Online peer-to-peer lending platform and supply chain finance decisions and strategies

Taleizadeh, Ata Allah, Safaei, Aria Zaker, Bhattacharya, Arijit ORCID: https://orcid.org/0000-0001-5698-297X and Amjadian, Alireza (2022) Online peer-to-peer lending platform and supply chain finance decisions and strategies. Annals of Operations Research, 315. 397–427. ISSN 0254-5330

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Abstract

Online peer-to-peer (P2P) lending platform is an emerging FinTech business model that establishes a link between investors and recipients of capital in supply chains (SCs). Businesses face capital constraints impacting directly on their final product price and demand. This article studies optimal decisions and operational strategies in a logistics network considering two capital-constrained manufacturers who produce products of different qualities and sell them to a retailer having deterministic demand over a specific period. The high quality product manufacturer borrows capital through an online P2P lending platform with a service fee, while the low quality product manufacturer pre-sells products for competing with the high quality product manufacturer. In this study, we find optimal prices of the SC participants, service rate of the online P2P platform and percentage of the pre-ordering quantity of the retailer. We analyse optimal Stackelberg and Nash equilibrium of the SC participants. We find that an increase in the amount of opportunity cost will cause a decrease in the pre-ordering quantity of the retailer affecting the SC profit in numerous ways. The online P2P lending platform should consider the amount of the retailer’s target profit in determining the platform’s service rate. We posit some practical insights based on our numerical study and observations for SC managers enabling them to take appropriate measures about their optimal strategies according to the networks’ existing economic conditions.

Item Type: Article
Uncontrolled Keywords: capital constrained manufacturers,online peer-to-peer lending platform,pre-selling,optimal decisions,stackelberg game,nash equilibrium,decision sciences(all),management science and operations research ,/dk/atira/pure/subjectarea/asjc/1800
Faculty \ School: Faculty of Social Sciences > Norwich Business School
UEA Research Groups: Faculty of Social Sciences > Research Groups > Innovation, Technology and Operations Management
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Depositing User: LivePure Connector
Date Deposited: 25 Mar 2022 07:30
Last Modified: 22 Oct 2022 17:38
URI: https://ueaeprints.uea.ac.uk/id/eprint/84268
DOI: 10.1007/s10479-022-04648-w

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