Optimal strategies for financing a three-level supply chain through blockchain platform finance

ABSTRACT

The application of blockchain technology solves the trust problem between core enterprises (CEs), small and medium-sized enterprises (SMEs), and commercial banks, facilitating CEs and commercial banks to provide guarantee for SMEs and finance them, respectively. This study considers a three-level supply chain composed of a manufacturer, a distributor, and a capital-constrained retailer, and explores the operational strategies of blockchain platform finance (BPF), a supply chain finance mode enabled by blockchain technology. First, optimal decision solutions are obtained through decision and parameter sensitivity analyses. Second, by comparing the BPF and SME independent finance (SIF) modes, we obtain the applicable BPF mode conditions; for instance, when the retailer’s initial capital is low and the production cost is high, BPF is the better option for the manufacturer, distributor, and retailer compared to SIF. Third, we find that risk sharing improves the financing efficiency of the BPF mode. This study provides a theoretical basis for decision makers to implement blockchain supply chain finance at three levels: joint financing and operation decision-making, financing mode selection, and financing efficiency improvement.

KEYWORDS:

• Blockchain technology
• supply chain finance
• capital constraint
• blockchain platform finance
• three-level supply chain

Data availability statement

Data available within the article. The authors confirm that the data supporting the findings of this study are available within the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 https://www.supplychainbrain.com/articles/32605-supply-chain-financing-for-us-mid-market-will-benefit-economy

2 https://www.ibm.com/blockchain/solutions/trade-finance

Additional information

Funding

This work is supported by the National Natural Science Foundation of China [Grant Numbers 71902105; 72132007; 71725004; 12001329].

Notes on contributors

Lu Liu

Lu Liu is currently an associate professor at the College of Economics and Management, Shandong University of Science and Technology, China. He earned his PhD in the field of Management Science and Engineering at Nankai University in 2018. His research interests include the interface of finance and operations management and risk management in supply chain. He is working on a National Natural Science Foundation of China, namely: operation management innovation of supply chain finance under blockchain technology. His research articles have been published by various journals such as Decision Sciences, Transportation Research Part E: Logistics and Transportation Review, Operations Research Letters, and Electronic Commerce Research and Applications.

Yongjian Li

Yongjian Li is currently a professor, at College of Management and Economics of Tianjin University, China. He received his PhD degree from Nankai University, China in 2002. He was a postdoctoral fellow in The Chinese University of Hong Kong and Tsinghua University from 2001 to 2005, respectively. His research interests include Logistics and Supply Chain Management, Operations Management under Platform Economics, Behavioral Operations Management. He has published papers in many journals, including Production and Operations Management, International Journal of Production Research, Decision Sciences, IEEE Transactions, OMEGA-The International Journal of Management Science, European Journal of Operational Research, International Journal of Production Economics, and Journal of Operational Research Society. He is currently an associate editor of the journal Nankai Business Review International and Modern Supply Chain Research and Applications.

Tao Jiang

Tao Jiang received his PhD degree in mathematics in 2017 from the Nanjing University of Science and Technology, China. At present, he is an associate professor at the College of Economics and Management, Shandong University of Science and Technology, China. His research interests include queueing economics, service operation management, stochastic modelling, and supply chain management. He has published articles in Operations Research Letters, Asia-Pacific Journal of Operational Research, Optimization, Transportation Research Part E: Logistics and Transportation Review, etc.