Barbour Natalia, Menon Nikhil, Mannering Fred
Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX Delft, Netherlands.
Center for Urban Transportation Research (CUTR), 4202 E. Fowler Avenue, CUT 100, Tampa, FL 33620, USA.
Transp Res Interdiscip Perspect. 2021 Sep;11:100441. doi: 10.1016/j.trip.2021.100441. Epub 2021 Aug 10.
Responses to the COVID-19 pandemic have dramatically transformed industry, healthcare, mobility, and education. Many workers have been forced to shift to work-from-home, adjust their commute patterns, and/or adopt new behaviors. Particularly important in the context of mitigating transportation-related emissions is the shift to work-from-home. This paper focuses on two major shifts along different stages of the pandemic. First, it investigates switching to work-from-home during the pandemic, followed by assessing the likelihood of continuing to work-from-home as opposed to returning to the workplace. This second assessment, being conditioned on workers having experienced work-from-home as the result of the pandemic, allows important insights into the factors affecting work-from-home probabilities. Using a survey collected in July and August of 2020, it is found that nearly 50 percent of the respondents who did not work-from-home before but started to work-from-home during the COVID-19 pandemic, indicated the willingness to continue work-from-home. A total of 1,275 observations collected using the survey questionnaire, that was administered through a U.S. nationwide panel (Prime Panels), were used in the model estimation. The methodological approach used to study work-from-home probabilities in this paper captures the complexities of human behavior by considering the effects of unobserved heterogeneity in a multivariate context, which allows for new insights into the effect of explanatory variables on the likelihood of working from home. Random parameters logit model estimations (with heterogeneity in the means and variances of random parameters) revealed additional insights into factors affecting work-from-home probabilities. It was found that gender, age, income, the presence of children, education, residential location, or job sectors including marketing, information technologies, business, or administration/administrative support all played significant roles in explaining these behavioral shifts and post-pandemic preferences.
对新冠疫情的应对措施极大地改变了行业、医疗保健、出行和教育。许多员工被迫转向居家办公，调整通勤模式，和/或采取新的行为方式。在减少与交通相关的排放背景下，向居家办公的转变尤为重要。本文聚焦于疫情不同阶段的两个主要转变。首先，研究疫情期间转向居家办公的情况，接着评估继续居家办公而非返回工作场所的可能性。这第二个评估以员工因疫情而经历过居家办公为条件，有助于深入了解影响居家办公概率的因素。通过对2020年7月和8月收集的一项调查进行分析发现，在新冠疫情期间之前没有居家办公但开始居家办公的受访者中，近50%表示愿意继续居家办公。使用通过美国全国性面板（Prime Panels）进行管理的调查问卷收集的总共1275个观测数据用于模型估计。本文用于研究居家办公概率的方法通过在多变量背景下考虑未观察到的异质性的影响，捕捉了人类行为的复杂性，这使得能够对解释变量对居家办公可能性的影响有新的见解。随机参数logit模型估计（随机参数的均值和方差存在异质性）揭示了影响居家办公概率的因素的更多见解。研究发现，性别、年龄、收入、是否有孩子、教育程度、居住地点，或包括市场营销、信息技术、商业或行政/行政支持在内的工作部门，在解释这些行为转变和疫情后的偏好方面都发挥了重要作用。
