2026-09-20T23:35:12Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1515592023-08-01T04:22:17Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Rigobon, Roberto
Robinet, Mathilde
Sloan School of Management
2023-07-31T19:48:34Z
2023-07-31T19:48:34Z
2023-06
2023-07-14T20:00:02.785Z
https://hdl.handle.net/1721.1/151559
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.
S.M.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright retained by author(s)
https://rightsstatements.org/page/InC-EDU/1.0/
Unveiling the ESG Landscape: Exploring Revealed Preferences
through Archetypal Analysis of Decision-Makers in
Environmental, Social, and Governance Causes
Thesis
application/pdf
Master
Master of Science in Management Studies
Publication
unknown
unknown
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<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.</Abstract>
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