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使用超级决策软件对弹性工程进行评估。

Evaluation of resilience engineering using super decisions software.

作者信息

Shirali Gholam Abbas, Nematpour Leila

机构信息

Department of Occupational Safety and Health Engineering, Faculty of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

出版信息

Health Promot Perspect. 2019 Aug 6;9(3):191-197. doi: 10.15171/hpp.2019.27. eCollection 2019.

Abstract

Resilience engineering (RE) is a new approach to upgrade safety management systems. Due to its novelty in the field of safety, RE seems to be promising in providing good indicators to assess priorities in organizational strengths/weaknesses while planning to promote safety within organizations. Several methods have been recently developed to evaluate REperformance. The current study is an attempt to quantify and determine the priorities of REdimensions in a steel industry using analytic network process (ANP). In this cross-sectional study, 489 male workers of a steel industry participated. For this purpose, the RE questionnaire was distributed among workers and, then, super decisions software (version 3.2) was used to analyze the data. The results indicated that there was a sufficient level of RE in the organization where top management commitment with normalized weight 0.1781 and awareness-opacity with normalized weight 0.1483 were ranked as the first and last priorities of the organization, respectively. The results of this study showed that the top management system, with the adoption of safety policies, has been able to improve the performance of RE in the organization. Managers should consider appropriate measures to improve the RE situation.

摘要

弹性工程(RE)是一种升级安全管理系统的新方法。由于其在安全领域的新颖性,弹性工程在规划组织内促进安全时,似乎有望提供良好的指标来评估组织优势/劣势的优先级。最近已经开发了几种方法来评估弹性工程的绩效。当前的研究试图使用网络层次分析法(ANP)来量化和确定钢铁行业中弹性工程维度的优先级。在这项横断面研究中,一家钢铁行业的489名男性工人参与其中。为此,向工人发放了弹性工程问卷,然后使用超级决策软件(版本3.2)来分析数据。结果表明,该组织中存在足够水平的弹性工程,其中高层管理承诺的标准化权重为0.1781,意识-不透明度的标准化权重为0.1483,分别被列为该组织的第一和最后优先级。这项研究的结果表明,高层管理系统通过采用安全政策,已经能够提高组织中弹性工程的绩效。管理者应考虑采取适当措施来改善弹性工程状况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b68/6717918/892e7108b4c2/hpp-9-191-g001.jpg

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