Unveiling daily activity pattern differences between telecommuters and commuters using human mobility motifs and sequence analysis

Impact of working from home on activity-travel behavior during the COVID-19 Pandemic: An aggregate structural analysis

“…Similarly, counties with a low median income tended to have a lower WFH proportion compared to middle and high median income counties. Similar findings were reported in Su et al (2021) for the pre-pandemic period and in Rafiq et al (2020) and Beck and Hensher (2020a) for the during-pandemic period. As anticipated, counties having a longer commute time on average had a higher WFH proportion compared to medium commute time (positive effect).…”

Assessment of the Bus Transit Network: A Perspective from the Daily Activity-Travel Organization of Travelers

“…Depending on the nature of the data (call detail records, GPS, travel surveys) and the definition of the motif (location-or activity-based), motif-related research shows between 10 and 17 motifs that can capture 90% of the population activity-travels. These motifs also show spatio-temporal regularity and stability over several months [16][17][18][19][20]. This tends to confirm that typical locational and activity patterns exist and can be leveraged to capture a greater diversity of activity-travel behaviors.…”

The role of pre-pandemic teleworking and E-commerce culture in the COVID-19 dispersion in Europe

“…A recent study on pre- COVID-19 US data (Su et al. 2021 ) demonstrates that while telecommuters were more likely to stay at home during a workday, they exhibit more diversity in their trip destinations and time, as well as increased trips and vehicle miles traveled compared to regular commuters. Even though the population and circumstance of our analysis are different, another study also points to teleworking as the culprit for the increased number of trips during the pandemic (Riggs 2020 ).…”