FUZZY MULTIPLE CRITERIA GROUP DECISION-MAKING IN PERFORMANCE EVALUATION OF MANUFACTURING COMPANIES

Q3 Economics, Econometrics and Finance
Sara SALEHI
{"title":"FUZZY MULTIPLE CRITERIA GROUP DECISION-MAKING IN PERFORMANCE EVALUATION OF MANUFACTURING COMPANIES","authors":"Sara SALEHI","doi":"10.35784/acs-2023-23","DOIUrl":null,"url":null,"abstract":"Today's market competition requires constant improvement of manufacturing companies. The primary key to sustainable improvement is evaluating the efficiency of manufacturing processes, which inevitably demands access to thorough and comprehensive information. However, due to the multiple numbers of effective factors that are varied in nature and value, it is impossible to identify certain factors that ensure the efficiency of a manufacturing procedure. As a solution, this paper proposes a novel approach that applies fuzzy TOPSIS. This approach provides the flexibility of evaluating multiple and varied factors of different weights in scrutinizing the efficiency of a manufacturer. The proposed approach has been applied to three different manufacturers (i.e., alternatives) in three steps. In the first step, with reference to the related literature and comments of manufacturing experts, the valuable factors (i.e., the criteria) have been selected to which experts specified linguistic terms. Linguistic terms were then converted to fuzzy numbers. Fuzzy TOPSIS was applied to analyze the efficiency performance of manufacturers. In the last step, to determine the impact of criteria weights on the decision-making process, sensitivity analysis was carried out. The findings confirm the implacability of the proposed approach to manufacturing performances in a consolidated manner. The approach can be employed by marketing managers, senior administrators, and other authorities in the manufacturing and business sectors.","PeriodicalId":36379,"journal":{"name":"Applied Computer Science","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35784/acs-2023-23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0

Abstract

Today's market competition requires constant improvement of manufacturing companies. The primary key to sustainable improvement is evaluating the efficiency of manufacturing processes, which inevitably demands access to thorough and comprehensive information. However, due to the multiple numbers of effective factors that are varied in nature and value, it is impossible to identify certain factors that ensure the efficiency of a manufacturing procedure. As a solution, this paper proposes a novel approach that applies fuzzy TOPSIS. This approach provides the flexibility of evaluating multiple and varied factors of different weights in scrutinizing the efficiency of a manufacturer. The proposed approach has been applied to three different manufacturers (i.e., alternatives) in three steps. In the first step, with reference to the related literature and comments of manufacturing experts, the valuable factors (i.e., the criteria) have been selected to which experts specified linguistic terms. Linguistic terms were then converted to fuzzy numbers. Fuzzy TOPSIS was applied to analyze the efficiency performance of manufacturers. In the last step, to determine the impact of criteria weights on the decision-making process, sensitivity analysis was carried out. The findings confirm the implacability of the proposed approach to manufacturing performances in a consolidated manner. The approach can be employed by marketing managers, senior administrators, and other authorities in the manufacturing and business sectors.
制造企业绩效评价中的模糊多准则群体决策
当今的市场竞争要求制造企业不断改进。可持续改进的主要关键是评估制造过程的效率,这不可避免地需要获得彻底和全面的信息。然而,由于多种有效因素在性质和价值上各不相同,因此不可能确定确保制造过程效率的某些因素。为了解决这个问题,本文提出了一种应用模糊TOPSIS的新方法。这种方法提供了灵活的评估多个不同权重的因素在审查制造商的效率。建议的方法已分三个步骤应用于三个不同的制造商(即替代品)。在第一步中,参考相关文献和制造专家的评论,选择专家指定语言术语的有价值因素(即标准)。然后将语言术语转换为模糊数。运用模糊TOPSIS对生产企业的效率绩效进行分析。最后一步,为了确定准则权重对决策过程的影响,进行了敏感性分析。研究结果证实了以综合方式提出的制造绩效方法的不可调和性。营销经理、高级管理人员以及制造业和商业部门的其他权威人员都可以使用这种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Applied Computer Science
Applied Computer Science Engineering-Industrial and Manufacturing Engineering
CiteScore
1.50
自引率
0.00%
发文量
0
审稿时长
8 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信