Investigating the effects of ICT evolution and the COVID-19 pandemic on the spatio-temporal fragmentation of work activities

碎片(计算) 信息和通信技术 大流行 2019年冠状病毒病(COVID-19) Probit模型 人口经济学 工作(物理) 社会距离 信息通信技术 地理 经济地理学 计算机科学 计量经济学 医学 经济 工程类 机械工程 疾病 病理 万维网 传染病(医学专业) 操作系统
作者
Yu-Tong Cheng,Patricia Sauri Lavieri‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬,Ana Luiza Santos de Sá,Sebastián Astroza
出处
期刊:Transportation Research Part A-policy and Practice [Elsevier]
卷期号:187: 104192-104192 被引量:3
标识
DOI:10.1016/j.tra.2024.104192
摘要

The evolution of information and communication technologies (ICTs) has transformed how, where, and when work activities are performed. Additionally, the work-from-home (WFH) culture has gained traction as a public health strategy to reduce the spread of the COVID-19 virus in the past years. Hence, ICTs and the COVID-19 pandemic might have influenced spatial and temporal fragmentation of activities (dismantlement into multiple subtasks and episodes) and changed activity-travel behaviour. In this context, this study investigates the effects of the ICT evolution along with the influence of the COVID-19 pandemic on the spatio-temporal fragmentation of work activities. Data from the American Time Use Survey from 2003 to 2020 is used to jointly estimate a multiple discrete–continuous probit and multivariate hurdle count model (MDCP-MC). Spatio-temporal fragmentation effects are evaluated considering work activities in three location categories: (1) workplace, (2) home, and (3) other places. Among the study's main results, first, we observe that ICT evolution led to an increase in the spatial fragmentation of work, as time allocated to work activities in the workplace was transferred into WFH and work from other places. Second, during the COVID-19 pandemic, decreased spatial fragmentation was observed due to stay-at-home social distancing measures. However, temporal fragmentation of work was intensified during the pandemic, especially when individuals worked from home. Finally, workers are found to fragment work differently depending on their socio-demographic characteristics. Specifically, income levels are associated with spatial work fragmentation driven by ICTs, while COVID-19-induced temporal work fragmentation is influenced by occupations and employment characteristics.

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