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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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Mon Aug 01 2016
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Fri Oct 19 2018
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Journal Of Economics And Administrative Sciences
the impact of knowledge management on organizational innovation in aviation companies operating in sudan
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Abstract

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Wed May 01 2019
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The Social Dimension and Its Role in the Applicability of Smart Cities in Iraq
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Publication Date
Sun Jul 01 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
ESTIMATION OF GENETIC VARIATIONS IN DIFFERENT TAXA IN BRASSICACEAE BY RAPD AND ISSR ANALYSIS
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Twelve species from Brassicaceae family were studied using two different molecular techniques: RAPD and ISSR; both of these techniques were used to detect some molecular markers associated with the genotype identification. RAPD results, from using five random primers, revealed 241 amplified fragments, 62 of them were polymorphic (26%).

 

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Publication Date
Fri Dec 30 2011
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Causative Organisms and Risk Factors In Bacterial Meningitis in Al-Elwia Childhood Hospital - Baghdad
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it is followed by Streptococcus Pneumonia, and
then N. meningitides, in addition to other
microorganisms.
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bacterial meningitis.
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The Influences of Aminophylline and Indomethacin in Glycerol-Induced Acute Renal Failure in Rats
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Method: Glycerol induced ARF was produced by a
single dose (10ml/kg, 50%v/v with distilled water i.m)
in rats, which were restricted to drinking water.
Aminophylline was used in our study in a dose of
25mg/kg, i.p) while the dose of indomethacin was
10mg/kg, i.p), assessment of renal function was done
by measuring blood urea
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Sat Jan 07 2023
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Fimasartan attenuates edema and systemic changes in egg albumin-induced paw inflammation in rats
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Electrochemical Behavior of Phosphotized Reinforcing Steel in Concrete in Presence of Sugar Can Ash
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Publication Date
Sun Aug 01 2021
Journal Name
Nano Biomedicine And Engineering
In-vivo and In-vitro Anti-Acinetobacter Baumannii Activity of Citrate-Capped Silver Nanoparticles
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Silver nanoparticles (AgNPs) are of potential interest because of their effective antibacterial and antiviral activities. Capping agents are used for exhibiting a better antibacterial activity than uncapped Ag NPs. There are very few reports that have shown the usage of AgNPs for in-vivo antibacterial therapy. Citrate-capped silver nanoparticles were synthesized chemically by citrate reduction method; the size of Cit-AgNPs was determined by an atomic force microscope (AFM) and was between 15-90 nm. Acinetobacter baumannii (A. baumannii) isolates were the only sensitive species to Cit-AgNPs. MICs and MBC of Cit-AgNPs were determined by using A. baumannii. The results showed an additive effect of Cit-AgNPs. Four mice groups were infected with

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