The Impact of Racial Profiling on Consumers in Canadian Retail Settings: A Mixed-Method Study Exploring Negative Emotions

Abstract

This research investigated the negative emotions of 514 Canadians who reported being suspected of shoplifting in retail settings. Consumer racial profiling (CRP) is an important topic of consideration due to the links to General Strain Theory, everyday racism, and victimization. The research focused on two research questions. First, does race have a significant association with negative emotions following incidents of CRP? Second, are factors beyond race, like profiler characteristics, retail demographics, profiling method, and victim demographics, associated with negative emotions among customers who have experienced CRP? Descriptive information is provided to contextualize the relevance of each variable. Quantitative and qualitative analyses indicated that the number of profilers, victim gender, retail location, and the profiling method are associated with changes in negative emotions following CRP. Practical implications regarding the examination of the profiling method and the number of profilers are discussed at length.

Keywords

consumer racial profiling mixed-methods shoplifting general strain theory retail stores racial discrimination

A recent human rights complaint in Saskatchewan reignited a conversation about racial discrimination in private businesses in Canada. A father and daughter of the Heiltsuk Nation claim they were humiliated after they were suspected of theft in a local retail store (Miljure, 2024). When relaying their discomfort to another store employee, they were met with a racially charged comment about how Indigenous individuals are known thieves. The father and daughter claim that this was a clear example of Consumer Racial Profiling (CRP), a practice that affects many racial and ethnic minorities in Canada who are denied service, searched, or ignored due to discriminatory stereotypes (Tuttle, 2022). In addition to the impact on service, customers may experience significant negative emotions from being a target of CRP. Although Canadian law makes it illegal to deny someone access to any good or service based on race, the recent incident from Saskatchewan demonstrates how the practice is still common and impacts the lives of many minorities. Activists understand that CRP is an example of the racism people experience every day, and that it can have a lasting impact on young people of color (Bundale, 2018).

The results of this study provide a deeper understanding of the intersection between negative emotions and racial profiling in retail settings. This is crucial to better understand CRP and its influence on negative emotions to combat the pervasive discrimination in Canadian businesses. The following section examines current literature related to this project, while also explaining the research gap that can be narrowed by the current project.

Consumer Racial Profiling

Despite extensive research on racial profiling in social sciences, empirical investigations examining CRP within the criminal justice discipline remain limited (Gabbidon & Higgins, 2020a, 2020b; Henderson et al., 2016). CRP, as defined by Gabbidon and Higgins (2020a, p. 418), refers to the “use of race/ethnicity as the primary characteristic used to identify potential thieves in retail settings.” This phenomenon is related to what Bourabain and Verhaeghe (2019) characterize as daily racism or everyday discrimination, the subtle but pervasive unequal treatment of ethnic groups based on their ethnic-cultural origins (Pager & Shepherd, 2008).

There has been a growing interest in the presence of CRP, particularly in retail establishments (Gabbidon, 2003; Gabbidon & Higgins, 2020a; Henderson et al., 2016). Previous survey data highlight the prevalence of CRP in retail contexts, with 86% of African Americans reporting differential treatment based on race compared with 34% of White consumers (Williams & Snuggs, 1997). More recently, the Gallup Poll Social Audit Series on Black/White Relations in the United States revealed that 35% of Black respondents experienced unfair treatment while shopping in the last 30 days (Jones & Lloyd, 2021). Unlike police-involved incidents, however, CRP incidents typically occur on private property, resulting in limited documentation and official statistics (Gabbidon & Higgins, 2020b). The underreporting of CRP incidents has been a significant challenge to understanding its full scope. Empirical evidence suggests that only 20% of CRP victims report their experiences (Gabbidon & Higgins, 2020a). This pattern of underreporting was similarly observed in studies of Black students at historically Black colleges and universities, where researchers discovered that most students did not report their CRP experience (Gabbidon et al., 2008). However, research also indicates that the intensity of negative emotions resulting from CRP experiences correlates positively with the likelihood of victim reporting (Gabbidon et al., 2008; Gabbidon & Higgins, 2020a).

Research has also explored the perceptual and emotional dimensions of CRP across racial groups. Evett et al. (2013) demonstrated that while both people of color and White participants recognize CRP as problematic and respond emotionally to such incidents, they often propose different remedial approaches. Beyond individual impacts, CRP carries significant implications for retail brands. Recent research conceptualized CRP as “a service failure unfairly targeting consumers based on their race” and revealed its detrimental effects on purchase intentions, a concerning aspect attributed to negative moral emotions and public sentiment toward brands engaging in discriminatory practices (Youn et al., 2024, p. 1). Such results align with the findings that CRP can tarnish not only the immediate retail brand but potentially affect other products associated with the corporate name (Sierra et al., 2010).

Negative Emotions and Racial Discrimination

The relationship between CRP and negative emotions has been highlighted by recent research (Gabbidon et al., 2008; Gabbidon & Higgins, 2020a, 2020b). Studies have also found the associations between discriminatory experiences and adverse psychological outcomes, examining both immediate emotional responses and long-term psychological consequences (Isom & Seal, 2019; Plümecke et al., 2023). Empirical evidence suggests that different forms of racial discrimination elicit distinct emotional responses. For instance, Isom and Seal (2019) found that while everyday discrimination correlates with depressive symptoms, police-based discrimination specifically triggers anger responses that partially mediate subsequent offending behavior. Plumecke et al. (2023) explored how routine discriminatory encounters generate feelings of humiliation and powerlessness that evolve into chronic psychological distress, leading to fear of law enforcement, erosion of institutional trust, and self-restricted movement in public spaces. Jones et al.’s (2020) investigation of Black women’s discrimination experiences highlighted how depression and awareness of racial barriers predict offending behavior, suggesting that multiple marginalized identities may compound the negative emotional effects of discriminatory treatment.

While a high volume of literature examined the connection between everyday racial discrimination and negative emotions leading to delinquent behavior, the specific factors that influence emotional responses to CRP remain largely unexplored. Studying the contextual factors that shape the intensity and nature of negative emotions following CRP experiences is critical to understanding the emotional impact of everyday racism. Moreover, research examining CRP’s consequences has predominantly focused on business-oriented outcomes, particularly examining the impact of brand image, consumer behavior, and corporate reputation (Sierra et al., 2010; Youn et al., 2024). Although recent scholarship has begun to bridge CRP with criminal justice perspectives (Gabbidon & Higgins, 2020b), the volume of literature examining CRP through a criminological lens remains notably sparse, particularly regarding the factors that influence emotional responses and their potential behavioral consequence.

Theoretical Framework: General Strain Theory

Moving from the traditional criminological theories, which simply determined Black individuals have more strain, more deviance, and less control (Agnew, 2006; Akers, 2009; Hagan et al., 2005), more recent scholars focused on the race-based explanations of crime (Delgado & Stefancic, 2017; Isom & Grosholz, 2019). Agnew (2006) and Kaufman et al. (2008) applied race in General Strain Theory (GST) by acknowledging that the somewhat unique social position of Black individuals may generate strained experiences, emotional reactions, and coping mechanisms (Isom & Grosholz, 2019). GST suggests that strains–loss of valued things, negative experiences, or failure to achieve goals–lead to negative emotions that may result in criminal behavior (Agnew, 1992, 2006). Building on this, Kaufman et al. (2008) developed the Racialized General Strain Theory (RGST) to explain racial differences in offending. RGST argues that Black Americans and Canadians experience more numerous and qualitatively different strains than White individuals due to their uniquely disadvantaged social position (i.e., economic hardships, familial tension, and racial discrimination; Agnew, 2006; Isom & Grosholz, 2019; Kaufman et al., 2008). Due to limited access to legitimate coping resources and support, Black Americans are hypothesized to be more likely to respond to these strains and negative emotions through criminal coping (Kaufman et al., 2008). Previous literature displayed mixed support for such propositions, finding varying effects of different types of strain on depression and delinquency across race (Jang & Johnson, 2003; Peck, 2013; Piquero & Sealock, 2010). In the Canadian context, particularly, while racial disparities are acknowledged as a central element of the socio-economic landscape–evidence by the lower social and economic status among racialized groups and Indigenous peoples–as well as their distinct experiences within the criminal justice system, an analysis of the relationship between criminal behaviors and various racial strains remains notably absent (Galabuzi, 2010).

Among various strains, discriminatory experiences represent particularly potent sources of strain due to their perceived unjust nature, harmful impact, and ongoing presence (Broidy & Santoro, 2018). As Agnew (2006) explained, strain is most likely to lead to deviance when perceived as unjust and identity-threatening. Therefore, racial discrimination should be highlighted in applying GST to minority group members (Peck, 2013). The emotional impact of discrimination is especially significant because it functions as a “mundane extreme environmental stress” that permeates everyday experience (De Coster & Thompson, 2017, p. 910). Another study on the Negative Social Interactions (NSIs), mentions “upsetting interpersonal encounters in daily life” as intersections of gender, race, and immigration status, which can have detrimental effects on an individual’s mental health in Canada (Chuang et al., 2023, p. 2058). Empirical applications of GST have found its implications in explaining various outcomes. For instance, Latino youth’s perceived discrimination increases substance use through heightened acculturation stress (Kam et al., 2010), while Black youth exhibit both emotional distress and an increased likelihood of delinquent behavior in response to racial discrimination (Peck, 2013). The relationship between discrimination and emotions operates through multiple pathways, with research indicating that strain from discrimination predicts both depression and delinquency (Jones et al., 2020). Furthermore, negative emotions strongly increase the likelihood of illegitimate coping responses compared with legitimate responses (Broidy & Santoro, 2018).

This theoretical framework predicts that experiencing CRP results in negative emotions that may produce a cyclical pattern where discriminatory experiences generate negative emotions that increase the likelihood of problematic behavioral responses (Kam et al., 2010; Peck, 2013). Understanding the specific factors that influence such emotional responses is crucial, given that previous research has indicated that the intensity of negative emotions can influence both reporting behavior (Gabbidon & Higgins, 2020a) and subsequent coping responses (Broidy & Santoro, 2018). This understanding provides important insights for developing interventions and policy responses to address CRP’s immediate and long-term consequences.

Current Study

The body of research surrounding racial discrimination and consumer profiling indicates that little is known about the influences on negative emotions related to CRP. Specifically, previous research has identified the relationship between profiling and negative emotions (Higgins & Gabbidon, 2009), but the influences on negative emotions are left understudied. Furthermore, we decided to study the different impact variables for negative emotions. In addition, GST provides a theoretical basis for further identifying relationships involving negative emotions and profiling (Broidy & Santoro, 2018; De Coster & Thompson, 2017). Therefore, the current study identifies negative emotions as the key dependent variable.

Two research questions were investigated to better understand the influences on negative emotions following CRP. First, does race have a significant association with negative emotions following incidents of CRP? Second, are factors beyond race, like profiler characteristics, retail demographics, profiling method, and victim demographics, associated with negative emotions among customers who have experienced CRP? Analyzing each of these research questions will expand the literature surrounding CRP and negative emotions. In addition, a qualitative analysis of open-ended survey responses was conducted to better characterize the nuances of the negative emotions evoked by CRP.

Quantitative Methodology

This study utilized data provided by the third-party research company “Real-Time Interactive World-Wide Intelligence” (RIWI). This research firm has a global presence, which involves past data collection efforts across 229 countries and territories. RIWI survey methodologies aim to capture citizen perceptions, thoughts, desires, and interactions with the environment. Two survey methodologies were used during this project’s data collection. First, “Random Device Engagement” was used to gather data through apps, websites, and pop-ups. This approach aims to gather information from a broad online audience through the use of random survey engagement opportunities. Individuals encountering the survey through a pop-up may receive a coupon or some form of in-app currency. All “Random Device Engagement” involves transparency regarding incentives and privacy. Second, “RIWI Communities” were utilized. This approach involves distributing surveys through validated partners, who can employ online services, social listening, and focus groups.

In terms of this project’s sample, the RIWI services employed both sampling methodologies to distribute online surveys to Canadians during May 2024. All data collection for this project was reviewed and approved by Penn State’s Office of Research Protections (STUDY#00024773). This process ensured informed consent from all participants, which adheres to ethical guidelines and welfare protections for survey respondents. A quota sampling method was used for the survey distribution, with a target sample of 850 individuals. Though quota sampling is partially limited by sampling bias and decreased generalizability, it is important to properly examine CRP across different racial samples (Higgins & Gabbidon, 2009). Therefore, the quota sampling method was selected for this exploratory research on a race-integrated topic. The quotas were selected to provide ample data on experiences from a diverse mix of racial groups. Specifically, the data collection process aimed to collect responses from 200 Black, 200 White, 100 Indigenous, and 100 Latino individuals. There were also 250 individuals from a combination of other racial minority groups. After data collection ended, the sample met each quota, with 205 Black, 211 White, 101 Indigenous, 104 Latino, and 252 other individuals (East Asian, Southeast Asian, Middle Eastern, South Asian, and Other).

The Canadian racial context is a particularly suitable setting for the current research. Notably, Canadian racial diversity and social attitudes toward racial diversity represent multicultural acceptance, immigration positivity, and racial inclusivity (Galabuzi, 2010). In addition, racial diversity within the Canadian provinces has become far more politicized and socially recognized following increases in Canadian immigration. Therefore, sampling Canadians extends the range of racial context.

Beyond race, the survey inquired about demographic factors, including age, gender, income, household, and education. In addition, factors related to Canadian CRP, such as retail location, retail type, profiling method, and profiling responses, were included. Considering that this project aimed to better understand CRP outcomes, the sample of 873 individuals was reduced to only include those who indicated that CRP had occurred. Therefore, the final sample included 514 individuals.

Dependent Variable

The dependent variable stems from seven negative emotion-related questions on the original survey. This project chose to consider negative emotions as the dependent variable following the work of Higgins and Gabbidon (2009). In their study, Higgins and Gabbidon studied respondent indicators of negative emotions following an incident of CRP. Each emotion question was measured on a 4-point Likert-type scale, with a range from 1 (strongly disagree) to 4 (strongly agree). Some examples of negative emotions include anger, sadness, shock, and embarrassment. After gathering responses for all seven emotion-related Likert-type scale questions, Higgins and Gabbidon (2009) created a new variable that captured the full impact of negative emotions. The new variable was a scale of negative emotions ranging from 7 to 28. Higher scores indicate more negative emotions.

To further conceptualize the relationship between CRP and emotions, this project uses the same seven-question scale with the same range (7–28). Again, the original questions were measured on a 4-point Likert-type scale. Questions included perceptions of stress, anger, shock, sadness, embarrassment, self-worth, and negativity. A reliability test was conducted to assess the strength of this new scale measure. The Cronbach’s alpha value (.874) indicates that the new “negative emotions” scale variable is reliable (Field, 2018).

Independent and Control Variables

Each of the independent variables was specifically related to one of the two research questions. The first research question asked about the relationship between race and negative emotions. Within the data, there were nine distinct racial categories. To account for the statistical power limitations stemming from low frequencies, the data were condensed into six categories. These categories included Black, White, Latino, Indigenous, Asian, and other. The “Asian” category was created through the combination of East Asian, Southeast Asian, and South Asian. The “Other” category was expanded to include Middle Eastern. Though it is not ideal to condense the racial categories, this project focused on negative emotions within the CRP experience, which can still be explored through broader racial considerations (Higgins & Gabbidon, 2009). After coding the race into six new categories, a dummy variable was created for the first analysis. This variable helped identify racial differences observed within the literature on CRP. Specifically, the variable “Black” was created to better understand the relationship between negative emotions and Black racial identification, compared with all other racial categories. This variable was coded with “Black” = 1 and “All else” = 0.

The second research question asked about possible associations beyond race. Therefore, key variables found throughout the CRP literature were included to characterize profiler information, store demographics, profiling methods, and victim demographics. Profiler race was included as a categorical variable. These categories include White, Black, Asian, and Other. The number of profilers was also included, with values ranging from 1 to 4+. The final profiler variable examined profiler position, which listed four categories including sales, management, security, and other. Retail characteristics included location (rural, suburban, urban) and store type (department, grocery, clothing, hardware, drug, convenience, restaurant, and other).

Moving to the profiling method, there were originally nine questions that indicated the method of profiling that the participant reported experiencing. These questions relate to being watched, followed, approached, asked to leave, accused of theft, escorted out, verbally abused, verbally abused with a racial slur, or something else. Though this variety provided specific insight into the method of profiling, the nine options were condensed. This coding change was guided by previous scholarship on police racial profiling, which separates contact and non-contact profiling in its conceptualization (Plümecke et al., 2023; VanDerwerken et al., 2023). Notably, police profiling is described as a non-contact act that involves following and watching, or a contact act that involves stops and arrests. Therefore, the data were recoded to create a new variable describing the method of CRP (passive, active, aggressive). Passive profiling includes non-contact acts like being watched and followed. Active profiling includes contact acts like being approached, asked to leave, accused of theft, and getting escorted out. Aggressive profiling includes acts that do not conceptually fit in the other categories because it involves verbal abuse or verbal abuse with racial slurs. For this final set of variables, aggressive was selected as the reference category.

Finally, the data included multiple demographic variables, which were utilized as control variables. These variables include race, gender, age, education, and income. Race followed the sample coding procedure outlined above. Gender was recoded into a dummy variable with values for “man” and “all else.” This coding strategy was selected in an effort to include gender identifications outside of the binary (i.e., gender fluid). In addition, the selection of men in the dummy coding was based on previous literature related to negative emotions and gendered experiences with mental health (Chuang et al., 2023). Age was coded into six different age ranges (18-24, 25-34, 35-44, 45-54, 55-64, and 65+). Education was coded into seven different categories ranging from less than high school to graduate degree. Finally, income was coded into nine income ranges from less than $10,000 to more than $150,000.

Plan of Analysis

To better explore the influences of negative emotions following a CRP experience, this project employed two analyses. Splitting the analysis into two separate sections allowed for a specialized understanding of each research question. The first analysis explored the relationship between negative emotions (DV) and victim race (IV). Previous scholarship explains profiling experiences across racial identities, including White identity (Lynch et al., 2008/2009). In fact, the data included information on negative emotions across racial categories. When rank ordered, mean negative emotions are highest for White individuals (15.51), then Indigenous individuals (14.91), then Black individuals (14.51), then Latino individuals (14.39), then Asian individuals (14.33) and then “Other” individuals (13.96). However, considering that the literature largely references the Black experience with CRP, the victim racial category was dummy coded with Black as 1 and all else as 0 (Evett et al., 2013; Isom & Grosholz, 2019; Jones & Lloyd, 2021; Kaufman et al., 2008). An independent-samples t test was conducted for the continuous DV (negative emotions) and binary IV (Black). By conducting the t-test, a preliminary understanding of racial associations with negative emotions can be contextualized. Results suggested further examination of negative emotions was required.

The second analysis explored the relationships between negative emotions (DV) and other variables beyond race. Notably, profiler characteristics, store characteristics, profiling method, and victim demographics are included for the analysis. A full description of each variable can be found in Table 1. Based on the continuous nature of the DV, an ordinary least square regression was selected. In addition, considering that the second analysis is also exploratory, the independent and control variables were added in a stepwise fashion. Stepwise methods identified the variables of significance, while excluding those of non-significance.

Table 1:

Descriptive Statistics for all Quantitative Variables (N = 514)

Variable	n	%	Mean/Median	SD
Dependent Variable
Negative Emotions			14.56	4.384
Profiler Characteristics
Profiler White	248	48.2%
Profiler Asian	110	21.4%
Profiler Black	67	13.0%
Profiler Other	63	12.3%
Number of Profilers			1.77	1.146
Sales	261	50.8%
Management	62	12.1%
Security	51	9.9%
Other Position	140	27.2%
Retail Characteristics
Rural	54	10.5%
Suburban	161	31.3%
Urban	286	55.6%
Department	67	13.0%
Grocery	98	19.1%
Clothing	87	16.9%
Hardware	13	2.5%
Drug	49	9.5%
Convenience	65	12.6%
Restaurant	80	15.6%
Other Store	55	10.7%
Method of Profiling
Method Passive	305	59.3%
Method Active	193	37.5%
Method Aggressive	122	23.7%
Control Variables
Black	156	30.4%
Asian	102	19.8%
Indigenous	70	13.6%
Latino	63	12.3%
White	72	14.0%
Other	51	9.9%
Man	227	44.2%
Other Gender	287	55.8%
Age			25-34	-
Education			Community college	-
Income			40,000-60,000	-

Qualitative Methodology

The qualitative data were drawn from responses to the following open-ended question included at the end of the survey: “Please provide any additional comments related to Consumer Racial Profiling.” To analyze the data, responses to the survey prompt were downloaded from the quantitative data analysis tool SPSS and linked to the qualitative data analysis tool Atlas.ti. In total, 513 respondents replied to the prompt, but this analysis considers the responses of only 121 individuals (or 23.59% of the total sample) due to several non-substantive or unclear responses (n = 392; e.g., “I don’t know rather not say” and “it’s ok”). One researcher independently coded the open-ended response data using an iterative open coding technique (Tracy, 2019). In this process, each line of text is read, and codes are developed and assigned as focal theme concepts emerge. In total, 67 codes were inductively derived from the data, which were then sorted into six broader categories: (1) views/conceptualization of CRP (26 unique codes), (2) experience with shoplifting (two unique codes), (3) attitudes toward profiler (two unique codes), (4) perception of profiler’s attitudes/orientation (six unique codes), (5) research practices/design (five unique codes), and (6) emotional reactions to CRP (25 unique codes). One code was developed and applied to comments that were not substantive or otherwise unclear. This code was applied to 392 cases.

In terms of specific information surrounding the qualitative sample, all 121 individuals identified an experience with CRP. The ages ranged from 18 to 98, though the average was 37. Most of the individuals identified as male (n = 64) and a large portion identified as Black (n = 43), compared with Indigenous (n = 16), Latino (n = 23), White (n = 12), and other (n = 27).

The qualitative analysis was used to better understand the feelings of those who experience CRP. Notably, this analysis focuses on the views/conceptualization of CRP and emotional reactions to CRP codes as they are directly relevant to the broader research questions of this article. Importantly, the qualitative findings help contextualize the results of the quantitative analyses. This links statistically significant associations with consumer thoughts.

Quantitative Results

Table 1 presents descriptive statistics for all quantitative variables. The data revealed that the sample was well diversified by gender and race. Notably, 44.2% of the sample identified as men, 55.8% of the sample identified as women or other, and each racial category makes up at least 9.9% of the sample. In terms of other demographics, the average age range for respondents was 25 to 34 years old, the average income range was $40,000-$60,000, and a majority of the sample had a high school diploma. In addition, the dependent variable (negative emotions) has an average value of 14.56, indicating the presence of negative emotions within the sample.

As noted in the methodology, it is important to begin the analysis of negative emotions following CRP with an evaluation of race. To examine the possible relationship between race and negative emotions, an independent-samples t test was conducted using “negative emotions” as a dependent variable and “Black” as a demographic variable. The selection of “Black” allowed for a broad understanding of Black individuals’ experiences with negative emotions compared with individuals within other racial categories. This approach was guided by previous literature, which suggests that Black individuals have unique experiences with CRP compared with other racial groups (i.e., White individuals; Evett et al., 2013; Isom & Grosholz, 2019; Jones & Lloyd, 2021; Kaufman et al., 2008).

The results from the independent samples t-test ran counter to the previous literature on racial differences with CRP. As reported in Table 2, the level of negative emotions following experiences of CRP was not significantly associated with a Black racial identification (p = .844). These preliminary findings suggest that the exploration of other variables outside of race may account for the existing variation in the negative emotions.

Table 2:

T-Test Between Negative Emotions and Race “Black” (N = 514)—Two-Sided

Variable	Black		Non-Black		t(512)	p	d
Variable	Mean	SD	Mean	SD	t(512)	p	d
Negative Emotions	14.51	4.52	14.59	4.33	.197	.844	4.38

Note. d = Cohen’s d.

Following the results of the independent samples t-test, it was determined that more exploration of negative emotion associations was needed. To properly explore the significance of other variables, an ordinary least squares regression was conducted in a stepwise fashion. Specifically, variables related to profiler characteristics, store demographics, profiling method, and victim demographics were added into the model along with the victim race variables. Five total models were executed using the stepwise method, which identifies associations based on individual levels of statistical significance. After including each study variable, only five variables remained in the output based on statistical significance.

Before the results could be interpreted, a series of diagnostic tests were conducted to assure statistical relevance. First, normal distribution for the included variables was consistent across the variables measured beyond the categorical level. Second, collinearity diagnostics reported some multicollinearity concerns. However, the selection of variables was based on previous CRP and GST research, which suggest possible levels of multicollinearity. Third, variance inflation factor (VIF) and Tolerance statistics were calculated, each meeting acceptable regression benchmarks.

The first model identified the relationship between “Method Active” and negative emotions as statistically significant (p = .001). Model 2 added the association between “Man” gender identity and negative emotions (p = .003). Next, Model 3 included the relationship between “Method Aggressive” and the DV (p = .005). Following this, Model 4 included the relationship between “Other Store” and the DV as a statistically significant association (p = .015). Finally, Model 5 added “Number of Profilers” (p = .023). All other variables were excluded due to lacking statistical significance.

When looking at Model 5 specifically, there were some interesting results. The data suggest that compared with those who experience passive profiling methods, individuals who experience active profiling had a 1.192 unit decrease in negative emotions (p = .003). Similarly, when compared with the reference of passive profiling methods, those who experience aggressive profiling had a 1.201 unit decrease in negative emotions (p = .008). Apart from the method of profiling, it seems that gender had a relationship with negative emotions following CRP. Specifically, compared with other gender identities, men experienced a 1.269 unit increase in negative emotions (p < .001). In addition, in terms of store and profiler characteristics, the results identified notable relationships. Compared with department stores, CRP experienced in “Other” store types increased negative emotions by 1.571 units (p = .010). Also, as the number of profilers increased by one-unit, negative emotions decreased by 0.385 units (p = .023). More results can be found in Table 3.

Table 3:

OLS Stepwise Regression Analysis on Negative Emotions (N = 514)

Model		Unstandardized coefficients		Standardized coefficients	t	p
Model		B	Std. error	Beta	t	p
1	(Constant)	15.044	.243		62.032	< .001
	Method Active	–1.277	.396	–.141	–3.226	.001
	R² = .141
	adj. R² = .018
2	(Constant)	14.561	.291		50.030	< .001
	Method Active	–1.321	.393	–.146	–3.361	< .001
	Man	1.130	.383	.128	2.948	.003
	R² = .191
	adj. R² = .033
3	(Constant)	14.886	.311		47.802	< .001
	Method Active	–1.446	.393	–.160	–3.680	< .001
	Man	1.175	.381	.133	3.084	.002
	Method Aggressive	–1.255	.447	–.122	–2.805	.005
	R² = .226
	adj. R² = .045
4	(Constant)	14.698	.319		46.033	< .001
	Method Active	–1.372	.392	–.152	–3.498	< .001
	Man	1.214	.380	.138	3.197	.001
	Method Aggressive	–1.327	.446	–.129	–2.974	.003
	Other Store	1.494	.612	.105	2.770	.015
	R² = .249
	adj. R² = .055
5	(Constant)	15.248	.399		38.252	< .001
	Method Active	–1.192	.399	–.132	–2.990	.003
	Man	1.269	.379	.144	3.349	< .001
	Method Aggressive	–1.201	.448	–.117	–2.682	.008
	Other Store	1.571	.611	.111	2.572	.010
	Number of Profilers	–.385	.168	–.101	–2.287	.023
	R² = .267
	adj. R² = .062

Qualitative Results

Context and Experiences of CRP

Overwhelmingly, and perhaps not surprisingly, respondents described CRP as racist and “very bad” or “not good.” For example, Gregory (pseudonym) responded that, “profiling is something that. . . Black people will not be able to get away from. It is something that is going to stick with us forever, but we can act as a society to . . . work to this out.” Similarly, Laila (pseudonym) commented, “I might be black and look as expensive as my worth, but that doesn’t give anyone the right to watch me in a store.” These stories illuminate another pervasive aspect of profiling–stereotypes and collective punishment. Many respondents remarked that racial profiling is fueled by existing stereotypes that lead retail workers to preemptively view consumers of specific racial categories (predominantly, Black people) as devious. For instance, Carl (pseudonym) stated that “no[t] every black individual is up to no good.” Imani (pseudonym) spoke to the experience of many when he recalled that, “People have [the] wrong impression for people of colour, just because one person does something wrong does not mean we are all going to do the same. We need to give people the benefit of the doubt before judging.” From Carl and Imani’s experiences, we see how shoppers of color feel unfairly targeted by retail workers due to the actions of a smaller subset of their respective population. While respondents recognized why they are profiled, their overwhelming message is that they want to be viewed based on how they behave, not how others behave. This was particularly irritating for some respondents because they believe that everyone, regardless of race, class, or age, is capable of shoplifting. Moreover, respondents reported that CRP was a frequent occurrence in their lives, with Mike (pseudonym) retorting, it “sucks but it’s a normal thing these days.” Taken collectively, these excerpts illustrate the lived experience of CRP and how the practice reinforces negative stereotypes and contributes to feelings of resentment.

Emotional Reactions to CRP

Respondents described 21 different emotional reactions in response to being racially profiled in retail settings. Figure 1 displays a word cloud of all reported emotions.

CRP victims most commonly reported feeling annoyed, embarrassed, and sad (n = 3 for all cases). For example, Sarah (pseudonym) recounted her annoyance, saying, “it is annoying for someone to approach one person and ask to check their bags and receipt and let another group of people leave and claim that it is random.” For Sarah, her annoyance stemmed from her perception that the incident was not random, as claimed by store agents. Tom (pseudonym) focused more on how racial profiling made him feel embarrassed, particularly as the incident occurred in front of his family. He relayed, “Consumer Racial Profiling is beyond embarrassing and [is] a way of belittling one in front of their family . . . especially little children who do not understand racism.” For Tom, not only did the incident impact his own emotional state (i.e., feeling embarrassed), but he also worried about the emotional effects for a child who sees one’s parent unfairly targeted. Some individuals felt saddened after experiencing CRP, like Sam (pseudonym), who remarked, “It was sad [to realize that] people think of me in that way.” For Sam, the incident was saddening because she realized that other people view her in a negative, judgmental light. People also remarked that the event was “stressful.” The remaining 17 emotions were mentioned only once, but ran the gamut from feeling criminalized, to feeling devalued, to feeling scared. For a full list of all emotions, see Figure 1. Collectively, this range of emotions demonstrates the far-reaching effects of CRP and underscores the power retail workers have on emotions.

Discussion

In terms of the project’s theoretical framework, there are some important implications to discuss. Notably, there is a distinction between the goals of this project and the goals of other projects that use GST. The current project did not aim to test GST but instead included the framework for two distinct purposes. First, GST was used to link CRP research, which broadly exists beyond the realm of traditional criminal justice considerations, to possible criminal justice impacts. For example, previous literature suggests that individuals who experience negative emotions due to discriminatory practices like CRP may be at risk of increased problematic behavioral responses and even delinquency (Kam et al., 2010; Peck, 2013). Also, in line with GST, customers who experience negative emotions from CRP may end up engaging in illegitimate coping responses and even future criminal behavior (Broidy & Santoro, 2018). Additional research demonstrates that youth are at particular risk for this negative response to discrimination and strain (Kam et al., 2010; Peck, 2013). Therefore, including GST in the framework helped to identify the specific significance of the current study to the field of criminal justice. Second, GST is implemented to justify a portion of the variable selection process. Understanding the relationship between strain and criminal justice outcomes made it possible to identify variables, like profiler characteristics and method of profiling, that are significant to the criminal justice scholarship on race, profiling, and negative outcomes.

In this sample of 514 Canadians who experienced CRP, both quantitative and qualitative analyses suggested that influences on negative emotions vary. While negative emotions may be a natural reaction to being profiled as a consumer, this study explored factors that were directly associated with the customer experience during profiling incidents. Both analyses reported that Black individuals did not necessarily experience negative emotions differently than other racial categories following CRP. In addition, negative emotions were not statistically influenced by the race or position of the employee profiler. However, the number of employees engaged in a profiling incident and the method of profiling seemed to impact consumer negative emotions.

The findings related to the number of profilers and method of profiling run counter to the expected result. For example, if additional retail staff target and/or confront a consumer, it is reasonable to assume the customer may feel more intimidated or threatened. Yet, these results show that customers report higher negative emotions when only a single employee profiles a consumer. Similarly, individuals that experience more passive methods of profiling, compared with active or aggressive methods, experience heightened negative emotions. Although these results are surprising, Bourabain and Verhaeghe’s (2019) conceptualization of everyday discrimination helps explain the outcomes. Particularly, when multiple employees practice CRP, it can be considered an administrative or corporate choice. Inversely, when single employees target a customer, it may feel like a personal attack. In addition, the use of aggressive profiling methods would be broadly condemned by retailers. However, more passive methods may suggest personal bias. In both cases, the factors related to everyday racism are associated with negative emotions.

Results for the influence of retail characteristics only identified one statistically significant variable. Specifically, profiling at “other” store locations was associated with increased negative emotions. The implication of these findings indicates that customers may experience CRP in a wide variety of places and locations. In addition, this finding might suggest that when profiling occurs outside of a common setting, negative emotions may be amplified. Such results highlight the importance of personnel training in reducing CRP. Recent anti-CRP actions proposed by retail shops include branding, merchandising, hiring, and training programs (Howland, 2022). This study’s empirical findings suggest that it is recommendable for retailers to focus their budget and time on employee training programs to effectively reduce CRP.

The qualitative findings broadly support the quantitative analyses. Notably, the qualitative responses elucidated the specific emotions experienced by customers and the underlying context that influenced these emotions. Participants focused on the perceived injustice of being targeted based on race. Again, this fits well with the concept of everyday racism (Bourabain & Verhaeghe, 2019). Respondents were frustrated by the prevalence of racial stereotypes and collective punishment of individuals who are a part of specific racial groups. Although the quantitative results suggested that the race of the consumer was not a significant factor in experiencing higher levels of negative emotions, respondents still noted that employees should specifically focus on the actions of the customer, rather than race. Respondents also expressed some resignation to the prevalence of racism. It is possible the pervasiveness of negative stereotypes explains the statistical insignificance of race in the quantitative models; racism is common enough that some customers may be resigned to its impact on their negative emotions. The emotional response to CRP was to be annoyed, sad, and embarrassed, but some participants stressed deeper negative emotions like feeling traumatized and shameful. The intensity of emotional response speaks to the far-reaching impact of CRP. Therefore, stronger emotions may not dissipate quickly and may color future customer experiences.

These findings suggest how retailers and employers can potentially improve customer experiences and reduce negative emotions due to CRP. Specific training for employees could help focus on reducing discrimination and racially motivated behavior. Increased negative emotions for customers who experienced profiling methods like getting watched or followed are not a necessary part of the consumer experience. In fact, these are specific behaviors that can be targeted in corporate and administrative training. While retailers have the right to ensure asset protection, the abusive behaviors within certain profiling methods have no place in any business.

Also, customers expressed the desire to be treated fairly. Employers should ensure that product retention techniques are distributed across all customers fairly. This may reduce the negative emotions experienced when customers are asked to show their bags or have their receipts checked. Research suggests that these policies and training options should be implemented in all types of retail establishments and geographical locations, as no specific setting was more prone to influencing customers’ negative emotions in response to CRP. In addition, customers themselves are not without redress when experiencing CRP. All Canadian provinces and territories have a human rights agency that handles complaints of discrimination against privately run businesses (Canadian Human Rights Commission, 2024). Several legal cases about CRP highlight that racism feeds the “pernicious stereotype” that Black people are criminals (Tuttle, 2022, p. 1). These cases resulted in increased awareness and protection for consumers. Customers should be made aware of their rights both in public and private business situations. Increased challenges to the Human Rights Commissions may help reduce the practice of CRP by increasing sensitivity regarding the negative emotions it causes customers and the potential negative backlash to places of business.

Previous scholarship on CRP focused on how the intensity of negative emotions impacted a consumer’s likelihood of reporting the behavior and coping with the experience. This study examined the specific influences of the retail setting, victim demographics, and profiler characteristics on those negative emotions. Analyzing this gap in research allows for more understanding about what factors influence negative emotions, potentially giving insight into how retailers can improve customer relationships and reduce incidents of CRP. Reducing CRP is critical not just for improving customer experience but also limiting the negative emotions that can cause strain on profiled individuals.

Limitations and Future Directions

While the current research utilized a mixed-methods approach to enhance and expand the understanding of how experiencing CRP and related factors cause negative emotions, it is not without limitations. For this study, more than 500 Canadians were sampled. Despite this healthy sample, it is recommended that cross-national research be conducted in the future. The influence of nationality, country population, demographic diversity, and historical context has the potential to generate a more holistic analysis of CRP and emotions.

In addition, the cross-sectional survey methods allowed for an examination of associations, yet this approach may neglect the long-term effects of CRP on negative emotions. The immediate response to the CRP may be different from the emotions consumers feel later on. Also, there could be mediating factors that facilitate negative or positive emotional changes over time. Thus, a longitudinal study focusing on the mediating factors impacting the emotional status of the victims is recommended for the future.

Finally, this study utilized a theoretical framework of GST, which connects CRP and negative emotions to problematic behaviors. While the current research successfully analyzed significant relationships associated with negative emotions, the direct connection between the negative emotion and the problematic behavior was not analyzed. Of course, the qualitative analysis presented possible behavioral outcomes related to negative emotions; however, a further empirical analysis between CRP and problematic behaviors or antisocial tendencies could deepen our understanding of the GST framework.

Conclusion

When considering both the quantitative and qualitative analyses, it becomes easier to identify the relationship between negative emotions and CRP. Factors ranging from profiler characteristics to victim characteristics seem to influence emotions following CRP incidents. Therefore, this research can extend the understanding of racial considerations within retail settings more broadly. There is a need for further research on CRP; however, the results identified by this project suggest that change within the Canadian retail sector can be implemented now.

Footnotes

Authors’ Note:

This research was supported by Penn State’s Criminal Justice Research Center housed in the College of Liberal Arts. There are no conflicts of interest to declare. All authors contributed to the conceptualization and creation of the study.

ORCID iDs

Andrew Martone

Bryce Kushmerick-McCune

Shaun L. Gabbidon

Andrew Martone, MA, is a doctoral student in the Department of Criminal Justice and Criminology at Sam Houston State University. Through participation with multiple externally funded grants, his research examines correctional experiences and reentry barriers, with a specific emphasis on health and appearance.

Sunhye Kang, MA, is a doctoral student in the Department of Criminal Justice and Criminology at Sam Houston State University and currently serves as the managing editor of the International Journal of Offender Therapy and Comparative Criminology. With expertise in comparative studies, translational criminology, and child sexual exploitation, she has led multiple international research projects through various nongovernmental and governmental bodies and presented her findings at global conferences in Asia, Europe, and Africa.

Laura McCarty, MPA, is a doctoral student in the Department of Criminal Justice and Criminology at Sam Houston State University. Her research interests in treatment courts and pretrial justice stem from her decade of experience as a court administrator in Houston, Texas.

Bryce Kushmerick-McCune, MA, is a doctoral student in the Department of Criminal Justice and Criminology at Sam Houston State University. Through ethnographic observation and in-depth interviews, her research examines social control of deviant behavior through both institutional and community-based approaches.

Shaun L. Gabbidon, PhD, is a distinguished professor of criminal justice at Penn State Harrisburg. He also holds a joint appointment in the Department of Sociology and Criminology at the University Park campus. Professor Gabbidon is a Fellow of both the American Society of Criminology (ASC) and the Academy of Criminal Justice Sciences (ACJS). In 2024, he was the recipient of the Faculty Scholar Medal for the Social Sciences, which is the highest award for scholarship at Penn State University.

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