Information Content Measurement of ESG Factors via Entropy and Its Impact on Society and Security

Abstract

We conducted a singular and sectoral vulnerability assessment of ESG factors of Dow-30-listed companies by applying the entropy weight method and analyzing each ESG factor’s information contribution to the overall ESG disclosure score. By reducing information entropy information, weaknesses in the structure of a socio-technological system can be identified and improved. The relative information gain of each indicator improves proportionally to the reduction in entropy. The social pillar contains the most crucial information, followed by the environmental and governance pillars, relative to each other. The difference between the social and economic pillars was found to be statistically not significant, while the differences between the social pillar, respective to the economic and governance pillars were statistically significant. This suggests noisy information content of the governance pillar, indicating improvement potential in governance messaging. Moreover, we found that companies with lean and flexible governance structures are more likely to convey information content better. We also discuss the impact of ESG measures on society and security.

Do Companies in Different Industries Respond Differently to Stakeholders’ Pressures When Prioritising Environmental, Social and Governance Sustainability Performance?

“…The relative performance of each sector to the average sector performance was analysed to determine which sectors communicate ESG well, and which sectors distort the information content of the corresponding ESG measure. The study found that the healthcare, defence, and automotive sectors are conveying unclear messaging within the environmental and social pillar, while the financial, consumer goods, and industrial sectors convey messages very efficiently in these pillars [43]. Another key finding was that sectors with clear, lean, and flexible governance structures, such as automotive, IT, and travel, are most effective in messaging [43].…”

“…The study found that the healthcare, defence, and automotive sectors are conveying unclear messaging within the environmental and social pillar, while the financial, consumer goods, and industrial sectors convey messages very efficiently in these pillars [43]. Another key finding was that sectors with clear, lean, and flexible governance structures, such as automotive, IT, and travel, are most effective in messaging [43].…”

“…Reference [43] performed a sector analysis of the 12 sectors represented on the US Dow 30 Index according to their entropy contribution in each of the ESG pillars, relative to each other. The relative performance of each sector to the average sector performance was analysed to determine which sectors communicate ESG well, and which sectors distort the information content of the corresponding ESG measure.…”

On Conditional Tsallis Entropy

“…Depending on the entropy measure used, all of these have been applied in many different areas of knowledge, such as physics [20], information theory [21,22], complexity theory [23][24][25], security [26][27][28], biology [29][30][31][32], finances [33], and medicine [34][35][36], among others. The conditional Tsallis entropy, as suggested in Reference [37], can be directly applied to information theory, especially coding theory.…”