Mobile sensing helps explain link between work performance and trips to and from the office – sciencedaily

According to a study conducted by Dartmouth, information on the movement of workers from smartphones and fitness trackers can predict individual performance at work.

The study confirms the behavioral and physical effects of commuting to work on the quality of work. The study also shows how data from personal technology devices can help improve employee productivity and satisfaction.

“Your commute predicts your day,” said Andrew Campbell, Albert Bradley 1915 Third Century computer science professor in Dartmouth, principal investigator and co-author of the study. “This research demonstrates that mobile detection is able to identify how travel to and from the office affects individual workers.”

Study participants used a Garmin vivoSmart 3 activity tracker and smartphone sensing app to capture physiological and behavioral patterns during commutes, including activity levels, phone use, frequency. heart and stress. The system also captured external factors such as location, weather, trip times and trip variability.

Researchers analyzed data from 275 workers collected over a one-year period before the outbreak of the COVID-19 pandemic. Workers, nearly 95% of whom drove, were monitored while on the move. They were also monitored for 30-minute periods before and after the trips.

“We were able to create machine learning models to accurately predict job performance,” said Subigya Nepal, PhD student at Dartmouth and lead author of the article. “The key was to be able to objectively assess the stress of the ride as well as the physiological response to the experience of the ride.”

The study assessed workers using two recognized criteria of job performance: counterproductive work behavior and organizational citizenship behavior. Counterproductive behavior deliberately harms an organization, while citizenship behaviors are beneficial. Baselines for both measures were established regularly through self-report questionnaires.

“Compared to the lower achievers, the higher achievers show more consistency in the time they arrive and leave work,” said Pino Audia, professor of management and organizations at the Tuck School of Business, senior scientist of the study team and co-author of the study. “This dramatically reduces the negative impacts of travel variability and suggests that the secret to high performance may lie in adhering to better routines.”

Other differences in the commuting habits of top and bottom performers include:

  • Top performers tend to have physiological indicators consistent with fitness and resistance to stress.
  • People who perform poorly have higher stress levels before, during and after travel.
  • The poor performers use their phones more while on the move.

Overall, research also found that workers spend more time commuting between home and work than commuting to work.

According to the study, previous research on commuting indicates that the stress, anxiety and frustration associated with commuting can lead to a less efficient workforce, an increase in counter-work behaviors. productive and reduced organizational citizenship behavior.

This is the first study to use portable devices and discrete smartphones to predict worker performance based on commuting data alone. Previous studies have used more intrusive and expensive technologies, such as head supports and electrodes, to understand the commute experience, researchers say, but no study had previously linked the data. on commuting and the impact on performance at work.

“The information from this proof-of-concept study demonstrates that this is an important area of ​​research for the future of work,” said Campbell, co-director of the DartNets Lab in Dartmouth.

The study also shows that not all daily commutes can be bad. By tracking commuting characteristics such as walking distance and steps, research confirms that commuters who participate in active forms of commuting generally experience increased productivity at work.

Going forward, researchers expect ubiquitous sensing technology to detect commuter stress and deliver tailored interventions such as music, podcasts, connect them to friends and family, or offer advice for short stops.

The study was accepted for publication in The Future of Work: COVID-19 and Beyond, a special issue ofUbiquitous Computing IEEE.

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Material provided by Dartmouth College. Original written by David Hirsch. Note: Content can be changed for style and length.

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