Search results

This paper aims to investigate the relationship between information integration, supply chain capabilities and credit quality of small and middle enterprises (SMEs) in supply chain finance (SCF).

Grounded in the resource-based view (RBV) and signaling theory, this study proposes a theoretical model. Then, structural equation modeling and interview analysis are employed to test the theoretical model.

The results show that both two aspects of information integration, namely, information technology and information sharing, have positive effects on the SMEs’ credit quality in SCF, and these effects are mediated by supply chain capabilities.

First, the paper contributes to SCF literature by simultaneously examining the role of two dimensions of information integration (information technology and information sharing) in enhancing SMEs’ credit quality. Second, this paper enriches the existing theoretical research on SCF by integrating the SMEs perspective and SCF service provider perspective. Moreover, this paper explores the indirect effects of information integration on SMEs’ credit quality by incorporating supply chain capabilities as a mediating factor.

The purpose of this paper is to examine how a supply chain (SC) network helps small and medium enterprises (SMEs) to obtain liquidity and working capital for enhancing their performance while developing the relationships among SC members through information sharing. Moreover, this study also investigates whether a strong tie or bridge tie improves the availability of SMEs’ credit and performance.

Using a survey approach, data were collected from textile SMEs, located in Pakistan. Structural equation modeling and hierarchical regression model were run to validate the proposed model and the relationships.

Findings highlighted that strong tie and bridge tie of SMEs positively and significantly enhance the credit quality and SMEs’ performance. Furthermore, information sharing significantly moderates the relationship between SC network ties and SMEs’ credit quality. Credit quality significantly explains the indirect (mediation) association between the strong tie and the firm performance.

This study will help the SMEs’ entrepreneurs and SC executives to strengthen the liquidity position of SME and improve SMEs’ performance by developing the bridge ties. SMEs should share more information in their SC network while performing business transactions so that financers or lenders can easily access their operational capabilities and individual characteristics to offer them quality credit such as supply chain finance (SCF).

SMEs always face the issue of risk-free financing which adversely affects the firm performance. This study covered the hidden gap in SCM and SMEs’ financing literature by identifying the crucial role of SCF as quality credit in the development of SMEs. Moreover, SMEs can get benefits (e.g. quality credit=SCF) for better embedding in an SC network through information sharing.

The purpose of this paper is to understand how knowledge spillover and access in a supply chain network enhance the credit quality in supply chain finance (SCF) of small and medium enterprises (SMEs).

Drawing on network theory and a knowledge-based view (KBV) of SCF, this paper proposes a theoretical model and tests it using survey data from a sample of 248 SMEs in China.

The main finding is that both strong ties and dense ties within a supply chain network have positive effects on SMEs’ credit quality, and these effects are mediated by knowledge spillover and knowledge access. Interestingly, knowledge spillover is found to have a positive effect on knowledge access.

This paper is the first to investigate the relationship between supply chain network and supply chain financing from a KBV. The proposed model captures the complexity in the interaction among different attributes of supply chain networks (i.e. strong ties and dense ties), different aspects of knowledge transfer (i.e. knowledge spillover and knowledge access) and SMEs’ credit quality in SCF. The results not only show the importance of SMEs’ supply chain networks to SMEs’ credit quality but also contribute to the understanding of the KBV in SCF.

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.

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.

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.

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.

This study examines the role of financial service providers (FSPs) in assessing the supply chain credit of small and medium-sized enterprises (SMEs) and how they help SMEs obtain supply chain finance (SCF) through an established digital platform using big data analytics (BDA).

This study conducted data mining analysis on the archival data of China's FSPs in the mobile production industry from 2015 to 2018, using neural networks in the first stage and multiple regression in the second stage.

The findings suggest that digital platforms sponsored by FSPs have a discriminative effect based on implicit BDA on identifying the quality and potential risks of borrowers. The results also show that tailored information utilised by FSPs has a supportive effect based on explicit BDA in helping SMEs obtain financing.

This study contributes to the emergent research on BDA in supply chain management by extending the contextual research on information signalling and platform theory in SCF. Furthermore, it examines the distinctive financing decision models of FSPs and provides a solution that addresses the information deficiency and overload of both lenders and borrowers and plays a certain reference role in alleviating the financing problems of SMEs.

In industrial and business-to-business (B2B) marketing research, a business network ecosystem is an important antecedent of small- and medium-sized enterprises’ (SMEs’) performance. The purpose of this study is to clarify the direct and indirect effects of ecosystem network health on SMEs’ credit quality.

The data is collected from a survey of operations managers and financial managers of 282 SMEs in China. Structural equation modeling is used to test the hypotheses, and latent moderated structural equations are used to estimate the moderating effect model.

This research indicates that ecosystem network health can directly affect SMEs’ credit quality and have an indirect impact on credit quality through value co-creation capability. In addition, better informal institutional arrangements in the ecosystem can amplify the positive effects of network health and value co-creation capability on SMEs’ credit quality.

From an ecosystem perspective, it is necessary to bring the ecosystem characteristics into business scenario and explore their impacts on SMEs’ financing behaviors. This study contributes to B2B marketing research in terms of investigating the role played by ecosystem characteristics and value co-creation capability.

The purpose of this study is to examine how the quality management of small and medium-sized enterprises (SMEs) impacts their supply chain financing performance (SCFP). This study also investigates the mediating roles of organisational dependence between quality management and the SCFP of SMEs, as well as the moderating role of environmental dynamics.

Questionnaires were administered to 248 financial managers responsible for supply chain finance (SCF) in SMEs in China. Data analysis techniques used include necessary condition analysis and multiple regression analysis.

Research findings show that, in SCF, the quality management of SMEs positively predicts their SCFP through the mediation of the organisational dependence of the focal enterprises in the supply chain network. Environmental dynamics are also found to moderate the relationship between quality management and SCFP through the organisational dependence of capital providers.

To the best of our knowledge, this is the first study to explore the relationships between SMEs' quality management and their SCFP. Also, this study provides a new theoretical lens through which to study SCF by introducing signalling theory.

This study empirically investigates how ambidextrous innovations and their balancing affect the supply chain financing performance (SCFP) of small and medium-sized enterprises (SMEs), based on signaling theory. Moreover, this study explores the moderating effect of the breadth and depth of digital technology deployment on the relationship between ambidextrous innovations and the SCFP of SMEs.

A mixed-methods design is used, including a qualitative study and a quantitative study. Qualitative data have been collected from six multi-cases in different industries. Questionnaire data have been collected from 259 SMEs in China, and a multiple regression model is used to verify the research hypotheses.

The findings indicate that, in supply chain financing, both exploitative innovation and exploratory innovation are helpful in improving the SCFP of SMEs. For resource-constrained SMEs, a relative balance between exploitative innovation and exploratory innovation can help improve SCFP. The breadth of digital technology deployment can strengthen the relationship between exploitative innovation and SCFP, while the depth of digital technology deployment can weaken the relationship between exploratory innovation and SCFP. In addition, increasing the depth of digital technology deployment strengthens the positive correlation between the relative balance of ambidextrous innovations and SCFP.

To effectively obtain supply chain financing, SMEs can either concentrate their limited resources on a single type of innovation or use relative balance strategies to simultaneously pursue two innovations. In addition, in the process of obtaining supply chain financing by ambidextrous innovations, SMEs should appropriately deploy digital technologies.

This study first deconstructs the impact mechanism of ambidextrous innovation capabilities on SCFP based on signaling theory, and then discusses the balancing effect of ambidextrous innovations on SCFP in the cases of resource-constrained SMEs. This study also goes further and finds the negative moderating effect of digital technology deployment in the process of supply chain financing.

The purpose of this study is to examine how existing supply chain finance challenges confronting SMEs are affected by the emergence of smart fintech providers. In so doing the paper aims at uncovering critical role of fintech service provision in SCF and associated mechanisms that affect the SCF partners.

An in-depth case study approach has been applied in this study. The overall design is informed by a 5-stage-based case study approach developed in operation management, including the literature review and research question, followed by case selection and instrument development, the data gathering, the analysis and findings and dissemination.

The study shows that fintech service provider is capable of offering different digital technologies adapted to specific needs while concomitantly orchestrating the information flow across the partners. Key mechanisms that influence the establishment of trust-based relationships among the SCF partners, and related service processes and value creation based on the platform system architecture are explained.

Several practical implications for digital platform management and other key digital SCF partners are identified.

This paper contributes a novel perspective on the importance of digital trust in SCF and also contributes to the existing literature by filling up a gap with a new and fine-grained understanding of the role of fintech companies in SCF.

The purpose of this paper is to propose a data-driven model to predict credit risks of actors collaborating within a supply chain finance (SCF) network based on the analysis of their network attributes. This can support applying reverse factoring mechanisms in SCFs.

Based on network science, the network measures of the actors collaborating in the investigated SCF are derived through a social network analysis. Then several supervised machine learning algorithms are applied to predict the credit risks of the actors on the basis of their network level and organizational-level characteristics. For this purpose, a data set from an SCF within an automotive industry in Iran is used.

The findings of the research clearly demonstrate that considering the network attributes of the actors within the prediction models can significantly enhance the accuracy and precision of the models.

The main limitation of this research is to investigate the applicability and effectiveness of the proposed model within a single case.

The proposed model can provide a well-established basis for financial intermediaries in SCFs to make more sophisticated decisions within financial facilitation mechanisms.

This study contributes to the existing literature of credit risk evaluation by considering credit risk as a systematic risk that can be influenced by network measures of collaborating actors. To do so, the paper proposes an approach that considers network characteristics of SCFs as critical attributes to predict credit risk.