已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Prioritizing the European Investment Sectors Based on Different Economic, Social, and Governance Factors Using a Fuzzy-MEREC-AROMAN Decision-Making Model

公司治理 投资(军事) 模糊逻辑 业务 决策模型 环境经济学 计算机科学 经济 财务 人工智能 政治学 政治 法学
作者
Andreea Larisa Olteanu,Alina Elena Ionașcu,Sorinel Cosma,Corina Aurora Barbu,Alexandra Popa,Corina Georgiana Cioroiu,Shankha Shubhra Goswami
出处
期刊:Sustainability [Multidisciplinary Digital Publishing Institute]
卷期号:16 (17): 7790-7790 被引量:7
标识
DOI:10.3390/su16177790
摘要

This study tackles the challenge of identifying optimal investment sectors amid the growing importance of environmental, social, and governance (ESG) factors, which are often complex and conflicting. This research aims to effectively evaluate and prioritize ten investment sectors based on twelve ESG criteria by integrating expert evaluations with two advanced multi-criteria decision-making (MCDM) methods. Three expert teams assessed each sector’s performance based on these criteria using fuzzy logic to manage uncertainties in expert judgments. The MEREC (MEthod based on the Removal Effects of Criteria) identified biodiversity and land use as the most critical factor, while transparency and disclosure was least significant. The AROMAN (Alternative Ranking Order Method Accounting for two-step Normalization) method was further used to rank the ten alternative sectors, with impact investing funds emerging as the top choice, followed by renewable energy and sustainable responsible investment funds. Conversely, ESG-compliant stocks, ESG-focused exchange-traded funds, and ESG-focused real estate investment trusts ranked the lowest. The study’s findings were validated through comparisons with other MCDM tools and sensitivity analysis, confirming the robustness of the proposed model. This research offers a valuable framework for investors looking to incorporate ESG considerations into their decision-making, promoting sustainable and responsible investing practices.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI6.4的应助被Jeff采纳,获得10
刚刚
个性鹭洋完成签到,获得积分10
1秒前
1秒前
2秒前
Ph完成签到 ,获得积分10
3秒前
有魅力的雨竹完成签到,获得积分10
8秒前
JamesPei的应助被Parker采纳,获得30
8秒前
ycx完成签到,获得积分10
8秒前
MC_412发布了新的文献求助10
9秒前
小小彭完成签到,获得积分10
11秒前
XX的应助被elise采纳,获得10
12秒前
qianshui完成签到 ,获得积分10
14秒前
庾芯发布了新的文献求助10
14秒前
科研通AI6.4的应助被Sarina采纳,获得10
14秒前
吃土的牛马完成签到,获得积分10
16秒前
16秒前
合适尔蝶发布了新的文献求助10
17秒前
yang完成签到,获得积分10
17秒前
伍柒叁完成签到,获得积分10
20秒前
yang发布了新的文献求助10
20秒前
精明的彩虹完成签到,获得积分10
22秒前
24秒前
香蕉觅云的应助被yang采纳,获得10
28秒前
科研通AI6.2的应助被yang采纳,获得10
28秒前
xuan完成签到 ,获得积分10
30秒前
Moo完成签到 ,获得积分10
30秒前
30秒前
科研通AI2S的应助被PURPLE采纳,获得10
31秒前
爆米花的应助被氰空采纳,获得10
33秒前
33秒前
dandan发布了新的文献求助10
34秒前
Wendy完成签到,获得积分10
34秒前
小小彭发布了新的文献求助10
35秒前
36秒前
grassland的应助被ddround采纳,获得10
36秒前
852的应助被ddround采纳,获得10
36秒前
39秒前
大模型的应助被庾芯采纳,获得10
39秒前
Jeff发布了新的文献求助10
40秒前
40秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Rosenblum, Global Change Biology 800
自動車の空力技術 800
Organizational Behavior 510
Management and the Arts 510
Issues in Task-Based Language Teaching 500
Geschichtliche Grundbegriffe (GGB), Band 5: Pro–Soz 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7788369
求助须知:如何正确求助?哪些是违规求助? 9326585
关于积分的说明 20411733
捐赠科研通 7377324
什么是DOI,文献DOI怎么找? 3322399
关于科研通互助平台的介绍 2470227
邀请新用户注册赠送积分活动 2339151