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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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Sat Oct 20 2018
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Measurement and analysis of financial liberalization in Iraq
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Tue Jun 14 2016
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The Suggestive Semantic of Paratexte in printed screenplay
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Recent studies have tended to look at Mottagorat texts for seeking more of the information provided by the book for the reader, has been known by several terms Mottagorat texts, including thresholds, including the margins of the text and the parallel texts, and came this difference, according to researchers who ate the subject of research and investigation. Thus, the researchers assert that all these texts must be subjected to provide information even if propaganda of the text. Hence arose the importance of these texts in Informatics scientific material being wrapped body of the text as well as being propaganda material to evoke the recipient to read, and then to the importance of this topic, the search came on five chapters, the first c

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Publication Date
Sun Sep 07 2008
Journal Name
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Proparyation of Low frequency microwave in dusty Plasma
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Publication Date
Sun Feb 03 2019
Journal Name
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Detection of selected cells in multi choice sheets
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Publication Date
Fri Sep 15 2023
Journal Name
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The aesthetic of structural relationships in linear formations
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PHRASEOLOGY AND ITS ROLE IN THE RUSSIAN LANGUAGE
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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of The College Of Languages (jcl)
Colonization and Civilization in Aimé Cesaire’s A Tempest
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A Tempest is analysed to reveal the counter literary strategy used by Aimé Cesaire, and to disclose the reasons why re-writing and writing back are considered as vital and inescapable tasks. Shakespeare’s The Tempest, which deals with the

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Negation in American Discourse: A Socio-Cognitive Study
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The present study cognitive aims to investigate the negation phenomenon in American political discourse under Critical Discourse Analysis (CDA) principles. The research sample includes two speeches given by Clinton and Trump in their election campaigns in 2016. Since the nature of the study follows the social-cognitive approach, the researcher adopted two models of analysis to achieve the study’s objectives: First, the theoretical framework of MST (developed by Fauconnier (1994), Fauconnier and Sweetser (1996) to examine meaning construction resulting from building different levels of negative mental spaces by two different genders the selected speeches. Second, pragmatic model to examine the role of gender from the functional per

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Deep Spoof Face Detection Techniques in React Native
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The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

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