A Multidimensional Approach of Corporate Sustainability Ranking

Abstract

As capital flows increasingly follow responsible investing principles, the need for reliable ESG scores increases. ESG scores provided by rating agencies may be incomplete, inconsistent, and incomparable. This research aimed to present techniques to improve ESG scores for multidimensional decision-making. First, the Linguistic Ordered Weighted Geometric Aggregating LOWGA operator was used to obtain the Fuzzy ESG score of the firms where linguistic attributes were added to ESG scores generated by Refinitiv. This was followed by ranking firms based on the Fuzzy ESG score, stock return, and volatility by using the TOPSIS method. The results showed by adding linguistic attributes to the ESG scores using a LOWGA operator the ESG scores changed significantly. In addition, the study found that the recomputed ESG scores and ranking of firms were significantly different from the rating and scores provided by rating agencies after using the TOPSIS method in ranking as the output was more informative and provides multidimensional information for investors. The study suggests a practical implication for the rating agencies to consider using LOWGA operator and TOPSIS including risk and return measures for more altered and reflective ESG scores to enable the investor to have multidimensional information for more responsible and sustainable investment decision-making.