Continuous Visiting Behavior–Measurement Model

Abstract

The Continuous Visiting Behavior–Measurement Model (CVB-MM), developed by Cahigas, Prasetyo, Nadlifatin, Persada, and Gumasing (2023), is an empirical psychometric instrument engineered to investigate the cognitive, affective, and environmental determinants governing tourists’ repeat patronage and continuous visiting behavior toward travel accommodations. Grounded in the empirical context of Palawan, Philippines—a globally renowned ecotourism destination—the scale evaluates how pre-consumption uncertainty mitigation strategies synthesize with post-consumption evaluative mechanisms to drive long-term behavioral loyalty. The measurement model reconciles two prominent theoretical architectures: Uncertainty Reduction Theory (URT) and the Expectation Confirmation Theory (ECT).

The refined operational instrument measures latent constructs across nine focal dimensions: Interactive Uncertainty (IU), Perceived Performance (PP), Confirmation (C), Physical Environment (PE), Attitude of Employees (AE), Service Experience (SE), Price Acceptance (PA), Tourist Satisfaction (TS), and Continuous Visiting Behavior (CVB). Administered using a standard 5-point Likert response format (ranging from 1 = Strongly Disagree to 5 = Strongly Agree), the CVB-MM captures the multifaceted customer journey from social information retrieval and interpersonal inquiries to perceived tangible/intangible service quality, psychological confirmation, economic value calibration, and ultimate revisit intention. Psychometric validation conducted via structural equation modeling (SEM) confirmed robust internal consistency, with Cronbach’s alpha values across latent dimensions ranging from .73 to .91. Convergent validity was established via composite reliability and average variance extracted (AVE), while discriminant validity was verified using both the Fornell–Larcker criterion and the Heterotrait-Monotrait (HTMT) ratio of correlations. The CVB-MM provides researchers and hospitality professionals with a statistically validated framework for assessing the drivers of tourist retention in competitive hospitality environments.

Keywords

Continuous Visiting Behavior, Measurement Model, Uncertainty Reduction Theory, Expectation Confirmation Theory, Tourist Satisfaction, Hospitality Management, Service Experience, Physical Environment, Price Acceptance, Confirmatory Factor Analysis, Psychometrics, Consumer Loyalty, Ecotourism.

Authors

The Continuous Visiting Behavior–Measurement Model was developed and validated by a multidisciplinary team of researchers specializing in industrial engineering, human factors, systems management, and consumer decision-making:

• Maela Madel L. Cahigas – School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines.
• Yogi Tri Prasetyo (Corresponding Author) – International Bachelor Program in Engineering, Yuan Ze University, Taoyuan, Taiwan; School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines. ORCID: 0000-0003-3535-9657. Email: [email protected].
• Reny Nadlifatin – Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya, Indonesia.
• Satria Fadil Persada – Entrepreneurship Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta, Indonesia.
• Ma. Janice J. Gumasing – School of Industrial Engineering and Engineering Management, Mapúa University, Manila, Philippines.

Purpose

The central purpose of the Continuous Visiting Behavior–Measurement Model (CVB-MM) is to systematically operationalize, evaluate, and predict the complex psychological determinants that govern consumer revisit intentions within the travel accommodation sector. In contemporary hospitality and tourism management, customer acquisition costs substantially exceed retention costs. Consequently, establishing why consumers develop persistent loyalty and repeatedly choose specific lodging facilities over competing alternatives represents a strategic imperative. The CVB-MM addresses critical theoretical and methodological gaps in the literature by linking pre-consumption information-gathering behaviors directly to post-consumption experiential evaluations.

In consumer psychology and destination marketing, traditional assessment scales have often conceptualized revisit intentions through narrow, isolated paradigms—such as focusing exclusively on brand image, generic service quality (e.g., standard SERVQUAL dimensions), or transactional pricing. However, modern travel consumers operate under conditions of cognitive uncertainty when booking accommodations in geographically remote or nature-based tourist hubs. The CVB-MM addresses this complexity by examining how tourists mitigate cognitive vulnerabilities prior to booking, how on-site sensory and human interactions reinforce or alter expectations, and how economic perceptions calibrate overall satisfaction to foster continuous visiting behavior.

From an applied research perspective, the scale functions as an empirical diagnostic instrument for:

• Hospitality Diagnostic Audits: Allowing resort managers, boutique hotel operators, and destination stakeholders to pinpoint deficits within their service delivery pipeline, distinguishing whether client attrition stems from physical infrastructure failures, interpersonal employee shortcomings, perceived price-performance disparities, or unmet baseline expectations.
• Ecotourism and Destination Loyalty Modeling: Supplying tourism researchers with a psychometrically validated battery suited to regions where natural geography, sustainability requirements, and varying infrastructural maturity impact tourist perceptions (e.g., island destinations like Palawan).
• Cross-Validation of Decision Paradigms: Offering behavioral scientists an integrated empirical tool capable of testing structural equation models that bridge communication-based cognitive theories with consumer satisfaction frameworks.

By capturing the cognitive progression from uncertainty reduction to post-stay behavioral loyalty, the CVB-MM provides an empirically validated, actionable blueprint for deciphering the mechanisms behind repeat tourism patronage.

Psychological Construct

The Continuous Visiting Behavior–Measurement Model conceptualizes repeat patronage as a multidimensional structural process mediated by cognitive, affective, sensory, and economic evaluations. Rather than treating continuous visiting behavior as an isolated outcome, the model defines it as the behavioral culmination of eight interrelated precursor constructs. The theoretical nature and operational definitions of each construct within the measurement model are detailed below:

1. Interactive Uncertainty (IU)

Grounded in interpersonal communication dynamics, Interactive Uncertainty captures the degree to which a consumer seeks direct verbal or digital communication with social networks—specifically friends, family, and peer referents—to resolve cognitive ambiguity and perceived decision risks before booking. Unlike passive information retrieval (such as browsing static marketing pages), interactive uncertainty involves active dialogue and reliance on interpersonal word-of-mouth (WOM). Sample indicator: “My decision in booking travel accommodation depends on friends’ and family’s feedback.”

2. Perceived Performance (PP)

Perceived Performance reflects the tourist’s prospective cognitive appraisal regarding the credibility, competence, and reliability of the accommodation provider based on synthesized pre-booking signals. This construct measures the consumer’s psychological confidence that the selected facility will operate effectively and fulfill its promised hospitality functions. Sample indicator: “I feel that the information I gathered about the travel accommodation is trustworthy.”

3. Confirmation (C)

Derived from Expectation Confirmation Theory, Confirmation represents the psychological outcome of comparing pre-purchase cognitive expectations with actual on-site service delivery. Positive confirmation occurs when the accommodation matches or exceeds prior anticipations regarding operational fidelity, amenity disclosure, and visual accuracy. Sample indicator: “The travel accommodation kept promises and commitment to the services they offered.”

4. Physical Environment (PE)

The Physical Environment construct operationalizes the tangible, spatial, and aesthetic dimensions of the accommodation facility—frequently conceptualized in environmental psychology as the servicescape. It encompasses room dimensions, architectural interior design, atmospheric aesthetics, and fundamental ambient cleanliness. Sample indicator: “I expect the travel accommodation’s interior design to be aesthetically pleasing.”

5. Attitude of Employees (AE)

This dimension evaluates the relational, communicative, and emotional labor displayed by hospitality personnel during guest interactions. It encompasses perceived courtesy, professional demeanor, proactive problem-solving competence, and emotional empathy. Sample indicator: “I expect that the travel accommodation’s employees demonstrate their willingness to help me.”

6. Service Experience (SE)

Service Experience represents the holistic, gestalt evaluation of qualitative encounters during the stay. It bridges sensory infrastructure with human-delivered services, reflecting overall structural quality and execution. Sample indicator: “I expect adequate and quality travel accommodation room.”

7. Price Acceptance (PA)

Price Acceptance captures the consumer’s cognitive cost-benefit appraisal and economic tolerance. It evaluates whether the tourist perceives the monetary expenditure as equitable, worthwhile, and well-aligned with the delivered amenities and promotional value. Sample indicator: “The food and beverage served at travel accommodations are worth their prices.”

8. Tourist Satisfaction (TS)

Tourist Satisfaction functions as the primary affective and cognitive post-consumption evaluation state. It measures the aggregate emotional gratification and perceived success of the lodging experience, encapsulating both transactional fulfillment and overall experiential contentment. Sample indicator: “I feel satisfied with the travel accommodation’s overall service.”

9. Continuous Visiting Behavior (CVB)

The primary focal outcome of the model, Continuous Visiting Behavior, defines the consumer’s conative commitment and behavioral intention to repeatedly revisit, prioritize, and maintain sustained patronage with the specific accommodation provider during future travels. Sample indicator: “I intend to prioritize the travel accommodation I went to compared to other accommodations when traveling to Palawan.”

Theoretical Framework

The theoretical framework of the CVB-MM synthesizes two complementary socio-psychological paradigms: Uncertainty Reduction Theory (URT), originally formulated by Charles Berger and Richard Calabrese (1975), and Expectation Confirmation Theory (ECT), established by Richard L. Oliver (1980). By uniting these two paradigms, the model accounts for both pre-consumption cognitive mechanisms and post-consumption experiential assessments within a unified behavioral trajectory.

URT posits that when individuals encounter unfamiliar environments or high-involvement purchasing situations—such as securing lodging in an ecotourism destination where logistical predictability may fluctuate—they experience heightened cognitive uncertainty and perceived vulnerability. To re-establish psychological equilibrium, individuals deploy specific communication strategies. While URT classically delineates passive, active, and interactive information-seeking strategies, Cahigas et al. (2023) identified that within modern experiential travel contexts, interactive uncertainty reduction (seeking interpersonal confirmation from peer networks and experienced referents) exercises a profound influence on shaping initial expectations and crystallizing Perceived Performance.

Complementing this pre-purchase phase, Oliver’s Expectation Confirmation Theory provides the scaffolding for post-purchase psychological processing. According to ECT, consumers formulate baseline expectations prior to acquiring a product or service. Once consumed, the actual performance is cognitively contrasted against these baseline reference points. This psychological comparison produces one of three cognitive outcomes: positive disconfirmation (performance surpasses expectations), confirmation (performance aligns with expectations), or negative disconfirmation (performance falls short of expectations).

The CVB-MM embeds the physical servicescape (Physical Environment), human relational capital (Attitude of Employees), broad experiential quality (Service Experience), and economic calibration (Price Acceptance) as direct inputs into the Confirmation and Tourist Satisfaction nexus. When interactive uncertainty reduction successfully guides a tourist toward an accommodation provider whose tangible and relational delivery confirms expectations, Tourist Satisfaction reaches optimal levels. Consequently, satisfied consumers exhibit cognitive stabilization, loyalty crystallization, and an elevated propensity for Continuous Visiting Behavior, minimizing future search costs by continuously patronizing the trusted provider.

Validity

The psychometric integrity of the Continuous Visiting Behavior–Measurement Model was established through rigorous analytical procedures, utilizing structural equation modeling (SEM) to evaluate construct validity, convergent validity, and discriminant validity in a representative cohort of Filipino adult tourists visiting Palawan accommodations (Cahigas et al., 2023).

Convergent Validity

Convergent validity was evaluated using two primary statistical benchmarks: standardized factor loadings (λ) and the Average Variance Extracted (AVE). According to established psychometric standards (Hair et al., 2010), factor loadings should ideally exceed 0.50, and AVE values should exceed 0.50, signifying that a latent construct accounts for more than half of the variance observed across its operational indicators.

Statistical analysis indicated that the AVE parameters for the majority of the latent dimensions exceeded the conservative 0.50 threshold:

• Interactive Uncertainty (IU): AVE > 0.50
• Perceived Performance (PP): AVE > 0.50
• Attitude of Employees (AE): AVE > 0.50
• Service Experience (SE): AVE > 0.50
• Price Acceptance (PA): AVE > 0.50
• Tourist Satisfaction (TS): AVE > 0.50
• Continuous Visiting Behavior (CVB): AVE > 0.50

Two constructs—Confirmation (C) and Physical Environment (PE)—yielded AVE metrics marginally below the 0.50 criterion due to item loadings clustering close to the 0.50 lower threshold. However, following the widely accepted methodological criterion established by Fornell and Larcker (1981), convergent validity remains statistically adequate if the construct’s Composite Reliability (CR) remains well above 0.60 to 0.70. Because both Confirmation and Physical Environment demonstrated robust composite reliability values exceeding 0.70, convergent validity was empirically retained for all model dimensions.

Discriminant Validity

Discriminant validity was established to confirm that each latent construct represents a distinct psychological phenomenon not duplicated by other variables in the model. This was verified through two rigorous methods:

1. The Fornell–Larcker Criterion: The square root of the AVE for each latent variable was verified to be strictly greater than the correlation coefficients shared between that construct and any other latent variable in the measurement model, confirming that each construct shared more variance with its own indicators than with other dimensions.
2. Heterotrait-Monotrait (HTMT) Ratio of Correlations: The HTMT ratios across all construct pairings fell below the stringent conservative threshold of 0.85 (and well within the liberal 0.90 ceiling; Henseler et al., 2015), providing conclusive evidence that the nine constructs of the CVB-MM maintain clear empirical divergence.

Reliability

The scale’s internal consistency was comprehensively evaluated using both Cronbach’s alpha (α) and Composite Reliability (CR). These metrics assess the degree to which items within each subscale reliably capture their underlying construct with minimal measurement error.

Empirical analyses reported by Cahigas et al. (2023) established that all latent constructs demonstrated strong to excellent internal consistency:

• Internal Consistency Range: Cronbach’s alpha coefficients across the model’s dimensions ranged from .73 to .91, uniformly exceeding the accepted psychometric benchmark of .70 for research and diagnostic instruments (Nunnally & Bernstein, 1994).
• Composite Reliability: Composite reliability values similarly exceeded the conventional .70 threshold across all nine dimensions, demonstrating that the measurement indicators exhibit robust communal variance and high stability.
• Error Variance Control: The systematic refinement of the scale—eliminating low-loading or cross-loading items—substantially reduced random measurement error, resulting in stable scale configurations across sub-samples.

These reliability parameters confirm that the CVB-MM produces consistent, reproducible scores when evaluating customer perceptions across accommodation providers.

Factor Analysis

The factor structure of the CVB-MM underwent rigorous psychometric refinement via Confirmatory Factor Analysis (CFA) within a structural equation modeling framework. The initial conceptualization drew from an exploratory pool of 11 distinct theoretical constructs and 48 candidate items adapted from hospitality, consumer behavior, and tourism scales (e.g., Al-Refaie, 2014; Chen et al., 2014; El-Adly, 2018; Lee et al., 2011; Nunkoo et al., 2020).

During structural model specification and iterative measurement refinement, psychometric criteria dictated the removal of non-performing items and redundant dimensions to optimize model fit, prevent multicollinearity, and enhance parsimony:

• Construct-Level Deletion: Two full constructs were eliminated from the final model: Passive Uncertainty (PU) and Food and Beverage (FB). Passive information-seeking (e.g., general website browsing) demonstrated statistical redundancy and weak structural predictive power relative to interactive word-of-mouth channels. Similarly, Food and Beverage failed to function as an independent primary determinant of continuous visiting across diverse lodging categories (such as non-catering boutique accommodations).
• Item-Level Deletion: Eighteen individual items were systematically excised due to low factor loadings (< 0.50), high residual covariance, or substantial cross-loadings. The eliminated items were: PP2, PP4, IU4, PE4, PE6, PE7, PE8, PE9, AE4, SE3, SE4, SE5, SE7, PA2, PA3, PA5, PA7, and CVB4.
• Final Factor Loadings: In the finalized measurement model comprising the 9 core constructs and 30 retained indicator items, all standardized factor loadings (λ) cleanly exceeded the minimum psychometric cut-off criterion of 0.50 (with the majority surpassing 0.70), demonstrating that each item is a statistically sound indicator of its designated latent factor.
• Model Fit Indices: The refined 9-construct structural measurement model demonstrated acceptable goodness-of-fit across global indices, satisfying standard structural thresholds (such as χ²/df ratio, Comparative Fit Index [CFI], Tucker-Lewis Index [TLI], and Root Mean Square Error of Approximation [RMSEA]), confirming that the empirical data aligns well with the hypothesized theoretical model.

Instrument / Measurement Tool

The operational specifications of the Continuous Visiting Behavior–Measurement Model are structured as follows:

• Instrument Name: Continuous Visiting Behavior–Measurement Model (CVB-MM)
• Test Type: Psychometric Self-Report Questionnaire / Multi-Attribute Rating Inventory
• Target Population: Adult tourists (18 years and older; male and female) who have stayed at travel accommodations
• Language Available: English (administered and validated in the Philippines)
• Constructs / Subscales (9 Dimensions):
  • Interactive Uncertainty (IU) – 3 retained items (IU1, IU2, IU3)
  • Perceived Performance (PP) – 2 retained items (PP1, PP3)
  • Confirmation (C) – 4 retained items (C1, C2, C3, C4)
  • Physical Environment (PE) – 5 retained items (PE1, PE2, PE3, PE5, PE8 [retained in intermediate model] / operational 3 core items)
  • Attitude of Employees (AE) – 3 retained items (AE1, AE2, AE3)
  • Service Experience (SE) – 2 retained items (SE1, SE2)
  • Price Acceptance (PA) – 3 retained items (PA1, PA4, PA6)
  • Tourist Satisfaction (TS) – 4 retained items (TS1, TS2, TS3, TS4)
  • Continuous Visiting Behavior (CVB) – 3 retained items (CVB1, CVB2, CVB3)
• Response Format: Standard 5-Point Likert-type Scale:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Neutral (Neither Agree nor Disagree)
  • 4 = Agree
  • 5 = Strongly Agree
• Scoring and Interpretation Procedures:
  • Individual dimension scores are computed by calculating the arithmetic mean or summation of the retained indicator items within each subscale.
  • No reverse-scored items are included; higher aggregate scores indicate stronger endorsement of the respective construct (e.g., higher interactive uncertainty reduction, superior perceived performance, greater satisfaction, and higher continuous visiting intention).
  • In structural equation modeling (SEM) applications, composite or factor-score weights should be utilized to represent latent constructs directly within path analyses.

Permissions & Fee and Test Year

The Continuous Visiting Behavior–Measurement Model was published in 2023 by Cahigas, Prasetyo, Nadlifatin, Persada, and Gumasing. The original empirical research was published in PLoS ONE under an open-access Creative Commons Attribution 4.0 International License (CC BY 4.0).

• Fee: Free. There are no licensing fees or financial charges associated with administering or adapting the instrument for scientific research, academic education, or operational evaluation.
• Permissions & Reproduction: Scholars, students, and practitioners are permitted to share, copy, adapt, and build upon the instrument, provided appropriate credit is given to the original authors (Cahigas et al., 2023) and changes are indicated.
• Commercial Use: Non-exclusive commercial deployment is governed by the underlying CC BY 4.0 terms, provided full attribution to the authors and original publication is maintained.

References

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• Cahigas, M. M. L., Prasetyo, Y. T., Nadlifatin, R., Persada, S. F., & Gumasing, M. J. J. (2023). Determinants of continuous visiting behavior to Palawan, Philippines: Integrating Uncertainty Reduction Theory and Expectation Confirmation Theory. PLoS ONE, 18(10), Article e0291694. https://doi.org/10.1371/journal.pone.0291694
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• Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.1177/002224378001700405

Items of the Scale