Creative Tourist Segmentation for Nature-Based Tourism: A Social Media Framework for Sustainable Recreation Planning and Development in Thailand’s National Parks
Abstract
1. Introduction

2. Materials and Methods
2.1. Research Framework
2.2. Data Collection
2.2.1. Part 1: Selection of Creative Tourism Activities
2.2.2. Part 2: Visitor Survey
2.3. Data Analysis
2.3.1. Part 1: Identification of Creative Tourism Activities in National Parks
2.3.2. Part 2: Visitor Segmentation
- Descriptive Analysis: Descriptive statistics were used to summarize the demographic and trip characteristics of the respondents. This included variables such as age, gender, education level, travel group type, and purpose of visit. These data provided a general profile of national park visitors and served as a contextual foundation for the segmentation process.
- Cluster Formation: To classify visitors into distinct groups, a hybrid clustering approach was applied. Traditional hierarchical and k-means procedures were first tested but produced unstable results due to the heterogeneity of visitor interests. Therefore, to ensure interpretive clarity and practical applicability for recreation management, respondents were allocated to clusters corresponding to the factor with the highest mean score among the three main factors including (1) level of interest in creative tourism activities, (2) social media use patterns, and (3) tourism characteristics, cluster analysis was applied to group individuals by their dominant interests. This approach represents a dominant-preference classification, which identifies the primary behavioral or motivational tendency of each respondent. While this method differs from traditional statistical clustering procedures, it provides a transparent and behaviorally interpretable segmentation structure that aligns with the study’s managerial objectives. To address potential limitations related to within-group variability and statistical generalizability, the classification results were validated against k-means clustering outputs, which revealed consistent segment patterns. This validation enhances methodological transparency and conceptual coherence, supporting the application of segmentation in protected area management and sustainable tourism planning.
- Comparative and Inferential Analysis: To compare segments, mean scores across media format preferences and content influence were analyzed. Media format influence was rated using a 5-point Likert scale, while content influence was measured with binary (Yes/No) responses. Chi-square tests were used to assess statistical differences in demographic and trip-related variables across clusters. Where significant associations were found, post hoc comparisons were conducted. All tests were performed at a 95% confidence level (p < 0.05), with confidence intervals reported as appropriate.
3. Results
3.1. Examining Creative Tourism Activities Within Thailand’s National Parks
3.1.1. Identification and Selection of Creative Tourism Activities
3.1.2. Factor Analysis of Creative Tourism Activities
3.2. Visitor Segments Based on Creative Activity Preferences and Social Media Engagement Patterns
3.2.1. Demographic Profiles of Respondents
3.2.2. Visitor Segmentation and Behavioral Profiles
4. Discussion
4.1. Theoretical Contributions and Extensions of the Creative Tourism Framework
4.2. Digital Engagement, Media Effects, and Generational Influences
4.3. Methodological Reflections and Research Limitations
4.4. Practical and Managerial Implications for Creative Tourism Development in Protected Areas
- Broaden the Creative Tourism Landscape in Nature-Based Contexts: While creative tourism has traditionally been associated with urban or heritage settings, this study confirms its strong relevance in natural environments. Activities such as birdwatching workshops, survival training, forest cooking, craft-making, and conservation volunteering align with participatory and skill-building principles central to creative tourism [28]. National parks can therefore be positioned not only as sites for recreation but also as platforms for learning, cultural exchange, and personal growth.
- Design Targeted Programs for Distinct Visitor Segments: The five visitor clusters (Local advocates, Nature explorers, Food enthusiasts, Nature Learners, and Diverse Enthusiasts) demonstrate the need for differentiated programming. Creative activities should reflect each segment’s motivations and behaviors. For example, immersive visual content for Nature explorers, culinary sustainability for Food enthusiasts, and community-based workshops for Local advocates.
- Enhance Community Engagement and Local Economic Participation: The growing interest in local culture and products underscores the importance of integrating community enterprises into park-based experiences. While such initiatives exist, they often lack visibility or interpretive depth. Strengthening storytelling, cultural interpretation, and emotional connection can increase visitor engagement and generate tangible benefits for local livelihoods.
- Leverage Media Strategies to Deepen Engagement: Although visual media broadly influence all visitor groups, learning-oriented segments also respond to text-based and educational content. Communication strategies should align content formats with their intended functions, such as short videos for visual appeal, infographics for education, and livestreams for real-time interaction. Segment-specific media approaches can therefore enhance both emotional resonance and cognitive engagement.
- Promote Transformative Engagement: Creative tourism should cultivate emotional engagement that inspires reflection, learning, and environmental stewardship. By embedding conservation messages within participatory experiences—such as QR-tagged scenic trails, interactive interpretation, or behind-the-scenes storytelling—parks can shift visitors from passive observation to active advocacy. This approach aligns with transformative learning theory and supports long-term sustainability objectives.
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
| EFA | Exploratory Factor Analysis |
| DNP | Department of National Parks, Wildlife, and Plant Conservation |
| ELM | The Elaboration Likelihood Model |
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| Analysis Component | Statistical Method | Purpose/Objective |
|---|---|---|
| Raw Mean-Based Clustering | To categorize tourists into distinct groups based on their major preferences for creative tourism activities. |
| Mean Comparison and Cross-tabulation | To examine and summarize differences in activity preferences, media usage, and content engagement across the identified segments. |
| Chi-square Test | To identify statistically significant differences in demographic characteristics and content preferences among visitor clusters. |
| Post hoc Tests | To determine specific variables or items that differ significantly between individual visitor clusters. |
| Creative Tourism Activity Spectrum | |||
|---|---|---|---|
| Buying | Seeing | Tasting | Learning |
|
|
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| Creative Tourism Activities | Exp | ||||
|---|---|---|---|---|---|
| Mean | Loading | Eigen Values | % of Variance | Cronbach | |
| Group 1: Nature-based learning | 10.51 | 52.571 | 0.819 | ||
| 3.83 | 0.772 | |||
| 3.78 | 0.793 | |||
| 3.73 | 0.862 | |||
| 3.67 | 0.839 | |||
| 3.60 | 0.900 | |||
| 3.54 | 0.905 | |||
| Group 2: Scenic immersion | 1.61 | 8.061 | 0.827 | ||
| 4.13 | 0.865 | |||
| 4.02 | 0.893 | |||
| 4.00 | 0.907 | |||
| 3.90 | 0.815 | |||
| 3.86 | 0.759 | |||
| Group 3: Community participation | 1.43 | 7.128 | 0.845 | ||
| 3.71 | 0.739 | |||
| 3.56 | 0.823 | |||
| 3.52 | 0.845 | |||
| 3.49 | 0.787 | |||
| 3.48 | 0.849 | |||
| Group 4: Culinary activities | 0.990 | 4.947 | 0.803 | ||
| 3.95 | 0.858 | |||
| 3.90 | 0.830 | |||
| 3.80 | 0.869 | |||
| 3.78 | 0.851 | 10.51 | ||
| Total Variance Explained and Cronbach Alpha of All items | 72.707 | 0.862 | |||
| Group of Creative Tourism Activity | Cluster | F | p-Value | ||||
|---|---|---|---|---|---|---|---|
| Local Advocates | Nature Explorers | Food Enthusiasts | Nature-Based Learners | Diverse Enthusiasts | |||
| Nature-based learning | 3.38 | 3.41 | 3.57 | 4.00 | 3.95 | 31.66 | 0.000 |
| Scenic immersion | 3.50 | 4.28 | 3.79 | 3.58 | 4.04 | 33.56 | 0.000 |
| Community participation | 3.96 | 3.31 | 3.42 | 3.38 | 3.74 | 26.48 | 0.000 |
| Culinary activities | 3.38 | 3.53 | 4.31 | 3.56 | 4.03 | 56.39 | 0.000 |
| Frequency | 70 | 289 | 232 | 86 | 456 | ||
| % | 6.18 | 25.50 | 20.48 | 7.59 | 40.25 | ||
| Cluster | Creative Activities Interest | Media Preference | Trip Character | |
|---|---|---|---|---|
| 1. | Local Advocates |
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| 2. | Nature explorers |
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| 3. | Food enthusiasts |
|
|
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| 4. | Nature learners |
|
|
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| 5. | Diverse enthusiasts |
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| Cluster | Dominant Interest | Transformative Strategy | Illustrative Activity or Content |
|---|---|---|---|
| Local advocates | Community-based products | Link local crafts to sustainability and forest ecosystems | Storytelling posts: “From Forest to Fabric”; maker interviews with conservation backstories |
| Nature explorers | Scenic landscapes, hiking, photography | Reframe scenic beauty through ecological interpretation | QR viewpoints: “Why This Forest Looks Like This”; “The Story of Erosion and Time” |
| Food enthusiasts | Tasting, cooking, food trails | Connect gastronomy to ecosystems and cultural traditions | Video series: “Cooking with Wild Herbs”; food heritage map with biodiversity links |
| Nature Learners | Workshops, birdwatching, volunteering | Transform passive learning into hands-on participation | Citizen science kits: “DIY Bird Logbook”; tree-tagging and habitat observation activities |
| Diverse Enthusiasts | High interest in all dimensions | Deliver integrated, immersive, and reflective experiences | Multi-sensory experiences: “Creative Learning Trail”, interactive maps, and Maker–Explorer–Taster checkpoints |
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Share and Cite
Sinsup, K.; Phumsathan, S. Creative Tourist Segmentation for Nature-Based Tourism: A Social Media Framework for Sustainable Recreation Planning and Development in Thailand’s National Parks. Sustainability 2025, 17, 10005. https://doi.org/10.3390/su172210005
Sinsup K, Phumsathan S. Creative Tourist Segmentation for Nature-Based Tourism: A Social Media Framework for Sustainable Recreation Planning and Development in Thailand’s National Parks. Sustainability. 2025; 17(22):10005. https://doi.org/10.3390/su172210005
Chicago/Turabian StyleSinsup, Kinggarn, and Sangsan Phumsathan. 2025. "Creative Tourist Segmentation for Nature-Based Tourism: A Social Media Framework for Sustainable Recreation Planning and Development in Thailand’s National Parks" Sustainability 17, no. 22: 10005. https://doi.org/10.3390/su172210005
APA StyleSinsup, K., & Phumsathan, S. (2025). Creative Tourist Segmentation for Nature-Based Tourism: A Social Media Framework for Sustainable Recreation Planning and Development in Thailand’s National Parks. Sustainability, 17(22), 10005. https://doi.org/10.3390/su172210005

