고령자의 Aging in Place를 위한 주거환경 만족도 영향요인 분석 : 기계학습 및 Impact Asymmetry Analysis 방법론을 활용하여

초록

Aging in Place (AIP) has become a fundamental approach in global welfare policies for older people, reflecting their natural desire to remain in familiar homes and neighborhoods as their health and functionality decline. AIP is not only aimed at enhancing individual well-being and quality of life but it is also viewed as a solution to support sustainable development in aging societies. For AIP to be successful, it is essential that older people are highly satisfied with their residential environment, which plays a critical role in its sustainability. This study focused on individuals ≥65 years old, in Korea, aiming to identify the key neighborhood environment factors that influence residential satisfaction. Using the Gradient Boosting Decision Tree algorithm, the relative importance of various factors was determined, followed by an Impact Asymmetry Analysis to assess their asymmetric effects on satisfaction. The factors were categorized into five types: Frustrator, Dissatisfier, Hybrid, Satisfier, and Delighter. The results revealed that satisfaction with housing significantly influenced residential environment satisfaction across all age groups. Additionally, for older age groups, the safety and crime prevention factor was identified as a key area for improving residential environment satisfaction. This study provides important policy implications for enhancing the residential satisfaction and quality of life of older people in Korea.

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