A Fuzzy Model for Personnel Risk Analysis: Case of Russian-Finnish Export-Import Operations of Small and Medium Enterprises

Tatiana Yu. Kudryavtseva, Angi E. Skhvediani, Maiia S. Leukhina, Alexandra O. Schneider
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Abstract

Small and medium enterprises (SMEs) have limited resources for balancing risks which occur during international activities. The main hypothesis tested in this research is that the qualification of employees is the main area of personnel risks in cross–border cooperation. The fuzzy-logic model for personnel risks analysis was developed for quantification of the risks related to international activities. First, different risk factors and their elements were identified and formulated as linguistic variables. Second, with the use of experts’ judgments, a fuzzy logic-based system was constructed and evaluated. Risk level was calculated using MATLAB fuzzy logic toolbox and its factors were ranked accordingly. This model was applied to survey data from SMEs on Russia-Finland import-export operations during the 2020 – 2021 period. The personnel risk related to export-import Russia - Finland operations belonged to the above-average risk levels. Based on a more detailed analysis of risk elements, such elements as personnel development and training had the greatest coefficient and is an obvious high-risk area. The second highest value of the risk coefficient belonged to the element associated with personnel management. The lowest value belonged to elements related to motivation and recruitment processes. Therefore, theoretical contribution of the article is a model which allows us to quantify and identify micro-level personnel related risks in cross-border cooperation and present linguistic interpretation of these risks. This model can be use in practice by managers of specific SMEs or policy makers for obtaining broader and more representative results on risks related to international activities.
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人员风险分析的模糊模型——以俄芬中小企业进出口业务为例
中小型企业在平衡国际活动中发生的风险方面的资源有限。本研究检验的主要假设是员工素质是跨境合作中人员风险的主要领域。为了量化与国际活动相关的风险,建立了人员风险分析的模糊逻辑模型。首先,识别不同的风险因素及其构成要素,并将其表述为语言变量。其次,利用专家的判断,构建了一个基于模糊逻辑的系统并进行了评价。利用MATLAB模糊逻辑工具箱计算风险等级,并对各因素进行排序。该模型应用于2020 - 2021年期间俄罗斯-芬兰进出口业务中小企业的调查数据。俄罗斯-芬兰进出口业务的人员风险属于高于平均水平的风险水平。在对风险要素进行更详细分析的基础上,人员发展和培训等要素的系数最大,是一个明显的高风险区域。风险系数的第二高值属于与人事管理有关的因素。最低值属于与激励和招聘过程有关的因素。因此,本文的理论贡献是建立了一个模型,使我们能够量化和识别跨境合作中微观层面的人员相关风险,并对这些风险进行语言解释。具体中小企业的管理人员或政策制定者可以在实践中使用该模型,以获得有关国际活动风险的更广泛和更具代表性的结果。
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