مقاله انگلیسی رایگان در مورد تامین مالی زنجیره تامین: رتبه بندی اعتباری – الزویر ۲۰۱۸

مقاله انگلیسی رایگان در مورد تامین مالی زنجیره تامین: رتبه بندی اعتباری – الزویر ۲۰۱۸

 

مشخصات مقاله
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی  ۲۱ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه الزویر
نوع مقاله ISI
عنوان انگلیسی مقاله Supply chain finance: From traditional to supply chain credit rating
ترجمه عنوان مقاله تامین مالی زنجیره تامین: از سنتی به رتبه بندی اعتباری زنجیره تامین
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مهندسی صنایع، مدیریت
گرایش های مرتبط لجستیک و زنجیره تامین، مدیریت مالی
مجله مجله مدیریت خرید و تامین – Journal of Purchasing and Supply Management
دانشگاه Politecnico di Milano School of Management – Milano – Italy
کلمات کلیدی تامین مالی زنجیره تامین، رتبه بندی مالی، امتیاز فروشنده، عملکرد زنجیره تامین، ریسک اعتباری
کلمات کلیدی انگلیسی Supply chain finance, Financial rating, Vendor rating, Supply Chain Performance, Credit risk
شناسه دیجیتال – doi
https://doi.org/10.1016/j.pursup.2018.06.004
کد محصول E8315
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بخشی از متن مقاله:
۱٫ Introduction

The 2008 financial crisis caused a dramatic reduction in the concession of new loans to companies; at the same time, relevant growth in the interest charged by banks was reported (Ivashina and Scharfstein, 2010). These phenomena were caused by a strong increase in perceived corporate risk, as depicted by corporate credit ratings. In fact, the postcrisis distribution of corporate credit ratings among the most relevant rating agencies showed a considerable decrease in the number of “investment grade” non-financial corporations, as well as a considerable increase in worse ratings (Chava and Purnanandam, 2011). The worsening of credit ratings has a direct impact on bank lending, especially under the Basel requirements (BIS, 2011). Further, the increased perception of credit risk and higher capital requirements driven by Basel II led to an overall increase in bank risk aversion, which led to a restriction of trade finance facilities toward more risky parties (Asmundson et al., 2011). In such a contest, liquidity-scarce companies tried to compensate for the contraction in bank lending through increased access to trade credit, i.e., increasing payment terms toward suppliers and/or reducing settlement terms with customers, with the risk of triggering liquidity shortages along the chain (Klapper and Randall, 2011). These liquidity shortages have a clear supply chain effect: late payments, and even worse defaults, propagate from a company to its suppliers (Raddatz, 2010). In one case out of four, a liquidity shock (for example, related to a customer default) is transferred to the upstream actors along the supply chain (Boissay and Gropp, 2007). This context of cash shortage contributed greatly to the development of solutions for inter-organizational working capital management. Among these, one of the most important approaches is supply chain finance (SCF), which aims to optimize financial flows at an inter-organizational level (Hofmann, 2005; Pfohl and Gomm, 2009) through solutions implemented by financial institutions or technological providers (Chen and Hu, 2011; Lamoureux and Evans, 2011). SCF consists of a broad range of solutions and approaches (Gelsomino et al., 2016a), but all share a common feature: supply chain characteristics, such as the quality of relationships between supply chain players and with financial institutions, greatly affect the successful adoption of SCF solutions (Wuttke et al., 2013). For example, reverse factoring (i.e., one of the most common SCF solutions in which a buyer company facilitates early payment of its trade credit obligations to suppliers) is based on the assessment of buyer-supplier relationships to finance a risky supplier, thanks to its buyer creditworthiness (Caniato et al., 2016). However, traditional financial credit rating models do not adopt the SCF perspective: they are mainly based on the financial characteristics of the single company, such as the level of their debt and their profitability (Edwards, 1997; Wood, 1981). In fact, these financial performance metrics are somehow also impacted by operational performance, but several issues limit their effectiveness to properly assess credit ratings.

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