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Analyzing guests' preferences for Airbnb bookings in Japan using machine learning algorithms.
James Ryan Fernandez1, Maela Madel L Cahigas2, Jaime Vega Bautista1
1School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila, 1002, Philippines; School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila, 1002, Philippines.
Acta Psychologica
|April 24, 2026
Summary
Understanding Airbnb guest satisfaction in Japan is crucial. Machine learning identified Accuracy, Value, and Communication as key drivers, with logistic regression achieving 98.92% accuracy in predicting ratings.
Area of Science:
- * Travel and Tourism
- * Data Science and Machine Learning
- * Consumer Behavior Analysis
Background:
- * Growing global popularity of Airbnb necessitates market-specific research.
- * Limited understanding of guest behavior in the Asian Airbnb market, especially Japan.
- * Previous studies primarily focused on Western markets, leaving an Asian research gap.
Purpose of the Study:
- * To predict Airbnb's overall rating status in Japan using listing sub-scores.
- * To identify key factors influencing guest satisfaction within the Japanese Airbnb market.
- * To bridge the knowledge gap regarding Asian Airbnb consumer behavior.
Main Methods:
- * Application of machine learning classifiers: Support Vector Machines (SVM), Decision Trees (DT), Random Forests (RF), and Logistic Regression (LR).
- * Prediction of binary overall rating status using listing-level star sub-scores.
- * Feature importance analysis to determine key drivers of guest satisfaction.
Main Results:
- * Logistic Regression model achieved the highest accuracy (98.92%) in predicting guest ratings.
- * Accuracy (24.39%), Value (23.80%), and Communication (16.79%) were identified as the most critical factors for guest satisfaction.
- * Japan reported 98.51% positive Airbnb feedback, with Communication satisfaction at 99.06%.
Conclusions:
- * This study is the first to highlight the significant impact of the 'Accuracy' factor in the Asian Airbnb market.
- * The findings provide actionable insights for Airbnb hosts in Japan to improve guest experiences.
- * Enhanced guest satisfaction can contribute positively to the growth of Japan's tourism sector.
