Sadegh Amalnick Mohsen, Zarrin Mansour
Department of Industrial Engineering, College of Engineering, University of Tehran , Tehran, Iran.
Int J Health Care Qual Assur. 2017 Mar 13;30(2):160-174. doi: 10.1108/IJHCQA-06-2016-0089.
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.
目的 本文旨在提出一个综合框架，用于从健康、安全、环境与工效学（HSEE）管理体系因素以及作为著名卓越商业模式之一的欧洲质量管理基金会（EFQM）标准方面，对人力资源（HR）进行绩效评估与分析。
设计/方法/途径 在本研究中，开发并运用了基于自适应神经模糊推理系统（ANFIS）的智能算法以及模糊数据包络分析（FDEA）来评估公司绩效。此外，通过对结果进行敏感性分析，确定这些因素对公司绩效的影响以及它们的优势和劣势。同样，进行了实验设计以按重要性顺序对这些因素进行排序。
发现 结果表明，EFQM模型对公司绩效的影响远大于HSEE管理体系。根据所得结果，可以认为HSEE与EFQM的整合会带来公司绩效的提升。
实际意义 在当前研究中，执行所提出框架所需的数据是通过有效的问卷收集的，这些问卷由位于伊朗德黑兰的一家航空业公司的员工填写。
原创性/价值 管理人力资源绩效有助于提高可用性、可维护性和可靠性，并最终显著降低商业航空事故率。此外，对影响人力资源绩效因素的研究有助于相关部门参与开发系统，以帮助运营商更好地管理人为失误。本文首次提出了一个基于ANFIS、FDEA和统计测试的智能框架，用于人力资源绩效评估与分析，能够处理现实世界环境中存在的不确定性和模糊性。
