Integrating multiple ESG investors' preferences into sustainable investment: A fuzzy multicriteria methodological approach

Integrating multiple ESG investors' preferences into sustainable investment: A fuzzy multicriteria methodological approach
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DOI:
10.1016/j.jclepro.2017.06.143
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发表时间:
2017-09-20
影响因子:
11.1
通讯作者:
Angeles Fernandez-Izquierdo, Maria
Angeles Fernandez-Izquierdo, Maria
中科院分区:
环境科学与生态学1区
文献类型:
--
作者:
Escrig-Olmedo, Elena;Maria Rivera-Lirio, Juana;Angeles Fernandez-Izquierdo, Maria

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将环境、社会和治理(ESG)标准纳入资产评估过程是一个被社会责任投资者广泛接受的主题。然而,在这一过程中,投资者偏好的整合并没有得到充分的发展。面临的挑战是综合不同投资者的偏好----不仅是传统投资者,而且还有对可持续性问题特别敏感的投资者(对社会负责的投资者)----考虑到对社会负责的投资者不一定是同质的。本文试图通过开发一种基于模糊多标准决策方法(MCDM)的应用方法来解决这一挑战,以整合ESG投资者的偏好,共同考虑。由于投资者的偏好可能会有所不同,这取决于哪些材料方面被认为是在一个部门,这项研究已经使用服装部门的数据进行了测试。结果证实的有用性的方法提出了一个适当的一代的“商业解决方案”,集成了不同的投资者的偏好,同时是一致的个人定义的偏好。(C)2017爱思唯尔有限公司版权所有
The integration of environmental, social and governance (ESG) criteria into the evaluation process of assets is a theme that is widely accepted among socially responsible investors. In this process, however, the integration of investors' preferenceS has not been adequately developed. The challenge is to integrate the preferences of heterogeneous investors- not only conventional investors but also investors who are particularly sensitive to sustainability issues (socially responsible investors)-considering that socially responsible investors are not necessarily homogeneous. This paper attempts to address this challenge by developing a methodological approach based on an application of fuzzy multicriteria decision-making methods (MCDM) to integrate ESG investors' preferences, as jointly considered. Because investors' preferences may vary depending on which material aspects are considered within a sector, this study has been tested using clothing-sector data. Results confirm the usefulness of the methodological approach proposed for a proper generation of a 'commercial solution' that integrates the preferences of various investors and simultaneously is consistent with individually defined preferences. (C) 2017 Elsevier Ltd. All rights reserved.