Travel behavior and activity resilience regarding the COVID-19 pandemic in Brazil: An approach based on smartphone panel data

Thayanne Gabryelle Medeiros Ciriaco; Cira Souza Pitombo; Lucas Assirati

doi:10.1016/j.cstp.2023.100998

Travel behavior and activity resilience regarding the COVID-19 pandemic in Brazil: An approach based on smartphone panel data

Case Stud Transp Policy. 2023 Jun:12:100998. doi: 10.1016/j.cstp.2023.100998. Epub 2023 Mar 30.

Authors

Thayanne Gabryelle Medeiros Ciriaco¹, Cira Souza Pitombo¹, Lucas Assirati¹

Affiliation

¹ Department of Transportation Engineering, São Carlos School of Engineering, University of São Paulo, São Carlos, Brazil.

Abstract

The COVID-19 pandemic has caused significant changes around the world. The circumstances resulted in a radical shift in people's lives, including the way they move around the cities and/or carry out their activities. This study carries out a travel behavior analysis using commuting panel data collected over 7 days using smartphones. The study focuses on the Maceió Metropolitan Area (MMA), which is in the state of Alagoas in the northeast region of Brazil. Cluster analysis, using the k-means algorithm, divided the sample into three groups of travel behavior: Group A ("Infrequent travelers, for work or shopping trip purposes and very prone to do remote work"), Group B ("Intermediate travelers, for work or shopping trip purposes and prone to do remote work"), and Group C ("Frequent travelers, for work or meal purchases and not likely to do remote work"). Groups B and C are predominantly formed by individuals who carry out activities that are less likely to do remote work. By analyzing the groups, it is possible to understand the changes that occurred during the period studied (September/October 2020) and what are the expectations for a post-pandemic scenario, associated with each behavioral group. It was observed that "Working" was the main trip purpose during the pandemic and that the possibility of teleworking depends on the type of activity carried out. Making a scale of the resilience of activities considering the replacement of out-of-home activities by in-home remote activities, it can be observed that Group A was the most resilient, followed by Group B and C, respectively. For the post-pandemic scenario, Groups A and B are also the most likely to use Information and Communication Technologies (ICTs) and continue carrying out other remote activities, such as grocery shopping and meals, replacing, in the future, predominantly trips using ICTs.

Keywords: Case study; Cluster analysis; Disruptive event; Post-pandemic scenario; Remote activities; Resilience.