Attitude Toward Word-of-Mouth (On-line) (ATWOM)

1. Abstract

The Attitude Toward Word-of-Mouth (On-line) (ATWOM) scale is a psychometric instrument designed to assess a consumer’s generalized cognitive, affective, and behavioral disposition toward online peer evaluations, consumer reviews, and electronic word-of-mouth (eWOM). Developed by Adwait Khare, Lauren I. Labrecque, and Anthony K. Asare (2011) in their foundational work on the assimilative and contrastive dynamics of review volume in the Journal of Retailing, the instrument addresses a critical gap in digital consumer psychology. While earlier marketing instruments assessed interpersonal susceptibility to face-to-face influence or generic website usability, the ATWOM scale specifically isolates how individuals perceive, trust, enjoy, and habituate the consumption and dissemination of peer-generated product feedback across digital retail platforms.

Comprising six items calibrated across a seven-point Likert-type response format, the ATWOM scale measures four key experiential facets: perceived comfort with navigating and reading digital reviews, behavioral reliance on reviews during pre-purchase decision deliberation, hedonic enjoyment derived from exchanging consumption narratives, and overarching normative beliefs regarding the collective utility of crowd-sourced consumer intelligence. Psychometric evaluations demonstrate that the instrument functions as an internally consistent, unidimensional construct exhibiting high reliability (Cronbach’s alpha typically ranging between α = .88 and α = .91 across empirical samples). Confirmatory factor analyses confirm robust structural validity, with standardized factor loadings routinely exceeding .70 and average variance extracted (AVE) values surpassing the conventional threshold of .50. The scale displays strong convergent, discriminant, and predictive validity, functioning reliably as both an independent predictor and an essential moderating variable in empirical investigations examining how review valence, volume, and consumer information processing interact to guide purchase intention and brand attitudes.

2. Keywords

Attitude Toward Word-of-Mouth, ATWOM, electronic word-of-mouth, eWOM, online consumer reviews, psychometrics, consumer information processing, decision-making, social proof, consumer skepticism.

3. Authors

The Attitude Toward Word-of-Mouth (On-line) (ATWOM) scale was formulated and validated by an academic team of marketing and consumer behavior scholars:

• Adwait Khare, Ph.D. — Associate Professor of Marketing, Department of Marketing, College of Business, The University of Texas at Arlington, Arlington, TX, United States. Primary research specializations: consumer judgment and decision-making, behavioral pricing, numerical cognition, and the cognitive heuristics underpinning digital review interpretation.
• Lauren I. Labrecque, Ph.D. — Professor of Marketing, Department of Marketing, College of Business, University of Rhode Island, Kingston, RI, United States (formerly affiliated with Loyola University Chicago and Northern Illinois University). Primary research specializations: digital marketing, consumer power dynamics, interactive media, algorithmic branding, and online social interactions.
• Anthony K. Asare, Ph.D. — Professor of Marketing, School of Business, Quinnipiac University, Hamden, CT, United States. Primary research specializations: marketing strategy, business-to-business relationship dynamics, electronic consumer channels, and organizational information dissemination.

4. Purpose

The emergence of participatory digital environments, online marketplaces (such as Amazon and eBay), and independent aggregator ecosystems (such as Yelp and TripAdvisor) fundamentally decentralized marketing communications. Historically, consumer decisions were guided by marketer-generated communications, such as traditional advertising and public relations, complemented by localized word-of-mouth from immediate acquaintances. The advent of electronic word-of-mouth (eWOM) transformed consumer choice architectures by granting shoppers immediate access to voluminous product appraisals generated by anonymous peers. However, consumers do not respond uniformly to crowd-sourced feedback. While some individuals treat online reviews as highly diagnostic, objective, and reassuring, others view them with deep skepticism, cognitive fatigue, or indifference.

To quantify these individual differences, Khare, Labrecque, and Asare (2011) developed the ATWOM scale to serve as a standardized, psychometrically validated tool for measuring an individual’s baseline dispositional orientation toward digital peer feedback. The primary purpose of the ATWOM instrument is to quantify the degree to which an individual approaches eWOM with openness, reliance, and subjective value, versus cognitive avoidance and cynicism. Rather than measuring a situational evaluation of a specific product review or an isolated retail vendor, the ATWOM scale captures an enduring psychological orientation.

In empirical research, the scale serves critical theoretical and methodological functions:

• Moderation of Heuristic versus Systematic Processing: The ATWOM scale is used to explain why consumers exposed to identical review configurations (such as variations in review volume, variance, or star-rating extremity) arrive at divergent evaluative outcomes. Consumers exhibiting elevated ATWOM scores tend to interpret review volume as a strong indicator of social consensus and product reliability, triggering assimilative evaluative shifts. Conversely, individuals scoring low on ATWOM often process the same metrics through a lens of skepticism, resulting in contrastive cognitive responses.
• Market Segmentation and Behavioral Profiling: In applied marketing research, the instrument assists firms in segmenting audiences based on review receptivity. Understanding a segment’s ATWOM profile allows commercial organizations to tailor the prominence of user reviews on e-commerce product detail pages.
• Control of Individual Differences in Experimental Designs: Laboratory studies in consumer psychology frequently deploy the ATWOM scale as a covariate or screening tool to isolate experimental effects from participants’ pre-existing habits and beliefs concerning digital user feedback.

5. Psychological Construct

The psychological construct captured by the ATWOM scale is a multifaceted yet unidimensional disposition that unifies affective, cognitive, and behavioral dimensions into an integrated evaluative stance toward digital peer discourse. In classical social psychology, attitudes are conceptualized as overall evaluations that integrate cognitive appraisals, affective responses, and behavioral intentions (Eagly & Chaiken, 1993). The ATWOM construct maps directly onto these theoretical components within the domain of computer-mediated peer communications:

Cognitive Dimension (Perceived Diagnosticity and Utility)

The cognitive facet reflects the consumer’s belief structure regarding the informational value, veracity, and functional utility of online reviews. Individuals scoring high in this dimension evaluate online word-of-mouth as an essential source of objective data that reduces information asymmetry between purchasers and commercial vendors. They hold the firm belief that the collective knowledge of past buyers clarifies non-contractible product attributes (such as fabric feel, durability, or usability) more effectively than commercial specifications. Conversely, consumers with a negative cognitive appraisal question the authenticity of crowd-sourced feedback, suspecting fraudulent practices such as review manipulation or promotional astroturfing.

Affective Dimension (Comfort and Enjoyment)

The affective dimension reflects the emotional comfort and subjective pleasure experienced when engaging with peer reviews. High ATWOM consumers report feeling at ease while reading community comments; they view the process as engaging and informative rather than overwhelming or frustrating. This dimension also captures a degree of hedonic enjoyment: these consumers often browse product narratives and community dialogues as a leisure activity or a form of social voyeurism, taking satisfaction in vicariously experiencing how fellow consumers navigate market offerings.

Behavioral and Habitual Dimension (Past Reliance and Active Usage)

Attitudes both stem from and drive recurrent behaviors. The behavioral component of the ATWOM construct captures the extent to which consulting online reviews has become an automatic, standard routine in the individual’s pre-purchase evaluation process. High-scoring individuals systematically consult customer feedback prior to finalizing a purchase, rarely committing financial resources to unfamiliar brands without cross-referencing user ratings. Furthermore, this dimension reflects an inclination to participate in the feedback loop by contributing reviews, thereby reinforcing the consumer’s identity as an active participant in digital community governance.

Normative Dimension (Belief in Collective Empowerment)

Underpinning the ATWOM construct is a normative belief regarding consumer democracy. This facet reflects an ideological conviction that digital word-of-mouth empowers the buying public, redistributes market authority away from corporate gatekeepers, and promotes accountability. A consumer with high ATWOM views user reviews not merely as a convenient shopping aid, but as a valuable civic and economic asset that protects consumer interests.

6. Theoretical Framework

The conceptual architecture of the ATWOM scale integrates several complementary theoretical frameworks from social psychology, communication theory, and cognitive consumer research:

The Accessibility-Diagnosticity Model

Formulated by Feldman and Lynch (1988), the Accessibility-Diagnosticity Model posits that the likelihood an item of information is used to form a judgment depends on its cognitive accessibility relative to competing inputs, as well as its perceived diagnosticity—the degree to which the information helps discriminate between competing hypotheses or product alternatives. In digital shopping environments, review volume and average ratings are highly accessible heuristics. However, an individual will only integrate this accessible data into their product evaluations if they perceive it to be diagnostic. The ATWOM construct operationalizes a consumer’s chronic predisposition to treat online word-of-mouth as diagnostic. For a consumer possessing high ATWOM, peer reviews provide clear, trustworthy guidance, making them the primary anchor for product evaluations.

Dual-Process Theories of Information Processing

The Elaboration Likelihood Model (ELM) (Petty & Cacioppo, 1986) and the Heuristic-Systematic Model (Chaiken, 1980) provide key theoretical insights into how ATWOM governs cognitive effort. When consumers encounter electronic word-of-mouth, they can evaluate it through systematic elaboration (such as critically analyzing the substantive arguments, logical coherence, and technical detail within specific review texts) or through heuristic processing (such as using the overall number of reviews or aggregate star ratings as simple cues for product quality). Khare, Labrecque, and Asare (2011) demonstrated that an individual’s ATWOM score acts as a psychological lens directing these processing routes:

• Assimilation Dynamics: Consumers with high ATWOM tend to rely on heuristic cues such as review volume. When volume is high, they infer widespread peer endorsement, which pulls their product evaluations upward (an assimilative effect).
• Contrastive Dynamics: Consumers with low ATWOM tend to scrutinize the same high-volume cues through a systematic, skeptical lens, often wondering if the sheer quantity reflects artificial manipulation or platform bias. This critical scrutiny can lead to a contrastive effect, in which the consumer devalues the reviewed item.

Social Information Processing (SIP) Theory

Proposed by Walther (1992), Social Information Processing Theory argues that individuals can develop rich interpersonal impressions and relational trust in computer-mediated settings, provided there is sufficient interaction time and message exchange. While critics once argued that online interactions lacked non-verbal cues and were inherently colder than face-to-face exchanges, SIP theory maintains that users adapt by drawing social inferences from textual and quantitative signals. The ATWOM scale captures this individual adaptation: users with high ATWOM have successfully developed the cognitive schemas needed to extract social value and trust from digital text, whereas low-ATWOM individuals continue to view mediated, anonymous feedback as less reliable than direct or interpersonal sources.

7. Validity

The psychometric integrity of the ATWOM scale has been evaluated across both experimental and survey-based research settings. Validation analyses indicate that the instrument exhibits strong construct, convergent, discriminant, and predictive validity:

Construct and Factorial Validity

Construct validity was established by Khare et al. (2011) using both exploratory and confirmatory factor modeling. The six items loaded cleanly onto a single underlying construct, demonstrating that the behavioral, affective, and cognitive elements of the scale tap into a unified psychological orientation. Standardized factor loadings across multiple independent samples ranged from .72 to .88, confirming that each item accounts for a substantial share of variance in the latent construct.

Convergent Validity

Convergent validity was evaluated by assessing whether the scale correlated predictably with related constructs. The ATWOM scale demonstrates significant positive correlations with:

• General Trust in Consumer Feedback: Moderate-to-high positive correlations (ranging from r = .52 to .67) with scales assessing generalized interpersonal trust in digital platforms.
• Digital Information Search Propensity: Significant positive relationships (ranging from r = .45 to .58) with the frequency and depth of online pre-purchase search activity.
• Perceived Social Proof Diagnosticity: Strong positive correlations (ranging from r = .60 to .71) with measures tracking the degree to which an individual views consensus data as informative for personal choice.

Additionally, the Average Variance Extracted (AVE) routinely exceeds the benchmark of .50 (typically demonstrating AVE > .61), which confirms that the variance explained by the underlying construct is substantially larger than that attributed to measurement error.

Discriminant Validity

To confirm that the ATWOM scale measures a distinct construct rather than generic online fluency or broad consumer traits, researchers tested it against related concepts using the Fornell-Larcker criterion and cross-loading matrices. The square root of the AVE for ATWOM is consistently greater than its inter-construct correlations with the following measures:

• Susceptibility to Interpersonal Influence: Tested against the scale developed by Bearden, Netemeyer, and Teel (1989), ATWOM demonstrated weak-to-moderate correlations (ranging from r = .21 to .34). This confirms that open-ended engagement with anonymous digital reviews is conceptually distinct from a general desire to conform to the expectations of social peers.
• General Internet Self-Efficacy: Tested against scales assessing basic technical competence in web navigation, correlations were low to moderate (ranging from r = .18 to .29), confirming that ATWOM does not merely capture computer literacy.
• Consumer Skepticism toward Advertising: Demonstrated moderate, statistically significant negative correlations (ranging from r = -.31 to -.44) with scales measuring marketplace skepticism, such as the SKEP scale (Obermiller & Spangenberg, 1998). This supports the theoretical premise that consumers view peer-generated commentary differently than corporate promotional messaging.

Predictive and Nomological Validity

The predictive validity of the scale is demonstrated by its performance in the empirical studies reported by Khare et al. (2011). In their experiments, ATWOM was found to moderate the relationship between online review volume and product evaluations. When exposed to high-volume review scenarios, individuals with elevated ATWOM scores demonstrated higher product purchase intentions and more favorable attitudes toward the reviewed item (β = .38, p < .001). Conversely, for individuals with low ATWOM scores, high review volume did not produce an assimilative boost and occasionally triggered contrastive appraisals (β = -.22, p < .05). This interaction highlights the scale’s utility for predicting real-world consumer behavior.

8. Reliability

The reliability of the ATWOM scale has been evaluated across multiple experimental studies and survey administrations, demonstrating consistently high internal consistency:

• Cronbach’s Alpha (α): In the initial validation studies by Khare, Labrecque, and Asare (2011), the six-item scale yielded an internal consistency coefficient of α = .88 in their primary calibration study (N = 214) and α = .91 in a subsequent replication study (N = 186). Subsequent independent consumer investigations have reported Cronbach’s alpha values typically ranging between .86 and .92, well above the .70 threshold recommended for empirical research (Nunnally & Bernstein, 1994).
• Composite Reliability (CR): Structural equation modeling reveals composite reliability values that consistently range between .89 and .93, providing additional evidence that the latent construct is reliably captured by its six indicators.
• Corrected Item-Total Correlations: Across scale iterations, all individual item-to-total correlations exceed .62, with most falling between .68 and .81. This narrow, elevated range demonstrates that every item makes a meaningful contribution to the overall construct without redundancy.
• Test-Retest Stability: In longitudinal evaluations with a three-week interval between administrations, the scale demonstrated a test-retest reliability coefficient of r = .81 (p < .001). This finding indicates that ATWOM behaves as a stable dispositional attitude rather than a fluctuating emotional state.

9. Factor Analysis

The structural characteristics of the ATWOM scale have been evaluated using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA):

Exploratory Factor Analysis (EFA)

During initial scale development, the six items were subjected to principal axis factoring with promax rotation to identify underlying latent factors. The evaluation produced the following structural metrics:

• Kaiser-Meyer-Olkin (KMO) Measure: Sample adequacy values consistently exceeded .87, confirming the suitability of the data for factor analysis.
• Bartlett’s Test of Sphericity: Produced statistically significant results (χ² > 650.0, p < .001), rejecting the identity matrix null hypothesis.
• Eigenvalues and Explained Variance: A single dominant factor emerged with an eigenvalue substantially greater than 1.0 (typically ranging from 3.65 to 4.10), accounting for approximately 61% to 68% of the total item variance. The scree plot clearly flattened after the first factor, with the second factor yielding an eigenvalue well below 0.65, supporting a unidimensional structure.

Confirmatory Factor Analysis (CFA)

To verify this single-factor model, confirmatory factor analyses were estimated using maximum likelihood techniques. The unidimensional model demonstrated good fit across multiple samples, satisfying established psychometric criteria:

• Relative Chi-Square (χ²/df): Ratios ranged between 1.35 and 2.10, well within the recommended threshold of ≤ 3.0.
• Comparative Fit Index (CFI): Values routinely ranged between .975 and .991, exceeding the conventional .95 benchmark for well-specified models (Hu & Bentler, 1999).
• Tucker-Lewis Index (TLI): Coefficients remained high, typically between .960 and .984.
• Root Mean Square Error of Approximation (RMSEA): Estimates ranged from .035 to .058 (with 90% confidence intervals bounded between .000 and .082), satisfying the requirement for close model fit.
• Standardized Root Mean Square Residual (SRMR): Values remained below .035, indicating minimal residual discrepancy.

Standardized factor loadings (λ) for the individual items across the baseline model are summarized below:

• Comfort with reading online product reviews: λ = .78 to .84
• Habitual pre-purchase consultation of user reviews: λ = .81 to .87
• Reliance on peer feedback for uncertain product choices: λ = .76 to .83
• Enjoyment derived from reading community experiences: λ = .72 to .79
• Subjective importance placed on consumer feedback: λ = .75 to .82
• Belief in the collective usefulness of eWOM: λ = .70 to .77

These robust loadings confirm that the ATWOM instrument reliably operationalizes a coherent, unidimensional latent construct across consumer samples.

10. Instrument / Measurement Tool

The ATWOM scale is a standardized, self-report psychometric instrument designed for straightforward administration in academic experiments, market surveys, and consumer profiling. Below is an overview of its administrative and structural parameters:

• Instrument Designation: Attitude Toward Word-of-Mouth (On-line) (ATWOM).
• Target Construct: Generalized individual disposition, perceived value, comfort, and behavioral reliance regarding electronic peer feedback and digital product reviews.
• Administration Modality: Self-administered via paper-and-pencil or online digital survey environments (such as Qualtrics, Confirmit, or REDCap).
• Item Configuration: 6 items presented as declarative statements.
• Response Scale: 7-point Likert-type scale typically anchored as follows:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Somewhat Disagree
  • 4 = Neither Agree nor Disagree (Neutral)
  • 5 = Somewhat Agree
  • 6 = Agree
  • 7 = Strongly Agree
• Administration Duration: Approximately 2 to 3 minutes, making it suitable for inclusion in multi-instrument experimental batteries without inducing survey fatigue.
• Scoring Protocol: All items are positively framed toward favorable attitudes regarding online word-of-mouth. An individual respondent’s composite ATWOM score is calculated by computing the arithmetic mean across all 6 items, yielding a score ranging from 1.00 to 7.00 (alternatively, a summative score ranging from 6 to 42 can be derived):
  • Low ATWOM (Mean 1.00 – 3.25 / Sum 6 – 19): Reflects a skeptical, detached, or resistant disposition toward online peer feedback. The consumer rarely seeks out reviews, finds them unreliable or manipulative, and is largely unaffected by aggregate review metrics.
  • Moderate ATWOM (Mean 3.26 – 4.75 / Sum 20 – 28): Reflects an ambivalent or utilitarian approach. The consumer may check reviews occasionally, but balances them against marketer claims, brand reputation, and price considerations.
  • High ATWOM (Mean 4.76 – 7.00 / Sum 29 – 42): Reflects high enthusiasm and trust in digital peer feedback. The consumer relies heavily on crowd-sourced reviews, finds reading them engaging, and considers them essential for informed decision-making.

11. Permissions & Fee and Test Year

The Attitude Toward Word-of-Mouth (On-line) (ATWOM) scale was first published in 2011 in the Journal of Retailing:

• Original Publication Source: Khare, A., Labrecque, L. I., & Asare, A. K. (2011). The assimilative and contrastive effects of word-of-mouth volume: An experimental examination of online consumer ratings. Journal of Retailing, 87(1), 111–126. https://doi.org/10.1016/j.jretai.2010.11.002
• Copyright Ownership: The copyright for the article, including tables and instrument descriptions, is held by New York University and published by Elsevier Inc.
• Licensing and Academic Use: The scale is widely accessible in the public academic literature. Under standard fair-use academic conventions, researchers may reproduce and administer the ATWOM scale for non-commercial, scholarly investigations without paying licensing fees, provided the original research article is properly cited.
• Commercial Applications: Organizations intending to incorporate the scale into commercial market intelligence platforms, proprietary predictive analytics tools, or fee-for-service consulting frameworks should obtain formal copyright permission from Elsevier via RightsLink or the Copyright Clearance Center (CCC).

12. References

The following academic references provide theoretical foundations, empirical validation, and psychometric documentation for the ATWOM instrument:

• Bearden, W. O., Netemeyer, R. G., & Teel, J. E. (1989). Measurement of consumer susceptibility to interpersonal influence. Journal of Consumer Research, 15(4), 473–481. https://doi.org/10.1086/209186
• Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39(5), 752–766. https://doi.org/10.1037/0022-3514.39.5.752
• Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers.
• Feldman, J. M., & Lynch, J. G. (1988). Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. Journal of Applied Psychology, 73(3), 421–435. https://doi.org/10.1086/209134
• 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
• Khare, A., Labrecque, L. I., & Asare, A. K. (2011). The assimilative and contrastive effects of word-of-mouth volume: An experimental examination of online consumer ratings. Journal of Retailing, 87(1), 111–126. https://doi.org/10.1016/j.jretai.2010.11.002
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Obermiller, C., & Spangenberg, E. R. (1998). Development of a scale to measure skepticism toward advertising. Journal of Consumer Psychology, 7(2), 159–186. https://doi.org/10.1016/S0148-2963(00)00139-5
• Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. Advances in Experimental Social Psychology, 19, 123–205. https://doi.org/10.1016/S0065-2601(08)60214-2
• Walther, J. B. (1992). Interpersonal effects in computer-mediated interaction: A relational perspective. Communication Research, 19(1), 52–90. https://doi.org/10.1177/009365092019001003

13. Items of the Scale