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A latent class accelerated hazard model of social activity duration

机译：社会活动持续时间的潜在类加速危害模型

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Over the past decade, activity scheduling processes have gained increasing attention in the field of transportation research. However, still little is known about the scheduling of social activities even though these activities account for a large and growing portion of trips. This paper contributes to this knowledge. We analyze how the duration of social activities is influenced by social activity characteristics and characteristics of the relationship between the respondent and the contacted person(s). To that end, a latent class accelerated hazard model is estimated, based on social interaction diary data that was collected in the Netherlands in 2008. Chi-square tests and analyses of variance are used to test for significant relations between the latent classes and personal and household characteristics. Findings suggest that the social activity characteristics and the characteristics of the relationship between the socializing persons are highly significant in explaining social activity duration. This shows that social activities should not be considered as a homogenous set of activities and it underlines the importance of including the social context in travel-behavior models. Moreover, the results indicate that there is a substantial amount of latent heterogeneity across the population. Four latent classes are identified, showing different social activity durations, and different effects for both categories of explanatory variables. Latent class membership can be explained by household composition, socio-economic status (education, income and work hours), car ownership and the number of interactions in 2 days.
机译：在过去的十年中，活动调度过程在交通研究领域越来越受到关注。但是，尽管社交活动的安排占出行的大部分且在不断增长，但对社交活动的安排知之甚少。本文为这一知识做出了贡献。我们分析了社交活动的持续时间如何受到社交活动特征以及受访者与被联络人之间的关系特征的影响。为此，根据2008年在荷兰收集的社交互动日记数据，估算了潜在类别加速危害模型。卡方检验和方差分析用于检验潜在类别与个人和个人之间的重要关系。家庭特征。研究结果表明，社交活动特征和社交人群之间的关系特征在解释社交活动持续时间方面具有重要意义。这表明，社交活动不应被视为同类活动，并且强调了将社交环境纳入旅行行为模型的重要性。此外，结果表明整个人群中存在大量潜在的异质性。确定了四个潜在类别，分别显示了不同的社会活动持续时间和两种解释变量类别的不同影响。潜在的班级成员身份可以通过家庭组成，社会经济状况（教育，收入和工作时间），汽车拥有量以及两天内的互动次数来解释。

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