In the footsteps of Artificial Intelligence : Examining logical relationships between employee turnover and behavior patterns

Bernadett Domokos, Zoltán Baracskai
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Abstract

In this study, the initial problem is the capacity of the human mind to set up a conceptual model. The novelty of this article is that we show that defined concepts created by the human mind can be passed on to an artificial intelligence-based expert system. The expert system helps the human mind to settle the logical connections between the defined terms and the conceptual model thus the created model will be better than what man could have set up without an expert system. These articles have examined the impact of employee turnover in countless aspects as one of potential index of a corporation. As a starting point for our research, we systematically reviewed the literature on employee turnover and selected six concepts that are bilaterally related to our phenomenon. Based on the terms and the correlation of it, we created a conceptual model that was examined with the help of an artificial intelligence-based system. Based on our experience in observing, consulting, and working with decision-makers, we examined the aspects of employee turnover phenomenon in the analysis. This was performed using a rule-based system, which used logical rules and found classical “if-then” connections in the employee behavior cases. According to our examination, our outcomes can provide credible results for further research activities as well as for practitioners.
在人工智能的脚步:检查员工流动和行为模式之间的逻辑关系
在这项研究中,最初的问题是人类大脑建立概念模型的能力。本文的新颖之处在于,我们展示了由人类思维创造的定义概念可以传递给基于人工智能的专家系统。专家系统帮助人类思维解决定义的术语和概念模型之间的逻辑联系,因此创建的模型将比没有专家系统的情况下人类可能建立的模型更好。这些文章研究了员工流动率在无数方面的影响,作为公司的潜在指标之一。作为我们研究的起点,我们系统地回顾了关于员工离职的文献,并选择了六个与我们的现象双边相关的概念。基于术语及其相关性,我们创建了一个概念模型,并借助基于人工智能的系统进行了检查。根据我们在观察、咨询和与决策者合作方面的经验,我们在分析中考察了员工流失现象的各个方面。这是使用基于规则的系统执行的,该系统使用逻辑规则并在员工行为案例中找到经典的“如果-那么”联系。根据我们的研究结果,我们的结果可以为进一步的研究活动以及从业者提供可信的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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