Supply chain network, information sharing and SME credit quality

Abstract

Purpose – The purpose of this paper is to examine the effect of small and medium enterprises (SMEs)’ supply chain network on influencing credit quality, or more specifically, whether bridging tie (structural network) or strong tie (relational network) of SMEs in the supply chain can improve the availability of equity and debt capital through information sharing. Design/methodology/approach – A survey was conducted in manufacturing industry in China and 208 valid questionnaires were used to test all the hypotheses. The data were then analyzed by employing partial least squares path modeling. Findings – The results suggest that both strong tie and bridging tie of SMEs can lead to a positive effect on information sharing in supply chain, which can further enhance the credit quality for SMEs. However, without information sharing, the strong tie has not significant influence on SMEs’ credit quality, while bridging tie can directly impact on credit quality. Originality/value – Despite their crucial role in sustaining national economies, SMEs are beset by the critical constraint of risk-free financing. Based on a survey, this research finds that the credit quality of SMEs is affected by two important factors: one concerns information sharing in supply chain and the other relates to the attributes of SMEs’ supply chain network. This study implies that a SME may have a financing advantage for better embedding in the supply chain network, but different effects will be experienced according to constraints associated with information asymmetry in the supply chain.

The joint effects of lead time, information sharing, and the accounts receivable period on reverse factoring

“…Pezza As for the informational and technological factors, Caniato et al (2019) highlight the role of real time information and digital technologies in improving information sharing along the supply chain and selecting the most suitable supply chain financing scheme. Song et al (2016) report that information sharing in supply chains can significantly enhance firms' credit quality which facilitates their supply chain financing adoption. Pezza (2011) also emphasizes the role of information technology in providing online 6 visibility into supply chain activities in the implementation of supply chain finance.…”

Forecasting SMEs' credit risk in supply chain finance with an enhanced hybrid ensemble machine learning approach

“…The current economic downturn and variations, as shaped after the 2008 global financial crisis, has further increased the financial pressure on SMEs, and thus SMEs urgently search for new ways of financing to obtain easy credit (Ali et al, 2018, Lekkakos andSerrano, 2016). In the past, SMEs would seek financing from commercial banks based on their own terms and credits (Song et al, 2016). However, a limited operating history, incomplete financial statements, insignificant performance, high levels of risk, and many other factors have constrained most SMEs to effectively receive financing through traditional methods Wang, 2013, Song et al, 2016).…”

“…From an economic globalization perspective, Lekkakos and Serrano (2016) argue that the global financial crunch, credit shortages and high borrowing costs hinder SMEs from obtaining loans; nevertheless, the SCF promptly facilitates SMEs' settlement of their operations in this modern age of globalization. As set forth above, it is appreciated that SMEs are capitalconstrained and weak supply chain members whose financing performance and competitiveness in supply chains are significantly improved by SCF (Song et al, 2016).…”

Performance Indicators in the Wine Supply Chain Context: a Framework for Explanation and Action

“…In the WSC, through links previously built between the members, it is possible to identify different types of flows. Of particular importance are the physical flows (raw materials, semifinished products, and finished products) and the information flows that enable monitoring of physical flows (Lam et al, 2013;Franken, 2014;Song et al, 2016). Craighead et al (2007) identify these three types of flows more precisely: (1) "forward" flow corresponds to the movement of materials and products from a WSC member located upstream to a WSC located downstream; (2) "backward" flow refers to the flow of materials from a WSC member located down stream to a WSC member located upstream (e.g.…”