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      An Interactive Model among Potential Human Risk Factors: 331 Cases of Coal Mine Roof Accidents in China

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          Abstract

          In order to explore optimal strategies for managing potential human risk factors, this paper developed an interactive model among potential human risk factors based on the development processes of accidents. This model was divided into four stages, i.e., risk latency stage, risk accumulation stage, risk explosion stage and risk residue stage. Based on this model, this paper analyzed risk management procedures and relevant personal’s responsibility in each stage, and then probed into the interactive mechanism among human risk factors in three aspects, i.e., knowledge, information and communication. The validity and feasibility of the model was validated by analyzing a coal mine roof accident in China. In addition, the contribution of different functional levels’ personnel in risk evolution was discussed. It showed that this model can effectively reveal the interactive mechanism of potential human risk factors, and can thus give significant insights into the development of risk management theories and practices. It also proves that the contribution of different functional levels’ personnel in the model is different. This can further help practitioners design enhanced Behavioral-Based Safety (BBS) intervention approaches which can have a more sustainable and persistent impact on corporate personnel’s safety behavior. Specific recommendations and suggestions are provided fundamentally for future BBS practices in the coal mine industry.

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          Safety management practices and safety behaviour: assessing the mediating role of safety knowledge and motivation.

          Safety management practices not only improve working conditions but also positively influence employees' attitudes and behaviours with regard to safety, thereby reducing accidents in workplace. This study measured employees' perceptions on six safety management practices and self-reported safety knowledge, safety motivation, safety compliance and safety participation by conducting a survey using questionnaire among 1566 employees belonging to eight major accident hazard process industrial units in Kerala, a state in southern part of India. The reliability and unidimesionality of all the scales were found acceptable. Path analysis using AMOS-4 software showed that some of the safety management practices have direct and indirect relations with the safety performance components, namely, safety compliance and safety participation. Safety knowledge and safety motivation were found to be the key mediators in explaining these relationships. Safety training was identified as the most important safety management practice that predicts safety knowledge, safety motivation, safety compliance and safety participation. These findings provide valuable guidance for researchers and practitioners for identifying the mechanisms by which they can improve safety of workplace.
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            Highway accident severities and the mixed logit model: An exploratory empirical analysis

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              The risk concept—historical and recent development trends

              Terje Aven (2012)
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                01 June 2018
                June 2018
                : 15
                : 6
                : 1144
                Affiliations
                [1 ]School of Resources & Safety Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China; tongruipeng@ 123456126.com (R.T.); zhaicunli@ 123456163.com (C.Z.); jiaqingli@ 123456163.com (Q.J.)
                [2 ]School of Economics and Management, Beihang University, Beijing 100191, China
                [3 ]Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beihang University, Beijing 100191, China
                [4 ]Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands; y.liu-9@ 123456tudelft.nl
                [5 ]School of Safety Engineering, China University of Labor Relations, Beijing 100048, China; xuesurui@ 123456126.com
                Author notes
                [* ]Correspondence: wuchunlin@ 123456buaa.edu.cn ; Tel.: +86-151-1693-8794
                Author information
                https://orcid.org/0000-0002-8003-5478
                https://orcid.org/0000-0003-4577-2859
                https://orcid.org/0000-0001-8706-6712
                Article
                ijerph-15-01144
                10.3390/ijerph15061144
                6025142
                29865150
                060222ab-d985-4cd4-a089-ee7cc56a7f94
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 April 2018
                : 30 May 2018
                Categories
                Article

                Public health
                human risk,potential factor,interactive model,knowledge level,information integrity,communication degree

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