarios

The scenario was based on facts from actual consumer discrimination lawsuits decided by federal courts (Harris, 2003; see Appendix). It features Lisa, a customer identified as being in her 30s, dressed in a business suit, shopping in a department store during her lunch break from work. She needs assistance from Cathy, a White salesperson in her 40s, to see some watches locked in a jewelry case. In all versions of the scenario, Cathy ignores Lisa for more than 30 minutes but promptly attends to another customer who is White and who arrives later. Different variations of the scenario were presented to capture a variety of factors present in retail discrimination cases (Harris et al., 2005). For example, in some versions of the scenario, Cathy accuses Lisa of attempting to steal and calls the security guard; in some versions, she eventually refuses to help Lisa at all.2

Lisa was identified as African American, Hispanic American, or Asian American. For the analyses, we combined the responses to the three scenarios because previous research shows that members of all three racial groups report being discriminated against while shopping (e.g., ABC News/Washington Post, 2009; Henderson, 2009; Jordan et al., 2009; Sue et al., 2007a).

Procedure

Participants read a consent form. They were randomly assigned to read one scenario about the incident at the jewelry counter. Participants rated: (1) their perceptions of the scenario, (2) their emotional responses to it, and (3) the behavioral responses they thought Lisa should have. They then responded to a number of questions about their perceptions of the degree of societal discrimination experienced by her target group. Participants were debriefed following completion of the survey.

Individual Difference Variables

Participant race

We included the participants’ race as a key independent variable based on the theory of perceptual segregation, which suggests that people of color and Whites interpret incidents of discrimination differently. We combined the participants of color into a single group (N = 559) and compared their responses to those of the White participants (N = 642).

Perceived societal discrimination against the customer's racial group (PSD)

To systematically explore conscientization, we included a measure of participants’ perception of the societal discrimination faced by people of color (PSD). That is, some people perceive that discrimination occurs frequently in society whereas others have lower levels of perceived discrimination. These differences in PSD may reflect variation in how much discrimination participants have actually witnessed and in their interpretations of whether specific situations constitute discrimination. We modified the Perceived Ethnic Discrimination Questionnaire-Community Version (PEDQ-CV) originally developed to measure people's perceptions of discrimination directed at their own racial/ethnic group (Brondolo et al., 2005). Scores on this measure have been shown to affect how people of color perceive and respond to specific incidents of discrimination (Broudy et al., 2007). Seventeen questions relate to unfair treatment by coworkers, classmates, and police officers, receiving poor service in stores and restaurants, being ignored or treated as lazy, etc. Respondents rate how frequently they experience such treatment because of their ethnicity. For our study, instead of reporting about their own experiences with discrimination, participants were asked how often members of the customer's racial/ethnic group experience discrimination. For example, when the customer (Lisa) was identified as African American, participants rated how often each experience “happened to African Americans in the last 5 years, because of their ethnicity.” The terms “Hispanic” and “Asian American” were substituted when Lisa was identified as being a member of those groups. Six additional questions measured the extent to which members of Lisa's group experience CRP. Items included being tailed in stores, accused of stealing, and searched. Ratings for the 23 statements were made on a scale from 1 (not at all) to 7 (a lot).

Both the modified PEDQ and the CRP scales had high internal reliability, Cronbach's alpha ranged from .96 to .99. The modified PEDQ and the CRP scales were correlated (r = .82, p < .001). It therefore made sense to combine them into an overall score of PSD against the target group. The scores were standardized and then summed.

Mediator Variables

Perceptions of the scenario

Participants rated their agreement with nine statements regarding how the customer was treated using a scale from 1 (strongly disagree) to 7 (strongly agree). These ratings were submitted to factor analysis. The best solution was a two-factor oblique (correlated factors) solution. We labeled the first factor General Disapproval of the sales clerk. “Sales clerk treated Lisa unfairly” had a strong positive loading while “Sales clerk was justified in her response to customer” and “Customer acted in a threatening manner toward sales clerk” had strong negative loadings. These items provided participants the opportunity to disapprove of the clerk's behavior without having to acknowledge the possibility that racism was involved. The second factor, Race Attribution, tapped the tendency to attribute the sales clerk's behavior to Lisa's race/ethnicity. “Sales clerk made customer feel like an outsider who doesn't fit in because of her race/ethnicity” and “Sales clerk's treatment of customer was due to race/ethnicity of the customer” both loaded strongly. These items allowed participants to take the perspective of the targeted group and recognize that racism could have played a role in the incident. Together, these two factors captured the divergent perspectives of oppressor and oppressed that are highlighted by liberation psychology. We computed factor scores for these two factors. These factor scores were correlated (r = .52, p < .001) indicating that they are different but related.

Emotional responses to the scenario

Participants rated how strongly they felt each of a number of emotions on a scale from 1 (not at all) to 5 (very much). The factor analysis yielded a 3-factor oblique solution, which we labeled Anger (furious/frustrated/disgusted), Anxiety (nervous/hopeless/fearful), and Empowerment (stronger/wiser/confident) based on the items that loaded highly on these factors. The factor scores Anger and Anxiety were somewhat correlated (r = .36, p < .001) and were unrelated to Empowerment. Furthermore, Anger was somewhat correlated with General Disapproval (r = .35, p < .001) and Race Attribution (r = .28, p < .001), Anxiety was correlated with General Disapproval (r = –.12, p < .001), and Empowerment was slightly correlated with General Disapproval (r = –.08, p < .05).

Dependent Variables: Behavioral Responses to the Scenario

Participants rated their agreement with 13 statements regarding the way in which Lisa should respond on a scale from 1 (strongly disagree) to 7 (strongly agree). The factor analysis yielded a 4-factor Varimax solution which we labeled: Exit/Return Later, Internal Complaint, External Complaint, and Physical Demonstration. The items that loaded strongly on the Exit/Return Later factor included Lisa should walk away and shop in another part of the store or come back later when another sales clerk is there. For Internal Complaint, the items that loaded strongly concerned whether Lisa should contact customer service or store management and assert her right to be treated with respect. The items that loaded strongly on the External Complaint factor included: Lisa should contact the Better Business Bureau, the Chamber of Commerce, the local newspaper or an attorney and she should organize a boycott. The items that loaded most strongly on Physical Demonstration were: Lisa should slam her hand on the counter and grab the clerk by the arm and demand service. Participants consistently disagreed strongly with these items across all conditions and, due to this restricted range, we did not include Physical Demonstration as a dependent variable. We computed factor scores for the three remaining factors. They vary along a continuum ranging from a system-reproducing response that downplays the seriousness of the incident (Lisa should just come back another time) to a more assertive response of contacting management for individual redress, to a social justice, system-challenging response of reaching out to the community at large.

Data Analytic Strategy

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

First, we used t-tests to identify differences between the responses of participants of color and Whites. Second, to determine how individual differences influence emotional and behavioral responses, sets of hierarchical regression analyses were run on the mediators and dependent variables. All the scale variables were centered prior to analysis. Centering the variables facilitates interpretation of the results of interactions (Cohen, Cohen, West, & Aiken, 2003). Because the mean of a centered variable is 0, the interaction term drops out at the mean of either variable. The independent variables were participant race (people of color, White) and level of PSD against the customer's racial group. In all the analyses, these independent variables were entered at step 1. The mediating variables—perception of the event (General Disapproval and Race Attribution) and emotional response (Anger, Anxiety, Empowerment)—were analyzed first as dependent variables and were then entered at step 2 as predictors of the behavioral responses Lisa should have (Exit/Return Later, Internal Complaint, External Complaint). The same analyses were run with the interaction of participant race and PSD at step 2 followed by the mediators at step 3. The interaction effects were not significant so they are not discussed further.3

Results

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

t-Tests

The responses of participants of color and Whites were compared using t-tests (see Table 1). Participants of color reported higher levels of PSD against the target group than did White participants, t (1,045) = 6.21, p < .001. White participants reported slightly higher levels of general disapproval than participants of color, t (1,045) = 2.03, p = .043. White participants also felt more anxiety after reading the scenario, t (1,045) = –4.38, p < .001, whereas participants of color reported significantly greater levels of empowerment, t (1,045) = 9.44, p < .001. In reporting how the customer should respond to the incident in the jewelry department, White participants more strongly agreed that Lisa should exit the store and return later than did participants of color, t (1,045) = –3.02, p = .003. In contrast, participants of color more strongly agreed that Lisa should complain externally than did White participants, t (1,045) = 5.63, p < .001.

Table 1. Mean Centered Scores as a Function of Participant Race
VariableParticipants of colorWhite participantsCohen's D
  1. *p < .05, **p < .01, ***p < .001.

PSD.39–.33***.38
Gen Disapproval−.06.05*−.13
Race Attribution.01−.01
Anger−.03.03
Anxiety−.13.11***−.27
Empowerment.28−.24***.58
Exit/Return Later−.09.08**−.19
Internal Complaint.04−.03
External Complaint.17−.14***.35

Hierarchical Regression Analyses

Standardized regression coefficients are presented in Table 2. The predictor variables of participant race and PSD were slightly correlated (r = .19, p < .001).

Table 2. Regression Coefficients for Hierarchical Regression Analyses of Mediators and Dependent Variables
 Mediators: perceptual and emotional responses
Predictor VariablesGeneral DisapprovalRace AttributionAngerAnxietyEmpowerment 
  1. *p < .05, **p < .01, ***p < .001.

  2. Note. For Participant Race, positive Betas indicate participants of color scored higher than Whites.

Individual difference variables
 Participant Race−.074*−.006−.056−.157***.280*** 
 Perceived Societal Discrimination PSD.063*.124***.122***.120***.002 
 Dependent variables: behavioral responses
 Exit/Return LaterInternal ComplaintExternal Complaint
Predictor VariablesIVs onlyIVs + mediatorsIVs onlyIVs + mediatorsIVs onlyIVs + mediators
Individual difference variables      
 Participant Race−.094**−.119***.022.023.143***.122***
 Perceived Societal Discrimination PSD.003.011.088**.037.152***.116***
Mediators: perception of the scenario
 General Disapproval−.220***.303***−.014
 Race Attribution.045.066*.032
Mediators: emotional response to the scenario
 Anger−.172***.284***.160***
 Anxiety.177***−.088**.112***
 Empowerment.098***.088**.165***
Overall R2 .132*** .277*** .133***
Mediators

Hierarchical regression analyses on the mediators revealed main effects for the predictors but no interactions. Consistent with the t-tests, White participants reported significantly higher general disapproval and more anxiety but lower levels of empowerment than did participants of color. In addition, independent of their race, participants with higher levels of PSD reported more general disapproval, more attribution of the clerk's behavior to Lisa's race, and more anger and anxiety.

Exit/return later

Participants indicated the extent to which they thought Lisa should exit the jewelry department and return to shop at another time. White participants more strongly agreed that Lisa should exit and return later than participants of color. In addition, the more participants generally disapproved and felt anger, the less they thought Lisa should exit and return later. In contrast, the more anxiety and empowerment participants felt, the more they thought Lisa should exit and return later.

Internal complaint

Participants indicated the extent to which they thought Lisa should complain to the clerk and store management. Participant race did not significantly predict internal complaint. However, participants with higher levels of PSD more strongly agreed that Lisa should complain internally. This effect was completely mediated by general disapproval, race attribution, and anger such that the more they agreed with these perceptions and feelings, the more they thought Lisa should complain internally (see Figure 1).4 anxiety also mediated this effect in the negative direction such that the more participants reported feeling anxiety, the less they thought Lisa should complain internally. Finally, the more empowerment participants felt, the more they thought Lisa should complain internally.

image

Figure 1. Effect of PSD on Internal Complaint is mediated by General Disapproval, Race Attribution, Anger, and Anxiety. Dotted lines are negative relationships. *p < .05, **p < .01, ***p < .001.

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External complaint

Participants indicated the extent to which they thought Lisa should complain externally by contacting the Better Business Bureau or the local Chamber of Commerce, writing to the newspaper, telling friends and family about the way she was treated, conducting a boycott, or contacting a lawyer. Consistent with the results of the t-test, participants of color more strongly agreed that Lisa should complain externally than White participants. In addition, participants with higher levels of PSD agreed more strongly that Lisa should complain externally. Finally, the more the participants reported feeling anger, anxiety, and empowerment, the more they thought Lisa should complain externally.5

Discussion

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

In this study, we attempted to understand the perceptual, emotional, and behavioral responses to an incident of consumer discrimination using two complementary theoretical perspectives. Previous research has demonstrated that people of color and White participants are likely to have different perceptions and emotional reactions to such an incident and thus, different behavioral responses (Baker et al., 2008; Robinson, 2008). However, the work of other social scientists suggests looking beyond race to consider the extent to which individuals perceive societal discrimination (Adams et al., 2006; Johnson, Simmons, Trawalter, Ferguson, & Reed, 2003; Nelson, 2010). Our findings are consistent with both perceptual segregation and the liberation psychology tenets of de-ideologization and conscientization. They support the hypotheses that race and PSD influence participants’ responses.

Effects of Participant Race/Ethnicity

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

Consistent with perceptual segregation and liberation psychology, we found that participants’ own racial/ethnic backgrounds influenced their perceptions of the scenario and their reactions to it. Compared to Whites, participants of color more strongly agreed that Lisa should engage in system-challenging behaviors by communicating with people and organizations outside the store. In contrast, White participants more strongly agreed that Lisa should exit the jewelry department and return to shop later. The difference in their responses may stem from the differences in motivation to detect oppression between Whites and people of color. Whereas Whites tend to downplay the role of prejudice or see it as an individual-level problem, people of color are more likely to perceive racial bias as a systemic phenomenon embedded in cultural and institutional practices. The White participants’ system-reproducing response may reveal their belief that the sales clerk's poor treatment of Lisa was an isolated incident best resolved by walking away. The system-challenging response favored by participants of color is consistent with the higher levels of emotional empowerment they reported. White participants expressed higher levels of general disapproval of the sales clerk's behavior and higher levels of anxiety. And their anger did not differ from people of color. One possible explanation is that White participants may feel uncomfortable with the behavior of the White sales clerk who treated Lisa so poorly. Their expressions of anger and anxiety and their agreement that Lisa should leave the store allow them to maintain an unprejudiced self-image by distancing themselves from the “racist” White sales associate while refraining from challenging the status quo (O'Brien et al., 2010).

Effects of PSD

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

In addition to participants’ race, we found that their level of PSD explained the variation in their perceptual, emotional, and behavioral responses to the scenario. As expected, higher levels of PSD were associated with more system-challenging responses. Importantly, independently of race, participants with higher levels of PSD responded by agreeing that Lisa should challenge the system and complain publicly—to family, friends, and the community at large—about her treatment at the jewelry counter. These actions have the potential to raise others’ awareness of the discrimination occurring in retail stores and consequently could reduce future occurrences.

Participants with higher levels of PSD also recommended that Lisa stand up for her rights by complaining to store management about the sales clerk's behavior. The effect of PSD on internal complaint was mediated by the participants’ perceptions of and emotional reactions to the incident. The more PSD participants reported, the more they generally disapproved of the clerk's behavior and attributed it to Lisa's race suggesting a higher level of conscientization. They also reported more anger and anxiety and these were then associated with agreement that Lisa should complain to store personnel, and to a lesser extent, take external action. These mediation effects demonstrate that emotions play an important role in participants’ responses to service failure, an effect also found by Chebat and Slusarczyk (2005). Together, these findings have implications for retail establishments when they respond to their customers’ perceptions of and emotional reactions to consumer discrimination. Because complaining internally represents a moderate reaction on the continuum between system-challenging and system-reproducing behavior and because there was no participant race effect on internal complaint, it is likely to be a response around which common ground can be reached among victims of consumer discrimination and others who do not experience it regularly.

Our findings are analogous to those of Baker and Meyer (2011) who showed that differences in Whites’ level of empathy influenced their perception of the severity of a service failure in a restaurant, the degree of anger they reported feeling, and their attribution of the incident to racial discrimination. Baker and Meyer (2011) posited that when and why Whites have empathetic reactions to a service failure in a store may be a function of the value they place on the welfare of the other person. Similarly, higher levels of PSD may have increased the value participants placed on Lisa's welfare in the store and their interest in her receiving better treatment.

Limitations

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

One of the biggest challenges in this domain of research concerns the presentation of the discriminatory act. Many different approaches are taken both to communicate the details and to highlight the basis (race, sexual orientation, dress, etc.) of the discrimination. In this study, this information was presented in a short paragraph. This was necessary in the context of a Web-based survey and provided uniformity in the presentation of the information. We controlled the exact details, such as what the salesperson said and how long the customer waited. In addition, we had precise control over the racial/ethnic background of the characters in the scenario and could make that explicit to our participants.

Unlike field studies, this structured format inherently restricts the richness of real situations. People's facial expressions, tone of voice, and the reactions of other customers are lost in a written format. In an attempt to broaden the scope of the scenarios, we added several variations. The customer was varied to be African American, Hispanic American, or Asian American. The specific nature of the discrimination was also varied (e.g., service was degraded or outrightly denied). Interestingly, in all cases, the participants perceived the service to be very poor. Thus, the overall variability in responses to the scenario was somewhat limited. Most participants found the salesperson's behavior to be highly unacceptable and were angry about the situation. Furthermore, the presence of the White shopper who received good service provided a context in which racial discrimination could be more easily inferred (see similar findings by Baker & Meyer, 2011; Baker et al., 2008). While these limitations led to small effect sizes, we still detected differences based on participants’ own race/ethnicity and PSD.

Another limitation in this research concerns the timing of the measurement of PSD. We did not want to sensitize participants to issues of historical discrimination before presenting the scenario and measuring their responses to it. Our approach was based on the notion that participants came to the study with a previously formed understanding of the level of racial and ethnic discrimination that occurs in society. However, by measuring a key predictor variable after the dependent and mediator variables, we recognize that reading and responding to the scenario may have influenced the participants’ beliefs about societal discrimination. On a related point, PSD was slightly correlated with participant race. In our statistical analyses, we examined the independent effects of participant race and PSD on the other variables and found no evidence that PSD mediated the effects of participant race.

We made efforts to recruit participants of different racial and ethnic backgrounds. Nevertheless, the people of color in our sample are predominantly Black. Future research could explore similarities and differences between Blacks and other people of color.

Conclusion and Future Directions

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

An implication of this research is that Whites can increase their awareness of the everyday discrimination faced by people of color. Research demonstrates that increasing participants’ awareness of historical cases of oppression (by providing them with information) changes their perceptions of current discriminatory events (Nelson et al., 2010). Future research could similarly endeavor to increase awareness of societal discrimination to study its influence on perceptions of and responses to consumer discrimination.

In keeping with the philosophy of Martín-Baró (1994), it is essential that we continue to hear the voices of those oppressed by systemic discrimination. While he focused on severe forms of oppression and the stripping of human rights, social scientists now understand the deleterious effect of repeated exposure to discriminatory microaggressions (Sue et al., 2007b). Since consumer discrimination is a common microaggression, understanding the phenomenon may provide insight about fighting it in court and challenging it in the community (Hakstian & Evett, 2009). To that end, we are currently engaged in a more direct assessment of the experiences of targets of consumer discrimination. We have collected stories through in-depth interviews to more fully understand people's expectations in these situations, the emotional impact of the discrimination, and their satisfaction with the efforts of businesses to resolve their complaints (Henderson, 2009).

While hearing the voice of the victims is an essential component to this line of research, the role of the broader community is also critical. Through the process of conscientization, people of color and Whites may come to a common understanding of racial discrimination. Such a shared perspective will promote greater engagement in the action-oriented steps necessary to challenge—and hopefully change—the systems that perpetuate racism.

  1. 1

    We are mindful that race itself is not the “determinant” but rather is associated with a host of experiences that arise in social interactions due to political, historical and cultural influences (Zuberi, 2001).

  2. 2

    There were no clear patterns of variation among the scenario types. Because they do not relate to the central research question, we combined them in the interest of simplicity.

  3. 3

    We ran the same set of analyses including participants’ gender, region, and age as predictor variables as well as the interactions of these variables with participant race. Only a few results were significant and no consistent patterns emerged suggesting that these effects might simply be Type I errors.

  4. 4

    In accordance with Baron and Kenny's (1986) guidelines, mediation occurs when the independent variable predicts both the mediators and the dependent variable and the effect of the independent variable on the dependent variable becomes smaller when the mediators are added to the analysis. As reported above, the first two criteria were met. In addition, the effect of PSD on Internal Complaint which was statistically significant at step 1, p = .005 is no longer significant at step 2, p = .177, when the mediators are added to the model.

  5. 5

    As with Internal Complaint, Anger and Anxiety appeared to partially mediate the effect of PSD on External Complaint such that its effect was smaller after the mediators were added to the model, albeit still statistically significant, p < .001.

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  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies
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Appendix

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies

Becky and Lisa are shopping in a department store during their lunch break from work. They do not know each other. They are both wearing the business suits that they wore to work. Both women are in their 30's. Lisa is African American and Becky is White. They entered the store at the same time and are shopping in different departments. Lisa is shopping for a new watch. She browses for several minutes at the jewelry counter and then wants to see some watches that are locked in the jewelry case. She tries to get the attention of Cathy, the White salesperson, who is in her late 40's. Cathy is straightening scarves on a rack nearby and seems to be acting like she doesn't see Lisa. Lisa waits for 10 minutes, repeatedly trying to get Cathy's attention. Becky, who has been browsing in another department, now also approaches the jewelry counter. Cathy comes over immediately and assists Becky for 15 minutes, showing her bracelets and necklaces from the case. Becky buys a necklace with her credit card. As Becky is putting away her wallet and gathering her purchase, Lisa tells Cathy “Excuse me, I've been waiting for 30 minutes now and I'd like to see some watches in the case.” Cathy ignores Lisa, shakes her head, and whispers to Becky, “That Black woman thinks that I am going to drop everything to help her!” After several more minutes pass, Lisa asks Cathy, “Are you going to help me?” Cathy reluctantly takes out the watches and stands watching Lisa with her hands on her hips. Lisa selects a watch to buy and Cathy rings up the sale without speaking to her. Lisa turns away from Cathy.

Biographies

  1. Top of page
  2. Abstract
  3. Perceptual Segregation
  4. Liberation Psychology
  5. Methods
  6. Data Analytic Strategy
  7. Results
  8. Discussion
  9. Effects of Participant Race/Ethnicity
  10. Effects of PSD
  11. Limitations
  12. Conclusion and Future Directions
  13. References
  14. Appendix
  15. Biographies
  • SOPHIA R. EVETT is a professor of Psychology at Salem State University. She received her PhD in Social Psychology from the University of Wisconsin–Madison. Her research interests include prejudice and stereotyping, consumer racial profiling, and jury decision making.

  • ANNE-MARIE G. HAKSTIAN is an associate professor of Business Law in the Bertolon School of Business at Salem State University. She received her JD from the George Washington University School of Law and is working towards her PhD in Law and Public Policy from Northeastern University. Her research interests include jury decision making and racial profiling.

  • JEROME D. WILLIAMS is the Prudential Chair in Business and Research Director of The Center for Urban Entrepreneurship & Economic Development in the Rutgers Business School-Newark and New Brunswick. He received his PhD in Marketing from the University of Colorado–Boulder. His research interests cover multicultural marketing, marketplace discrimination, and public health communication.

  • GERALDINE R. HENDERSON is an associate professor of Marketing in the Rutgers Business School-Newark and New Brunswick. She received her PhD in Marketing from Northwestern University's Kellogg School of Management. Her primary areas of research include global marketplace diversity and consumer social networks.