Abstract
Objective: Using artificial neural network models and cluster analysis, this study analyzed and predicted the intention to use digital leisure services among the elderly based on their adoption of non-face-to-face services.
Methods: Utilizing raw data from the 2022 Urban Policy Indicator Survey, 2,239 residents of Seoul aged 50 and above were selected for the study. The research predicted the intention to use non-contact leisure services based on demographic characteristics, adaptability to non-face-to-face environments, and frequency of social media usage. Collected data were processed using SPSS 23 and Modeler 14.2, and subjected to frequency analysis, hierarchical clustering, K-means clustering analysis, artificial neural network analysis, logistic regression analysis, cross-tabulation analysis, and one-way ANOVA.
Results: The results identified four clusters. Cluster 3, comprising males in their 60s living with their families, showed the strongest intention to use digital leisure services despite low social media usage and high adaptability to non-face-to-face environments.
Conclusion: This suggests that policies and programs to promote the use of digital leisure services among the elderly should enhance digital accessibility and adaptability to non-face-to-face environments. Additionally, given the limitations of the research subjects and data, further research is needed on a broader age range and more diverse sample of the elderly population. The study also emphasizes the need for digital education programs for the elderly and the provision of leisure services through various digital platforms.