Abstracts – Browse Results
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Bresnen, M (2017) Being careful what we wish for? Challenges and opportunities afforded through engagement with business and management research. Construction Management and Economics, 35(01), 24-34.
Hallowell, M R, Alexander, D and Gambatese, J A (2017) Energy-based safety risk assessment: Does magnitude and intensity of energy predict injury severity?. Construction Management and Economics, 35(01), 64-77.
- Type: Journal Article
- Keywords: injury; accident; occupational health and safety; safety; risk analysis; construction accidents & safety; risk assessment; hypotheses
- ISBN/ISSN: 0144-6193
- URL: https://doi.org/10.1080/01446193.2016.1274418
- Abstract:
Although the quantity and quality of safety risk data have improved in recent years, available data do not link directly to natural principles and are, therefore, limited in their application and scientific extension. The present study aims to test the hypothesis that the quantity and intensity of energy observable prior to an incident predicts the severity of the incident. The hypothesis is built upon the theory that energy is translated to an injury through uncontrolled release of the energy, transfer of the energy to the human body and the vulnerability of the body and associated protective equipment. To test the hypothesis, a multi-phase experiment was conducted. First, over 500 injury reports were gathered from national databases and private companies. For each report, the leading information describing the work operations and environment and the lagging information describing the injury were extracted, separated and isolated. Second, the magnitude of the energy was estimated using only leading information. Once energy magnitude was quantified, the distribution was compared across injury severity levels using analysis of variance tests. As hypothesized, energy magnitude is a strong predictor of injury severity. Although computationally intensive, energy intensity, defined as the magnitude of energy divided by the area of contact between an object and the human body, showed strong predictive validity. This research indicates that energy-based safety risk analysis has predictive validity and is a promising line of scientific inquiry with the potential to increase our understanding of the natural phenomena that contribute to injuries.; Although the quantity and quality of safety risk data have improved in recent years, available data do not link directly to natural principles and are, therefore, limited in their application and scientific extension. The present study aims to test the hypothesis that the quantity and intensity of energy observable prior to an incident predicts the severity of the incident. The hypothesis is built upon the theory that energy is translated to an injury through uncontrolled release of the energy, transfer of the energy to the human body and the vulnerability of the body and associated protective equipment. To test the hypothesis, a multi-phase experiment was conducted. First, over 500 injury reports were gathered from national databases and private companies. For each report, the leading information describing the work operations and environment and the lagging information describing the injury were extracted, separated and isolated. Second, the magnitude of the energy was estimated using only leading information. Once energy magnitude was quantified, the distribution was compared across injury severity levels using analysis of variance tests. As hypothesized, energy magnitude is a strong predictor of injury severity. Although computationally intensive, energy intensity, defined as the magnitude of energy divided by the area of contact between an object and the human body, showed strong predictive validity. This research indicates that energy-based safety risk analysis has predictive validity and is a promising line of scientific inquiry with the potential to increase our understanding of the natural phenomena that contribute to injuries.;
Koskela, L (2017) Why is management research irrelevant?. Construction Management and Economics, 35(01), 4-23.
Sacks, R, Seppänen, O, Priven, V and Savosnick, J (2017) Construction flow index: A metric of production flow quality in construction. Construction Management and Economics, 35(01), 45-63.
Styre, A (2017) Thinking about materiality: The value of a construction management and engineering view. Construction Management and Economics, 35(01), 35-44.