Measuring ESG Risk in Supply Networks

Abstract

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.

Figures (12)

• Figure 1: (a) Shows an ostensibly good company $a$, with a good ESG rating, being supplied by and supplying badly rated companies. (b) Shows a company with a bad ESG rating, $b$ effectively trading with $a$ through an intermediary $w$.
• Figure 2: An example supply network. We will mostly focus on the target company $a$. Colours represent ESG ratings, the more red, the worse the rating.
• Figure 3: (a) Under max aggregation $x_{MAX}(a) = x_{MAX}(b)$, the behaviour of any company but the worst is irrelevant. (b) Under average aggregation $x_{AVG}(a) = x_{AVG}(b)$, a bad association can be compensated by good ones, giving a neutral effect.
• Figure 4: Contribution from paths originating at $b$ to the harm at $a$ using (a) all paths (b) all shortest paths (c) shortest path.
• Figure 5: (a) Tree-like network. (b) Same network as (a) with two companies added at the base of the supply chain and a direct link between the company labelled 75 and the target. (c) Adds loops. Colour corresponds to harm, more red is means higher $h(i)$, labels show the exact values.