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Measurement of happiness of daily activity-travel schedules
Travel Behaviour and Society ( IF 5.850 ) Pub Date : 2024-04-17 , DOI: 10.1016/j.tbs.2024.100807
Hui Shi , Jingyi Xiao , Rongxiang Su , Konstadinos G. Goulias

Although the relationship between travel and quality of life has garnered much research interest, we find a gap in understanding the correlation among daily activity-travel patterns, location characteristics and happiness. In this study, the 2017 National Household Travel Survey (NHTS) in California and the 2017 and 2013 American Time Use Surveys (ATUS) are merged to estimate the happiness of daily activity-travel schedules. Prior to the merging of ATUS and NHTS data, hierarchical clustering is employed to identify and harmonize daily patterns. Then, the weighted duration proportion of each home activity for each daily patternand the average happy score for each activity are transferred from ATUS to NHTS. The individual happiness index issubsequentlycalculated for NHTS records and determinants of this index analyzed using an ordinary least square regression (OLS) model and a spatial lag model (SLM) to account for spatial correlation. The outcomes demonstrate that the SLM outperforms the OLS, with a better fit to the data and a smaller spatial correlation of unexplained variation. People's daily activity-travel pattern happiness is affected by their personal attributes, household characteristics, land use surrounding their residence, and added spatial correlation with the happiness of their neighbors. This analysis shows the feasibility and potential of transferring data between ATUS and NHTS, substantial and observable heterogeneity in the spatial clustering of happiness, and possible new ways of exploring emotions in activity-travel patterns.

中文翻译:

日常活动-旅行安排的幸福感测量

尽管旅行与生活质量之间的关系引起了很多研究兴趣,但我们发现在理解日常活动-旅行模式、地点特征和幸福感之间的相关性方面存在差距。在这项研究中,将 2017 年加利福尼亚州全国家庭旅行调查 (NHTS) 以及 2017 年和 2013 年美国时间使用调查 (ATUS) 合并起来,以估算日常活动-旅行安排的幸福感。在合并 ATUS 和 NHTS 数据之前,采用层次聚类来识别和协调日常模式。然后,将每个日常模式的每个家庭活动的加权持续时间比例和每个活动的平均快乐得分从 ATUS 传输到 NHTS。随后计算 NHTS 记录的个人幸福指数,并使用普通最小二乘回归 (OLS) 模型和空间滞后模型 (SLM) 分析该指数的决定因素以考虑空间相关性。结果表明,SLM 优于 OLS,更适合数据并且无法解释的变化的空间相关性更小。人们的日常活动-出行模式幸福感受到个人属性、家庭特征、居住周围土地利用的影响,并与邻居的幸福感增加了空间相关性。该分析显示了 ATUS 和 NHTS 之间传输数据的可行性和潜力、幸福空间聚类中显着且可观察到的异质性,以及探索活动-旅行模式中情感的可能新方法。
更新日期:2024-04-17
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