Investigating the role of flex-time working arrangements in optimising morning peak-hour travel demand: A survival analysis approach

A flex-time arrangement offers an alternative to the traditional 8:00 am to 4:00 pm work. It has proven to be an effective way of reshaping peak-hour travel demand, allowing workers to alter their departure time. Prior studies focused on the departure times of fixed and flex-time workers without categorising them by work-from-home options (non-teleworkers, hybrid workers, and passive teleworkers). Nevertheless, the factors influencing the departure time may vary among worker categories. Furthermore, the data source of prior studies was the Household Travel Survey, collected pre-COVID-19. However, the pandemic has substantially altered workers’ perspectives on flexible work arrangements. Therefore, understanding the departure time of various workers in the post-COVID-19 era is crucial to managing peak-hour travel demand effectively. Hence, this study aims 1) to investigate the departure time distribution of various worker categories, 2) to examine the factors influencing it, and 3) to propose a suitable policy to optimise the peak-hour travel demand.

Survival analysis was used to analyse the continuous nature of departure time using data collected from 10 June to 20 July 2023 in Greater Kuala Lumpur, Malaysia. The results showed that the departure time reaches its peak at 7:30 am. The departure time distribution of non-teleworkers is statistically significantly different from hybrid workers and passive non-teleworkers. Fixed-time workers significantly consider multiple factors when determining their departure time, surpassing the considerations of flex-time workers. The departure time of fixed-time workers is significantly influenced by gender, travel duration and workplace location. The sensitivity analysis results show that optimum travel demand can be achieved by implementing transport policies integrated with 50% flex-time and 50% fixed-time workers arrangements. The proposed methods will contribute to developing a tool to test the effect of various flex-test arrangements on peak-hour travel demand. This study will assist transport planners and policymakers in achieving optimum employer-based travel demand management.