Development and Application of Safety Technology Adoption Decision-Making Tool
Publication: Journal of Construction Engineering and Management
Volume 146, Issue 4
Abstract
The need to enhance worker safety in construction has often studied recently due to the high rates of fatalities and injuries in the construction industry. To abate this scourge, various control methods including the use of technology have been adopted to improve workplace safety performance in construction. However, not all of the technologies adopted by industry personnel for safety management have achieved the desired outcome or have proved to be effective. More research is needed regarding the adoption of safety technologies in the construction industry. Importantly, industry stakeholders need to evaluate their readiness to adopt safety technologies. The present study develops a decision-making tool that can aid in the adoption of safety technology in the construction industry. The safety technology decision-making adoption tool is developed using the fuzzy synthetic evaluation technique and consists of three categories of safety technology predictors: external, organization, and technology-related. Technology-based predictors have emerged as the most impactful predictor. Subsequently, a technology adoption assessment protocol was developed and applied to a case study to assess an organization’s readiness to adopt wearable sensing devices. The present work contributes to the body of knowledge by identifying, quantifying, and categorizing predictors of technology adoption and then integrating the predictors into an evaluation protocol to assess the adoption of safety technologies in the construction industry. This contribution is translated into practice by developing a user-friendly tool called the Construction Safety Technology Adoption Index (C-STAI). The developed tool is expected to help construction professionals and practitioners make informed decisions regarding the adoption of safety technology. Improved technology adoption in construction is expected to lead to enhanced safety and reduce injuries on construction projects.
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Data Availability Statement
Data generated or analyzed during the study are available from the corresponding author by request. Information about the Journal’s data-sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263.
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Journal of Construction Engineering and Management
Volume 146 • Issue 4 • April 2020
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©2020 American Society of Civil Engineers.
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Received: Apr 19, 2019
Accepted: Oct 4, 2019
Published online: Feb 14, 2020
Published in print: Apr 1, 2020
Discussion open until: Jul 14, 2020
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