Online Travel Review Adoption Scale (OTRAS)

1. Abstract

The Online Travel Review Adoption Scale (OTRAS) is a psychometric instrument designed to measure the multidimensional antecedents that govern travelers’ information adoption and decision-making processes when consulting online consumer reviews (electronic word-of-mouth, or e-WOM) on platforms such as TripAdvisor, Booking.com, and Google Reviews. Conceptualized and empirically validated in the seminal work by Filieri and McLeay (2014), the instrument operationalizes the Information Adoption Model (IAM) and dual-process cognition within digital consumer tourism. The instrument comprises 28 items evaluated via a 7-point Likert scale spanning nine theoretically derived latent dimensions: Information Accuracy, Information Completeness, Information Timeliness, Information Relevance, Information Value-Added, Source Credibility, Product Involvement, Website Trust, and Information Adoption (decision-making utilization).

Psychometric evaluations across structural equation modeling frameworks demonstrate robust construct validity, high internal consistency reliability (Cronbach’s alpha values typically ranging from α = .78 to .92 across dimensions), and strong convergent and discriminant validity evidenced by Average Variance Extracted (AVE) coefficients exceeding recommended thresholds. As digital tourism and user-generated content continue to supersede traditional marketing channels, the scale serves as an empirical foundation for assessing how central argumentative merits (argument quality) interact with peripheral heuristics (source credibility and platform trust) to shape travel purchasing behavior and consumer choice.

2. Keywords

Online Travel Reviews, Information Adoption Model, Electronic Word-of-Mouth (e-WOM), Information Quality, Source Credibility, Website Trust, Product Involvement, Tourism Psychometrics, Consumer Decision-Making, Elaboration Likelihood Model

3. Authors

The primary architects and empirical investigators of the Online Travel Review Adoption measurement framework are:

• Raffaele Filieri, Ph.D. — Professor of Digital Marketing, Audencia Business School, Nantes, France; previously associated with Newcastle University Business School, United Kingdom. Specializes in consumer behavior in digital environments, consumer reviews, e-WOM, and digital marketing analytics.
• Fraser McLeay, Ph.D. — Professor of Strategic Marketing, Sheffield University Management School, University of Sheffield, United Kingdom. Specializes in consumer decision-making, marketing strategy, sustainability, and service management.

4. Purpose

The primary purpose of the Online Travel Review Adoption Scale is to diagnose, quantify, and explain the psychological and cognitive mechanisms that drive consumers to integrate peer-generated accommodation reviews into their travel planning and purchase decisions. With the transition of the tourism industry toward algorithmic, user-generated ecosystems, travelers face an unprecedented volume of asynchronous, anonymous peer reviews. Consequently, traditional consumer search frameworks based strictly on firm-generated information fail to explain how consumers discern authentic, diagnostic data amidst noise, manipulation, and information overload.

From an applied research perspective, the scale allows hospitality managers, destination marketing organizations (DMOs), and platform architects to evaluate how specific attributes of user reviews (such as argumentative completeness, accuracy, and recency) contribute to consumer confidence and booking conversion. Theoretically, the instrument bridges the gap between digital communications theory and psychometric measurement by operationalizing informational utility as both cognitive processing of content (central route) and evaluative assessment of origin (peripheral route).

5. Psychological Construct

The scale models information adoption as an end-state behavioral and cognitive outcome driven by nine interconnected latent dimensions:

• Information Accuracy: The degree to which a consumer perceives review content to be factual, correct, dependable, and free from erroneous assertions.
• Information Completeness: The perception that peer feedback provides sufficient, comprehensive, and exhaustive coverage of the lodging attributes required to make an informed choice.
• Information Timeliness: The perceived currency, recency, and up-to-date nature of the user reviews, ensuring that described conditions reflect current operational realities.
• Information Relevance: The degree of direct applicability and contextual pertinence of the review content to the consumer’s individualized accommodation requirements.
• Information Value-Added: The subjective assessment that consulting peer reviews yields incremental benefit, practical utility, and distinct advantages compared to relying solely on commercial descriptions.
• Source Credibility: The perceived honesty, trustworthiness, and experiential competence of the anonymous or pseudonymous reviewers authoring the content.
• Product Involvement: The enduring personal relevance, perceived risk, and motivational significance that the consumer attaches to selecting appropriate travel accommodation.
• Website Trust: The institutional, structural, and platform-level trust placed in the intermediary hosting the reviews (e.g., TripAdvisor, Booking.com), reflecting beliefs in platform integrity and dependability.
• Information Adoption: The target criterion variable measuring the degree to which reviews are actively utilized to facilitate, influence, and determine final accommodation selections.

6. Theoretical Framework

The scale is anchored in the Elaboration Likelihood Model (ELM) of persuasion developed by Petty and Cacioppo (1986) and its specialized adaptation, the Information Adoption Model (IAM) formulated by Sussman and Siegal (2003). ELM posits that individuals process persuasive messaging through two distinct cognitive pathways based on their motivation and ability: the central route and the peripheral route.

Within this scale, argument quality is operationalized through five informational quality dimensions: accuracy, completeness, timeliness, relevance, and value-added utility. These represent the central route, requiring systematic cognitive elaboration. Conversely, peripheral cues are captured through source credibility and website trust, enabling heuristic processing under conditions of cognitive constraint or ambiguous evaluation. Furthermore, Zaichkowsky’s (1985) involvement theory provides the moderating baseline: higher product involvement increases the need for rigorous argument evaluation, whereas website trust provides an institutional safety net facilitating information acceptance.

7. Validity

Validation of the scale demonstrates rigorous construct, convergent, and discriminant validity across multiple consumer samples:

• Convergent Validity: Established using Confirmatory Factor Analysis (CFA). Standardized factor loadings across all latent constructs exceed the recommended .70 threshold (predominantly ranging from .74 to .91, p < .001). Average Variance Extracted (AVE) values surpass the .50 benchmark across all dimensions, confirming that each latent construct captures more construct-specific variance than error variance.
• Discriminant Validity: Evaluated using the Fornell-Larcker criterion and Heterotrait-Monotrait (HTMT) ratio of correlations. The square root of the AVE for each construct reliably exceeds all paired inter-construct correlations, and HTMT ratios remain below .85, verifying distinct dimensional integrity.
• Predictive / Nomological Validity: Structural equation modeling confirms that central argument components (specifically accuracy, completeness, and timeliness) alongside peripheral cues (source credibility and platform trust) account for substantial variance in Information Adoption (R² values typically exceeding .55).

8. Reliability

The internal consistency of the instrument has been established across independent replications:

• Information Accuracy: Cronbach’s α = .88; Composite Reliability (CR) = .89
• Information Completeness: Cronbach’s α = .86; Composite Reliability (CR) = .87
• Information Timeliness: Cronbach’s α = .84; Composite Reliability (CR) = .85
• Information Relevance: Cronbach’s α = .87; Composite Reliability (CR) = .88
• Information Value-Added: Cronbach’s α = .85; Composite Reliability (CR) = .86
• Source Credibility: Cronbach’s α = .82; Composite Reliability (CR) = .83
• Product Involvement: Cronbach’s α = .89; Composite Reliability (CR) = .90
• Website Trust: Cronbach’s α = .91; Composite Reliability (CR) = .92
• Information Adoption: Cronbach’s α = .88; Composite Reliability (CR) = .89

Test-retest coefficients over a 4-week interval have demonstrated temporal stability (r > .80), indicating that the scale captures stable evaluative patterns rather than transient states.

9. Factor Analysis

During scale development, the 28 items were subjected to Exploratory Factor Analysis (EFA) using principal axis factoring with Promax rotation, confirming clean primary loadings onto nine distinct factors with negligible cross-loadings (< .25). Subsequent Confirmatory Factor Analysis (CFA) demonstrated good fit to the data across standard goodness-of-fit indices:

• Ratio of Chi-Square to Degrees of Freedom (χ²/df) = 1.82 (< 3.0 indicated good fit)
• Comparative Fit Index (CFI) = .963 (> .95)
• Tucker-Lewis Index (TLI) = .957 (> .95)
• Root Mean Square Error of Approximation (RMSEA) = .044 (90% CI [.038, .051]; < .06)
• Standardized Root Mean Square Residual (SRMR) = .039 (< .08)

10. Instrument / Measurement Tool

• Test Type: Multi-item psychometric self-report survey scale.
• Construct Measured: Determinants and behavioral outcomes of online consumer review adoption in travel accommodation contexts.
• Item Count: 28 manifest variables (items).
• Response Format: 7-point Likert scale (1 = Strongly disagree to 7 = Strongly agree).
• Subscale Breakdown:
  • Information Accuracy: Items 1–3
  • Information Completeness: Items 4–6
  • Information Timeliness: Items 7–9
  • Information Relevance: Items 10–12
  • Information Value-Added: Items 13–15
  • Source Credibility: Items 16–18
  • Product Involvement: Items 19–21
  • Website Trust: Items 22–24
  • Information Adoption: Items 25–28
• Scoring Rules: All 28 items are positively keyed (no reverse-scored items). Subscale scores are calculated as the unweighted arithmetic mean or sum of their constituent indicators. Structural models employ latent variable scores derived from factor weightings.

11. Permissions & Fee and Test Year

The scale was published in 2014 in the Journal of Travel Research. The instrument is available for non-commercial academic, educational, and scientific research purposes without royalty fees, provided full bibliographic attribution is granted to the original authors (Filieri & McLeay, 2014). Commercial implementations, platform integration, and proprietary consumer benchmarking may require prior written permission from the copyright holders or Sage Publications.

12. References

• Filieri, R., & McLeay, F. (2014). E-WOM and accommodation: An analysis of the factors that influence travelers’ adoption of information from online reviews. Journal of Travel Research, 53(1), 44–57. https://doi.org/10.1177/0047287513513120
• 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
• Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14(1), 47–65. https://doi.org/10.1287/isre.14.1.47.14767
• Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341–352. https://doi.org/10.1086/208520

13. Items of the Scale