Financing models for an online seller with performance risk in an E-commerce marketplace

Sambit Brata Rath, Preetam Basu, Prasenjit Mandal and Samit Paul

Transportation Research Part E: Logistics and Transportation Review, 2021, vol. 155, issue C

Abstract: Third-party sellers on e-commerce marketplaces (e.g., Amazon and Alibaba) have been primarily dependent on conventional financing modes such as bank credit financing (BCF) to meet their working capital requirements. Many of these platforms have recently started novel financing programs (platform credit financing, PCF) for the sellers under the umbrella of Supply Chain Finance. For example, Amazon provides unsecured loans to third-party sellers on its platform under the Amazon lending program. These loans are risky for the platform. If the seller is unable to fulfill customer’s orders because of some internal inefficiencies (performance risk), the platform loses the loan amount and incurs a goodwill cost among its customer base. In this paper, we develop a series of game-theoretic models to analyze and compare BCF and PCF for a cash-constrained third-party seller on an e-commerce marketplace. We derive optimal interest rates that the platform may charge the seller depending on its performance risk. We derive conditions under which either BCF or PCF could be more profitable for the seller. We introduce innovative contracts (Guaranteed Demand Increment Contract and Lending Rate Matching Contract initiated by the platform and Lumpsum Transfer Contract initiated by the seller) that incentivize the seller or platform to act in a mutually beneficial way. Our analysis shows that these contracts achieve win–win outcomes and increase the total supply chain profit.

Keywords: E-commerce; Supply chain finance; Performance risk; Contract; Game theory (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (12)

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DOI: 10.1016/j.tre.2021.102468

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