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首页> 外文期刊>International journal of management science and engineering management >Performance evaluation of employees using Bayesian belief network model
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Performance evaluation of employees using Bayesian belief network model

机译：使用贝叶斯信念网络模型的员工绩效评估

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摘要

It is a generally acknowledged fact that employee performance evaluation is a critical managerial tool for any organisation. In the global economy, the modern industrial and commercial organisation needs to develop effective methods for assessing the performance of their human resources. In this study, a Bayesian belief network (BBN) model is developed to evaluate the performance of an employee considering the dependencies and correlations between the criteria. The capabilities of the proposed approach are demonstrated on the lumber assembly section of a furniture manufacturing company in Bangladesh. Kendall's rank correlation coefficient is used to identify the correlation between the criteria. The results indicate that the proposed BBN-based model can explicitly quantify uncertainties and handle the complex relationships between the criteria better when compared with existing performance evaluation methods. The proposed model is also capable of assessing the credibility of multiple experts and ranking employees for different purposes such as reward, improvement, training, promotion, termination, compensation, etc.
机译：员工绩效评估是任何组织的关键管理工具，这是一个公认的事实。在全球经济中，现代工商组织需要开发有效的方法来评估其人力资源的绩效。在这项研究中，开发了贝叶斯信念网络（BBN）模型来评估考虑标准之间的依赖性和相关性的员工绩效。孟加拉一家家具制造公司的木材组装部分展示了该方法的功能。肯德尔的秩相关系数用于识别标准之间的相关性。结果表明，与现有的绩效评估方法相比，该基于BBN的模型可以明确量化不确定性并更好地处理标准之间的复杂关系。所提出的模型还能够评估多位专家的信誉，并针对不同目的（例如奖励，改进，培训，晋升，解雇，薪酬等）对员工进行排名。

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