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<p>Nighttime leisure activities play a crucial role in enhancing the quality of life for urban residents. However, existing studies have rarely differentiated the diverse spatial contexts in which nighttime leisure-related activities occur, limiting understanding of their spatiotemporal patterns and underlying mechanisms. This study aims to fill this gap by integrating mobile phone signaling data with areas of interest (AOI) datasets to systematically analyze the spatial and temporal distribution and determinants of nighttime leisure activities among residents in Guangzhou, China. We categorize leisure areas into four types to capture the diversity of nighttime leisure activities. Employing an optimal-parameter-based geographical detector model, we investigate the independent and interactive effects of various factors influencing nighttime leisure activities. Our findings reveal that among the four types of leisure areas, commercial service areas are the most popular venues for nighttime activity. Furthermore, high accessibility and well-developed surrounding facilities are identified as crucial factors facilitating nighttime leisure engagement. This study enriches the theoretical framework of urban leisure behavior by highlighting the spatiotemporal complexities and the distinctive driving factors of nighttime leisure. These findings advance the theoretical understanding of nighttime leisure dynamics and provide scientific guidance for urban nightlife management.</p>

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Understanding nighttime leisure activities in various urban leisure spaces: a multi-factor interaction perspective based on mobile signaling data

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月21日

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  • Chengzhi Zhang,
  • Shaoli Li,
  • Shaoying Li,
  • Caigang Zhuang,
  • Feng Gao,
  • Zhifeng Wu

摘要

Nighttime leisure activities play a crucial role in enhancing the quality of life for urban residents. However, existing studies have rarely differentiated the diverse spatial contexts in which nighttime leisure-related activities occur, limiting understanding of their spatiotemporal patterns and underlying mechanisms. This study aims to fill this gap by integrating mobile phone signaling data with areas of interest (AOI) datasets to systematically analyze the spatial and temporal distribution and determinants of nighttime leisure activities among residents in Guangzhou, China. We categorize leisure areas into four types to capture the diversity of nighttime leisure activities. Employing an optimal-parameter-based geographical detector model, we investigate the independent and interactive effects of various factors influencing nighttime leisure activities. Our findings reveal that among the four types of leisure areas, commercial service areas are the most popular venues for nighttime activity. Furthermore, high accessibility and well-developed surrounding facilities are identified as crucial factors facilitating nighttime leisure engagement. This study enriches the theoretical framework of urban leisure behavior by highlighting the spatiotemporal complexities and the distinctive driving factors of nighttime leisure. These findings advance the theoretical understanding of nighttime leisure dynamics and provide scientific guidance for urban nightlife management.