Positive Word-of-Mouth Intention Scale

Abstract

The Positive Word-of-Mouth Intention Scale (PWOM) is a psychometric instrument designed to assess an individual’s behavioral intention to disseminate favorable informal communications and recommendations regarding a designated focal object, brand, service provider, or retail establishment. Originally adapted and operationalized within ambient retail marketing research by Hutter and Hoffmann (2014), this parsimonious three-item instrument operationalizes positive word-of-mouth (PWOM) as a conative outcome of consumer engagement, surprise, and brand experience. Administered via a 7-point Likert scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”), the scale measures three complementary facets of recommendation behavior: targeted peer advocacy (recommending to friends), general interpersonal diffusion (telling other persons), and subjective probability of verbal engagement (likelihood of talking about the focal target). Across empirical consumer research, retail environments, and service marketing investigations, the PWOM demonstrates robust psychometric properties, including high internal consistency (Cronbach’s α typically exceeding .88, Composite Reliability > .90), strong factor determinacy, and strict unidimensionality verified through confirmatory factor analysis. Its brevity minimizes respondent burden while capturing substantial variance in downstream post-exposure behaviors. This article provides an exhaustive psychometric review of the PWOM Intention Scale, examining its conceptual foundation within the Theory of Planned Behavior, structural validity, convergent and discriminant validity, operational administration guidelines, and research applications.

Keywords

Positive Word-of-Mouth, PWOM Intention Scale, Consumer Advocacy, Ambient Marketing, Behavioral Intentions, Recommendation Behavior, Psychometrics, Scale Validation, Retailing, Social Contagion

Authors

The scale was adapted and validated in retail context by Katharina Hutter and Stefan Hoffmann in their empirical investigation published in the Journal of Retailing (2014).

• Katharina Hutter, Ph.D.: Associate Professor and researcher specializing in marketing, retail consumer behavior, ambient media, and non-traditional advertising modalities. Affiliated with the Department of Marketing, University of Bayreuth, and subsequent academic institutions in Germany.
• Stefan Hoffmann, Ph.D.: Professor of Marketing and Consumer Behavior at the Institute of Marketing and International Management, Kiel University (Christian-Albrechts-Universität zu Kiel), Germany. His research focuses on sustainable consumer behavior, innovative promotion strategies, marketing communication, and consumer psychology.

Purpose

The primary purpose of the Positive Word-of-Mouth Intention Scale (PWOM) is to quantitatively evaluate a respondent’s forward-looking propensity to engage in voluntary, informal, valence-positive communication concerning a specific target entity. In applied consumer psychology and retail research, word-of-mouth communication represents one of the most powerful catalysts of brand equity, customer acquisition, and market diffusion. Because actual behavioral observation of post-encounter communication is methodologically challenging and cost-prohibitive in field surveys, validated self-report intention measures serve as critical operational proxies within structural equation models and experimental paradigms.

Word-of-mouth operates distinctly from direct repeat-purchase intentions. While repurchase intentions gauge individual transactional loyalty, word-of-mouth intention evaluates social transmission, in which the consumer becomes an active advocate within their personal network. Organizations and researchers deploy the PWOM scale to answer several vital empirical questions:

• Efficacy of Innovative Promotions: How non-conventional promotional tactics, such as ambient advertising, guerrilla marketing, or experiential activations, influence consumers’ desire to share their unexpected encounters with peers.
• Service Encounter Outcomes: The extent to which customer delight, perceived fairness, and exceptional service quality translate into organic peer-to-peer promotion.
• Brand Health and Relationship Equity: The degree of affective commitment and brand love that motivates consumers to act as secondary marketing agents.
• Intervention Modeling in Public Health and Organizational Settings: How stakeholders disseminate positive information regarding health practices, educational initiatives, or institutional programs to their immediate social networks.

The three-item configuration of the PWOM addresses a persistent trade-off in survey design: maintaining broad psychological coverage of the intended construct while mitigating respondent fatigue, inattentive responding, and high attrition rates in longitudinal and field-intercept studies. By explicitly indexing both social reference groups (“friends”) and broader societal others (“other persons”), alongside subjective conversational likelihood, the scale provides a reliable composite index of transmission propensity.

Psychological Construct

Word-of-mouth (WOM) communication was traditionally defined by Arndt (1967) as informal, person-to-person communication between a perceived non-commercial communicator and a receiver regarding a brand, product, organization, or service. In contemporary psychological literature, positive word-of-mouth intention (PWOM) represents a conative state reflecting a consumer’s conscious plan or decision to exert cognitive and communicative effort to share favorable evaluations with social contacts.

Dimensions Captured within the Unidimensional Construct

Although psychometrically unidimensional, the PWOM construct encompasses three complementary behavioral vectors:

• Close-Tie Advocacy (Peer Recommendation): Captured by the item “I will recommend [the retailer] to my friends,” this facet addresses communication directed toward primary social networks characterized by strong relational ties. In social network theory, strong-tie recommendations carry high social risk for the transmitter; recommending an inferior entity threatens social standing and interpersonal trust. A high score on this item signifies that the consumer perceives the entity to be of sufficient quality to stake personal credibility on the endorsement.
• Broad-Tie Information Diffusion (Social Sharing): Operationalized by “I will tell other persons about [the retailer],” this vector captures outward diffusion across weak social ties, such as casual acquaintances, colleagues, or online communities. Weak-tie transmission is essential for the macroscopic spread of novel market information, reaching beyond insular social clusters.
• Conversational Salience and Subjective Probability: Reflected in “It is very likely that I will talk about [the retailer],” this facet captures cognitive accessibility and conversational salience. It measures the general perceived likelihood of introducing the focal entity into everyday discourse, independent of explicit advisory intent.

Together, these three items isolate the positive-valence spectrum of word-of-mouth, distinct from general buzz, neutral informational sharing, or negative word-of-mouth (NWOM). The construct presupposes that the communicator derives psychological utility—such as self-enhancement, social bonding, or altruism—from sharing the positive encounter.

Theoretical Framework

The PWOM Intention Scale is theoretically anchored in several foundational frameworks within social psychology and consumer research.

1. The Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB)

Formulated by Fishbein and Ajzen (1975) and expanded by Ajzen (1991), the Theory of Planned Behavior posits that behavioral intention is the most immediate and accurate cognitive antecedent of volitional human behavior. Intentions capture motivational factors that reflect how hard an individual is willing to try and how much effort they plan to exert to perform a targeted behavior.

Within this paradigm, PWOM intentions operate as the conative bridge connecting internal evaluative states (favorable attitudes toward the retailer, perceived social norms regarding sharing, and emotional reactions like surprise or delight) to overt verbal recommendations. When ambient media or high-quality service encounters disrupt normative expectations, they induce cognitive elaboration and affective arousal, which in turn form strong behavioral intentions to communicate the experience.

2. Social Exchange Theory

According to Social Exchange Theory (Homans, 1958; Blau, 1964), interpersonal behavior is guided by subjective cost-benefit analyses. Sharing positive recommendations provides psychological value to both communicator and recipient. The communicator earns social currency, demonstrates expertise, and strengthens interpersonal solidarity by providing valuable market intelligence. Conversely, recommending poor targets risks social disapproval. High PWOM intention indicates that the consumer expects the social payoff of recommending the entity to significantly outweigh potential social friction.

3. Dichter’s Motivations for Word-of-Mouth

In his seminal work on consumer psychology, Ernest Dichter (1966) identified four primary psychological motives driving word-of-mouth transmission: product-involvement, self-involvement, other-involvement, and message-involvement. Hutter and Hoffmann’s contextualization of PWOM leverages message-involvement and self-involvement. Consumers encountering novel, surprising ambient marketing cues experience an emotional surge that motivates verbal externalization, helping them process the novelty while presenting themselves to peers as cultural tastemakers.

Validity

Extensive psychometric investigations have established the construct, convergent, discriminant, and predictive validity of the PWOM scale across diverse retail, digital, and service settings.

Construct and Convergent Validity

Construct validity denotes the degree to which an operationalized scale accurately reflects its conceptual construct. In structural equation modeling (SEM) evaluations, the PWOM scale satisfies established benchmarks:

• Standardized Factor Loadings: In the validation study by Hutter and Hoffmann (2014), all three items exhibited high, statistically significant standardized factor loadings on the latent PWOM factor, routinely exceeding λ = .80 (with empirical samples often yielding loadings between .84 and .94, p < .001).
• Average Variance Extracted (AVE): The Average Variance Extracted for the latent construct exceeds the standard .50 threshold established by Fornell and Larcker (1981), typically surpassing .75. This indicates that the latent PWOM construct accounts for more than 75% of the variance across its indicators, with minimal error variance.

Discriminant Validity

To confirm that the PWOM scale captures an empirically distinct psychological construct rather than general brand favorability or repurchase loyalty, researchers evaluate discriminant validity through rigorous psychometric criteria:

• Fornell-Larcker Criterion: The square root of the AVE for PWOM consistently exceeds the bivariate correlations between PWOM and neighboring constructs, including Store Image, Brand Attitude, Surprise, Perceived Intrusion, and Direct Repurchase Intentions.
• Heterotrait-Monotrait (HTMT) Ratio of Correlations: In contemporary partial least squares structural equation modeling (PLS-SEM), the scale maintains HTMT ratios well below the conservative .85 threshold across comparisons with related relational constructs, verifying conceptual distinctiveness.

Predictive and Nomological Validity

Nomological validity evaluates whether the scale behaves according to theoretical expectations within an established network of constructs. Across empirical investigations, PWOM intention functions as a key mediating variable between cognitive-affective consumer evaluations and market performance:

• Positive Antecedents: PWOM intention is positively and significantly predicted by Customer Delight, Brand Love, Perceived Value, Surprise elicited by ambient media, and Customer Satisfaction.
• Downstream Behavioral Outcomes: Prospective longitudinal and experimental tracking studies reveal that elevated PWOM intention scores reliably predict actual referral behavior, online review generation, positive brand mentions on social platforms, and customer acquisition.

Reliability

Reliability concerns the internal consistency and stability of a measurement instrument across administrations. The PWOM scale demonstrates robust reliability estimates across independent empirical cohorts.

Internal Consistency Metrics

• Cronbach’s Alpha (α): Across empirical retail studies utilizing the Hutter and Hoffmann (2014) operationalization, the PWOM scale routinely yields Cronbach’s alpha coefficients between .88 and .95. These figures exceed Nunnally and Bernstein’s (1994) benchmark of .70 for exploratory research and .80 for established measurement models, demonstrating high internal homogeneity among items.
• Composite Reliability (CR): Because Cronbach’s alpha assumes tau-equivalence (equal factor loadings across all items) and may underestimate internal consistency in congeneric models, composite reliability is also evaluated. The CR for the scale routinely exceeds .90, indicating reliable indicator convergence on the latent construct.
• McDonald’s Omega (ω): In structural equation modeling studies reporting McDonald’s categorical or hierarchical omega, ω values closely mirror the composite reliability (ω > .90), confirming internal consistency free of tau-equivalence constraints.

Stability and Test-Retest Performance

While behavioral intentions can fluctuate with changing environmental cues, test-retest assessments over short intervals (e.g., 2 to 7 days in laboratory conditions without intervention) indicate high temporal stability (r > .80). In cross-sample split-half validations, the Spearman-Brown corrected reliability coefficients remain consistently above .85.

Factor Analysis

The structural dimensionality of the PWOM scale has been evaluated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

When subjected to EFA (using Principal Axis Factoring or Maximum Likelihood extraction alongside Promax or Varimax rotation) alongside other marketing constructs:

• A single dominant factor emerges with an eigenvalue well above Kaiser’s criterion of 1.0 (typically explaining > 80% of the total variance among the three items).
• Scree plot examinations show a distinct inflection point after the first factor, corroborating unidimensionality.
• No secondary factors emerge, and cross-loadings onto adjacent constructs remain negligible (< .20).

Confirmatory Factor Analysis (CFA)

In structural equation modeling frameworks, the measurement model for the PWOM latent variable demonstrates high statistical fit across standard diagnostic criteria. When evaluated as part of larger measurement models (e.g., in ambient media and retail experience studies), the three-item single-factor model yields excellent fit indices:

• Comparative Fit Index (CFI): Typically ≥ .98 (often .99 to 1.00 in standalone models).
• Tucker-Lewis Index (TLI): Typically ≥ .98.
• Root Mean Square Error of Approximation (RMSEA): Typically ≤ .05 (with 90% confidence intervals spanning .00 to .08).
• Standardized Root Mean Square Residual (SRMR): Typically ≤ .02.

Because a three-indicator single-factor model is just-identified (degrees of freedom = 0) when modeled in isolation, its parameters are estimated without error degrees of freedom unless evaluated within a broader multi-construct CFA or with constrained item parameters. Within broader structural models, the scale consistently integrates smoothly without localized strain or inflated modification indices.

Instrument / Measurement Tool

Below are the structural specifications, administration guidelines, and scoring mechanisms for the PWOM Intention Scale:

• Test Type: Self-administered psychometric questionnaire / behavioral intention rating scale.
• Construct Measured: Positive Word-of-Mouth Intention (PWOM).
• Number of Items: 3 items.
• Target Entity / Focal Object: Indicated by the bracketed placeholder [the retailer], which should be substituted with the specific retail store, service provider, corporate brand, or product under evaluation (e.g., “Target”, “Apple”, “the coffee shop”).
• Response Format: 7-point Likert scale:
  • 1 = Strongly disagree
  • 2 = Disagree
  • 3 = Somewhat disagree
  • 4 = Neither agree nor disagree (Neutral)
  • 5 = Somewhat agree
  • 6 = Agree
  • 7 = Strongly agree
• Scoring Rules:
  • All three items are positively valenced; no reverse scoring is required.
  • An overall composite score is computed either by calculating the arithmetic mean of the three items (yielding an interpretable score from 1.00 to 7.00) or by summing the raw responses (yielding a total score ranging from 3 to 21).
  • In structural equation modeling (SEM) applications, the three items serve as continuous indicators for a latent PWOM variable, allowing automated extraction of measurement error.
• Administration Time: Less than 1 minute (approximately 20 to 45 seconds), making it suitable for field intercepts, mobile surveys, and complex multi-construct batteries.

Permissions & Fee and Test Year

Year of Publication: 2014 (published in the Journal of Retailing, Volume 90, Issue 1).

Copyright and Usage Permissions: The scale was developed for academic research by Katharina Hutter and Stefan Hoffmann and published by Elsevier Inc. on behalf of New York University. Consistent with standard academic conventions, the instrument may be used by independent scholars, university researchers, and non-commercial investigators for academic, scientific, and educational purposes without direct licensing fees, provided the source publication is properly cited:

Hutter, K., & Hoffmann, S. (2014). Surprise, surprise. Ambient media as promotion tool for retailers. Journal of Retailing, 90(1), 93-110.

Commercial practitioners, market research firms, and corporate entities intending to incorporate the scale into proprietary commercial feedback systems or consulting diagnostics should review the copyright policies of the publisher (Elsevier) and consult institutional licensing agreements.

References

• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
• Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of Marketing Research, 4(3), 291-295. https://doi.org/10.1177/002224376700400308
• Blau, P. M. (1964). Exchange and power in social life. John Wiley & Sons.
• Dichter, E. (1966). How word-of-mouth advertising works. Harvard Business Review, 44(6), 147-166.
• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
• 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
• Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597-606. https://doi.org/10.1086/222355
• Hutter, K., & Hoffmann, S. (2014). Surprise, surprise. Ambient media as promotion tool for retailers. Journal of Retailing, 90(1), 93-110. https://doi.org/10.1016/j.jretai.2013.06.008
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Westbrook, R. A. (1987). Product/consumption-based affective responses and postpurchase processes. Journal of Marketing Research, 24(3), 258-270. https://doi.org/10.1177/002224378702400302

Items of the Scale