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Trade Finance Contracts for Small-Business Suppliers

Trade Finance Contracts for Small-Business Suppliers
小型企业供应商的贸易融资合同
批准号:
1435158
负责人:
Diwakar Gupta
金额:
$28.22万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-01 至 2017-10-31

项目摘要

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中文摘要
翻译
网络平台正在改变小企业(供应商)销售产品和获得贸易融资的方式。具体来说,小企业是美国创造就业机会的引擎,他们经常在亚马逊、E-bay和spin等网络平台(零售商)上销售产品,并可能直接从零售商那里获得融资(通过贷款或购买承诺),也可能通过KickStarter、IndeGoGo和Crowdfunder等众筹方式获得融资。本研究将开发新的数学模型来评估新兴的贸易融资选择,包括:(1)直接融资,(2)购买承诺,(3)众筹,从小企业、零售商和供应链的角度出发。具体而言,本研究项目旨在回答以下问题:1。在每种融资方案下,供应商和零售商的最佳运营和财务决策是什么?2. 哪一种选择更适合小企业供应商?3. 哪个选项有潜力实现供应链效率最大化?4. 第三方信贷的可用性是否提高了供应链的效率?(这是因为如果供应商从零售商或众筹渠道获得一些融资,第三方贷款机构(如银行)通常更愿意提供贷款。)贸易融资很重要,因为小企业往往难以获得商业贷款来支持其运营;小企业占美国所有就业岗位的60%至80%;美国人口普查局(U.S. Census Bureau)报告称,电子商务的势头稳步增长,从2000年第一季度占零售总额的0.8%(约为7400亿美元中的58亿美元)增长到2013年第三季度的5.9%(约为1.14万亿美元中的670亿美元);2012年,众筹平台在全球范围内通过100多万次个人活动筹集了27亿美元;通过允许公司参与基于股权的在线众筹,《就业法案》有望加快众筹的步伐。这项研究的结果将告知供应商和零售商哪种融资方案对他们和整个供应链是最好的。这项研究将为工程学博士和本科生提供研究机会,有助于培养高素质的人才。本研究项目将带来(1)为经济上重要的小企业供应商建立最优贸易融资和运营策略的新模型,(2)不同融资选择下最优生产政策结构的新见解,以及(3)众筹范式的经济模型。这些方法将包括随机比较、动态程序、单周期和多周期博弈的均衡分析以及众筹数据的统计分析(例如,混合效应模型)。潜在的多周期随机优化问题具有挑战性,因为最优生产策略的结构是未知的。此外,以往没有研究过零售商在多期环境下选择利率或承诺率的问题。同样,对试图通过众筹筹集资金的供应商所面临的决策问题建模的研究也很有限——例如,向出资者提供多少价格折扣。通过对新兴贸易融资范式进行建模,本研究将为其他研究人员开辟新的研究领域。首席研究员的努力还将帮助小企业供应商做出更好的贸易融资和运营决策。
英文摘要
Web platforms are transforming the way small businesses (suppliers) sell their products and obtain trade finance. Specifically, small businesses, the engines of job creation in the U.S., often sell their products on web platforms (retailers) such as Amazon, E-bay, and Spun and may obtain financing either directly from the retailer (via either a loan or a purchase commitment) or crowd-funding options such as KickStarter, IndeGoGo, and Crowdfunder. This research will develop new mathematical models to evaluate emerging trade-finance options including (1) direct financing, (2) purchase commitment, and (3) crowd-funding, from the viewpoint of small businesses, retailers, and supply chains. Specifically, this research project seeks to answer the following questions: 1. What are the optimal operational and financial decisions for suppliers and retailers under each finance option? 2. Which option is superior for small-business suppliers? 3. Which option has the potential to achieve maximum supply chain efficiency? 4. Does the availability of third-party credit improve supply chain's efficiency? (This is motivated by the fact that third-party lenders (e.g., banks) are often more willing to offer loans if suppliers receive some financing from either retailers or crowd sources.) Trade finance is important because small businesses often find it difficult to obtain commercial loans to support their operations; small businesses account for 60 to 80 percent of all US jobs; U.S. Census Bureau reports that e-commerce has steadily gained momentum, increasing from about 0.8 percent of total retail sales in the first quarter of 2000 [approximately $5.8 billion of $740 billion] to 5.9 percent in the third quarter of 2013 [approximately $67 billion of $1.14 trillion]; crowd-funding platforms raised $2.7 billion in 2012 across more than 1 million individual campaigns globally; and the JOBS Act is expected to accelerate the pace of crowd-funding by permitting companies to participate in equity-based, online crowd-funding. The results of this research will inform suppliers and retailers which financing options are best for them and for the supply chain as a whole. The research will help train highly qualified personnel by offering research opportunities for doctoral and undergraduate students in engineering. This research project will lead to (1) new models for establishing optimal trade-finance and operations' strategies for economically significant small-business suppliers, (2) new insights about the optimal production-policy structure under different finance options, and (3) economic models for the crowd-funding paradigm. These methods will comprise stochastic comparisons, dynamic programs, equilibrium analysis of single and multi-period games, and statistical analysis of crowd-funding data (e.g., mixed-effects models). The underlying multi-period stochastic optimization problems are challenging because the structure of an optimal production-policy is not known. Moreover, no previous work has investigated the retailer's problem of choosing either the interest rate or the commitment rate in a multi-period setting. Similarly, there is limited research on modeling the decision problems faced by suppliers who attempt to raise capital via crowd-funding - e.g., how much price discount to offer to contributors. By modeling emerging trade-finance paradigms, this research will open new areas of inquiry for other researchers. The principal investigator's efforts will also help small-business suppliers make better trade-finance and operational decisions.
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  • 批准号:
    1755254
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.18万
  • 财政年份:
    2017
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    1755263
  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
    2017
  • 负责人:
    Diwakar Gupta
  • 依托单位:
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  • 批准号:
    1332680
  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
    2013
  • 负责人:
    Diwakar Gupta
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  • 批准号:
    0653451
  • 项目类别:
    Standard Grant
  • 资助金额:
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  • 财政年份:
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  • 负责人:
    Diwakar Gupta
  • 依托单位:
海外基金