Social preference-weighted sustainability index

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Stated social preference

Technical externalities

Impact materiality

Objectives

This research focuses on developing a novel weighting allocation strategy based on social preference—a departure from current market practices that rely solely on capital.

Given limited resources, which ESG actions should companies prioritize? The study proposes that each dollar of ESG investment should be allocated to initiatives yielding the greatest social benefit, as it not only maximizes impact but also strengthens companies’ incentives for implementation. Our results could provide a priority list for companies ESG actions in making larger social impact.

Key Innovation

The persistent divergence in ESG ratings is a long-standing challenge, extensively documented in academic literature and a major concern for both academia and industry. These discrepancies arise primarily from two sources: indicator selection and weighting allocation.

Currently, indicator selection relies heavily on corporate disclosures, while weightings are determined by rating agencies’ proprietary frameworks rather than empirical societal priorities. The lack of transparency in scoring methodologies further obscures how ESG ratings are calculated. This approach disconnects ESG performance from real-world impact, undermining its relevance for driving meaningful social change.

The research addresses these gaps by prioritizing indicators with tangible societal externalities and establishing weightings through empirically derived social preferences—offering a solution to the limitations of current market practices.

Variables and Formats

Methodology

Indicator Selection

The concept of ‘double materiality’, formally introduced by the European Commission in the 2019 Non-Financial Reporting Directive, requires companies to assess materiality through two lenses: financial relevance and societal/environmental impact.

While GRI standards operationalize the impact dimension of double materiality, they lack explicit weighting mechanisms. We thus adopt GRI’s universal disclosure standards as the foundation for our indicator pool, focusing on metrics with measurable societal externalities.

These indicators are classified into two categories:

- • Pecuniary externalities (internalized by market mechanisms, e.g., cost fluctuations reflected in financial statements).
- • Technical externalities (unpriced societal/environmental impacts, e.g., biodiversity loss).

Our framework prioritizes technical externalities, as they capture true societal costs omitted by traditional financial analysis.

Weighting Allocation

For technical externality indicators, weightings must reflect their marginal societal benefit (or cost)—not arbitrary assignments or capital market biases. To infer these weights (i.e., estimate non-market value), we propose social preference elicitation via: Choice Experiments (CE), a superior method that:

- • Forces multi-attribute trade-offs (e.g., carbon emissions vs. labour rights), mirroring real-world decisions.
- • Generates marginal values essential for ESG weighting and policy design.
- • Avoids contingent valuation’s pitfalls (e.g., overstated willingness-to-pay) through statistically robust discrete-choice modelling.
- • Adapts to dynamic scenarios (e.g., evolving regulatory landscapes).