Factors Influencing the Usage Frequency of Community Elderly Care Facilities and Their Functional Spaces: A Multilevel Based Study DOI Creative Commons
Wen Fang, Yan Zhang, Pengcheng Du

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(6), P. 1827 - 1827

Published: June 15, 2024

The construction of community elderly care facilities (CECF) is pivotal for promoting healthy aging and “aging in place” older people. This study focuses on the low utilization rates Dongcheng Xicheng Districts, core areas Beijing. explainable machine learning method used to analyze data across three dimensions: elderly’s individual attributes, characteristics station (CECS), features built environment around CECS subdistrict, identify important factors that influence usage frequency overall its different functional spaces, also correlation between CECS. It shows most are CSCF, including degree space acceptance satisfaction with services provided, which nine spaces (R2 ≥ 0.68) = 0.56). In addition, people’s factors, such as age physical condition, significantly specific rehabilitation therapy rooms assistive bathing rooms. relatively low, density bus stations housing prices within subdistrict mean distance from CECF nearest subway being more important. These findings provide a reference indoor environments, management service quality, optimal site selection future facilities.

Language: Английский

Indoor and outdoor airflow modeling in built and urban environments by water tank and channel experiments: A review DOI
Yifei Wang, Jian Hang,

Ziwei Mo

et al.

Building Simulation, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 26, 2025

Language: Английский

Citations

0
Three in Motion: A Mobile Study on the Interlinked Dynamics of CO2, Air Temperature, and PM2.5 DOI
Yuyang Zhang,

Dingyi Yu,

Daoyong Li

et al.

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: 506, P. 145449 - 145449

Published: April 15, 2025

Language: Английский

Citations

0
Powering the future: Unraveling residential building characteristics for accurate prediction of total electricity consumption during summer heat DOI
Yuyang Zhang,

Wenke Ma,

Pengcheng Du

et al.

Applied Energy, Journal Year: 2024, Volume and Issue: 376, P. 124146 - 124146

Published: Aug. 15, 2024

Language: Английский

Citations

3
Assessing bicycle safety risks using emerging mobile sensing data DOI

Yan Li,

Yuyang Zhang, Ying Long

et al.

Travel Behaviour and Society, Journal Year: 2024, Volume and Issue: 38, P. 100906 - 100906

Published: Sept. 20, 2024

Language: Английский

Citations

2
Factors Influencing the Usage Frequency of Community Elderly Care Facilities and Their Functional Spaces: A Multilevel Based Study DOI Creative Commons
Wen Fang, Yan Zhang, Pengcheng Du

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(6), P. 1827 - 1827

Published: June 15, 2024

The construction of community elderly care facilities (CECF) is pivotal for promoting healthy aging and “aging in place” older people. This study focuses on the low utilization rates Dongcheng Xicheng Districts, core areas Beijing. explainable machine learning method used to analyze data across three dimensions: elderly’s individual attributes, characteristics station (CECS), features built environment around CECS subdistrict, identify important factors that influence usage frequency overall its different functional spaces, also correlation between CECS. It shows most are CSCF, including degree space acceptance satisfaction with services provided, which nine spaces (R2 ≥ 0.68) = 0.56). In addition, people’s factors, such as age physical condition, significantly specific rehabilitation therapy rooms assistive bathing rooms. relatively low, density bus stations housing prices within subdistrict mean distance from CECF nearest subway being more important. These findings provide a reference indoor environments, management service quality, optimal site selection future facilities.

Language: Английский

Citations

0