Research

As suppliers' emissions contribute to a significant portion of the global environmental footprint, achieving supply chain wide carbon neutrality largely depends on suppliers' greenhouse gas (GHG) emissions reductions. Although suppliers' customers are increasingly signaling their commitment to tackling climate change through environmental disclosure, whether this signal contributes to supplier emissions reduction remains a question. Using signaling theory, this research proposes an emissions-reducing effect of customer base environmental disclosure on a supplier's GHG emissions level. Using a 2010–2017 panel dataset from multiple sources, we find empirical evidence supporting the upstream emissions-reducing effect of customer base environmental disclosure. Further, we identify two customer-base characteristics that affect this relationship: customer base climate innovation and competition. These findings contribute to the sustainable supply chain management literature by illustrating the effects of the customer base on supplier emissions performance. Specifically, customers could motivate a supplier's engagement in emissions reduction by collectively signaling their environmental commitment through enhanced disclosure. However, the effectiveness of this signaling effect can be contingent on the green innovation and competitive dynamics of the customer base.

Under review at Manufacturing & Service Operations Management.

Problem definition: When a firm discloses its environmental performance, how does it impact the suppliers’ disclosure? The answer is not immediately clear. On the one hand, one may expect the suppliers to also follow suit, due to either the direct pressure from the firm or the benefits of supply chain synergy created by the firm’s disclosure. However, this view overlooks an important factor, that suppliers may free-ride on the firm’s disclosure to avoid the associated risks and costs. We shed light on this problem by investigating the relationship between firms’ and suppliers’ disclosure decisions, and the factors that influence these decisions. 

Methodology/results: Using data from Bloomberg’s Environmental, Social, and Governance (ESG) and FactSet Revere datasets, we construct a comprehensive supply network model and employ a twoway clustering two-stage least squares (2SLS) estimation method based on firm-supplier dyads. Our results indicate that an increase in a firm’s environmental disclosure reduces its suppliers’ disclosure, supporting the supplier free-riding argument. We further show that this negative effect is stronger when the supplier is in a complex supply base, the supplier is exclusive to the firm’s product market, or the headquarters of the firm and the supplier are not co-located. 

Managerial implications: Our findings highlight the importance of recognizing the potential supplier free-riding on firms’ environmental disclosure efforts. To address this issue, managers need to adopt proactive measures to improve the visibility of their suppliers to suppress free-riding. For example, firms may collaborate with industry peers to establish shared supplier audit systems. Furthermore, our results can help identify riskier suppliers based on the supply network structure, to facilitate more effective resource allocation when coordinating with suppliers on the disclosure decisions. These insights are highly valuable for industries that demand high supply chain environmental transparency and accountability, such as the clothing sector.

In preparation for submission to Management Science.

In preparation for submission to Journal of Operations Management.