Drivers of self-reported destination loyalty intentions in an emerging tourism destination: A PLS-SEM study of tourists in Da Nang, Vietnam

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Type of the article: Research Article

Abstract
Growing competition among global tourism destinations has made it essential to understand what drives tourists to intend to return and recommend a place. This study aims to examine the direct and indirect relationships among destination image, tourist motivation, perceived value, destination experience, destination satisfaction, and destination loyalty intentions in Da Nang, Vietnam, in order to identify the key drivers of self-reported tourist loyalty in an emerging tourism destination. Data were collected from 428 international and domestic tourists who visited Da Nang between September and December 2024 through a structured questionnaire distributed both on-site and online. Respondents were recruited through non-probability convenience and intercept sampling among tourists aged 18 or older who were present at the destination during the study period. Partial Least Squares Structural Equation Modeling was used to test thirteen hypotheses. The results show that destination image significantly influences perceived value (β = 0.330, p < 0.001) and destination experience (β = 0.201, p = 0.003), but has no direct effect on satisfaction or loyalty intentions. Tourist motivation directly shapes perceived value (β = 0.173, p = 0.003), destination experience (β = 0.330, p < 0.001), and loyalty intentions (β = 0.113, p = 0.024). Perceived value is the strongest direct predictor of loyalty intentions (β = 0.367, p < 0.001), and destination experience is the primary driver of satisfaction (β = 0.394, p < 0.001). Because the loyalty outcome captures self-reported behavioral intentions rather than observed repeat behavior, the findings suggest that destination managers should prioritize enhancing perceived value and experiential quality over image-based marketing alone to build long-term tourist loyalty in emerging markets.

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    • Figure 1. The conceptual model
    • Figure 2. The confirmed model
    • Table 1. Demographic profile of participants
    • Table 2. Construct reliability and validity from PLS-SEM estimation
    • Table 3. R2 values of the model
    • Table 4. Effect size of the model
    • Table 5. Fornell-Larcker criterion from PLS-SEM estimation
    • Table 6. Confidence intervals bias corrected of HTMT values from PLS-SEM estimation (bootstrapping)
    • Table 7. Path coefficients from PLS-SEM estimation (bootstrapping)
    • Table A1. Constructs
    • Conceptualization
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Data curation
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Formal Analysis
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Investigation
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Methodology
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Project administration
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Software
      Pham Quang Tin
    • Supervision
      Pham Quang Tin
    • Validation
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Visualization
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Writing – original draft
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi
    • Writing – review & editing
      Pham Quang Tin, Minh-Chau Pham, Yen-Ngoc Vo-Thi