Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory

Abstract

The Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory (Gligor et al., 2023) is an empirical psychometric instrument developed to evaluate the structural interrelationships among perceived brand fairness, consumer-brand identification, and multidimensional customer engagement behaviors (CEBs), with an explicit analytical focus on gender-moderated variations. Emerging from the theoretical cross-section of social exchange theory, social identity theory, and the customer engagement value matrix, this scale systematically quantifies 26 items across six distinct primary and sub-construct dimensions: Perceived Brand Fairness (4 items), Brand Identification (7 items), and four distinct manifestations of Customer Engagement—namely Customer Purchases (3 items), Customer Referrals (4 items), Customer Influence (4 items), and Customer Knowledge (4 items). All manifest indicators are administered using a standard seven-point Likert-type response format ranging from 1 (“strongly disagree”) to 7 (“strongly agree”).

Psychometric evaluation of the instrument was conducted on a normative sample of adult consumers drawn from university populations in the United States, representing young adulthood (ages 18–29) and individuals in their thirties (ages 30–39). Confirmatory Factor Analysis (CFA) executed via Stata 15.1 established robust structural validity across the measurement dimensions (χ² [284] = 746.123, p < 0.001; Root Mean Square Error of Approximation [RMSEA] = 0.08; Comparative Fit Index [CFI] = 0.92; Tucker-Lewis Index [TLI] = 0.91; Standardized Root Mean Square Residual [SRMR] = 0.06). The scale demonstrated exceptional convergent validity, with all Average Variance Extracted (AVE) values exceeding the 0.50 threshold established by Hair et al. (2013). Discriminant validity was established via the Fornell-Larcker criterion, wherein the square root of each latent construct’s AVE surpassed all inter-construct correlations. Internal consistency reliability is high, with construct-specific Cronbach’s alpha values spanning 0.82 to 0.95. Procedural and statistical evaluations of common method variance (Harman’s single-factor test) confirmed that no single factor accounted for majority variance (accounting for 40.38%, well below the critical 50% cutoff). The inventory provides psychometric precision for modeling the differential mechanisms through which male and female consumers translate perceived justice and psychological self-brand alignment into non-transactional and transactional customer engagement values.

Keywords

Brand Fairness, Brand Identification, Customer Engagement, Customer Purchases, Customer Referrals, Customer Influence, Customer Knowledge, Gender-Related Differences, Social Exchange Theory, Social Identity Theory, Consumer Behavior, Psychometrics, Structural Equation Modeling, Confirmatory Factor Analysis, Marketing Psychology

Authors

The Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory was formulated and validated by an interdisciplinary research team specializing in marketing analytics, consumer psychology, organizational behavior, and political science:

• David Gligor, Ph.D. — Department of Marketing, School of Business Administration, University of Mississippi, Oxford, Mississippi, United States.
• Sıddık Bozkurt, Ph.D. — Department of Business Administration, Faculty of Economics and Administrative Sciences, Osmaniye Korkut Ata University, Osmaniye, Turkey.
• Emma Welch, Ph.D. (Corresponding Author) — Department of Marketing, School of Business Administration, University of Mississippi, Oxford, Mississippi, United States. Email: [email protected]; ORCID: 0000-0002-3466-5700.
• Nichole Gligor, Ph.D. — Department of Political Science, College of Liberal Arts and Social Sciences, University of North Texas, Denton, Texas, United States.

Purpose

The primary purpose of the Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory is to provide a standardized, psychometrically sound diagnostic instrument designed to isolate, assess, and compare the pathways connecting brand-level cognitive appraisals to behavioral customer engagement, explicitly accounting for the moderating role of consumer gender. In contemporary marketing psychology and relationship marketing, the conceptualization of consumer loyalty has migrated from purely transactional metrics—such as repeat purchase volume, recency, and customer lifetime monetary value—to a more holistic paradigm known as Customer Engagement Behaviors (CEBs). CEBs capture the behavioral manifestations that consumers direct toward a brand or firm beyond discrete purchasing events, emerging from underlying motivational drivers (van Doorn et al., 2010; Kumar et al., 2010).

Despite the widespread acceptance of multidimensional customer engagement models, empirical inquiry into how gender identity moderates engagement trajectories has historically suffered from theoretical fragmentation and inconsistent operationalizations. Historically, market researchers frequently treated gender as a rudimentary demographic covariate rather than an influential sociocognitive and evolutionary moderator of consumer-firm relationships. Rooted in social role theory (Eagly & Wood, 2012) and evolutionary psychological paradigms of relationship management, men and women often process justice, cognitive belonging, and social reciprocity through divergent normative expectations and relational orientations. Gligor, Bozkurt, Welch, and Gligor (2023) engineered this inventory to address these theoretical gaps by establishing a psychometrically stable baseline capable of assessing:

• How baseline evaluations of equity, organizational justice, and integrity (Perceived Brand Fairness) translate into deep, self-definitional integration (Brand Identification).
• How both brand fairness and brand identification independently and synergistically stimulate distinct behavioral components of customer engagement: transactional loyalty (Purchases), incentivized advocacy (Referrals), voluntary organic word-of-mouth (Influence), and collaborative co-creation (Knowledge).
• The degree to which consumer gender acts as an effect modifier across these structural pathways, clarifying whether relational attachments disproportionately drive expressive engagement among female consumers or agentic, incentive-driven actions among male consumers.

In applied research and managerial contexts, this inventory serves as an empirical platform for diagnosing why identical branding initiatives, corporate social responsibility campaigns, or loyalty architectures elicit asymmetrical responses across demographic cohorts. Rather than deploying blanket relationship-marketing investments, organizations can deploy this 26-item inventory to audit customer equity portfolios, identifying whether weaknesses in advocacy or co-creation stem from deficits in fundamental fairness perceptions, failures in social self-concept alignment, or gendered misalignments in communication framing.

Psychological Construct

The Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory operationalizes an integrated psychological network encompassing six distinct latent constructs. Each construct represents an established psychological domain tailored to consumer-brand relational dynamics.

1. Perceived Brand Fairness

Perceived brand fairness captures the consumer’s cognitive and evaluative appraisal of equity, integrity, non-exploitation, and moral justice exhibited by a commercial entity across its operational touchpoints. Grounded in the multidimensional traditions of organizational justice theory (Colquitt, 2001), this construct synthesizes three core justice modalities within consumer markets: distributive justice (fair outcomes and pricing transparency), procedural justice (consistency in policies, fulfillment of explicit and psychological contracts), and interactional justice (interpersonal dignity, politeness, and mutual respect). Within the scale, items evaluate the degree to which a brand honors promises, treats patrons with courtesy, ensures egalitarian treatment across customer segments, and avoids opportunistic behavior.

2. Brand Identification

Brand identification reflects the psychological state in which a consumer perceives, feels, and values a sense of oneness or psychological belonging with a brand. Deriving from Bhattacharya and Sen’s (2003) formulation of consumer-company identification, this construct reflects the extent to which the brand’s perceived identity, values, and symbolic aura overlap with the consumer’s actual self-concept, ideal self-concept, and social persona. When brand identification is elevated, the consumer no longer views the relationship merely as an arm’s-length commercial exchange; rather, the brand serves as an identity-signaling instrument and an extension of the self (Belk, 1988). Scale indicators capture self-concept overlap, identity expression, emotional connection, and personal developmental utility.

3. Customer Engagement: Purchases

Customer purchases represent the direct transactional dimension of customer engagement. Unlike passive transactional measures that register historical sales metrics, this construct operationalizes the psychological and forward-looking dimensions of economic commitment. It reflects the consumer’s intention to maintain commercial continuity, their emotional contentment derived from acquiring the brand’s offerings, and the positive affective valence associated with brand ownership. This sub-dimension anchors the engagement matrix within concrete economic exchange.

4. Customer Engagement: Referrals

Customer referrals capture an extrinsically incentivized form of promotional behavior wherein consumers actively solicit their immediate social circle—including friends, family members, and professional associates—to acquire products or services from the brand, driven predominantly by institutional rewards, monetary referral fees, discounts, or tangible bonuses (Kumar et al., 2010). This dimension reflects calculated customer advocacy, isolating behaviors where interpersonal social capital is mobilized in tandem with commercial reward structures.

5. Customer Engagement: Influence

Customer influence captures organic, non-incentivized advocacy and social contagion initiated by the consumer across public and private communication environments. Drawing upon word-of-mouth (WOM) and digital evangelism dynamics, this dimension evaluates how consumers naturally integrate the brand into their social discussions, post spontaneous feedback on digital and social media channels, articulate the subjective benefits they have derived, and position their relationship with the brand as a salient conversation topic. Unlike transactional referrals, customer influence represents intrinsic brand advocacy driven by personal enthusiasm and social validation.

6. Customer Engagement: Knowledge

Customer knowledge operationalizes the collaborative, value-co-creation dimension of customer engagement. It reflects the consumer’s willingness to invest intellectual capital, temporal resources, and cognitive effort to provide unsolicited or solicited constructive feedback, optimization suggestions, and new product ideation to the firm (van Doorn et al., 2010). Consumers exhibiting elevated customer knowledge behaviors transition from passive utility-maximizers into proactive co-innovators who directly participate in the brand’s research and development feedback loops.

Theoretical Framework

The Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory is anchored across four foundational paradigms within psychology, sociology, and behavioral economics:

Social Exchange Theory and the Norm of Reciprocity

Social exchange theory (Blau, 1964; Cropanzano & Mitchell, 2005) posits that interpersonal and inter-entity relationships evolve over time through reciprocal, contingent, and mutually rewarding exchanges. In a consumer context, when an individual perceives that an exchange partner adheres to standards of procedural, distributive, and interactional equity (Perceived Brand Fairness), a psychological state of indebtedness and trust is generated. Governed by Gouldner’s (1960) universal norm of reciprocity, consumers seek to balance this social ledger by offering non-contractual socioemotional resources back to the brand. These reciprocal contributions materialize not merely as financial expenditures (Purchases), but as external advocacy (Referrals, Influence) and collaborative investments (Knowledge).

Social Identity Theory and the Self-Concept

Social identity theory (Tajfel & Turner, 1979) and self-categorization theory provide the cognitive framework explaining how individuals categorize themselves into social groups and cognitive archetypes to bolster self-esteem and clarify identity. When extended to relationship marketing (Bhattacharya & Sen, 2003), consumers form cognitive bonds with brands whose perceived positioning matches their self-construal. Brand identification acts as a psychological bridge: perceived brand fairness serves as a foundational antecedent signaling that the brand possesses high organizational morality and social prestige, making identification psychologically safe and socially identity-enhancing. Once the brand is assimilated into the consumer’s extended self (Belk, 1988), brand preservation and brand promotion become acts of self-affirmation, driving behaviors that amplify the brand’s market standing.

Customer Engagement Value Paradigm

Historically, customer relationship management models focused narrowly on customer lifetime value (CLV) calculated strictly via gross margins from historical purchases. Kumar et al. (2010) expanded this paradigm by formalizing the Customer Engagement Value (CEV) matrix, which postdates that total customer asset value comprises four components:

1. Customer Lifetime Value (Purchases): Direct economic transaction value.
2. Customer Referral Value (Referrals): The net present value of prospective customers acquired through tracked, incentivized referral pathways.
3. Customer Influencer Value (Influence): The indirect value generated when a consumer influences others through organic word-of-mouth and public brand communication.
4. Customer Knowledge Value (Knowledge): The operational and innovative value contributed when a consumer assists the firm in product development, service refinement, and operational improvements.

The Gligor et al. (2023) inventory directly integrates Kumar et al.’s quadripartite model into an operational measurement instrument, enabling researchers to examine all four engagement values concurrently alongside their socio-cognitive determinants.

Social Role Theory and Gendered Cognitive Archetypes

Social role theory (Eagly & Wood, 2012) posits that socially constructed gender roles, along with evolutionary behavioral tendencies, encourage communal and relational values among women and agentic, achievement-oriented behaviors among men. Consequently, male and female consumers often manifest distinct sensitivities to relationship touchpoints. Female consumers frequently prioritize relational cohesion, interpersonal justice, communication authenticity, and long-term socioemotional reciprocity, potentially showing stronger pathways from brand identification to organic advocacy and knowledge sharing. In contrast, male consumers are often socialized to prioritize agentic outcomes, instrumental efficiency, and tangible resource optimization, which may strengthen pathways connecting direct transactional benefits and monetary incentives to referral outputs. Gligor et al.’s inventory provides the measurement framework required to systematically test these structural variations.

Validity

The psychometric evaluation of the Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory was executed following the methodological guidelines established by Hair, Black, Babin, and Anderson (2013) and Podsakoff, MacKenzie, Lee, and Podsakoff (2003). Evidence supporting content, convergent, discriminant, and nomological validity was established through empirical testing across consumer samples.

Content and Construct Validity

Content and face validity were secured during the instrument’s initial development phases through the adaptation of validated items from foundational consumer psychology and relationship marketing literature. The item pool was revised to ensure consistent referential framing across target brands. Measurement indicators underwent expert academic review to ensure semantic precision, cultural generalizability, and conceptual alignment with their underlying latent definitions.

Convergent Validity

Convergent validity evaluates the extent to which manifest indicators of a specific construct share a high proportion of common variance. In Gligor et al. (2023), convergent validity was evaluated using the Average Variance Extracted (AVE) metric. As prescribed by Hair et al. (2013), an AVE value exceeding 0.50 demonstrates that the latent construct explains more than half of the variance in its indicator items, confirming convergent validity:

• All latent dimensions (Perceived Brand Fairness, Brand Identification, Purchases, Referrals, Influence, Knowledge) surpassed the AVE > 0.50 threshold.
• Standardized factor loadings across all manifest variables were positive, statistically significant (p < 0.001), and loaded heavily onto their designated latent factors.

Discriminant Validity

Discriminant validity confirms that empirical measures of conceptually distinct constructs are not excessively correlated. This was verified through the classical Fornell-Larcker criterion (Hair et al., 2013). The empirical findings established that:

• The square root of the AVE for every single latent variable was substantially greater than any bivariate correlation coefficient observed between that construct and any other construct in the measurement model.
• Inter-construct correlations between the engagement dimensions remained well below problematic collinearity cutoffs (e.g., r < 0.85), confirming that despite their overarching engagement umbrella, Customer Purchases, Customer Referrals, Customer Influence, and Customer Knowledge represent distinct behavioral constructs.

Common Method Bias Assessments

Because all survey indicators were captured via a cross-sectional, self-report survey design, procedural and statistical controls were implemented to evaluate potential common method variance (CMV) (Podsakoff et al., 2003):

• Harman’s Single-Factor Test: An unrotated exploratory factor analysis containing all manifest variables revealed that the single largest unrotated factor accounted for 40.38% of the total variance. Because this figure falls well below the conservative threshold of 50.0%, common method bias was ruled out as a threat to empirical validity.
• CFA Single-Factor Diagnostic: A baseline model in which all 26 indicators loaded onto a single common factor was fitted to the data and exhibited exceptionally poor fit, demonstrating that a multidimensional structure is necessary to represent the empirical covariance matrix.

Reliability

The internal consistency reliability of the inventory was tested across each subscale. Reliability estimates quantify the proportion of true score variance relative to total observed variance, ensuring that individual test items reliably capture the underlying constructs without substantial measurement error.

As documented by Gligor et al. (2023), Cronbach’s alpha coefficients across all six constructs ranged from 0.82 to 0.95. These values comfortably exceed the standard psychometric threshold of 0.70 recommended by Nunnally and Bernstein (1994), as well as the more conservative 0.80 benchmark required for structural equation modeling. The high alpha for Brand Identification (α ≈ 0.95) reflects high internal consistency across its seven identity-integration items without redundant question phrasing. The transactional and behavioral engagement subscales maintained strong internal consistency (α ≥ 0.82), confirming that individual items capture their respective behavioral domains with limited error variance.

Factor Analysis

The dimensional architecture and structural integrity of the 26-item instrument were evaluated using Confirmatory Factor Analysis (CFA) executed in Stata 15.1. Rather than collapsing the items into a generalized engagement aggregate, the measurement model specified six correlated first-order latent constructs: Perceived Brand Fairness, Brand Identification, Customer Purchases, Customer Referrals, Customer Influence, and Customer Knowledge.

CFA Model Fit Indices

The measurement model demonstrated good fit to the empirical data across global, relative, and absolute fit metrics, aligning with the criteria established by Hu and Bentler (1999) and Hair et al. (2013):

• Chi-Square Metric: χ² (284) = 746.123, p > χ² = 0.000. While the chi-square test was statistically significant, this sensitivity is expected given the large sample size of the study cohort.
• Root Mean Square Error of Approximation (RMSEA): 0.08. This falls directly at the conventional upper threshold for acceptable fit in complex consumer behavior models, indicating adequate approximation in the population covariance matrix.
• Comparative Fit Index (CFI): 0.92. Exceeds the standard ≥ 0.90 threshold for acceptable fit, demonstrating strong comparative baseline improvement.
• Tucker-Lewis Index (TLI / Non-Normed Fit Index): 0.91. Exceeds the ≥ 0.90 benchmark, confirming model parsimony.
• Standardized Root Mean Square Residual (SRMR): 0.06. Comfortably below the conservative 0.08 threshold, demonstrating low residual covariance among observed items.

Factor Loadings and Parameter Estimates

All 26 manifest indicators demonstrated strong, statistically significant factor loadings on their intended latent factors (standardized λ > 0.65, with the majority exceeding 0.75, p < 0.001). Cross-loadings across alternative factors were constrained to zero in accordance with confirmatory testing procedures. Error variances remained within theoretical boundaries, with no Heywood cases (negative error variances) or standardized parameters exceeding 1.0 observed. These CFA parameters confirm that the operational indicators reflect their underlying psychological dimensions.

Instrument / Measurement Tool

The Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory is an instrument designed for standardized survey research, behavioral experiments, and customer experience audits.

• Test Type: Original Multi-Construct Psychometric Inventory / Structured Self-Report Questionnaire.
• Theoretical Dimensionality: Six correlated first-order latent dimensions:
  • Perceived Brand Fairness: 4 manifest items.
  • Brand Identification: 7 manifest items.
  • Customer Purchases: 3 manifest items.
  • Customer Referrals: 4 manifest items.
  • Customer Influence: 4 manifest items.
  • Customer Knowledge: 4 manifest items.
• Total Item Count: 26 items.
• Response Format: Seven-point Likert-type scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”).
  • 1 = Strongly disagree
  • 2 = Disagree
  • 3 = Somewhat disagree
  • 4 = Neither agree nor disagree (Neutral)
  • 5 = Somewhat agree
  • 6 = Agree
  • 7 = Strongly agree
• Administration Format: Self-administered paper-and-pencil instrument or computer-assisted web interview (CAWI). Completion time is approximately 6 to 10 minutes.
• Scoring and Computational Procedures:
  • Subscale Scores: Computed by calculating the unweighted arithmetic mean of the items comprising each subscale. Scores range from 1.00 to 7.00 for each dimension.
  • Reverse-Scored Items: None. All 26 items are positively keyed toward their underlying construct.
  • Latent Variable Modeling: In Structural Equation Modeling (SEM) environments, constructs are modeled as latent variables with manifest indicators freely estimated and constrained to load onto their respective theoretical factors.
• Target Population: Adult consumers (ages 18 and older), with validated applications across young adult populations (ages 18–29) and individuals in their thirties (ages 30–39).
• Available Language: English (original validation language).

Permissions & Fee and Test Year

The Brand Fairness, Brand Identification, and Customer Engagement–Model Inventory was published in 2023 in the Journal of Marketing Communications (Taylor & Francis). The complete scale properties and findings are documented in the original empirical paper:

• Publication Year: 2023.
• Copyright Holder: © 2022 Informa UK Limited, trading as Taylor & Francis Group.
• Permissions Information: The scale items, empirical operationalization, and structural models are documented in the academic literature. For academic, educational, and non-commercial research purposes, measurement scales published in Taylor & Francis journals may typically be cited and utilized under standard fair-use guidelines, provided full bibliographic attribution is granted to Gligor et al. (2023). For commercial reproduction, integration into commercial diagnostic software, or corporate monetization, formal permission must be secured via Taylor & Francis or the Copyright Clearance Center (CCC) / RightsLink.
• Fee: There are no licensing or usage fees required to administer the scale for non-commercial academic research.
• Corresponding Author Inquiries: Emma Welch, Department of Marketing, University of Mississippi, Oxford, MS, United States; Email: [email protected].

References

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• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). McGraw-Hill.
• Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
• Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In W. G. Austin & S. Worchel (Eds.), The Social Psychology of Intergroup Relations (pp. 33–47). Brooks/Cole. https://psycnet.apa.org/record/1980-10497-001
• van Doorn, J., Lemon, K. N., Mittal, V., Nass, S., Pick, D., Pirner, P., & Verhoef, P. C. (2010). Customer engagement behavior: Theoretical foundations and research directions. Journal of Service Research, 13(3), 253–266. https://doi.org/10.1177/1094670510375599

Items of the Scale