构建机械制造企业竞争力模糊认知图的方法

I. A. Buinevich, Y. A. Kriushina, Y. A. Khalin, A. I. Katykhin, Е. А. Kriushin
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引用次数: 0

摘要

研究目的是评估影响机械制造企业竞争力的因素,并开发一种模糊认知图法(FCM)来分析这些因素。本研究采用数据分析和建模方法,包括模糊认知图法,以正式确定各因素之间的关系及其对机械制造企业竞争力的影响。对影响竞争力的因素,如技术水平、产品质量、价格水平、创新潜力和管理经验等相关数据进行了分析。该研究开发了一种 FCM 方法,用于分析各因素之间的关系及其对机械制造企业竞争力的影响。评价了影响竞争力的因素,包括技术水平、产品质量、价格水平、创新潜力和管理经验。确定了对竞争力影响最大的关键因素,并使用量表确定了各因素对竞争力的影响程度。研究结果表明,FCM 方法是分析机械制造企业竞争力的有效工具。它允许输入数据的不确定性和模糊性,并能更好地理解概念变量之间的关系。所开发的 FCM 方法可用于做出明智决策,以提高企业竞争力。总之,这项研究证实了分析影响竞争力的因素的重要性,并表明,FCM 有助于以更直观、更易理解的形式表现复杂的系统及其关系。这有助于企业管理层做出明智决策,提高公司竞争力,扩大市场份额。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Method of Construction of a Fuzzy Cognitive Map of the Competitiveness of a Machine-Building Enterprise
The purpose of research is to evaluate the factors influencing the competitiveness of machine-building enterprises and to develop a methodology for fuzzy cognitive mapping (FCM) to analyze these factors.Methods. Data analysis and modeling methods, including FCM, were used in this study to formalize the relationships between factors and their influence on the competitiveness of machine-building enterprises. Data related to factors affecting competitiveness, such as technological level, product quality, price level, innovation potential, and managerial experience, were analyzed.Results. The study resulted in the development of an FCM methodology to analyze the relationships between factors and their influence on the competitiveness of machine-building enterprises. The factors influencing competitiveness, including technological level, product quality, price level, innovation potential, and managerial experience, were evaluated. Key factors with the greatest impact on competitiveness were identified, and the degrees of influence of each factor on competitiveness were established using a scale to formalize the strength of influence.Conclusion. The results of the study demonstrate that the FCM method is an effective tool for analyzing the competitiveness of machine-building enterprises. It allows for uncertainty and vagueness in the input data and provides a better understanding of the relationships between conceptual variables. The developed FCM methodology can be used to make informed decisions to improve enterprise competitiveness. Overall, the study confirms the importance of analyzing factors influencing competitiveness and demonstrates that FCM can help to represent a complex system and its relationships in a more visual and understandable form. This can be useful for enterprise management in making informed decisions to improve company competitiveness and increase market share.
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