Comparing households with every member out-of-home in developing countries using travel surveys

Comparing households with every member out-of-home in developing countries using travel surveys
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DOI:
10.1016/j.cities.2023.104351
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发表时间:
2023-08
期刊:
影响因子:
6.7
通讯作者:
T. Nakayama;Yoshihiro Sato;T. Maruyama
T. Nakayama;Yoshihiro Sato;T. Maruyama
中科院分区:
经济学1区
文献类型:
--
作者:
T. Nakayama;Yoshihiro Sato;T. Maruyama

文献摘要

相似文献

了解无人在家的情况是很重要的,因为这项检查可以帮助分析几个城市问题,包括送货上门失败和抢劫。在日本,有几项研究使用家庭旅行调查数据调查了所有成员都不在家的家庭(HEMO),但其他国家的数据尚未得到探讨。在这项研究中,我们使用1996年至2013年的家庭旅行调查数据比较了全球14个城市的HEMO率,揭示了城市的独特特征。时间分配和Tobit模型分析了HEMO持续时间,二元logit模型探索了HEMO速率分布。结果显示,主要位于亚洲,非洲和拉丁美洲的目标城市的HEMO情况的差异。这些差异可以归因于生活方式和文化。在保守文化的城市中观察到较低的HEMO发生率,其中女性通常留在家中(例如,卡拉奇)和家庭规模较大的城市(例如,马尼拉、马那瓜、贝伦和河内)。通过工业化,HEMO发生率和持续时间往往随着人均GDP的增加而增加。这项研究表明,家庭出行调查,主要用于交通规划,也可以用来揭示城市的特点,通过确定其HEMO配置文件。
Understanding the nobody-at-home situation is important because the examination can help analyze several urban problems, including home-delivery failures and burglaries. Several studies have investigated households with every member out-of-home (HEMO) using household travel survey data in Japan, but the data from other countries remain unexplored. In this study, we compared the HEMO rates in 14 cities worldwide using household travel survey data from 1996 to 2013, revealing unique features of cities. The time allocation and Tobit models analyzed the HEMO durations, and the binary logit models explored the HEMO rate profile. The results revealed the differences in the HEMO situation of the target cities located primarily in Asia, Africa, and Latin America. These differences can be attributed to lifestyle and culture. Lower HEMO rates were observed in cities with a conservative culture where females typically remain at home (e.g., Karachi) and cities with larger household sizes (e.g., Manila, Managua, Belem, and Hanoi). HEMO rates and durations tended to increase with GDP per capita via industrialization. This study shows that household travel surveys, which have mainly been used in transportation planning, can also be used to reveal city features by identifying their HEMO profiles.