Measuring ESG Risk in Supply Networks
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866912973848576000 |
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| author | Arthur, Rudy Machado, Guillherme |
| author_facet | Arthur, Rudy Machado, Guillherme |
| contents | Environmental, Social and Governance (ESG) rating is a way for investors to prioritise investments in companies with good corporate behaviour. However, ESG ratings are vulnerable to greenwashing in a number of ways. In this paper we study the effect that trade with badly rated companies has on a target company's own rating. To do this we introduce a measurement framework, generalising PageRank and Alpha Centrality, which allows tuning of aggregation and path counting approaches to resist greenwashing and reflect the rater's opinions and preferences for harm accumulation. These metrics allow updating of the target's ESG rating, identification of influential neighbours and assessment of vulnerability of the target to bad behaviour in their supply network. We study these metrics on synthetic ESG interaction networks as well as a real inter-company network and the international trade network. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_18543 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Measuring ESG Risk in Supply Networks Arthur, Rudy Machado, Guillherme Social and Information Networks Environmental, Social and Governance (ESG) rating is a way for investors to prioritise investments in companies with good corporate behaviour. However, ESG ratings are vulnerable to greenwashing in a number of ways. In this paper we study the effect that trade with badly rated companies has on a target company's own rating. To do this we introduce a measurement framework, generalising PageRank and Alpha Centrality, which allows tuning of aggregation and path counting approaches to resist greenwashing and reflect the rater's opinions and preferences for harm accumulation. These metrics allow updating of the target's ESG rating, identification of influential neighbours and assessment of vulnerability of the target to bad behaviour in their supply network. We study these metrics on synthetic ESG interaction networks as well as a real inter-company network and the international trade network. |
| title | Measuring ESG Risk in Supply Networks |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2603.18543 |