The Differences in Risk Perception between Practitioners in the Non-Coal-Mining Industry: Miners, Managers and Experts

Non-coal-mining accidents occur frequently in China, and individual unsafe behaviors are the direct cause. The cognitive diversity of practitioners in the non-coal-mining industry leads to various behaviors in work and hinders communication between groups. The aim of this study is to analyze the dif...

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Main Authors: Yuting Song, Shu Zhang
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Toxics
Subjects:
Online Access:https://www.mdpi.com/2305-6304/10/10/623
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author Yuting Song
Shu Zhang
author_facet Yuting Song
Shu Zhang
author_sort Yuting Song
collection DOAJ
description Non-coal-mining accidents occur frequently in China, and individual unsafe behaviors are the direct cause. The cognitive diversity of practitioners in the non-coal-mining industry leads to various behaviors in work and hinders communication between groups. The aim of this study is to analyze the differences in risk perception (accidents and occupational diseases) between non-coal-mining practitioners (experts, miners, and managers) and to explore the contributing factors. The questionnaire survey method was used to collect the data on risk perception and influencing factors from 402 respondents working in non-coal mines and universities in China. Project analysis and exploratory factor analysis were used for preprocessing. A t-test and linear regression analysis were used to test the significance of the differences and assess the function of the factors, respectively. Regarding risk perception, two risks both have significant differences between the three groups. With the perceptions of accidents and occupational diseases ranked from high to low, the order of the practitioners is as follows: managers (3.88), experts (3.71), miners (3.55) and experts (4.14), miners (3.90), and managers (3.88). Regarding the influencing factors, risk attitude, risk communication, educational level, enterprise trust, and occupational satisfaction have great effects on the three groups. More precisely, three groups have different important predictors. Risk attitude has the greatest impact on miners (0.290) and experts (0.369), but sensibility preference has the greatest impact on managers (0.518). In summary, cognitive discrepancies are common among non-coal-mining practitioners, but the degree of deviation varies with the type and dimension of the risk. There are six factors that have a significant impact on all practitioners, but the effect is limited by specific risks and groups.
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spelling doaj.art-9048ba5cb91c4d16b744d0300cac616c2023-11-24T02:58:14ZengMDPI AGToxics2305-63042022-10-01101062310.3390/toxics10100623The Differences in Risk Perception between Practitioners in the Non-Coal-Mining Industry: Miners, Managers and ExpertsYuting Song0Shu Zhang1School of Public Administration, Central South University, Changsha 410017, ChinaSchool of Resources and Safety Engineering, Central South University, Changsha 410083, ChinaNon-coal-mining accidents occur frequently in China, and individual unsafe behaviors are the direct cause. The cognitive diversity of practitioners in the non-coal-mining industry leads to various behaviors in work and hinders communication between groups. The aim of this study is to analyze the differences in risk perception (accidents and occupational diseases) between non-coal-mining practitioners (experts, miners, and managers) and to explore the contributing factors. The questionnaire survey method was used to collect the data on risk perception and influencing factors from 402 respondents working in non-coal mines and universities in China. Project analysis and exploratory factor analysis were used for preprocessing. A t-test and linear regression analysis were used to test the significance of the differences and assess the function of the factors, respectively. Regarding risk perception, two risks both have significant differences between the three groups. With the perceptions of accidents and occupational diseases ranked from high to low, the order of the practitioners is as follows: managers (3.88), experts (3.71), miners (3.55) and experts (4.14), miners (3.90), and managers (3.88). Regarding the influencing factors, risk attitude, risk communication, educational level, enterprise trust, and occupational satisfaction have great effects on the three groups. More precisely, three groups have different important predictors. Risk attitude has the greatest impact on miners (0.290) and experts (0.369), but sensibility preference has the greatest impact on managers (0.518). In summary, cognitive discrepancies are common among non-coal-mining practitioners, but the degree of deviation varies with the type and dimension of the risk. There are six factors that have a significant impact on all practitioners, but the effect is limited by specific risks and groups.https://www.mdpi.com/2305-6304/10/10/623risk perceptionnon-coal mineinfluencing factorrisk managementhuman factor analysis
spellingShingle Yuting Song
Shu Zhang
The Differences in Risk Perception between Practitioners in the Non-Coal-Mining Industry: Miners, Managers and Experts
Toxics
risk perception
non-coal mine
influencing factor
risk management
human factor analysis
title The Differences in Risk Perception between Practitioners in the Non-Coal-Mining Industry: Miners, Managers and Experts
title_full The Differences in Risk Perception between Practitioners in the Non-Coal-Mining Industry: Miners, Managers and Experts
title_fullStr The Differences in Risk Perception between Practitioners in the Non-Coal-Mining Industry: Miners, Managers and Experts
title_full_unstemmed The Differences in Risk Perception between Practitioners in the Non-Coal-Mining Industry: Miners, Managers and Experts
title_short The Differences in Risk Perception between Practitioners in the Non-Coal-Mining Industry: Miners, Managers and Experts
title_sort differences in risk perception between practitioners in the non coal mining industry miners managers and experts
topic risk perception
non-coal mine
influencing factor
risk management
human factor analysis
url https://www.mdpi.com/2305-6304/10/10/623
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