Combining Different Stakeholders’ Opinions in Multi-Criteria Decision Analyses Applying Partial Order Methodology

Standards Pub Date : 2022-12-19 DOI:10.3390/standards2040035
L. Carlsen, R. Bruggemann
{"title":"Combining Different Stakeholders’ Opinions in Multi-Criteria Decision Analyses Applying Partial Order Methodology","authors":"L. Carlsen, R. Bruggemann","doi":"10.3390/standards2040035","DOIUrl":null,"url":null,"abstract":"Multi-criteria decision analyses (MCDA) for prioritizations may be performed applying a variety of available software, e.g., methods such as Analytic Network Process (ANP) and Elimination Et Choice Translating Reality (ELECTRE III) as recently suggested by Kalifa et al. In addition to a data matrix, usually based on indicators and designed for describing the parts of the framework intended for the MCDA, these methods require input of a variety of other parameters that are not necessarily immediately obtainable. Often the indicators are simply combined by a weighted sum to obtain a ranking score, which is supposed to reflect the opinion of a multitude of stakeholders. A single ranking score facilitates the decision as a unique ordering is obtained; however, such a ranking score masks potential conflicts that are expressed by the values of the single indicators. Beyond hiding the inherent conflicts, the problem arises that the weights, needed for summing up the indicator values are difficult to obtain or are even controversially discussed. Here we show a procedure, which takes care of potential different weighting schemes but nevertheless does not mask any inherent conflicts. Two examples are given, one with a small (traffic) system and one with a pretty large data matrix (food sustainability). The results show how decisions can be facilitated even taking a multitude of stakeholder opinions into account although conflicts are not necessarily completely eliminated as demonstrated in the second case.","PeriodicalId":21933,"journal":{"name":"Standards","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Standards","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/standards2040035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Multi-criteria decision analyses (MCDA) for prioritizations may be performed applying a variety of available software, e.g., methods such as Analytic Network Process (ANP) and Elimination Et Choice Translating Reality (ELECTRE III) as recently suggested by Kalifa et al. In addition to a data matrix, usually based on indicators and designed for describing the parts of the framework intended for the MCDA, these methods require input of a variety of other parameters that are not necessarily immediately obtainable. Often the indicators are simply combined by a weighted sum to obtain a ranking score, which is supposed to reflect the opinion of a multitude of stakeholders. A single ranking score facilitates the decision as a unique ordering is obtained; however, such a ranking score masks potential conflicts that are expressed by the values of the single indicators. Beyond hiding the inherent conflicts, the problem arises that the weights, needed for summing up the indicator values are difficult to obtain or are even controversially discussed. Here we show a procedure, which takes care of potential different weighting schemes but nevertheless does not mask any inherent conflicts. Two examples are given, one with a small (traffic) system and one with a pretty large data matrix (food sustainability). The results show how decisions can be facilitated even taking a multitude of stakeholder opinions into account although conflicts are not necessarily completely eliminated as demonstrated in the second case.
基于偏序方法的多准则决策分析中不同利益相关者意见的结合
优先级的多标准决策分析(MCDA)可以应用各种可用的软件来执行,例如,Kalifa等人最近建议的分析网络过程(ANP)和消除选择翻译现实(ELECTRE III)等方法。除了数据矩阵(通常基于指标,用于描述MCDA框架的各个部分)之外,这些方法还需要输入各种其他参数,这些参数不一定能立即获得。通常,这些指标只是简单地通过加权总和组合起来,以获得排名分数,这应该反映众多利益相关者的意见。单个排名分数有助于决策,因为获得了唯一的排序;然而,这样的排名分数掩盖了单个指标值所表达的潜在冲突。除了隐藏内在冲突之外,还出现了一个问题,即难以获得汇总指标值所需的权重,甚至在讨论中存在争议。这里我们展示了一个过程,它考虑了潜在的不同权重方案,但并不掩盖任何内在的冲突。给出了两个例子,一个是小型(交通)系统,另一个是相当大的数据矩阵(食品可持续性)。结果表明,即使考虑到众多利益相关者的意见,也可以促进决策,尽管冲突不一定完全消除,如第二种情况所示。
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
自引率
0.00%
发文量
0
×
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