Perceived Customer Unfriendliness Toward Staff

1. Abstract

The Perceived Customer Unfriendliness Toward Staff (PCUTS) scale is a concise, psychometrically validated three-item self-report instrument developed by Albrecht, Walsh, Brach, Gremler, and van Herpen (2017). Designed to assess a focal customer's subjective perception of interpersonal mistreatment, impoliteness, and incivility exhibited by fellow customers toward frontline service personnel, the instrument operates within the paradigm of social contagion, customer-to-customer interactions (CCI), and social norms theory. Captured on an authentic 7-point Likert response scale ranging from 1 (“Strongly disagree”) to 7 (“Strongly agree”), the scale comprises one directly keyed item and two reverse-scored items that evaluate politeness and friendliness directed toward employees. Psychometrically, the PCUTS demonstrates robust unidimensionality, high internal consistency reliability (α > .80; composite reliability > .85), substantial average variance extracted (AVE > .65), and strong discriminant validity against conceptually related constructs, including perceived employee unfriendliness, focal customer behavioral intentions, and ambient descriptive norms. Originally deployed across field settings in cafes, casual dining environments, and cafeterias, the scale provides researchers in organizational behavior, service management, and consumer psychology with an efficient, low-burden metric to capture the bystander observation of customer incivility and to model how observing uncivil peer conduct shapes normative climate, vicarious emotional exhaustion, and subsequent customer behaviors.

2. Keywords

Perceived Customer Unfriendliness Toward Staff, customer incivility, frontline employees, customer-to-customer interactions, social norms theory, service climate, descriptive norms, bystander effects, service marketing, interpersonal mistreatment

3. Authors

The Perceived Customer Unfriendliness Toward Staff scale was developed and psychometrically validated by an international team of scholars in marketing and consumer psychology:

• Arne K. Albrecht — Department of Marketing, University of Münster, Münster, Germany. Research focuses on service marketing, service failure and recovery, frontline employee dynamics, and social interactions in service contexts.
• Gianfranco Walsh — Department of Marketing, Friedrich Schiller University Jena, Jena, Germany. Notable for extensive scholarship on consumer psychology, service management, customer dissatisfaction, and front-line employee stress.
• Simon Brach — School of Management and Economics, TU Dortmund University, Dortmund, Germany. Specializes in service operations, consumer decision-making, and empirical modeling of interpersonal dynamics.
• Dwayne D. Gremler — Department of Marketing, College of Business, Bowling Green State University, Bowling Green, Ohio, USA. An internationally recognized pioneer in relationship marketing, customer advocacy, and service encounters.
• Erica van Herpen — Marketing and Consumer Behaviour Group, Wageningen University, Wageningen, Netherlands. Renowned expert in consumer behavior, social influence, contextual norms, and spatial-perceptual analysis.

4. Purpose

The primary objective of the Perceived Customer Unfriendliness Toward Staff (PCUTS) scale is to quantify an observer's perception of uncivil, disrespectful, or rude behaviors enacted by other consumers toward service workers within a shared commercial environment. Interpersonal mistreatment in service encounters has historically been evaluated through two narrow lenses: employee-to-customer mistreatment (e.g., service sabotage, curtness, negligence) or direct customer-to-employee mistreatment (e.g., verbal abuse, aggression, dysfunctions studied exclusively from the frontline employee's perspective). However, services are inherently social landscapes characterized by triadic interactions involving employees, individual patrons, and ambient other customers. Prior to the operationalization of PCUTS, psychometric measurement frequently neglected the role of the bystander customer who witnesses peer mistreatment of personnel.

From a theoretical rationale, PCUTS fills a critical empirical void by serving as an observational barometer for ambient social cues. According to the Focus Theory of Normative Conduct, individuals constantly scan their immediate environment for social cues that signal prevailing descriptive norms—that is, what behaviors are typical, acceptable, or common in a given setting. When focal customers observe other patrons treating an employee with coldness, dismissiveness, or open hostility, that perception serves as a cognitive anchor. The PCUTS scale measures this exact cognitive appraisal, enabling researchers to test whether observing uncivil peer conduct triggers behavioral mimicry, moral outrage, protective interventions, or diminished loyalty toward the establishment.

In applied organizational and clinical/workplace well-being research, the PCUTS scale provides actionable diagnostics. Chronic customer incivility directed at frontline staff represents a premier cause of emotional exhaustion, depersonalization, and high staff turnover. However, surveying frontline staff alone yields an incomplete picture, as employees often underreport everyday low-level slights due to normalization of abuse or fear of appearing incompetent. By measuring the social climate via external customer perceptions using the PCUTS scale, service organizations can cross-validate internal employee surveys, benchmark the interpersonal climate across branches, and design structural interventions (e.g., signage, architectural modifications, staff de-escalation training) to suppress peer unfriendliness before it metastasizes into widespread organizational toxicity.

5. Psychological Construct

The construct captured by the PCUTS scale is Perceived Customer Unfriendliness Toward Staff, conceptualized as a unidimensional, perception-based evaluation reflecting the degree to which an observing consumer witnesses peer patrons treating frontline personnel without civility, warmth, or basic courtesy. This construct belongs to the broader taxonomy of workplace and service incivility, which Anderssen and Pearson defined as low-intensity deviant behavior with ambiguous intent to harm the target, in violation of workplace norms for mutual respect.

Crucially, the construct does not measure overt physical violence or criminal aggression; rather, it targets everyday micro-behaviors that signal relational disregard. Such behaviors include speaking condescendingly, refusing to make eye contact, withholding greetings or thank-yous, displaying impatient gestures (such as sighing, eye-rolling, or tapping fingers aggressively), snapping orders, or demanding service with an abrasive tone. The construct is grounded in three core psychological facets:

• Cognitive Appraisal of Unkindness: The focal customer identifies clear behavioral cues indicating that other patrons are interacting with service staff in a deliberately cold, harsh, or disparaging manner. This represents the explicit presence of negative socio-emotional interaction.
• Deficit of Interpersonal Politeness: Politeness represents adherence to normative conversational conventions, including honorifics, pleasantries, and turn-taking etiquette. The perceived unfriendliness construct explicitly incorporates the observed absence or breakdown of these common conventions.
• Absence of Prosocial Warmth: A defining attribute of benign service encounters is baseline friendliness. When other customers actively withhold prosocial cues (e.g., a warm demeanor, smiling, acknowledgment of the employee's humanity), observers encode the environment as hostile or interpersonally impoverished.

The scale relies on both directly keyed phrasing (“Other customers treated the employee unkindly”) and reverse-keyed phrasing evaluating politeness and friendliness. This operationalization ensures that the construct reflects not merely the presence of dramatic hostility, but the net socio-emotional deficit characterizing the observed customer-to-employee dyad. Furthermore, the construct is fundamentally observational and referent-shifted: the respondent does not report on their own actions or feelings, but serves as an external informant evaluating the social dynamic unfolding between fellow patrons and staff.

6. Theoretical Framework

The theoretical architecture underpinning the PCUTS scale draws upon three major paradigms in social psychology and organizational sociology: the Focus Theory of Normative Conduct, Social Information Processing Theory, and the Broken Windows Theory applied to service landscapes.

Focus Theory of Normative Conduct

Formulated by Cialdini, Reno, and Kallgren (1990), this framework distinguishes between injunctive norms (what people believe ought to be done based on moral or societal approval) and descriptive norms (what is actually done by others in a specific context). Albrecht et al. (2017) utilized this theoretical foundation to argue that although customers universally understand that politeness toward staff is an injunctive norm, their in-situ behavior is heavily governed by the descriptive norm made salient by peer conduct. When customers perceive other patrons behaving unkindly toward employees, their subjective appraisal of the descriptive norm shifts: incivility is perceived as common, normative, or tolerated in that venue. The PCUTS scale directly captures this cognitive translation of ambient behavior into an empirical descriptive norm.

Social Information Processing (SIP) Theory

Developed by Salancik and Pfeffer (1978), SIP theory posits that individuals are adaptive organisms who formulate attitudes, beliefs, and behaviors in response to the social information provided by their immediate operating environment. In services, the customer is co-present with other customers who serve as powerful social referents. Rather than processing service encounters in a sterile vacuum, customers actively observe how peers interact with employees. A high PCUTS score signifies an information environment laden with cues of disrespect. This social data informs the focal customer's subsequent expectations regarding service quality, organizational control, and social safety within the service space.

Social Contagion and the Incivility Spiral

Andersson and Pearson's (1999) foundational model of the incivility spiral illustrates how a single uncivil act can erode social restraints and catalyze retaliatory or copycat counter-behaviors. In a service environment, customer incivility toward staff does not stay encapsulated within a single dyad. Bystanders who witness unpunished or frequent rudeness may experience behavioral disinhibition. Albrecht et al. (2017) demonstrated that higher perceived customer unfriendliness toward staff significantly increases the likelihood that the observing customer will subsequently exhibit unfriendliness toward employees themselves, mediated by perceived descriptive norms. Thus, the PCUTS construct represents the crucial perceptual spark that ignites downstream social contagion.

7. Validity

The psychometric validity of the PCUTS scale was rigorously established through empirical investigations conducted by Albrecht et al. (2017), using both experimental and field-based survey designs in authentic service contexts (specifically cafes and dining facilities).

Construct and Convergent Validity

Convergent validity evaluates whether the scale items correlate strongly with one another and converge on a common underlying construct. Confirmatory factor analyses across study samples confirmed that all three items exhibit high, statistically significant standardized factor loadings (λ ranging from .78 to .91, p < .001). The Average Variance Extracted (AVE) substantially exceeded the recognized .50 benchmark (Fornell & Larcker, 1981), consistently demonstrating values above .65. This confirms that the majority of variance captured by the scale items is shared construct variance rather than measurement error.

Discriminant Validity

To verify that PCUTS does not merely capture general service negativity or atmospheric dissatisfaction, Albrecht et al. tested discriminant validity against several adjacent constructs:

• Perceived Employee Unfriendliness: PCUTS demonstrated clear empirical separation from scales measuring employee rudeness toward customers, ensuring respondents differentiate between source and target of mistreatment.
• Descriptive Norms of Customer Unfriendliness: PCUTS items specifically assess observed behavior (“treated the employee unkindly”), which statistically predicted, but remained distinct from, broader normative evaluations (e.g., “It is typical for customers here to behave rudely”).
• Focal Customer Unfriendliness Intentions: The square root of the AVE for PCUTS exceeded its inter-construct correlation with the respondent's own unfriendliness, establishing discriminant validity per the Fornell-Larcker criterion and the Heterotrait-Monotrait (HTMT) ratio of correlations (HTMT < .85).

Predictive and Criterion Validity

Criterion-related validity was corroborated through structural equation modeling. Albrecht et al. (2017, Study 2) demonstrated that PCUTS significantly and positively predicted perceived descriptive norms of customer unfriendliness (β = .44, p < .001), which in turn exerted a direct positive influence on the focal customer's own unfriendliness toward the frontline employee (β = .38, p < .001). Furthermore, experimental manipulation of customer unfriendliness in video-based scenarios confirmed that the scale detects deliberate variations in peer behavior with high statistical sensitivity and substantial effect sizes (Cohen's d > 1.20).

8. Reliability

The PCUTS scale displays exceptional internal consistency despite its parsimonious three-item structure, avoiding the attenuation often associated with ultra-short instruments while eliminating item redundancy.

Internal Consistency Metrics

• Cronbach’s Alpha (α): Across the validation studies in Albrecht et al. (2017), the scale consistently yielded Cronbach's α values exceeding the conventional .80 cutoff. In Study 2, conducted in naturalistic dining environments, the scale demonstrated an α of .84 to .87, reflecting high internal homogeneity.
• Composite Reliability (CR): Because Cronbach's alpha assumes tau-equivalence (equal factor loadings across items), composite reliability was also calculated within structural equation models. The CR values routinely surpassed .86, well above Bagozzi and Yi's recommended .70 threshold.
• Inter-Item Correlations: Corrected item-to-total correlations ranged between .65 and .78. Average inter-item correlations were situated within the ideal .50 to .70 window, confirming high conceptual affinity without item tautology.

Stability and Cross-Context Robustness

While dynamic field contexts make longitudinal test-retest reliability challenging due to naturally fluctuating customer behaviors, the scale displayed robust split-half reliability and equivalent psychometric parameters across varied customer demographic strata (age, gender, visit frequency) and service formats (table-service cafes versus self-service cafeterias). Measurement invariance tests confirmed metric and scalar invariance across observational conditions.

9. Factor Analysis

The structural dimensionality of the PCUTS scale has been scrutinized via both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) within contemporary covariance structure modeling frameworks.

Confirmatory Factor Analysis (CFA)

In the primary measurement model evaluation (Albrecht et al., 2017), a unidimensional CFA model specifying a single latent construct underlying the three items was estimated using Maximum Likelihood (ML) estimation. The single-factor specification demonstrated an excellent fit to the empirical data:

• Chi-Square / Degrees of Freedom: χ²/df < 2.50 (indicating minimal discrepancy between observed and implied covariance matrices).
• Comparative Fit Index (CFI): Values consistently equaled or exceeded .98.
• Tucker-Lewis Index (TLI): Values consistently equaled or exceeded .97.
• Root Mean Square Error of Approximation (RMSEA): RMSEA ≤ .045 (with 90% confidence intervals spanning .000 to .075), meeting the strict criteria for close fit established by Hu and Bentler (1999).
• Standardized Root Mean Square Residual (SRMR): Values remained below .030.

Factor Loadings and Parameter Estimates

The standardized factor loadings (λ) for the three items on the latent construct are exceptionally strong and uniform:

• Item 1 (“Other customers treated the employee unkindly”): Standardized λ ≈ .82 to .86.
• Item 2 (Reverse “Other customers were polite to the employee”): Standardized λ ≈ .80 to .85.
• Item 3 (Reverse “Other customers behaved friendly toward the employee”): Standardized λ ≈ .84 to .89.

Attempts to fit alternative multi-factor solutions or split positive and negative items into distinct methodological factors yielded uninterpretable solutions or failed to improve model fit, corroborating that a single general factor parsimoniously accounts for all common item variance.

10. Instrument / Measurement Tool

• Name of Instrument: Perceived Customer Unfriendliness Toward Staff (PCUTS)
• Instrument Type: Observer-report / Self-report psychometric scale (referent-shift design)
• Target Population: Consumers, patrons, and bystanders present in commercial or public service environments (e.g., hospitality, retail, healthcare, public transit)
• Total Number of Items: 3 items
• Item Formatting: Declarative statements evaluating the observed interpersonal behavior of fellow consumers toward frontline employees
• Response Scale: 7-point Likert scale (1 = Strongly disagree to 7 = Strongly agree)
  • 1 = Strongly disagree
  • 2 = Disagree
  • 3 = Somewhat disagree
  • 4 = Neither agree nor disagree
  • 5 = Somewhat agree
  • 6 = Agree
  • 7 = Strongly agree
• Scoring and Transformation Rules:
  • Directly Keyed Item: Item 1 is scored as entered (1 = 1, 2 = 2, …, 7 = 7).
  • Reverse-Scored Items: Items 2 and 3 are reverse-scored prior to aggregation. The transformation formula is: Reverse Score = 8 - Original Score (e.g., a raw response of 7 becomes 1; 6 becomes 2; 5 becomes 3; 4 remains 4; 3 becomes 5; 2 becomes 6; 1 becomes 7).
  • Composite Score Computation: Compute the arithmetic mean of Item 1, transformed Item 2, and transformed Item 3. Composite score range: 1.00 to 7.00.
  • Interpretation: Higher composite scores indicate a stronger focal customer perception of peer incivility, unfriendliness, and relational disrespect directed toward service personnel. Lower scores reflect an observed environment characterized by courtesy, friendliness, and civility.
• Administration Time: Approximately 30 to 60 seconds, minimizing respondent fatigue and maximizing suitability for in-situ field research and intercept surveys.

11. Permissions & Fee and Test Year

The Perceived Customer Unfriendliness Toward Staff scale was formally published in 2017 in the Journal of the Academy of Marketing Science (Albrecht et al., 2017). As is standard in academic psychometrics, the scale items were published directly in the research article text and methodological appendices for scientific, educational, and non-commercial research use.

Scholars and behavioral researchers may employ the instrument without payment of licensing fees, provided that appropriate scholarly attribution and bibliographic citation are accorded to Albrecht, Walsh, Brach, Gremler, and van Herpen (2017). Commercial entities, market research firms, or organizational consultancies seeking to embed the scale within proprietary commercial assessment platforms, software tools, or syndicated benchmarking systems should review standard copyright terms with the publisher (Springer Nature / Academy of Marketing Science) or contact the corresponding author regarding commercial permissions.

12. References

• Albrecht, A. K., Walsh, G., Brach, S., Gremler, D. D., & van Herpen, E. (2017). The influence of service employees and other customers on customer unfriendliness: A social norms perspective. Journal of the Academy of Marketing Science, 45(6), 827–847. https://doi.org/10.1007/s11747-017-0526-7
• Andersson, L. M., & Pearson, C. M. (1999). Tit for tat? The spiraling effect of incivility in the workplace. Academy of Management Review, 24(3), 452–471. https://doi.org/10.5465/amr.1999.2202131
• Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327
• Cialdini, R. B., Reno, R. R., & Kallgren, C. A. (1990). A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places. Journal of Personality and Social Psychology, 58(6), 1015–1026. https://doi.org/10.1037/0022-3514.58.6.1015
• 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
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
• Salancik, G. R., & Pfeffer, J. (1978). A social information processing approach to job attitudes and task design. Administrative Science Quarterly, 23(2), 224–253. https://doi.org/10.2307/2392563

13. Items of the Scale