Sambit Brata Rath;Preetam Basu;Tsan-Ming Choi;Prasenjit Mandal
{"title":"供应链运营的金融科技:平台信贷融资","authors":"Sambit Brata Rath;Preetam Basu;Tsan-Ming Choi;Prasenjit Mandal","doi":"10.1109/TEM.2024.3453595","DOIUrl":null,"url":null,"abstract":"Traditionally, in supply chain management, manufacturers such as \n<italic>Hewlett-Packard</i>\n and \n<italic>Procter&Gamble</i>\n fund their downstream retailers through \n<italic>trade credit financing</i>\n (TCF). Recently, with the advance of FinTech, platforms have also implemented innovative financing schemes called \n<italic>platform credit financing</i>\n (PCF). Both TCF and PCF are risky, which expose the lender to operational risks. Motivated by these real-world practices, we model a three-echelon supply chain in which a capital-constrained retailer, exposed to operational risk, orders from the manufacturer and sells on an online platform. We explore TCF and PCF, and determine the retailer's optimal financing options based on her operational risk and the platform's referral fee for the product category. Our results show that PCF becomes profitable for all three entities when the retailer's operational risk level is high. This result justifies the successful adoption of PCF under a high operational risk scenario where it becomes challenging for the retailer to obtain financing through traditional modes. We also find that TCF may achieve a win-win-win outcome in the presence of a loss-averse lender or in the partial demand fulfillment scenario. To derive more insights and check for the robustness of core findings, we examine several extended cases.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14789-14806"},"PeriodicalIF":4.6000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FinTech for Supply Chain Operations: Platform Credit Financing\",\"authors\":\"Sambit Brata Rath;Preetam Basu;Tsan-Ming Choi;Prasenjit Mandal\",\"doi\":\"10.1109/TEM.2024.3453595\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditionally, in supply chain management, manufacturers such as \\n<italic>Hewlett-Packard</i>\\n and \\n<italic>Procter&Gamble</i>\\n fund their downstream retailers through \\n<italic>trade credit financing</i>\\n (TCF). Recently, with the advance of FinTech, platforms have also implemented innovative financing schemes called \\n<italic>platform credit financing</i>\\n (PCF). Both TCF and PCF are risky, which expose the lender to operational risks. Motivated by these real-world practices, we model a three-echelon supply chain in which a capital-constrained retailer, exposed to operational risk, orders from the manufacturer and sells on an online platform. We explore TCF and PCF, and determine the retailer's optimal financing options based on her operational risk and the platform's referral fee for the product category. Our results show that PCF becomes profitable for all three entities when the retailer's operational risk level is high. This result justifies the successful adoption of PCF under a high operational risk scenario where it becomes challenging for the retailer to obtain financing through traditional modes. We also find that TCF may achieve a win-win-win outcome in the presence of a loss-averse lender or in the partial demand fulfillment scenario. To derive more insights and check for the robustness of core findings, we examine several extended cases.\",\"PeriodicalId\":55009,\"journal\":{\"name\":\"IEEE Transactions on Engineering Management\",\"volume\":\"71 \",\"pages\":\"14789-14806\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Engineering Management\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10670095/\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Engineering Management","FirstCategoryId":"91","ListUrlMain":"https://ieeexplore.ieee.org/document/10670095/","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
FinTech for Supply Chain Operations: Platform Credit Financing
Traditionally, in supply chain management, manufacturers such as
Hewlett-Packard
and
Procter&Gamble
fund their downstream retailers through
trade credit financing
(TCF). Recently, with the advance of FinTech, platforms have also implemented innovative financing schemes called
platform credit financing
(PCF). Both TCF and PCF are risky, which expose the lender to operational risks. Motivated by these real-world practices, we model a three-echelon supply chain in which a capital-constrained retailer, exposed to operational risk, orders from the manufacturer and sells on an online platform. We explore TCF and PCF, and determine the retailer's optimal financing options based on her operational risk and the platform's referral fee for the product category. Our results show that PCF becomes profitable for all three entities when the retailer's operational risk level is high. This result justifies the successful adoption of PCF under a high operational risk scenario where it becomes challenging for the retailer to obtain financing through traditional modes. We also find that TCF may achieve a win-win-win outcome in the presence of a loss-averse lender or in the partial demand fulfillment scenario. To derive more insights and check for the robustness of core findings, we examine several extended cases.
期刊介绍:
Management of technical functions such as research, development, and engineering in industry, government, university, and other settings. Emphasis is on studies carried on within an organization to help in decision making or policy formation for RD&E.