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Performance assessment of human resource by integration of HSE and ergonomics and EFQM management system: A fuzzy-based approach

机译:通过结合HSE和人体工程学以及EFQM管理系统对人力资源进行绩效评估:一种基于模糊的方法

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Purpose - The purpose of this paper is to present an integrated framework for performance evaluation and analysis of human resource (HR) with respect to the factors of health, safety, environment and ergonomics (HSEE) management system, and also the criteria of European federation for quality management (EFQM) as one of the well-known business excellence models. Design/methodology/approach - In this study, an intelligent algorithm based on adaptive neuro-fuzzy inference system (ANFIS) along with fuzzy data envelopment analysis (FDEA) are developed and employed to assess the performance of the company. Furthermore, the impact of the factors on the company's performance as well as their strengths and weaknesses are identified by conducting a sensitivity analysis on the results. Similarly, a design of experiment is performed to prioritize the factors in the order of importance. Findings - The results show that EFQM model has a far greater impact upon the company's performance than HSEE management system. According to the obtained results, it can be argued that integration of HSEE and EFQM leads to the performance improvement in the company. Practical implications - In current study, the required data for executing the proposed framework are collected via valid questionnaires which are filled in by the staff of an aviation industry located in Tehran, Iran. Originality/value - Managing HR performance results in improving usability, maintainability and reliability and finally in a significant reduction in the commercial aviation accident rate. Also, study of factors affecting HR performance authorities participate in developing systems in order to help operators better manage human error. This paper for the first time presents an intelligent framework based on ANFIS, FDEA and statistical tests for HR performance assessment and analysis with the ability of handling uncertainty and vagueness existing in real world environment.
机译:目的-本文的目的是针对健康,安全,环境和人体工程学(HSEE)管理系统的因素,以及欧洲联盟的标准,​​提出一个用于人力资源(HR)绩效评估和分析的综合框架。质量管理(EFQM)作为著名的卓越业务模型之一。设计/方法/方法-在这项研究中,开发了一种基于自适应神经模糊推理系统(ANFIS)和模糊数据包络分析(FDEA)的智能算法,并将其用于评估公司的绩效。此外,通过对结果进行敏感性分析,可以确定这些因素对公司绩效的影响以及优势和劣势。同样,进行实验设计以按重要性顺序对因素进行优先排序。结果-结果表明,EFQM模型对公司绩效的影响远大于HSEE管理系统。根据获得的结果,可以说HSEE和EFQM的集成可以提高公司的绩效。实际意义-在当前研究中,通过有效的调查表收集了执行建议的框架所需的数据,这些调查表由位于伊朗德黑兰的航空业工作人员填写。原创性/价值-管理人力资源绩效可提高可用性,可维护性和可靠性,并最终显着降低商业航空事故率。此外,对影响人力资源绩效主管部门的因素进行研究,以参与开发系统,以帮助操作员更好地管理人为错误。本文首次提出了一种基于ANFIS,FDEA和统计测试的智能框架,用于人力资源绩效评估和分析,能够处理现实环境中存在的不确定性和模糊性。

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