This study examines the factors that determine workplace autonomy in the choice of schedules, using GEIH data for formal employees from January 2023 to February 2024. A logistic regression model identified significant relationships between autonomy and variables such as company size, income, tenure, workplace, and job satisfaction. The results highlight the complexity of these factors and suggest the need for improvements in the predictive model.
@article{arxiv.2409.14271,
title = {Determinants of Workplace Flextime Flexibility: An Empirical Analysis},
author = {Cristian Espinal Maya and Santiago Jiménez Londoño},
journal= {arXiv preprint arXiv:2409.14271},
year = {2024}
}
Comments
The manuscript contains 15 pages and 3 figures. It analyzes workplace autonomy in schedule flexibility using GEIH data from January 2023 to February 2024. A logistic regression model evaluates the impact of variables like labor income, company size, tenure, workplace, and job satisfaction. Results suggest the need for further model refinements