Memorable Tourism Experiences: Bridging the Experience Economy and Spatial Hotspot Analysis
DOI:
https://doi.org/10.55980/ebasr.v5i1.412Keywords:
Rapid Appraisal for Tourism , Competitiveness , Multidimensional , Scaling , Spatial ClusteringAbstract
This study develops an integrated framework for sustainable tourism competitiveness by combining Memorable Tourism Experience (MTE), RAPTOURISM, explainable machine learning, and spatial analysis. Using survey data from coastal destinations in Kupang City and Kupang Regency, sustainability performance is evaluated through Multidimensional Scaling (MDS) and tested using Monte Carlo simulation. The goodness-of-fit results indicate strong model reliability, with stress values below 0.20 and R² exceeding 0.90 across most dimensions. Monte Carlo differences remain minimal, confirming the robustness of the sustainability index. Random Forest analysis identifies Meaningfulness, Eudaimonic Well-Being (EWB), and Involvement as the most influential attributes. Partial Dependence Plot (PDP) reveals non-linear threshold effects, showing that improvements in EWB significantly increase sustainability only when accompanied by high tourist involvement. Spatial hotspot–coldspot analysis using Getis–Ord Gi* demonstrates clear geographical clustering, with eastern coastal destinations forming experience hotspots, while several western areas persist as coldspots. These findings emphasize the need for place-based, experience-driven tourism policies to enhance long-term sustainability.
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Copyright (c) 2026 Rikhard Titing Christopher Bolang, Novi Theresia Kiak, Apriana Horiana Julia Fanggidae, Alexander Leonidas Kangkan
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