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Deposit Financing for Capital-Constrained Electric Vehicle Manufacturer in the Presence of Default Risk and Information Asymmetry
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DOI:10.1016/j.ijpe.2026.110065.png)
Abstract
En 中文
Recently, we observed that battery suppliers (BSs) require electric vehicle (EV)-manufacturers to pay deposits first and focus on their collateral levels before supplying batteries. This inevitably induces capital pressures for the capital-constrained EV-manufacturers. In this regard, bank loan financing (BLF) and trade credit financing (TCF) are substantially implemented. The success of both financing hinges on the EV-manufacturer’s default risk, and the relative effectiveness relates to the information asymmetry between the two financing providers (bank and BS). Moreover, multiple backup financing solutions exist once rejected in BLF/TCF. We thereby aim to investigate which financing scheme (BLF/TCF) performs better in the EV industry. Different from the traditional approach (a newsvendor model plus a Stackelberg game), we proposed an enhanced methodology, i.e., concurrently modeling the capital-constrained EV-manufacturer’s default risk by incorporating its cost effort of repayment, and establishing a signaling game under information asymmetry by signaling the EV-manufacturer’s efficiency type via the deposit price. Furthermore, we examine how backup financing synergy alters the performance. Consequently, our findings robustly demonstrate the dominance of TCF and illustrate that the BS sets the deposit at twice the EV-manufacturer’s collateral level and fixes the interest rate under TCF. Under BLF, the signaling game reveals a pooling equilibrium when equity financing is the backup, and both separating and pooling equilibria when it is not. Overall, this study provides theoretical insights for the capital-constrained EV supply chain in selecting the appropriate financing schemes and constructing the optimal contracts when default risk and information asymmetry coexist.
Keywords:
Deposit Financing
Electric Vehicle Manufacturer
Default Risk
Information Asymmetry
Trade Credit Financing
Journal
IF:
10
Papers:
7.9K
Citations:
3.6W
