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Ranking corporate sustainability: a flexible multidimensional approach based on linguistic variables
Author(s) -
Liern V.,
PérezGladish B.
Publication year - 2018
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/itor.12469
Subject(s) - sustainability , ranking (information retrieval) , topsis , corporate sustainability , corporate social responsibility , index (typography) , preference , corporate governance , rank (graph theory) , business , multiple criteria decision analysis , order (exchange) , fuzzy logic , operator (biology) , computer science , accounting , economics , operations research , mathematics , microeconomics , finance , artificial intelligence , ecology , biology , biochemistry , chemistry , repressor , combinatorics , world wide web , transcription factor , gene
Corporate sustainability implies a compromise between the present environmental, social, and economic needs of a firm's stakeholders and their future needs. Corporate sustainability is therefore a multidimensional concept. Nowadays, several independent rating agencies rate firms in terms of environmental, social, and governance (ESG) criteria. These ratings are usually used by main sustainability indices such as the Dow Jones Sustainability Index, FTSE4 Good, Stoxx Sustainability Index, or Euronext Vigeo Family to select companies to invest in. Only those firms performing better than the average of their sector are selected. However, although providing linguistic ratings about the performance of the firms in individual ESG criteria with respect to their sector, rating agencies do not usually provide overall ESG rates describing the global performance of the firms in terms of ESG. In this paper, we propose a flexible operator, linguistic ordered weighted geometric aggregating operator (LOWGA), which will allow us to define the fuzzy ESG performance of the firms based on the linguistic labels provided by the rating agencies. Once overall ESG scores have been obtained, we will use them together with financial criteria to rank the firms in terms of their sustainability using a suitable multiple criteria decision aid (MCDA) approach, namely, TOPSIS (technique for order preference by similarity to ideal solution).