Journal ArticleDOI
Safety management practices and safety behaviour: assessing the mediating role of safety knowledge and motivation.
M.N. Vinodkumar,M. Bhasi +1 more
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TLDR
Safety training was identified as the most important safety management practice that predicts safety knowledge, safety motivation, safety compliance and safety participation and path analysis using AMOS-4 software showed that some of the safety management practices have direct and indirect relations with the safety performance components.About:
This article is published in Accident Analysis & Prevention.The article was published on 2010-11-01. It has received 505 citations till now. The article focuses on the topics: Effective safety training & Occupational safety and health.read more
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Predicting safety behavior in the construction industry: development and test of an integrative model
TL;DR: In this paper, the authors developed and tested an integrative model of construction workers' safety behavior with an attempt to better understand the mechanisms by which key safety climate factors (i.e., management safety commitment, social support, and production pressure) and individual factors (e.g., safety knowledge and safety motivation) influence workers’ safety behavior.
Journal ArticleDOI
Strategic response to Industry 4.0: an empirical investigation on the Chinese automotive industry
TL;DR: The result shows that company size and nature do not increase the use of advanced production technologies, while other factors have positive impacts on improving the technology adoption among the companies surveyed.
Journal ArticleDOI
Behavior-based safety on construction sites: a case study.
TL;DR: The results proved that the BBS management technique can be applied to any country's culture, showing that it would be a good approach for improving the safety of front-line workers and that it has industry wide application for ongoing construction projects.
Journal ArticleDOI
WITHDRAWN: Reprint of “Exploratory analysis of the safety climate and safety behavior relationship”
M.D. Cooper,R.A. Phillips +1 more
TL;DR: The results suggest that the hypothesized climate-behavior-accident path is not as clear cut as commonly assumed and supports the use of safety climate measures as useful diagnostic tools in ascertaining employee's perceptions of the way that safety is being operationalized.
Journal ArticleDOI
Safety Climate in Organizations
Mark A. Griffin,Matteo Curcuruto +1 more
TL;DR: Safety climate is a collective construct derived from individuals' shared perceptions of the various ways that safety is valued in the workplace as mentioned in this paper, and it is an important predictor of safety behavior and safety outcomes.
References
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Journal ArticleDOI
Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives
Li-tze Hu,Peter M. Bentler +1 more
TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Book
Principles and Practice of Structural Equation Modeling
TL;DR: The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
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Coefficient alpha and the internal structure of tests.
TL;DR: In this paper, a general formula (α) of which a special case is the Kuder-Richardson coefficient of equivalence is shown to be the mean of all split-half coefficients resulting from different splittings of a test, therefore an estimate of the correlation between two random samples of items from a universe of items like those in the test.
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Multivariate Data Analysis
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Journal ArticleDOI
Multivariate data analysis
TL;DR: This chapter discusses Structural Equation Modeling: An Introduction, and SEM: Confirmatory Factor Analysis, and Testing A Structural Model, which shows how the model can be modified for different data types.
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