This study examines the role of financial service providers (FSPs) in assessing the supply chain credit of small and medium-sized enterprises (SMEs) and how they help SMEs obtain supply chain finance (SCF) through an established digital platform using big data analytics (BDA).
This study conducted data mining analysis on the archival data of China's FSPs in the mobile production industry from 2015 to 2018, using neural networks in the first stage and multiple regression in the second stage.
The findings suggest that digital platforms sponsored by FSPs have a discriminative effect based on implicit BDA on identifying the quality and potential risks of borrowers. The results also show that tailored information utilised by FSPs has a supportive effect based on explicit BDA in helping SMEs obtain financing.
This study contributes to the emergent research on BDA in supply chain management by extending the contextual research on information signalling and platform theory in SCF. Furthermore, it examines the distinctive financing decision models of FSPs and provides a solution that addresses the information deficiency and overload of both lenders and borrowers and plays a certain reference role in alleviating the financing problems of SMEs.
This study is supported by the National Natural Science Foundation of China (No. 71872177; 72072174).
Song, H., Li, M. and Yu, K. (2021), "Big data analytics in digital platforms: how do financial service providers customise supply chain finance?", International Journal of Operations & Production Management, Vol. 41 No. 4, pp. 410-435. https://doi.org/10.1108/IJOPM-07-2020-0485
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