Resumo:
Telework emerges as a potential tool for reducing commuting, lowering external costs, and
promoting quality of life. In this context, the main objective of this research is to investigate
the adoption of telework in the Brazilian context from a machine learning perspective.
Initially, a comprehensive conceptual model was developed to examine the relationships
between telework and socioeconomic, transportation, and environmental variables, based
on a systematic literature review of studies published up to 2025. The temporal analysis
of the literature highlights the growing academic interest in the topic, emphasizing
the profile of teleworkers, characterized by factors such as age, educational level, income,
and occupation type. Additionally, interactions between telework and urban aspects are
explored, including the adoption of sustainable transportation modes, such as walking
and cycling, as well as its relationship with urban sprawl. The impacts on quality of
life are also discussed, particularly regarding schedule flexibility and work–life balance.
The thesis analyzes the evolution of telework in Brazil from 2022 to 2025 through the
application of machine learning models to representative microdata from the Continuous
National Household Sample Survey, covering approximately 210,000 households per period.
A standardized processing workflow was implemented, including data preprocessing,
handling of missing values, class balancing through random undersampling, variable encoding
and normalization, as well as stratified data splitting with k-fold cross-validation.
Nine classification algorithms were evaluated, including Multinomial Logistic Regression,
Decision Trees, Random Forest, XGBoost, Support Vector Machines, MARS, and Neural
Networks, with hyperparameter tuning performed using the ANOVA racing method.
Model performance showed consistently high results (ROC AUC > 0.80) across all analyzed
periods. The analysis of variable importance indicates that the main determinants
of telework remain relatively stable over time, although their contributions vary, with a
notable increase in the influence of gender in more recent periods. The results demonstrate
that telework in Brazil is driven by a combination of sociodemographic and occupational
factors, reinforcing its selective nature. Overall, this thesis contributes to a deeper understanding
of the multiple dimensions of telework by integrating theoretical and empirical
evidence. Furthermore, the findings provide relevant insights for policymakers, organizational
managers, and urban planners, highlighting how telework shapes urban dynamics
and can support efforts to address contemporary urban challenges.