Information about worker commutes from smartphones and fitness trackers can predict individual job performance, according to a new study.
The study confirms the behavioral and physical effects of commuting on work quality. The study also shows how data from personal tech devices can help improve employee productivity and satisfaction.
«Your commute predicts your day,» said Andrew Campbell, the Albert Bradley 1915 Third Century Professor of computer science at Dartmouth, the lead researcher and co-author of the study. «This research demonstrates that mobile sensing is capable of identifying how travel to and from the office affects individual workers.»
Participants in the study used a Garmin vivoSmart 3 activity tracker and a smartphone-based sensing app to capture physiological and behavioral patterns during commuting, including activity levels, phone usage, heart rate, and stress. The system also captured external factors such as location, weather, commute duration, and commute variability.
Researchers analyzed data from 275 workers collected over a one-year period prior to the outbreak of the COVID-19 pandemic. The workers, close to 95% of whom drove, were monitored as they traveled. They were also monitored for 30-minute periods before and after commuting.
«We were able to build machine learning models to accurately predict job performance,» said Subigya Nepal a PhD student at Dartmouth and lead author of the paper. «The key was being able to objectively assess commuting stress along with the physiological reaction to the commuting experience.»
The study assessed workers using two recognized criteria of job performance: counterproductive work behavior and organizational citizenship behavior. Counterproductive behavior deliberately harms an organization, whereas citizenship behaviors are beneficial. Baselines for both measures were established regularly through self-reporting questionnaires.
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Materials provided by Dartmouth College. Original written by David Hirsch. Note: Content may be edited for style and length.