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An exploratory study of the relationship between construction workforce physical strain and task level productivity

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  • Umberto C. Gatti
  • Giovanni C. Migliaccio
  • Susan M. Bogus
  • Suzanne Schneider

Abstract

The monitoring of construction workforce physical strain can be a valuable management strategy in improving workforce productivity, safety, health, and quality of work. Nevertheless, clear relationships between workforce performance and physical strain have yet to be established. An exploratory investigation of the relationship between task level productivity and physical strain was conducted. Nine participants individually performed a four-hour simulated construction task while a wearable physiological status monitor continuously assessed their physiological condition. Heart rate, relative heart rate, and breathing rate were utilized as predictors of physical strain, and task level-single factor productivity was used as an index of productivity. Numerous regression models were generated using the collected data. This investigation initially unsuccessfully attempted to establish a relationship between physiological condition and productivity at the individual worker level. However, an analysis of the regression models showed that there is a relationship between productivity and either heart rate or relative heart rate at the group level, and that this relationship is parabolic. Breathing rate was proved to not be a significant predictor of productivity. Research results significantly improve understanding of the relationship between work physiology and task productivity. Researchers and practitioners may use the tested monitoring devices, analysis methods, and results to design further applied studies and to improve workforce productivity.

Suggested Citation

  • Umberto C. Gatti & Giovanni C. Migliaccio & Susan M. Bogus & Suzanne Schneider, 2014. "An exploratory study of the relationship between construction workforce physical strain and task level productivity," Construction Management and Economics, Taylor & Francis Journals, vol. 32(6), pages 548-564, June.
  • Handle: RePEc:taf:conmgt:v:32:y:2014:i:6:p:548-564
    DOI: 10.1080/01446193.2013.831463
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    Cited by:

    1. Farnad Nasirzadeh & Mostafa Mir & Sadiq Hussain & Mohammad Tayarani Darbandy & Abbas Khosravi & Saeid Nahavandi & Brad Aisbett, 2020. "Physical Fatigue Detection Using Entropy Analysis of Heart Rate Signals," Sustainability, MDPI, vol. 12(7), pages 1-17, March.

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