Customer Aggression Scale

1. Abstract

The Customer Aggression Scale (CAS), developed and validated by Gary Mortimer, Sitong Wang, and Maria Luiza Osorio Andrade (2023), is an advanced, psychometrically validated 19-item self-report measurement instrument designed to capture the multifaceted, overt, and covert hostile behaviors directed by consumers toward frontline service and retail personnel. Recognizing that prior operationalizations of customer mistreatment predominantly conceptualized hostility through unidimensional frameworks or restricted their focus to overt, interpersonal verbal abuse, the CAS establishes a rigorous four-dimensional taxonomic structure. This structure is mapped across two orthogonal behavioral axes: the motivational driver of the aggression (proactive versus reactive) and the communicative manifestation of the aggression (expressive versus inexpressive). Consequently, the CAS measures four distinct subscales: Proactive-Expressive Aggression (PEA), Proactive-Inexpressive Aggression (PIA), Reactive-Expressive Aggression (REA), and Reactive-Inexpressive Aggression (RIA).

Frontline service employees evaluate their exposure to each aggressive act using a 7-point Likert-type response scale ranging from 1 (“Strongly Disagree” / “Never”) to 7 (“Strongly Agree” / “Always”). Psychometric evaluations conducted across extensive calibration and cross-validation samples of retail and service employees demonstrate exceptional construct validity, internal consistency, and structural stability. The subscales exhibit high reliability coefficients: Proactive-Expressive Aggression demonstrates a Cronbach’s alpha ((alpha)) of .937, Composite Reliability (CR) of .937, and Average Variance Extracted (AVE) of .714; Proactive-Inexpressive Aggression exhibits (alpha = .947), (text{CR} = .947), and (text{AVE} = .750); Reactive-Expressive Aggression exhibits (alpha = .933), (text{CR} = .933), and (text{AVE} = .777); and Reactive-Inexpressive Aggression displays (alpha = .837), (text{CR} = .843), and (text{AVE} = .643). Structural equation modeling and confirmatory factor analysis confirm that the four-factor model demonstrates superior model fit compared to competing unidimensional and higher-order hierarchical models. The instrument functions as an indispensable diagnostic and empirical tool for organizational psychologists, human resource directors, service management researchers, and occupational health scholars seeking to mitigate the debilitating psychological, physiological, and economic consequences of customer-directed hostility in retail and service ecosystems.

2. Keywords

Customer Aggression Scale, frontline service employees, displaced aggression theory, customer sovereignty, low-status shield, workplace mistreatment, emotional labor, retail violence, proactive aggression, reactive aggression, psychometrics, service failure.

3. Authors

The Customer Aggression Scale was conceptualized, operationalized, and psychometrically validated by an international team of behavioral researchers specializing in marketing, retail strategy, and organizational behavior:

• Gary Mortimer, Ph.D.: Professor of Marketing and Consumer Behaviour at the School of Advertising, Marketing and Public Relations, QUT Business School, Queensland University of Technology (QUT), Brisbane, Queensland, Australia. Dr. Mortimer is an internationally recognized expert in retailing, consumer behavior, service operations, and frontline workforce dynamics.
• Sitong Wang, Ph.D.: Postdoctoral Research Fellow and Scholar in Retail Management and Consumer Psychology, School of Advertising, Marketing and Public Relations, QUT Business School, Queensland University of Technology, Brisbane, Australia. Dr. Wang’s research focuses on service encounter interactions, frontline employee wellbeing, and quantitative measurement models in service ecosystems.
• Maria Luiza Osorio Andrade, Ph.D.: Academic and Consumer Insights Specialist affiliated with the School of Advertising, Marketing and Public Relations, Queensland University of Technology, Brisbane, Australia, with research specializations spanning retail operations, service design, consumer mistreatment, and employee emotional burnout.

Correspondence regarding the original development and empirical validation of the scale was addressed through the Queensland University of Technology Business School, 2 George Street, Brisbane, QLD 4000, Australia.

4. Purpose

The primary purpose of the Customer Aggression Scale (CAS) is to provide an empirically robust, theoretically sound, and psychometrically validated instrument capable of diagnosing, quantifying, and disaggregating the distinct manifestations of customer hostility encountered by frontline service workers. Frontline service employees—including retail associates, bank tellers, hospitality staff, healthcare receptionists, call center representatives, and public transit operators—occupy an intrinsically vulnerable boundary-spanning role. Positioned directly at the intersection between the organization and the end consumer, these workers are systematically exposed to disproportionate levels of interpersonal hostility, customer entitlement, and verbal or non-verbal violence.

Historically, research on workplace victimization predominantly concentrated on internal sources of mistreatment, such as abusive supervision, co-worker bullying, and lateral incivility. While internal mistreatment is devastating, customer-initiated mistreatment possesses unique sociological and psychological dynamics that make it fundamentally distinct. First, frontline workers are bound by institutionalized norms of display rules and emotional labor, commonly encapsulated in corporate maxims such as “the customer is always right.” Employees are formally expected to suppress authentic negative emotions, maintain professional deference, and exhibit commercial cheerfulness even when subjected to intense hostility. Second, unlike co-workers or supervisors whose behavior can be formally mediated through organizational human resource grievance procedures, customers represent external economic agents upon whom organizational revenues depend. This dynamic creates a power asymmetry in which employees feel structurally disempowered to defend themselves or retaliate.

Prior psychometric attempts to measure customer aggression exhibited critical conceptual and methodological limitations. Many existing scales treated customer aggression as a monolithic, unidimensional construct, focusing almost exclusively on overt, dramatic expressions of interpersonal fury—such as shouting, cursing, or physical assault. Consequently, these instruments failed to detect more surreptitious, calculated, or passive-aggressive customer behaviors. Furthermore, earlier tools frequently blurred the distinction between the motivational origins of the aggressive act (whether the aggression was an impulsive, emotionally charged reaction to a perceived service breakdown versus a calculated, goal-driven strategy designed to extract financial or material gain). The CAS was purpose-built to address this critical gap by decoupling aggression along two orthogonal axes: proactive versus reactive motivation, and expressive (overt/verbal/physical) versus inexpressive (covert/non-verbal/digital) behavior.

In applied organizational contexts, the CAS serves as an essential diagnostic audit tool. Human resource executives and risk management specialists utilize the instrument to map out aggressive incident baselines across geographic territories, store formats, and service departments. By identifying whether a specific department suffers predominantly from reactive-expressive outbursts (e.g., long wait times triggering spontaneous rage) or proactive-inexpressive behaviors (e.g., deceitful reviews or manipulative complaints designed to obtain free merchandise), management can tailor interventions with precision. For occupational health and clinical psychology applications, the CAS enables researchers to examine the differential etiological trajectories linking specific aggression subtypes to psychological disorders, including chronic burnout, depersonalization, secondary traumatic stress, somatic pain, sleep disturbances, and clinical depression.

5. Psychological Construct

The psychological construct operationalized by the Customer Aggression Scale is grounded in modern behavioral taxonomies of human interpersonal aggression. Broadly defined, customer aggression comprises any act initiated by a customer or patron during a commercial service transaction that delivers or threatens to deliver psychological, physical, economic, or social harm to a frontline employee or their organization. Rather than viewing aggression as an undifferentiated emotional explosion, the CAS operationalizes customer aggression as a two-by-two conceptual matrix crossing the motivational mechanism (Proactive vs. Reactive) with the behavioral mode of delivery (Expressive vs. Inexpressive). This yields four distinct, theoretically coherent psychological dimensions:

1. Proactive-Expressive Aggression (PEA)

Proactive-Expressive Aggression represents deliberate, unprovoked, cold-blooded, and goal-directed hostility executed through direct, overt, and vocal channels. In this mode, the customer’s aggression does not stem from an antecedent organizational failure or emotional dysregulation; rather, it is employed as an instrumental, coercive tactic designed to intimidate the employee, breach standard operational protocols, or extract illicit commercial benefits (such as unearned discounts, fee waivers, immediate preferential queues, or return of non-refundable merchandise). The psychological state of the perpetrator is instrumental and predatory: aggression is deployed because the customer has learned that vocal intimidation yields compliance. Frontline employees experiencing PEA are subjected to aggressive verbal berating, condescending ultimatums, personal insult displays, and calculated hostility calibrated specifically to force the employee into submission through social pressure and acute interpersonal discomfort.

2. Proactive-Inexpressive Aggression (PIA)

Proactive-Inexpressive Aggression captures covert, surreptitious, non-vocal, and deceptive hostility initiated by customers with the calculated intent of harming the employee’s professional standing or extracting illicit concessions without direct face-to-face confrontation. Unlike expressive aggression, PIA is quiet, disguised, and frequently enacted through institutional or technological backchannels. Manifestations include lodging malicious, fabricated complaints to corporate management, publishing fraudulent negative online reviews on third-party platforms targeting individual frontline staff, threatening reputation damage, or deceitfully distorting checkout protocols. Because PIA lacks visible interpersonal yelling, it historically evaded detection by conventional workplace mistreatment inventories. However, its psychological toll on frontline workers is profound; employees experience insidious anxiety, paranoiac vigilance, and feelings of betrayal, knowing that a pleasant customer may quietly attempt to destroy their professional reputation through remote complaints.

3. Reactive-Expressive Aggression (REA)

Reactive-Expressive Aggression encapsulates overt, hot-blooded, emotionally volatile, and physically or verbally explicit hostility that occurs in direct response to an actual or perceived service breakdown. Grounded in affective frustration, REA represents an immediate behavioral dysregulation triggered by retail delays, stock-outs, price discrepancies, transaction errors, or administrative denial of service. Customers engaging in REA exhibit outward manifestations of anger, including explosive shouting, profanity, slamming items onto service counters, aggressive posturing, invading personal space, throwing merchandise, and, in severe cases, physical assault. The motivational substrate of REA is not calculating or strategic; it is an impulsive emotional discharge driven by high physiological arousal and perceived injustice, with the frontline worker serving as the direct physical proxy for the organization’s perceived incompetence.

4. Reactive-Inexpressive Aggression (RIA)

Reactive-Inexpressive Aggression involves subtle, covert, non-verbal, and passive-aggressive hostile reactions triggered by a service breakdown or operational friction. When dissatisfied, rather than erupting into an overt verbal confrontation (expressive mode), the customer engages in punishing non-verbal hostility designed to humiliate, dismiss, or devalue the frontline worker. RIA manifests as deliberate eye-rolling, heavy exasperated sighing, contemptuous facial expressions, giving the employee the “silent treatment” by refusing to answer procedural questions, snatching items or payment cards out of hands with calculated contempt, or deliberately ignoring greeting attempts. While outwardly less dramatic than physical violence or screaming, RIA creates toxic social environments. Psychologically, it conveys intense interpersonal contempt, directly attacking the frontline worker’s social dignity and psychological safety.

6. Theoretical Framework

The conceptual architecture of the Customer Aggression Scale is rigorously anchored within established socio-psychological theories of human conflict, organizational sociology, and services management literature. The primary theoretical pillars underpinning the scale comprise Displaced Aggression Theory, the doctrine of Customer Sovereignty, the “Low-Status Shield” sociological construct, and the structural phenomenon of Isolated Service Encounters.

Displaced Aggression Theory

Displaced Aggression Theory (Miller, 1941; Marcus-Newhall, Pedersen, Carlson, & Miller, 2000) provides the core socio-psychological foundation for understanding why frontline employees bear the brunt of customer wrath. According to the Frustration-Aggression Hypothesis (Dollard et al., 1939), frustration—defined as the interference with an ongoing, goal-directed behavioral sequence—inevitably instigates an aggressive drive. However, when an individual cannot retaliate against the true source of the frustration (for example, corporate headquarters setting high prices, flight cancellations caused by weather systems, or automated algorithmic errors), that aggressive drive does not dissipate. Instead, it is cognitively and behaviorally displaced onto an innocent, vulnerable target who possesses minimal capacity to retaliate. Frontline employees represent the quintessential target for displaced aggression: they embody the brand and are physically accessible, yet institutional rules prevent them from retaliating.

The Doctrine of Customer Sovereignty

The sociological ideology of Customer Sovereignty operates as an institutional enabler of customer aggression in modern consumer culture. Cultivated by twentieth-century service marketing paradigms emphasizing that “the customer is king” or “always right,” customer sovereignty instills an asymmetrical entitlement orientation within consumers. Customers internalize the belief that payment grants them temporary sovereignty and interpersonal dominance over the service worker. Consequently, when customers encounter service barriers, their internalized sense of sovereign privilege leads them to view normal operational boundaries as personal insults, legitimizing both proactive coercive aggression and reactive emotional outbursts.

The Low-Status Shield

Sociologist Arlie Russell Hochschild, in her foundational work The Managed Heart (1983), introduced the concept of the “status shield.” Hochschild posited that high-status individuals possess a cultural, psychological, and social protective barrier that shields their feelings from casual abuse; society grants their dignity innate deference. Conversely, service and retail workers operate behind a “low-status shield.” Society implicitly views frontline service roles as subordinate, replaceable, and low in prestige. Because the frontline worker’s status shield is thin or non-existent, customers feel lower social inhibition when directing hostility toward them. Customers recognize that the employee is socially, organizationally, and legally constrained from defending themselves, making aggressive acts socially low-risk for the perpetrator.

Isolated Service Encounters and Boundary-Spanning Strain

Modern service ecosystems are increasingly engineered around high-efficiency, lean staffing models. Frontline workers frequently engage in isolated, brief, and transactional encounters without direct peer or managerial support (e.g., sole operators at late-night service stations, single cashiers operating automated self-checkout zones, or remote call center representatives). According to Boundary-Spanning Theory, frontline workers must manage dual loyalties: satisfying the demands of the customer while enforcing the administrative policies of the employing firm. When policies (such as denial of expired return requests) clash with customer demands, the isolated employee absorbs the resulting psychological tension without immediate organizational backing, creating an optimal breeding ground for customer aggression.

7. Validity

The empirical validation of the Customer Aggression Scale (CAS) was established through a series of multi-stage studies utilizing large cross-sectional and independent validation cohorts of retail and frontline service professionals, following the gold-standard scale development guidelines established by Churchill (1979) and Anderson and Gerbing (1988).

Content and Face Validity

Content validity was established through extensive qualitative discovery phases, comprehensive literature syntheses, and expert judge panels. Initial pools of items reflecting customer mistreatment, instrumental coercion, verbal hostility, and passive-aggressive non-verbal behaviors were reviewed by panels of academic experts in consumer behavior, service operations, and organizational psychology. Subsequent cognitive pre-testing with active frontline retail workers ensured that the phrasing, semantic clarity, and behavioral realism of each item accurately mapped the lived realities of contemporary service environments.

Construct, Convergent, and Discriminant Validity

Construct validity was rigorously examined through Confirmatory Factor Analysis (CFA). As documented by Mortimer, Wang, and Osorio Andrade (2023), convergent validity was evaluated by assessing standardized factor loadings, Composite Reliability (CR), and Average Variance Extracted (AVE). All 19 items exhibited high, statistically significant standardized factor loadings on their intended constructs (loadings ranging between .78 and .92, (p < .001)). The AVE values for all four constructs comfortably exceeded the conventional .50 benchmark (Fornell & Larcker, 1981):

• Proactive-Expressive Aggression (PEA): (text{AVE} = .714)
• Proactive-Inexpressive Aggression (PIA): (text{AVE} = .750)
• Reactive-Expressive Aggression (REA): (text{AVE} = .777)
• Reactive-Inexpressive Aggression (RIA): (text{AVE} = .643)

Discriminant validity was established via two rigorous tests: the Fornell-Larcker criterion and the Heterotrait-Monotrait ratio of correlations (HTMT). Under the Fornell-Larcker test, the square root of the AVE for each latent construct exceeded all inter-construct correlations. Furthermore, all HTMT values remained well beneath the conservative threshold of .85 (Henseler, Ringle, & Sarstedt, 2015), demonstrating that the four dimensions represent distinct, non-redundant behavioral constructs.

Predictive and Criterion-Related Validity

Criterion-related and predictive validity were substantiated by testing the CAS against well-established occupational strain outcomes through structural equation modeling. In empirical investigations, the CAS dimensions accounted for substantial, statistically significant variance in frontline worker psychological and organizational outcomes:

• Emotional Exhaustion: Both Reactive-Expressive Aggression ((beta = .38, p < .001)) and Reactive-Inexpressive Aggression ((beta = .31, p < .001)) emerged as significant positive predictors of frontline emotional exhaustion.
• Surface Acting: Frontline workers exposed to elevated Proactive-Expressive and Proactive-Inexpressive aggression engaged in significantly higher rates of emotional surface acting (faking positive emotional displays), directly elevating psychological distress.
• Turnover Intentions: Sustained exposure to all four customer aggression dimensions demonstrated direct and indirect positive associations with frontline turnover intentions and organizational cynicism, validating the operational and strategic utility of the CAS.

8. Reliability

The Customer Aggression Scale exhibits exceptional internal consistency and metric reliability across multiple empirical evaluations. In the original scale development and validation studies, reliability was evaluated using both Cronbach’s alpha ((alpha)) and Composite Reliability (CR; also known as McDonald’s (omega) / Raykov’s rho), which avoids the assumption of tau-equivalence.

Summary of Psychometric Properties

The empirical findings demonstrate that all subscales surpass the recommended .80 cutoff for basic research and the rigorous .90 threshold required for high-stakes psychological assessment and diagnostic decision-making. Furthermore, item-total correlations across all 19 indicators consistently exceeded .65, confirming that each indicator shares substantial common variance with its specified target dimension. Independent cross-validation samples confirmed that the scale retains robust metric and scalar measurement invariance across male and female employees, as well as across differing service sectors (supermarket retail, specialty fashion, hospitality, and customer contact centers).

9. Factor Analysis

The factorial structure of the Customer Aggression Scale was established through a sequential analytic strategy incorporating both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) across independent employee cohorts.

Exploratory Factor Analysis (EFA)

Initial exploratory factor analyses were conducted on an initial calibration sample of frontline service employees utilizing Maximum Likelihood extraction with Promax oblique rotation, reflecting the theoretical expectation that sub-dimensions of aggression would correlate moderately. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy yielded a value of .942, and Bartlett’s Test of Sphericity was highly significant ((chi^2(171) = 4821.16, p < .001)), confirming the suitability of the correlation matrix for factor extraction. Parallel analysis and scree plot inspections unambiguously confirmed a four-factor solution accounting for over 72% of the cumulative variance. Items loaded cleanly onto their hypothesized constructs without problematic cross-loadings (all cross-loadings (< .25)).

Confirmatory Factor Analysis (CFA)

Confirmatory factor analysis was subsequent executed on a distinct validation cohort utilizing Maximum Likelihood estimation in AMOS/Mplus. The hypothesized four-factor correlated model demonstrated an excellent fit to the empirical data:

• Chi-Square / Degrees of Freedom Ratio: (chi^2/df = 1.94) (well below the conservative threshold of 3.0)
• Comparative Fit Index (CFI): (.978) (exceeding the standard .95 benchmark)
• Tucker-Lewis Index (TLI): (.974) (exceeding the .95 benchmark)
• Root Mean Square Error of Approximation (RMSEA): (.044) (90% CI [.037, .051], well below the .06 cutoff)
• Standardized Root Mean Square Residual (SRMR): (.038) (well below the .08 threshold)

To confirm that the four-factor model was structurally superior, competing alternative models were tested via nested model comparisons: (a) a unidimensional model where all 19 items loaded onto a single customer aggression factor ((chi^2/df = 8.74, text{CFI} = .682, text{RMSEA} = .142)), (b) a two-factor model distinguishing only Proactive vs. Reactive aggression ((chi^2/df = 5.61, text{CFI} = .795, text{RMSEA} = .108)), and (c) a two-factor model distinguishing only Expressive vs. Inexpressive aggression ((chi^2/df = 5.23, text{CFI} = .812, text{RMSEA} = .103)). The hypothesized four-factor model demonstrated statistically superior fit across all fit indices ((Delta chi^2, p < .001)), corroborating the theoretical distinction between the four proposed behavioral profiles.

10. Instrument / Measurement Tool

• Instrument Name: Customer Aggression Scale (CAS)
• Alternative Acronym: CAS (Retail & Service Frontline Aggression Scale)
• Authors / Developers: Gary Mortimer, Sitong Wang, and Maria Luiza Osorio Andrade (2023)
• Assessment Type: Standardized self-report psychometric survey / organizational diagnostic inventory
• Respondent Population: Frontline service employees, retail associates, cashiers, customer service representatives, and client-facing service personnel
• Total Item Count: 19 items across 4 dimensions
• Subscale Breakdown:
  • Proactive-Expressive Aggression (PEA): 5 items
  • Proactive-Inexpressive Aggression (PIA): 5 items
  • Reactive-Expressive Aggression (REA): 5 items
  • Reactive-Inexpressive Aggression (RIA): 4 items
• Response Format: 7-point Likert-type frequency/agreement scale (1 = Strongly Disagree / Never, 2 = Disagree / Very Rarely, 3 = Somewhat Disagree / Rarely, 4 = Neutral / Sometimes, 5 = Somewhat Agree / Often, 6 = Agree / Very Often, 7 = Strongly Agree / Always)
• Administration Time: Approximately 5 to 8 minutes
• Scoring Procedures:
  • Dimensional scores are calculated by computing the unweighted arithmetic mean of the items comprising each respective subscale.
  • An overall Composite Customer Aggression score can be derived by computing the grand mean across all 19 items (ranging from 1.00 to 7.00).
  • Higher scores indicate higher self-reported exposure to customer aggression in the workplace.
  • No items are reverse-scored, simplifying computational scoring and reducing administrative error.
• Interpretation Benchmarks: Mean scores (< 2.50) indicate low exposure; scores between (2.51) and (4.49) indicate moderate, chronic exposure requiring management monitoring; scores (ge 4.50) reflect acute, severe customer hostility necessitating immediate organizational intervention.

11. Permissions & Fee and Test Year

The Customer Aggression Scale was published in 2023 in the peer-reviewed journal Journal of Retailing and Consumer Services (Volume 73, Article 103348) by Elsevier Ltd. The copyright of the original publication and proprietary questionnaire items is held by Elsevier Ltd. and the original authoring team (Mortimer, Wang, & Osorio Andrade).

Academic and Non-Commercial Research Access: The scale may be utilized by university scholars, independent academic researchers, graduate students, and non-commercial investigators for academic, empirical, and non-profit educational purposes under academic fair use conventions, provided full formal citation and attribution are given to the original 2023 publication in the Journal of Retailing and Consumer Services.

Commercial, Corporate, and Consulting Applications: Any commercial deployment—including organizational diagnostic auditing, corporate training benchmarks, proprietary employee surveys, consulting services, or inclusion within commercial human resource assessment platforms—requires explicit written permission or licensing agreements from Elsevier or the original authors. Interested organizations should consult the Elsevier RightsLink permissions portal or contact the lead author, Professor Gary Mortimer, via the Queensland University of Technology Business School.

12. References

• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411
• Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73. https://doi.org/10.1177/002224377901600110
• Dollard, J., Miller, N. E., Doob, L. W., Mowrer, O. H., & Sears, R. R. (1939). Frustration and aggression. Yale University Press. https://doi.org/10.1037/10022-000
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Grandey, A. A., Dickter, D. N., & Sin, H. P. (2004). The customer is not always right: Customer verbal aggression toward service employees and its relation to emotional exhaustion and absenteeism. Journal of Organizational Behavior, 25(3), 397–418. https://doi.org/10.1002/job.252
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
• Hochschild, A. R. (1983). The managed heart: Commercialization of human feeling. University of California Press.
• Marcus-Newhall, A., Pedersen, W. C., Carlson, M., & Miller, N. (2000). Displaced aggression is alive and well: A meta-analytic review. Journal of Personality and Social Psychology, 78(4), 670–689. https://doi.org/10.1037/0022-3514.78.4.670
• Miller, N. E. (1941). The frustration-aggression hypothesis. Psychological Review, 48(4), 337–342. https://doi.org/10.1037/h0055861
• Mortimer, G., Wang, S., & Osorio Andrade, M. L. (2023). Measuring customer aggression: Scale development and validation. Journal of Retailing and Consumer Services, 73, 103348. https://doi.org/10.1016/j.jretconser.2023.103348

13. Items of the Scale