Customer base environmental disclosure and supplier greenhouse gas emissions: A signaling theory perspective

Date
2023
Authors
Song, Sining
Lian, Jie
Skowronski, Keith
Yan, Tingting (TTU)
Journal Title
Journal ISSN
Volume Title
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Abstract

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.

Description
© 2023 The Authors. Journal of Operations Management published by Wiley Periodicals LLC on behalf of Association for Supply Chain Management, Inc. cc-by-nc-nd
Keywords
environmental disclosure, GHG emissions, signaling theory, supply chain decarbonization
Citation
Song, S., Lian, J., Skowronski, K., & Yan, T.. 2023. Customer base environmental disclosure and supplier greenhouse gas emissions: A signaling theory perspective. Journal of Operations Management. https://doi.org/10.1002/joom.1272
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