Blockchain-enabled Supply Chain Financing (BCF)

Abstract

Blockchain technology holds promise for improving access to financing within supply chains, especially for small and under-financed suppliers. Yet, the specific ways in which blockchain technology mitigates financing frictions and the features that contribute to successful platform implementations remain unclear. We close that gap by analyzing blockchain-enabled supply chain finance (BCF) solutions, which combine blockchain technology with new supply chain finance mechanisms. In our analysis, we examine 312 documents with unstructured text describing 11 real-world BCF solutions, both successful and failed. Using AI-based large language models, we identify patterns connecting seven types of financing frictions and three key blockchain features. We find that transactional friction is the most frequently addressed friction, despite receiving limited attention in the academic literature, while frictions such as bankruptcy costs and taxes---commonly discussed in the literature---are rarely associated with blockchain features in our sample. Tokenization is used sparingly; however, unlike other features, it appears in successful BCF solutions only. Moreover, connections between frictions and features are not random: while transactional and hidden actions frictions are linked to all three blockchain features, other frictions are typically associated with only one. Our findings offer a deeper understanding of the mechanisms through which blockchain adds value in supply chain finance, suggest that aligning blockchain features with specific frictions may enhance the chances of success, and demonstrate a method for using AI to evaluate large amounts of unstructured data in operations management research.

Keywords: Supply Chain Finance, Blockchain, Large Language Models, Natural Language Processing

JEL Classification: G23, G39 ,L89, D22, D82, D85, D92