Unveiling the ESG Landscape: Exploring Revealed Preferences through Archetypal Analysis of Decision-Makers in Environmental, Social, and Governance Causes

Abstract

This research investigates the motivations and decision-making patterns driving individuals' behavior when giving to Environmental, Social, and Governance (ESG) causes. Through the concept of revealed preferences, this study offers a comprehensive exploration of the intricate landscape of ESG resource allocation. The analysis is conducted through the innovative use of the ESG Machine game, offering unique insights into how individual preferences shape unique allocation portfolios and the strategies underpinning these decisions.

The study identifies four distinct archetypes of decision-making - payoff-maximizer based, equality-based, proportional-based, and value-based - and employs a suite of indicators to measure the degree of each archetype in individuals. A key finding is the dominance of value-based decision-making, although strategies like impact maximization and equal distribution of payoffs across all causes also emerged.

These findings bear profound implications for ESG investing by offering invaluable insights that can shape the formulation of more potent investment strategies. By uncovering the complexities of individual decision-making and the differing strategies at play, this study paves the way for designing interventions that align personal values and financial choices effectively. This tailored approach has the potential to resonate deeply with individuals, engaging them based on their decision-making archetype, thereby enhancing the efficiency of ESG investments.