Aligning Cultural Tourism with SDGS: A Recommendation System Based on Frequent Patterns, Associations, and Correlations

Abstract

Objective: This study develops a recommendation system for cultural attractions in Bangkok, aligning with the Sustainable Development Goals (SDGs). The system aims to streamline travel planning and enhance tourist experiences by suggesting relevant attractions based on location and interests.   Theoretical Framework: The research utilizes association rules and data mining to identify patterns in tourist behavior, and recommender systems to provide personalized suggestions. It also incorporates principles of sustainable tourism, balancing economic, social, and environmental considerations.   Method: Data on 30 cultural attractions along Bangkok's BTS Skytrain green line was collected through interviews and questionnaires. The FP-Growth algorithm identified patterns and associations, generating rules for recommending attractions based on proximity and interests, while considering SDG alignment (cultural heritage, local communities, environmental impact). The method's performance was compared to decision tree and random forest approaches.   Results and Discussion: The proposed method generated five rules, achieving accuracy between 68.69% and 87.38%, outperforming the benchmark methods. The system's potential to improve tourist experiences, promote sustainable tourism, and aid urban planning is highlighted. Limitations include the dataset size and focus on a single transit line, suggesting future expansion and integration with SDG considerations.   Research Implications: The system can be integrated into platforms to provide personalized, SDG-conscious recommendations, enhancing experiences and encouraging responsible tourism. The study showcases data analytics' value in aligning tourism with the SDGs.   Originality/Value: The research introduces a novel approach, applying association rules for cultural attraction recommendations in Bangkok with an explicit SDG focus. The system's personalized recommendations based on location, interests, and SDG alignment streamline travel planning, foster fulfilling experiences, and contribute to the global sustainable development agenda.