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Influential safety technology adoption predictors in construction
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Purpose

Existing literature suggests that construction worker safety could be optimized using emerging technologies. However, the application of safety technologies in the construction industry is limited. One reason for the constrained adoption of safety technologies is the lack of empirical information for mitigating the risk of a failed adoption. The purpose of this paper is to fill the research gap through identifying key factors that predict successful adoption of safety technologies.

Design/methodology/approach

In total, 26 key technology adoption predictors were identified and classified using a combination of literature review and an expert panel. The level of influence for each identified safety technology adoption predictor was assessed and ranked using the Relative Importance Index. Analysis of variance was performed as well to assess the potential difference in perceived level of importance for the predictors when the study participants were clustered according to work experience and company size.

Findings

Statistical analysis indicates that 12 out of the 26 predictors identified are highly influential regarding technology adoption decision-making in construction. Technology reliability, effectiveness and durability were ranked as the most influential predictors. The participants who work for small companies and who had less than ten years of experience rated individual- and technology-related predictors significantly lower than the experienced participants working for medium and large companies.

Practical implications

The present study provides construction researchers and practitioners with valuable information regarding safety technology predictors and their magnitude, both of which are essential elements of a successful safety technology adoption process. Improved technology adoption can enhance workplace safety and minimize worker injuries, providing substantial benefits to the construction industry.

Originality/value

This study contributes to technology adoption knowledge by identifying and quantifying the influential predictors of safety technologies in relation to different organizational contexts. The study informs the need to develop an integrated conceptual model for safety technology adoption.

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Sun Jul 21 2019
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Determination of Volumetric Mass Transfer Coefficient in Fixed Bed Adsorption
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In general, the volumetric mass transfer coefficient increases with increasing hexane flow rate, and with increasing initial concentration of benzene in the mixture. The ultimate value of (Ky.a) was at 53 ml/min of hexane flow rate with benzene initial concentration of (6.53 wt. %), and it wa

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Publication Date
Sun Dec 31 2000
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Supra-Approximation Spaces Using Mixed Degree System in Graph Theory
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Color Stability of Different Aesthetic Archwires (An In vitro study)
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The role of prophylactic antibiotics in nasal packing for epistaxis
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