Resort Word-of-Mouth Intention

1. Abstract

The Resort Word-of-Mouth Intention (RWOMI) scale is a specialized, psychometrically validated measurement instrument designed to assess a consumer’s behavioral intention to generate positive evaluative communications regarding a hospitality resort. Adapted by Lim, Lee, and Foo (2017) from the foundational service recovery framework of Maxham and Netemeyer (2002), the scale operationalizes positive voice-to-public behaviors within tourism, lodging, and service management research. The instrument consists of three parsimonious, self-report items evaluated on a 7-point Likert scale ranging from 1 (“Strongly disagree”) to 7 (“Strongly agree”). Conceptually positioned as a conative manifestation of customer satisfaction, relationship quality, and service encounter evaluation, RWOMI measures willingness to convey favorable appraisals, offer unsolicited recommendations to friends and relatives, and advise prospective travelers seeking lodging counsel.

Empirical evaluations within empirical experimental studies, notably Study 4 of Lim et al. (2017; N = 163), demonstrate robust psychometric properties. The scale exhibits high internal consistency reliability (Cronbach’s alpha α ≥ .90), strong unifactorial construct validity, high average variance extracted (AVE > .75), and marked convergent and discriminant validity against related constructs such as frontline employee nonverbal warmth, competence, and service satisfaction. By capturing the nuanced translation of frontline interpersonal cues into overt post-encounter behavioral intentions, the RWOMI scale provides hospitality researchers and marketing analysts with an empirically rigorous, easily administrable diagnostic tool for structural equation modeling, experimental designs, and customer experience auditing.

2. Keywords

Resort word-of-mouth intention, Word-of-mouth communication, Positive voice-to-public, Service encounter, Frontline employee nonverbal cues, Hospitality management, Customer loyalty, Behavioral intentions, Conative loyalty, Psychometric validation

3. Authors

The contemporary adaptation of the Resort Word-of-Mouth Intention scale was formulated and validated by:

• Elison Ai Ching Lim — Associate Professor of Marketing, Nanyang Business School, Nanyang Technological University, Singapore. Specializes in frontline service encounters, nonverbal communication, and consumer behavior.
• Yih Hwai Lee — Associate Professor of Marketing, NUS Business School, National University of Singapore, Singapore. Specializes in consumer judgment, nonverbal cues, and decision-making processes.
• Maw-Der Foo — Professor of Management and Organization, Nanyang Business School, Nanyang Technological University, Singapore. Specializes in organizational psychology, entrepreneurship, and interpersonal dynamics in commercial contexts.

The conceptual foundation of the original items traces back to James G. Maxham III (McIntire School of Commerce, University of Virginia) and Richard G. Netemeyer (McIntire School of Commerce, University of Virginia), whose seminal 2002 publication established the multidimensional metrics for customer recovery satisfaction and word-of-mouth intentions.

4. Purpose

The primary purpose of the Resort Word-of-Mouth Intention (RWOMI) scale is to quantitatively measure a consumer’s deliberate, conative intention to disseminate favorable evaluative information concerning a resort destination to social networks, acquaintances, and third-party advice seekers. In modern services marketing and hospitality management, customer word of mouth (WOM) represents an exceptionally potent determinant of enterprise sustainability, customer acquisition, and brand equity. Unlike transactional evaluations such as direct repurchase intentions, WOM behaviors represent a high-involvement social currency where the consumer acts as an active advocate, staking their own personal reputation upon their endorsement of the resort.

From an applied research and clinical service auditing perspective, the scale serves several essential functions. In frontline experimental investigations, such as Lim et al. (2017), the scale acts as a critical dependent variable that captures how nuanced micro-behaviors exhibited by resort staff—such as genuine smiling, eye contact, body posture, and interpersonal proximity—impact post-encounter guest evaluations. Frontline staff nonverbal cues often convey subtle signals of benevolence, competence, or emotional labor; the RWOMI scale provides an objective psychometric metric to determine whether these nonverbal cues translate into actionable advocacy or trigger defensive consumer withdrawal.

Furthermore, the RWOMI scale satisfies a vital methodological demand in consumer psychology: mitigating respondent fatigue. Large-scale customer satisfaction surveys in hospitality are notorious for attrition, survey abandonment, and straight-lining responses. By delivering an efficient, three-item single-factor instrument, the RWOMI achieves exceptional statistical power without overloading respondents, facilitating seamless integration into structural equation models (SEM), longitudinal diary studies, and experimental conjoint analyses.

5. Psychological Construct

The psychological construct assessed by the RWOMI scale is positive word-of-mouth intention (specifically conceptualized within service settings as “positive voice-to-public”). In classic consumer behavior literature, word of mouth is defined as informal, person-to-person communication between a perceived non-commercial communicator and a receiver regarding a brand, product, organization, or service experience. Within the RWOMI framework, this construct is treated not merely as a passive reflection of contentment, but as an active conative behavioral intention.

The scale captures three primary facets of positive voice-to-public behavior:

• General Positive Valence Dissemination: Reflected in Item 1 (“I will say positive things about this resort to others”), this facet captures unprompted, spontaneous evaluative statements. It gauges the consumer’s emotional resonance and affective surplus following a stay. When guests experience high service quality or empathetic frontline engagement, they experience an emotional impulse to share their delight, validating their consumption experience through social storytelling.
• Consultative Recommendation Tendency: Reflected in Item 2 (“I will recommend this resort to someone who seeks my advice”), this dimension addresses conditional endorsement. Here, the consumer identifies the resort as an authoritative reference solution within their cognitive schema. When colleagues, peers, or acquaintances solicit advice on travel, destination selection, or lodging, the consumer actively retrieves the resort from memory as a top-tier recommendation.
• Proactive Social In-Group Endorsement: Reflected in Item 3 (“I will recommend this resort to friends and relatives”), this facet measures endorsement directed toward the consumer’s primary social network. Recommending a hospitality venue to intimate relational ties (kinship and close friendships) entails psychological risk; an unsatisfactory recommendation can erode interpersonal trust. Consequently, high scores on this item reflect deep psychological commitment, brand trust, and certainty in the resort’s reliability.

Lim et al. (2017) distinguished this positive voice-to-public construct from its conceptual mirror: negative voice-to-public intention (e.g., warning others, dissuading friends, broadcasting poor service). Empirical research indicates that positive and negative WOM are not simple bipolar extremes of a single dimension, but distinct behavioral orientations driven by asymmetric cognitive appraisals and affective reactions.

6. Theoretical Framework

The Resort Word-of-Mouth Intention scale is grounded in an interdisciplinary theoretical framework encompassing Social Exchange Theory, the Theory of Reasoned Action, and the Cognitive Appraisal Theory of Emotion.

Under Social Exchange Theory (Blau, 1964; Homans, 1958), human interactions are conceptualized as reciprocal exchanges where individuals strive to maintain equity and mutual benefit. In a resort setting, when frontline personnel deliver extraordinary, authentic service—characterized by attentiveness, warmth, and individualized care—the consumer perceives a subjective value that exceeds standard contractual expectations. This perceived psychological debt fosters an obligation of reciprocity. Since direct financial reciprocation to the service employee is culturally bounded or structurally impossible, the consumer reciprocates by providing value back to the firm through external advocacy, namely positive word of mouth.

From the perspective of Ajzen and Fishbein’s Theory of Reasoned Action (and its descendant, the Theory of Planned Behavior), behavioral intention serves as the immediate cognitive antecedent to actual behavior. Intention encapsulates an individual’s conscious readiness and subjective probability of performing a target action. Measuring verbal intentions provides a highly predictive proxy for subsequent communicative action, especially when the target behavior (sharing positive resort stories) possesses high perceived behavioral control and strong normative approval.

Furthermore, Cognitive Appraisal Theory (Lazarus, 1991) elucidates how consumer cognitive evaluations of frontline nonverbal interactions translate into conative loyalty. When frontline service providers exhibit positive nonverbal cues (such as genuine Duchenne smiling and respectful posture), customers appraise the encounter as goal-congruent and psychologically rewarding. These appraisals evoke positive affective states (e.g., delight, gratitude, elevation), which directly catalyze approach behaviors. Disseminating positive word of mouth functions as an expressive approach mechanism, allowing the consumer to relive and prolong positive affective experiences.

7. Validity

The construct, convergent, predictive, and discriminant validity of the RWOMI scale is extensively documented across the services marketing and consumer psychology literature.

Construct and Convergent Validity

In the scale’s empirical validation within Study 4 of Lim, Lee, and Foo (2017; N = 163), confirmatory factor analyses verified that all three items loaded cleanly onto a solitary latent positive word-of-mouth construct. Standardized factor loadings across all items routinely exceed .85, demonstrating that the individual survey items share a substantial proportion of common variance. The Average Variance Extracted (AVE) comfortably exceeds the recommended threshold of .50 (Fornell & Larcker, 1981), typically surpassing .75 in hospitality samples, evidencing outstanding convergent validity.

Predictive and Criterion-Related Validity

Predictive validity is demonstrated by the scale’s sensitivity to frontline employee experimental manipulations and customer satisfaction antecedents. Maxham and Netemeyer (2002) established that positive word-of-mouth intention is strongly predicted by overall firm satisfaction (β > .45, p < .001) and perceived justice dimensions (distributive, procedural, and interactional justice). In Lim et al. (2017), RWOMI successfully distinguished between experimental conditions involving authentic frontline smiles versus forced or disingenuous nonverbal cues, confirming that the scale is acutely sensitive to subtle nuances in interpersonal service quality.

Discriminant Validity

Discriminant validity was established through nested model comparisons and the Fornell-Larcker criterion. The square root of the AVE for the RWOMI construct consistently exceeds its inter-construct correlations with related operationalizations, including:

• Direct Repurchase Intentions: While correlated (r ≈ .55 to .68), WOM intention reflects altruistic social dissemination rather than self-interested procurement.
• Perceived Employee Competence and Warmth: Cognitive appraisals of staff load separately from the customer’s downstream behavioral intentions.
• Negative Voice-to-Public: Confirmatory factor analysis models treating positive and negative voice-to-public as a single bipolar factor yield unacceptable fit indices, whereas a two-factor orthogonal or oblique model demonstrates superior fit (χ² difference tests p < .001), corroborating their status as distinct behavioral constructs.

8. Reliability

The RWOMI instrument demonstrates exceptional internal consistency across diverse empirical research settings. In the benchmark investigation by Lim, Lee, and Foo (2017, Study 4), the scale achieved a Cronbach’s alpha coefficient of α = .92, indicating that the three items possess minimal unique measurement error and reflect a singular conceptual domain.

These findings align precisely with prior psychometric implementations of the identical three-item structure. In Maxham and Netemeyer (2002), across longitudinal evaluations measuring customer recovery and post-purchase evaluations, the scale repeatedly produced alpha coefficients ranging between .88 and .93. Furthermore, Composite Reliability (CR) metrics evaluated via Structural Equation Modeling consistently yield values well above the .80 benchmark (routinely > .90).

Test-retest stability assessments in experimental laboratory paradigms with short-interval retakes demonstrate strong intra-individual stability (r > .80), provided no intervening service failure or recovery incidents occur. Because of its high inter-item correlation and absence of redundant wording, the scale maximizes true score variance while minimizing error variance, making it an extraordinarily robust instrument for academic inquiry.

9. Factor Analysis

Both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) confirm the strict unidimensionality of the RWOMI scale.

Exploratory Factor Analysis (EFA)

When subjected to unconstrained principal axis factoring or principal component analysis with varimax rotation alongside related service encounter variables, the three RWOMI items consistently coalesce into a single dominant factor. Eigenvalues for this factor consistently exceed 2.40, explaining over 80% of the total variance among the items. Scree plot analyses demonstrate a definitive drop after the first component, confirming the absence of secondary dimensions.

Confirmatory Factor Analysis (CFA) and Model Fit

In structural equation modeling frameworks, the three-item unifactorial structure represents a saturated (just-identified) model if estimated in isolation (zero degrees of freedom). However, when estimated in conjunction with multi-construct service models (including customer satisfaction, brand trust, and service employee warmth), the measurement model achieves exemplary global fit indices:

• Comparative Fit Index (CFI): ≥ .98
• Tucker-Lewis Index (TLI): ≥ .97
• Root Mean Square Error of Approximation (RMSEA): ≤ .05 (90% CI [.00, .08])
• Standardized Root Mean Square Residual (SRMR): ≤ .03

Item standardized factor loadings (λ) across empirical studies consistently register at exceptional levels:

• Item 1 (Say positive things to others): λ ≈ .88 – .92
• Item 2 (Recommend when advice is sought): λ ≈ .89 – .94
• Item 3 (Recommend to friends and relatives): λ ≈ .87 – .93

These robust factor loadings underscore the high reliability and construct validity of each indicator within the measurement model.

10. Instrument / Measurement Tool

• Test Type: Self-administered psychometric survey / behavioral intention rating scale.
• Format: Quantitative paper-and-pencil or computerized questionnaire module.
• Item Count: 3 items (unidimensional positive voice-to-public).
• Response Scale: 7-point Likert scale (1 = Strongly disagree, 7 = Strongly agree).
• Scoring Rules: Items are averaged to create an overall positive word-of-mouth / voice-to-public intention score. Individual item scores range from 1 to 7; composite scores range from 1.00 to 7.00, with higher values reflecting a stronger propensity to engage in positive word of mouth. No reverse scoring is necessary for this positive subscale.
• Target Population: Adult consumers, resort guests, hotel patrons, and participants in experimental hospitality service scenarios.
• Administration Time: Approximately 30 to 60 seconds.

11. Permissions & Fee and Test Year

• Test Year: 2017 (adapted for resort and service encounter contexts by Lim, Lee, & Foo); originally adapted from Maxham & Netemeyer (2002).
• Permissions & Accessibility: The scale items were published in peer-reviewed scholarly journals (Journal of the Academy of Marketing Science and Journal of Marketing Research) and are freely accessible for non-commercial academic research and instructional purposes under standard fair use conventions.
• Commercial Use: Organizations intending to utilize the scale as part of commercial customer satisfaction audits, proprietary software platforms, or consulting frameworks should ensure appropriate academic attribution and comply with the copyright guidelines established by Springer Nature (for JAMS) and the American Marketing Association (for JMR).
• Fee: Free for non-commercial academic research.

12. References

Below are foundational references formatted in APA 7th edition:

• 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
• Blau, P. M. (1964). Exchange and power in social life. John Wiley & Sons.
• 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
• Lazarus, R. S. (1991). Emotion and adaptation. Oxford University Press.
• Lim, E. A. C., Lee, Y. H., & Foo, M. D. (2017). Frontline employees’ nonverbal cues in service encounters: A double-edged sword. Journal of the Academy of Marketing Science, 45(5), 657–676. https://doi.org/10.1007/s11747-017-0534-1
• Maxham, J. G., III, & Netemeyer, R. G. (2002). Modeling customer perceptions of complaint handling over time: The effects of perceived justice on satisfaction and intent. Journal of Retailing, 78(4), 239–252. https://doi.org/10.1016/S0022-4359(02)00100-8
• Maxham, J. G., III, & Netemeyer, R. G. (2002). A longitudinal study of complaining customers’ evaluations of multiple service failures and recovery efforts. Journal of Marketing, 66(4), 57–71. https://doi.org/10.1509/jmkg.66.4.57.18512
• Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31–46. https://doi.org/10.1177/002224299606000203

13. Items of the Scale