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首页> 外文期刊>SA Journal of Human Resource Management >A model for personnel selection with a data mining approach: A case study in a commercial bank
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A model for personnel selection with a data mining approach: A case study in a commercial bank

机译：具有数据挖掘方法的人员选择模型：一家商业银行的案例研究

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Orientation: The success or failure of an organisation has a direct relationship with how its?human resources are employed and retained.Research purpose: In this paper, a decision-making tool is provided for managers to use?during the recruitment process. The effective factors in employees' performance will be?identified by discovering covert patterns of the relationship between employees' test scores?and their performance at work.Motivation for the study: Large amounts of information and data on entrance evaluations?and processes have been kept in organisations. There is a need to discover the pattern in the?relationship between employee's test scores and their performance at work as a tool for use?during the recruitment process.?Research design, approach and method: The data mining technique that was used in this?project serves as the decision tree. Rules derivation was accomplished by the Quick Unbiased?and Efficient Statistical Tree(QUEST), Chi-squared Automatic Interaction Detector (CHAID),C5.0 and Classification And Regression Tree ?(CART) algorithm. The objective and the?appropriate algorithm were determined based on seemingly ‘irrelevant' components, which?the Commerce Bank Human Resources management's experts describe.Main finding: It was found that the ‘performance assessment' variable was not considered as?the objective. Also, it was concluded that out of 26 effective variables only five variables, such?as province of employment, education level, exam score, interview score and work experience,?had the most effect on the ‘promotion score' target.Practical/managerial implication: The database and personnel information of the Commerce?Bank of Iran (in 2005 and 2006) was studied and analysed as a case study in order to identify?the labour factors that are effective in job performance. Appropriate and scientific employment?of staff that were selected from the entrance exams of companies and organisations were of?crucial importance.Contribution/value-add: It is of great importance that an extensive use of data mining?techniques be applied in other management areas. Whilst this is a low-cost technique, it can?help managers to discover covert knowledge in their organisations.
机译：方向：组织的成败与组织如何使用和保留人力资源有直接关系。研究目的：本文提供了一种决策工具，供管理人员在招聘过程中使用。通过发现员工考试成绩与其工作绩效之间的秘密关系，可以确定员工绩效的有效因素。研究动机：保留了大量关于入职评估的信息和数据，并保留了过程在组织中。在招聘过程中，有必要发现员工的测验分数与他们的工作绩效之间的关系模式，作为一种使用工具。研究设计，方法和方法：在此过程中使用的数据挖掘技术？项目充当决策树。规则的推导是通过快速无偏高效统计树（QUEST），卡方自动交互检测器（CHAID），C5.0和分类回归树（CART）算法完成的。该目标和适当的算法是基于看似“不相关”的组件确定的，这是商业银行人力资源管理专家描述的。主要发现：发现“绩效评估”变量不被视为目标。此外，得出的结论是，在26个有效变量中，只有5个变量（例如就业省份，教育程度，考试成绩，面试成绩和工作经历）对``晋升成绩''目标的影响最大。含义：作为案例研究，对伊朗商业银行（2005年和2006年）的数据库和人员信息进行了分析，以识别对工作绩效有效的劳动力因素。从公司和组织的入学考试中选出的员工的科学合理的聘用至关重要。贡献/增值：在其他管理领域中广泛使用数据挖掘技术非常重要。虽然这是一种低成本的技术，但它可以帮助经理发现组织中的秘密知识。

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