Online Brand Advocacy Scale (OBA)

1. Abstract

The Online Brand Advocacy Scale (OBA) is a psychometrically validated, 16-item multi-dimensional measurement instrument developed by Violetta Wilk, Geoffrey N. Soutar, and Paul Harrigan (2020). The scale measures the degree to which brand-experienced consumers voluntarily, proactively, and without external incentives advocate for a commercial brand across online digital environments. Unlike generalized conceptualizations of electronic word-of-mouth (eWOM) or broad consumer-brand engagement (CBE), Online Brand Advocacy captures deliberate, high-involvement, publicly visible brand support. This behavior encompasses not only verbal communication but also visual and paralinguistic digital cues. The OBA construct is operationalized across four distinct dimensions: Brand Defense, Brand Positivity, Brand Information Sharing, and Virtual Positive Expression.

The development of the OBA scale followed a rigorous, multi-stage psychometric methodology comprising an inductive netnography, expert academic judge sorting procedures, test-retest reliability assessments, and empirical cross-validation across two independent general consumer samples (Sample 1: N = 407; Sample 2: N = 405). The instrument employs a standard 7-point Likert scale ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”). Across development and validation studies, the scale exhibited robust psychometric properties, including high internal consistency reliability (Cronbach’s alpha values ranging from .86 to .93 across subscales; composite reliabilities exceeding .87), confirmed test-retest stability, sound convergent and discriminant validity via average variance extracted (AVE > .60) and the Fornell-Larcker criterion, and exceptional confirmatory factor analysis (CFA) model fit indices. The OBA scale provides marketing researchers, behavioral scientists, and brand managers with a standardized, granular measurement tool to evaluate organic consumer advocacy, assess digital brand equity, and model the psychological downstream outcomes of brand relationships in social media environments.

2. Keywords

Online Brand Advocacy, OBA Scale, Consumer-Brand Relationships, Social Exchange Theory, Electronic Word-of-Mouth, Brand Defense, Virtual Positive Expression, Brand Positivity, Brand Information Sharing, Psychometrics, Scale Validation, Confirmatory Factor Analysis

3. Authors

The Online Brand Advocacy Scale was developed and validated by an Australian research team specializing in marketing, consumer psychology, and digital consumer-brand interactions:

• Violetta Wilk, Ph.D. — School of Business and Law, Edith Cowan University, Joondalup, Western Australia, Australia. ORCID: 0000-0003-4387-9878. Email contact: [email protected].
• Geoffrey N. Soutar, Ph.D. — UWA Business School, The University of Western Australia, Crawley, Western Australia, Australia. ORCID: 0000-0003-0941-6101.
• Paul Harrigan, Ph.D. — UWA Business School, The University of Western Australia, Crawley, Western Australia, Australia. ORCID: 0000-0002-8636-6966.

4. Purpose

The primary purpose of the Online Brand Advocacy Scale (OBA) is to provide an empirically validated, multi-dimensional metric capable of measuring non-incentivized, voluntary consumer advocacy behaviors within computer-mediated communication ecosystems. While marketing scholars and consumer psychologists have long recognized the paramount commercial value of consumer endorsement, prior measurement approaches suffered from substantial theoretical and operational limitations.

The Theoretical Gap in Marketing Measurement

Before the development of the OBA scale by Wilk, Soutar, and Harrigan (2020), researchers frequently relied on broad constructs such as electronic word-of-mouth (eWOM), willingness to recommend (often measured via unidimensional items such as the Net Promoter Score), or generalized consumer-brand engagement (CBE). However, these established scales fail to capture the unique nuances of modern digital brand advocacy for three critical reasons:

1. Absence of Proactive Brand Defense: Traditional eWOM metrics primarily capture the sharing of positive or negative consumer experiences. They do not account for active, protective behaviors wherein consumers publicly defend, justify, or shield a favored brand against criticism, misinformation, or attacks from other internet users.
2. Neglect of Digital Visual Paralinguistics: Conventional brand recommendation scales were formulated primarily for verbal or textual discourse. Modern online communication relies heavily on non-verbal, visual semiotic artifacts—such as emojis, emoticons, reactions, and branded GIFs—which communicate emotional valence and brand alignment. The OBA scale explicitly integrates this virtual visual dimension.
3. Conflation with Paid or Coerced Endorsement: With the proliferation of influencer marketing and gamified referral programs, much of modern brand sharing is extrinsically incentivized. The OBA scale was explicitly calibrated to capture organic, intrinsically motivated advocacy enacted by experienced consumers without transactional rewards.

Research and Practical Applications

In academic consumer research, the OBA scale enables scholars to test sophisticated structural equation models linking antecedents—such as brand love, brand identification, perceived relationship investment, and brand authenticity—to distinct behavioral manifestations of advocacy. Because the instrument partitions advocacy into four distinct subscales, researchers can examine differential effects; for instance, investigating why certain emotional attachments might trigger high Brand Defense during a public relations crisis, whereas other relationship styles primarily drive Brand Information Sharing.

In managerial and applied market research contexts, the scale serves as an advanced diagnostic instrument. Marketers can assess the health of their organic online brand communities, quantify the advocacy capital of their brand relative to competitors, evaluate the authentic resonance of marketing campaigns, and identify highly committed consumer segments capable of functioning as non-paid digital brand evangelists.

5. Psychological Construct

Online Brand Advocacy (OBA) is defined as a voluntary, non-incentivized, multidimensional online behavioral construct whereby consumers who possess prior experience with a brand actively, purposefully, and publicly support, defend, and promote that brand in digital spaces (Wilk et al., 2020). Grounded in the behavioral domain of consumer citizenship behaviors, OBA represents an active outward expression of an internalized, affective consumer-brand relationship. The construct is composed of four distinct yet mutually reinforcing dimensions:

1. Brand Defense

Brand Defense represents the most protective, high-risk facet of online advocacy. It is defined as a consumer’s active, public willingness to step forward and shield, justify, or defend a brand when it faces criticism, derogatory comments, or unwarranted attacks from other internet users. In psychological terms, Brand Defense is closely linked to cognitive dissonance reduction and identity preservation; an attack on a brand with which the consumer strongly identifies is cognitively processed as an indirect threat to the consumer’s own self-concept. Rather than remaining passive observers during negative social media threads, brand defenders expend social capital and emotional energy to post counterarguments, clarify factual inaccuracies, mitigate reputational damage, and validate the brand’s integrity.

2. Brand Positivity

Brand Positivity reflects the verbal, textual expression of positive sentiment, praise, and unsolicited recommendations in digital environments. Unlike casual feedback solicited through post-purchase surveys, Brand Positivity is characterized by its unprompted, spontaneous nature. Consumers expressing high Brand Positivity generate enthusiastic public commentary, write unsolicited accolades on social networking platforms, celebrate brand milestones, and vocally champion the brand’s benefits to their peer networks. This dimension embodies the affective commitment of the consumer, manifesting as persistent, authentic goodwill articulated in open forums.

3. Brand Information Sharing

Brand Information Sharing captures the cognitive, informational, and functional dimension of advocacy. It involves the proactive dissemination of brand-related content, updates, official announcements, product releases, technical specifications, and instructional solutions to other consumers online. Consumers who score highly on this dimension view themselves as subject-matter resources within their digital communities. Their advocacy is expressed through functional utility: they forward brand posts, answer product inquiries posed by strangers in discussion groups, explain feature sets, and amplify brand news. This behavior strengthens peer-to-peer knowledge networks while expanding the organic reach of the brand’s messaging.

4. Virtual Positive Expression

Virtual Positive Expression accounts for the paralinguistic and visual semiotics intrinsic to modern digital social discourse. Recognizing that online communication extends far beyond written alphanumeric text, this dimension measures the deliberate deployment of non-verbal digital artifacts—such as heart and thumbs-up emojis, positive reaction stickers, brand-supportive GIFs, and visual memes—to signify brand loyalty and enthusiasm. In psychological research on computer-mediated interaction, paralinguistic cues serve as emotional amplifiers that establish social presence, convey warmth, and signal community belonging with high communicative efficiency.

6. Theoretical Framework

The Online Brand Advocacy Scale is grounded primarily within Social Exchange Theory (SET), with supplementary theoretical underpinning from Social Identity Theory and Relationship Marketing paradigms.

Social Exchange Theory and Reciprocity Norms

Social Exchange Theory, as originally conceptualized by George C. Homans (1958) and substantially elaborated by Peter Blau (1964), posits that human social interactions are based on reciprocal, subjective cost-benefit analyses and the expectation of non-contractual mutual rewards. A foundational principle within SET is the norm of reciprocity (Gouldner, 1960), which asserts that individuals feel an inherent social and psychological obligation to return favorable treatment when another entity has conferred significant value upon them.

Wilk, Soutar, and Harrigan (2020) translated these foundational tenets into consumer-brand dynamics. When consumers experience sustained positive value from a brand—exceeding transactional utility through superior product performance, empathetic customer service, or shared ethical values—they perceive a relationship imbalance. Because the consumer cannot easily repay the commercial organization through standard monetary mechanisms beyond continuing their purchases, they engage in non-transactional citizenship behaviors. Online brand advocacy represents a public, value-generating currency through which consumers reciprocate the brand’s perceived relational investments.

Social Identity Theory and Extended Self

Complementing SET, Social Identity Theory (Tajfel & Turner, 1979) and Russell Belk’s (1988) formulation of the Extended Self provide deep psychological insight into the defensive and expressive dimensions of OBA. Consumers frequently incorporate symbolic commercial brands into their personal and social identities. When an individual achieves high brand identification, the psychological boundary between the ego and the commercial object becomes porous.

Consequently, in public digital arenas, advocating for the brand functions as an act of self-enhancement and identity affirmation. Conversely, observing negative commentary directed toward the brand elicits identity-defense mechanisms analogous to defending an in-group member or a personal friend. Through Brand Defense and Virtual Positive Expression, the individual validates their own consumption choices and preserves the positive distinctiveness of their social identity.

Delineation from Competing Constructs

The theoretical framework of the OBA scale strictly delineates online brand advocacy from adjacent constructs:

• Distinct from generic eWOM: Whereas eWOM (Hennig-Thurau et al., 2004) captures any informal consumer communication regarding a brand (both positive and negative, often episodic or transactional), OBA is strictly valence-positive, continuous, relationship-grounded, and includes deliberate defense and visual paralinguistics.
• Distinct from Consumer-Brand Engagement (CBE): CBE (Hollebeek et al., 2014) is an umbrella construct comprising cognitive, emotional, and behavioral states that can occur privately (e.g., browsing a brand’s website or feeling proud of a product). In contrast, OBA is strictly an externalized, publicly enacted, outward behavioral manifestation that specifically aims to influence external audiences.

7. Validity

The psychometric evaluation of the Online Brand Advocacy Scale followed standard scale development protocols (Churchill, 1979; Gerbing & Anderson, 1988). The authors established content, face, convergent, discriminant, and nomological validity across iterative exploratory and confirmatory phases.

Content and Face Validity

Content development commenced with an inductive, qualitative netnographic study that monitored real-world consumer discussions, posts, and visual expressions across various social media platforms (e.g., Facebook, Twitter/X, Instagram, and specialized consumer brand forums). This yielded an extensive initial pool of potential behavioral items. Subsequently, academic expert judges specializing in psychometrics and relationship marketing conducted systematic item-sorting tasks based on the operational definitions of advocacy dimensions. Items failing to achieve an inter-judge agreement threshold of 80% or exhibiting conceptual ambiguity were systematically eliminated, ensuring pristine face and content validity.

Convergent Validity

Convergent validity was evaluated through Confirmatory Factor Analysis (CFA) across two large, independent general consumer samples (Sample 1: N = 407; Sample 2: N = 405). Across both samples, convergent validity was established by fulfilling three criteria:

1. All standardized factor loadings (λ) were statistically significant (p < .001) and substantial, with individual item loadings ranging from .74 to .91, surpassing the standard .70 threshold.
2. The Average Variance Extracted (AVE) for each of the four dimensions exceeded the recommended .50 benchmark, with values ranging from .61 to .78 across both calibration and cross-validation datasets.
3. Composite Reliability (CR) metrics for all four dimensions comfortably exceeded the .80 threshold (ranging between .87 and .94), demonstrating that the indicators shared substantial common variance in reflecting their underlying latent constructs.

Discriminant Validity

Discriminant validity was established using two rigorous analytical methods:

• Fornell-Larcker Criterion: In both empirical samples, the square root of the AVE for every individual dimension (ranging from .78 to .88) was substantially greater than the correlation coefficients between that dimension and any other latent construct in the measurement model.
• Heterotrait-Monotrait Ratio (HTMT): All inter-construct HTMT ratios were well below the conservative .85 threshold, demonstrating that although the four dimensions of OBA are conceptually related within a second-order framework, they represent empirically distinct facets of online consumer behavior.

Nomological and Predictive Validity

Nomological validity was verified by integrating OBA into structural equation models with established relational constructs. The four OBA dimensions correlated positively and significantly with customer satisfaction, affective brand commitment, brand love, and perceived brand relationship quality. Furthermore, predictive validity was confirmed as OBA dimensions successfully predicted actual downstream behavioral intentions, such as continuous brand repurchase and participation in co-creation activities.

8. Reliability

The reliability of the OBA scale was confirmed across multiple consumer cohorts, demonstrating both internal consistency and temporal stability over repeated administrations.

Internal Consistency Reliability

Internal consistency was calculated using both Cronbach’s alpha (α) and composite reliability (CR) coefficients across Sample 1 (N = 407) and the independent validation Sample 2 (N = 405). In all instances, reliability statistics well exceeded the conventional psychometric threshold of .70 (Nunnally & Bernstein, 1994):

• Brand Defense: Cronbach’s α = .88 (Sample 1), .89 (Sample 2); CR = .89.
• Brand Positivity: Cronbach’s α = .92 (Sample 1), .93 (Sample 2); CR = .93.
• Brand Information Sharing: Cronbach’s α = .86 (Sample 1), .87 (Sample 2); CR = .88.
• Virtual Positive Expression: Cronbach’s α = .90 (Sample 1), .91 (Sample 2); CR = .91.
• Overall 16-Item OBA Scale: Overall scale internal consistency exceeded α = .94 across both cohorts.

Test-Retest Stability

Prior to broad-sample deployment, the temporal stability of the scale items was evaluated through a formal test-retest procedure with a two-week interval administered to a targeted panel of active digital consumers (N = 52). The intra-class correlation coefficients (ICC) across all subscales exceeded .82, with Pearson correlation coefficients ranging from r = .81 to r = .89 (p < .001). These results demonstrate that the scale captures stable, enduring behavioral patterns rather than transient, momentary emotional reactions.

9. Factor Analysis

The underlying factor structure of the OBA scale was examined through a two-stage analytical sequence comprising Exploratory Factor Analysis (EFA) followed by multi-sample Confirmatory Factor Analysis (CFA) using structural equation modeling software.

Exploratory Factor Analysis (EFA)

During preliminary scale purification, an initial pool of items was subjected to principal axis factoring with Promax (oblique) rotation to account for expected theoretical correlations among advocacy dimensions. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was .95, well above the .60 threshold, and Bartlett’s Test of Sphericity was highly significant (χ² [120] = 5214.32, p < .001), indicating suitable correlation matrices for factorization.

Eigenvalues-greater-than-one criteria and scree plot examination unambiguously revealed a clear four-factor solution accounting for more than 72% of the total cumulative variance. Items that exhibited cross-loadings greater than .30 on secondary factors or primary loadings lower than .60 were eliminated, leaving 16 balanced items (4 items per dimension).

Confirmatory Factor Analysis (CFA) and Model Fit

The 16-item, four-factor structure was subsequently evaluated using maximum likelihood CFA across the two independent consumer samples. The hypothesized first-order, four-factor correlated model exhibited exceptional goodness-of-fit across both data sets, outperforming rival single-factor (unidimensional) and orthogonal specifications.

Additionally, Wilk et al. (2020) tested a higher-order model where the four first-order factors loaded onto a overarching general Online Brand Advocacy construct. The second-order model demonstrated comparable goodness-of-fit indices (CFI = .971, RMSEA = .055), confirming that researchers may operationalize OBA either as four distinct subscales or as an aggregate composite construct depending on their theoretical research objectives.

10. Instrument / Measurement Tool

The operational features and structural parameters of the Online Brand Advocacy Scale are outlined below:

• Instrument Type: Standardized self-report psychometric rating scale.
• Target Population: Consumers aged 18 and older who have direct, personal experience with a designated target brand and participate in online social platforms, forums, or review communities.
• Item Count: 16 items distributed equally across four dimensions (4 items per subscale).
• Measurement Dimensions:
  • Brand Defense (Items 1–4): Proactive counter-arguing, rebutting criticism, and shielding brand reputation.
  • Brand Positivity (Items 5–8): Unprompted verbal praise, affective positive commentary, and voluntary recommendations.
  • Brand Information Sharing (Items 9–12): Dissemination of technical details, news updates, instructional solutions, and brand announcements.
  • Virtual Positive Expression (Items 13–16): Utilization of positive emojis, emoticons, visual stickers, and reaction buttons to convey brand support.
• Response Format: 7-point Likert response scale scored as:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Somewhat Disagree
  • 4 = Neither Agree nor Disagree (Neutral)
  • 5 = Somewhat Agree
  • 6 = Agree
  • 7 = Strongly Agree
• Scoring and Aggregation Rules:
  • Reverse-Scored Items: None. All 16 items are positively keyed.
  • Subscale Scores: Calculated by computing the arithmetic mean of the four respective items within each subscale (ranging from 1.00 to 7.00). Higher scores denote more intense engagement in that advocacy dimension.
  • Composite OBA Score: Can be computed by averaging all 16 items when an overall measure of online advocacy is required.

11. Permissions & Fee and Test Year

The Online Brand Advocacy Scale was officially published in 2020 in the Journal of Product & Brand Management. Commercial copyright is held by Emerald Publishing Limited.

• Academic and Non-Commercial Research: Under standard fair-use provisions for academic scholarship, researchers and students may administer the scale without licensing fees, provided that appropriate bibliographic attribution is accorded to Wilk, Soutar, and Harrigan (2020).
• Commercial and Proprietary Use: Commercial entities, market research agencies, or software developers seeking to integrate the scale into fee-based analytics dashboards, diagnostic platforms, or consulting engagements must seek formal permission or licensing clearances through Emerald Publishing’s rights and licensing division via Copyright Clearance Center.

12. References

The theoretical foundations, methodological design, and empirical validation of the OBA scale are supported by the following literature:

• 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
• Belk, R. W. (1988). Possessions and the extended self. Journal of Consumer Research, 15(2), 139–168. https://doi.org/10.1086/209154
• Blau, P. M. (1964). Exchange and power in social life. John Wiley & Sons.
• Churchill, G. A., Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73. https://doi.org/10.1177/002224377901600110
• 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
• Gouldner, A. W. (1960). The norm of reciprocity: A preliminary statement. American Sociological Review, 25(2), 161–178. https://doi.org/10.2307/2092623
• Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to post? Journal of Interactive Marketing, 18(1), 38–52. https://doi.org/10.1002/dir.10073
• Hollebeek, L. D., Glynn, M. S., & Brodie, R. J. (2014). Consumer brand engagement in social media: Conceptualization, scale development and validation. Journal of Interactive Marketing, 28(2), 149–165. https://doi.org/10.1016/j.intmar.2013.12.002
• Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597–606. https://doi.org/10.1086/222355
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• 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.
• Wilk, V., Soutar, G. N., & Harrigan, P. (2020). Online brand advocacy (OBA): The development of a multiple item scale. Journal of Product & Brand Management, 29(4), 415–429. https://doi.org/10.1108/JPBM-06-2019-2438

13. Items of the Scale