中国安全科学学报 ›› 2017, Vol. 27 ›› Issue (12): 1-7.doi: 10.16265/j.cnki.issn1003-3033.2017.12.001

• 安全人体学 •    下一篇

知识型和经验型矿工群体的不安全行为研究

成连华 副教授, 赵帅, 吴锋, 郭慧敏, 申坤   

  1. 西安科技大学 安全科学与工程学院,陕西 西安 710054
  • 收稿日期:2017-09-12 修回日期:2017-11-11 出版日期:2017-12-28 发布日期:2020-10-10
  • 作者简介:成连华 (1977—),男,山东莘县人,博士,副教授,主要从事安全管理与安全系统工程方面的科研工作。E-mail:chenglianhua@126. com。

Unsafe behavior of knowledge miners and experience miners

CHENG Lianhua, ZHAO Shuai, WU Feng, GUO Huimin, SHEN Kun   

  1. College of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an Shaanxi 710054,China
  • Received:2017-09-12 Revised:2017-11-11 Online:2017-12-28 Published:2020-10-10

摘要: 为进一步探讨拥有不同文化程度和工龄的矿工不安全行为(USB)的产生机制,根据工作年限和学历水平将矿工划分为知识型和经验型,基于社会认知理论,将自我效能感(SFE)作为调节变量,构建以自我价值强化(SWR)和外部利益强化(EBR)为中介变量的知识型矿工(KMs)、经验型矿工(EMs)群体与不安全行为影响关系的概念模型,运用问卷调查、回归分析等方法对其进行实证分析,并通过结构方程模型(SEM)加以验证。研究表明:知识型矿工更期望自我价值强化,并在自我价值强化的作用下作出安全行为;经验型矿工更期望外部利益强化,并在外部利益强化的作用下作出不安全行为,且经验型矿工可以不经过外部利益强化的传递,对不安全行为直接产生显著正向影响;自我效能感对外部利益强化与不安全行为间的关系具有显著正向调节效应,对自我价值强化与不安全行为间的关系具有显著负向调节效应。

关键词: 不安全行为(USB), 自我效能感(SFE), 结构方程模型(SEM), 知识型矿工(KMs), 经验型矿工(EMs)

Abstract: With an aim towards exploring the mechanism of USB of miners different in education degree and seniority, miners were divided into two types, knowledge type and experience type. Two conceptual models were built for the relationships between the two types of miners and USB, with SFE used as a regulating variable, with self-worth reinforcement (SWR) and external benefit reinforcement (EBR) used as mediating variables, basing on the social cognitive theory. The models were validated by using SEM. The results show that KMs prefer to expect SWR and act safely under the action of it, EMs prefer to expect EBR and perform USB under the action of it, moreover, EMs have a directly positive impact on USB. EMs' SFE positively regulates the relationship between EBR and USB, and KMs' SFE negatively regulates the relationship between SWR and USB.

Key words: unsafe behavior(USB), self-efficacy(SFE), structural equation model(SEM), knowledge miners(KMs), experience miners(EMs)

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