This study aims to explore conditions for the application of blockchain-enabled financing versus traditional prepayment. It seeks to understand how a short food supply chain can choose more efficient financing pattern under loan risk compensation policy, crucial for designing an optimal short food supply chain.
Employing Stackelberg game, decisions of the short food supply chain regarding the adoption of different financing patterns are modeled. The theoretical model’s outcomes are validated using data from the Ministry of Agriculture and Rural Affairs of China, including publicly available market prices and costs of soybeans and wheat over the past decade. Adjusted market prices are derived using consumer price index for residential prices to eliminate the impact of inflation.
The loan risk compensation rate, prepayment discount rate, blockchain-enabled financing interest rate and distribution of crop output create three distinct scenarios, prompting members of the short food supply chain to form various financing pattern preferences. Simultaneously, loan risk compensation effectively improves supply chain performance. Moreover, the impact of risk compensation is more pronounced at lower output rates.
This research emphasizes that the blockchain-enabled financing pattern is not always dominant. Government departments can shape the financing pattern preferences of supply chain members by adjusting risk compensation rate, thereby promoting the application of the blockchain-enabled financing pattern. This paper contributes to the literature on the adoption of blockchain technology for financing short food supply chain by delving into the issue of financing pattern selection.
