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

Ciriaco, Thayanne Gabryelle Medeiros; Pitombo, Cira Souza; Assirati, Lucas

doi:10.1016/j.cstp.2023.100998

Cited by 3 publications

(3 citation statements)

References 49 publications

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“…It was found that the percentage of people opting for remote work is directly proportional to the reduction in trips to workplaces. Indeed, studies showed that the restrictive measures imposed by COVID-19 led to a greater adoption of teleactivities (including teleworking), resulting in significant impacts on mobility [14][15][16]69]. Although no economic variables were included in the model, the potential teleworking percentage was included, and it is widely recognized that remote work is typically associated with a high level of education, and consequently, high incomes [57,59,62].…”

Section: Discussion Regarding the Main Findingsmentioning

confidence: 99%

Relationships between Teleworking and Travel Behavior in the Brazilian COVID-19 Crisis

Dias

2023

Future Transportation

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The COVID-19 pandemic caused a significant shift towards teleworking, resulting in changes in travel patterns. The relationship between teleworking and individual travel behavior is crucial for transportation planning and policymaking. Thereby, this article investigates the relationships between teleworking, COVID-19, and mobility patterns in Brazil during two different periods of the COVID-19 pandemic. Given the exceptional nature of recent events, it is crucial to conduct studies related to teleworking during the pandemic crisis to contribute relevant information and evidence to the literature on this phenomenon. Such research has the potential to provide new insights and perspectives that enhance our understanding of the challenges and opportunities associated with teleworking. Two different approaches were used in the methodological procedure. The first approach used exploratory analysis to study public aggregated data related to the beginning of the pandemic, followed by a cluster analysis and a multinomial logit model. The second approach, relative to a longer relaxation period of sanitary/health measures, collected disaggregated self-reported data using an online survey, which were analyzed through non-parametric tests. The results show a strong relationship between the teleworking regime and the frequency of trips, especially for work purposes. It also highlights the influence of economic development and the region of Brazil in the kind of work regime. The continuation of studies, such as this one, in current periods is important for analyzing possible impacts, such as the reduction in congestion, vehicle emissions, and to enable the use of teleworking as a demand management policy.

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Section: Discussion Regarding the Main Findingsmentioning

confidence: 99%

Relationships between Teleworking and Travel Behavior in the Brazilian COVID-19 Crisis

Dias

2023

Future Transportation

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“…This way, the initial goal of achieving a representative sample was attenuated in order to increase the total sample size and investigate the technical aspects of data collection by smartphone and of further processing and analysis of the data. Indeed, this raises the concern of representativity as recruitment strategy and collection methods affect respondent characteristics [59,68] in terms of socio-demographic characteristics and related mobility attitudes [51,[69][70][71][72].…”

Section: Recruitment Of Participantsmentioning

confidence: 99%

“…One group focuses on technical and methodological aspects, in order to verify and enhance the accuracy of the method. The second group focuses on the application of travel behavior data for analytical purposes [37,44] or for the needs of public policies (see [45] for an extensive overview of research domains; specific applications, for example, apply to bicycle safety and bicycle comfort [46][47][48][49] or the mobility impact of the COVID-19 pandemic [50,51]). On a larger scale, the French standard mobility observation mechanism has been revised towards a modular architecture with a core comprising optimized household travel surveys and options that react to changing needs and opportunities, one of which is the use of smartphone applications as a fully fledged method of data collection [52].…”

Section: Introductionmentioning

confidence: 99%

An Evaluation of Smartphone Tracking for Travel Behavior Studies

Gillis

Lopez

Gautama

2023

IJGI

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The use of smartphone tracking is seen as the way forward in data collection for travel behavior studies. It overcomes some of the weaknesses of the classical approach (which uses paper trip diaries) in terms of accuracy and user annoyance. This article evaluates if these benefits hold in the practical application of smartphone tracking and compares the findings of a travel behavior survey using smartphone tracking to the findings of a previous paper survey. We compare three phases of the travel behavior study. In the recruitment phase, we expect smartphone tracking to make people more willing to participate in surveys, given the innovative nature and reduced burden to participants. However, we found the recruitment of participants equally challenging as for classical methods. In the data collection phase, however, we observe that participants entering the smartphone tracking survey are much more likely to complete the data collection period than when using paper trip diaries. Because of the limited burden, the risk of drop-out from the survey is significantly lower, making the actual data collection more efficient, even for longer survey periods. Finally, in the data analysis phase, the travel behavior indicators derived from smartphone tracking data result in higher average trip rates, shorter average trip lengths and a higher share of active modes (bike, walking) than the results from the paper survey. Although this is explained by more complete and more consistent trip registration, this finding is problematic for comparability between surveys based on different methods, both for longitudinal monitoring (comparability over consequent surveys) and for benchmarking (comparability over geographical areas). Therefore, it is crucial to clearly report the applied data collection methods when describing or comparing travel indicators. In surveys, a combined approach of both written trip diaries and smartphone tracking is advised, where each method can complement the shortcomings of the other.

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