Wearable devices can predict work performance, how to improve it
According to research conducted at Dartmouth College, information about the movement of workers from smartphones and fitness trackers can predict their performance at work.
The study confirmed the behavioral and physical effects of commuting to work on the quality of work. He also showed how data from personal technology devices can help improve employee productivity and satisfaction. âYour commute predicts your day,â said Andrew Campbell, Albert Bradley 1915 Third Century computer science professor in Dartmouth, principal investigator and co-author of the study.
âThis research demonstrates that mobile detection is able to identify how travel to and from the office affects individual workers,â he added. Study participants used a Garmin Vivo Smart 3 activity tracker and smartphone-based sensing app to capture physiological and behavioral patterns during commutes, including activity levels, phone use , heart rate 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 period of one year before the outbreak of the COVID-19 pandemic. Workers, nearly 95% of drivers, were monitored while on the move. They were also monitored for 30-minute periods before and after the trips. âWe were able to create machine learning models to accurately predict job performance,â said Subigya Nepal, a PhD student at Dartmouth and lead author of the article.
“The key was to be able to objectively assess the stress of the journey as well as the physiological response to the experience of the journey,” Nepal added. The study assessed workers using two recognized job performance criteria; counterproductive work behavior and organizational citizenship behavior. Counterproductive behavior has deliberately harmed an organization, while citizenship behaviors are beneficial. Baselines for both measures were established regularly through self-report questionnaires.
âCompared to the lower achievers, the higher achievers show more consistency in the time they arrive and leave work,â 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. âThis dramatically reduces the negative impacts of commuting variability and suggests that the secret to high performance may lie in adhering to better routines,â Audio said.
Other differences in the commuting habits of high and low performing students are as follows: 1. Top performing students tend to have physiological indicators that correspond to physical fitness and resistance to stress.2 . The lower performers had higher stress levels before, during and after travel. 3. The poorest performers used 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 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. According to the researchers, previous studies have used more intrusive and expensive technologies, such as head supports and electrodes, to understand the experience of commuting, but no studies have previously linked the trip data. daily life and the impact on work performance. âThe information from this proof-of-concept study demonstrates that this is an important area of ââresearch for the future of work,â said Campbell, co-director of the DartNets Lab in Dartmouth.
The study also showed that not all daily commutes can be bad. By tracking commuting characteristics such as walking distance and steps, research has confirmed that commuters who participate in active forms of commuting generally have 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. (ANI)
(This story was not edited by Devdiscourse staff and is auto-generated from a syndicated feed.)