Evaluation based on Relative Utility and Nonlinear Standardization (ERUNS) Method for Comparing Firm Performance in Energy Sector

Authors

DOI:

https://doi.org/10.31181/dma21202419

Keywords:

Economic, Environment, Social and Governance (EESG) performance, Evaluation based on Relative Utility and Nonlinear Standardization, ERUNS, Multi-criteria Decision Making, MCDM, Logarithmic Percentage Change-driven Objective Weighting, LOPCOW

Abstract

The present paper introduces a new multi-criteria decision making (MCDM) model such as Evaluation based on Relative Utility and Nonlinear Standardization (ERUNS). The proposed method provides a number of unique features such as use of non-linear standardization combined with a new definition for calculating utility values of the alternatives and design flexibility. The new method is applied to compare the firm performances using Economic, Environment, Social and Governance (EESG) framework. Over the last few decades alongside economic gain, the firms have been equally emphasizing on environmental protection, social values and good governance. This paper aims to bring in the economic aspect in terms of market capitalization and enterprise value while uses rating scores for environment, social and governance to put forth an extended performance measurement framework. A set of eight leading firms belonging to the energy sector listed to NSE, India has been considered for the period FY 2022-23 as a case study. The criteria weights are calculated using the Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) method. It is observed that ERUNS provides a stable and reliable ranking result free from the rank reversal issue. This paper shall be of interest to both analysts and practitioners in terms of its robust method and practical performance assessment framework.

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References

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Published

2024-01-05

How to Cite

Biswas, S., Pamucar, D., Dawn, S., & Simic, V. (2024). Evaluation based on Relative Utility and Nonlinear Standardization (ERUNS) Method for Comparing Firm Performance in Energy Sector. Decision Making Advances, 2(1), 1–21. https://doi.org/10.31181/dma21202419