The return of the morning commute will ruin productivity, Trinity research reveals 

Posted on: 28 April 2021

As we look towards a return to the office in the coming months, new research from Wladislaw Rivkin at Trinity Business School, Fabiola Gerpott and Dana Unger demonstrates that commuting reduces productivity at work by draining mental energy, effecting our ability to fully focus on what we’re doing when we finally arrive at work.  

According to Wladislaw Rivkin Associate Professor in Organisational Behaviour; “Because of its regular occurrence commuting is an automatic habit. However, an unpleasant commute experience like heavy traffic requires employees’ self-regulation to shift toward controlled cognitive processing. For example, employees may need to adapt daily work plans when arriving later at work or decide during the commute whether to pass on information about potential delays to colleagues. In turn, states of controlled cognitive processing deplete regulatory resources and put employees into a resource protection, negatively effecting productivity.” 

The researchers recommend businesses implement clever work design (e.g., prevent interruptions during focused work) as well as reducing draining commutes by allowing flexible working arrangements or at least flexible time arrangements to avoid rush hour to mitigate this.  

“Although commuting is an everyday experience for most people, its dynamic nature and implication for daily life in organisations have been largely overlooked. Our research demonstrates that commuting reduces productivity at work through draining mental energy and thus preventing immersive states of flow. Leaders should focus on satisfying employees’ fundamental needs by assigning work tasks that enhance employees’ competences and providing employees with decision making autonomy,” says Wladislaw Rivkin. 

This research has been accepted for publication in the Journal of Applied Psychology. The researchers used two diary studies across 10 workdays each (Study 1: 53 employees, 411 day-level data points; Study 2: 91 employees, 719 day-level data points).