用于评估渔业企业社会经济效益的计算复合体

A. Sorokin, N. Maltseva, M. Rudenko, Vladimir I. Lobeiko, V. Esaulenko
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引用次数: 0

摘要

本文提出了渔业企业综合效益评价的理论基础。提出了一套参数,包括表征企业环境和社会效率的因素,以及影响企业管理体系有效性的因素。评价环境效率的因素包括评价温室气体和其他有害物质的排放、能源消耗水平以及对水资源造成的损害。评估社会效益的因素包括与工资水平、伤害水平、劳动保护措施有效性评估和工作人员住房条件评估有关的评估。为确定公司治理的有效性,应综合考虑质量管理体系评价、风险管理体系质量评价、企业整体财务状况评价等相关因素。所提议的计算机综合体由两个模块组成。第一个模块用于形成一个积分估计。第二个模块用于将收到的评估与州的七个类别之一相关联。提出的规定是基于模糊集理论的方法和基于Sugeno算法的分层模糊推理系统的特性。研究结果得出的结论是,该系统允许您跟踪每个参数的急剧偏差。分组值块的存在使得形成评估对象的状态类成为可能。每个状态类都用ESG评分值的七个级别中的一个来标识。所作的结论为进一步发展公司信息系统开辟了可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COMPUTING COMPLEX FOR ASSESSING THE SOCIO-ECONOMIC EFFICIENCY OF FISHING INDUSTRY ENTERPRISES
The paper proposes theoretical foundations for assessing the integrated efficiency of fishing industry enterprises. A set of parameters is proposed, including factors that characterize the environmental and social efficiency of the enterprise, as well as factors affecting the effectiveness of the enterprise management system. The factors for assessing environmental efficiency included assessments characterizing emissions of greenhouse gases and other harmful substances, the level of energy consumption, as well as the harm caused to water resources. The factors for assessing social effectiveness included assessments related to the level of wages, the level of injuries, the assessment of the effectiveness of labor protection measures and the assessment of staff housing conditions. To determine the effectiveness of corporate governance, factors related to the assessment of the quality management system, the assessment of the quality of risk management systems, and the assessment of the overall financial condition of the enterprise are taken into account. The proposed computer complex consists of two modules. The first module is used to form an integral estimate. The second module is used to correlate the received assessment to one of the seven classes of the state. The proposed provisions are based on the methods of fuzzy set theory and the property of the hierarchical fuzzy inference system, which is based on the Sugeno algorithm. The results of the study led to the conclusion that the system allows you to track the sharp deviation of each of the parameters. The presence of a block of grouping values makes it possible to form classes of states of the evaluated objects. Each of the state classes is identified with one of the seven levels of the ESG score value. The conclusions made open up the possibility of further development of corporate information systems.
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