Purpose – The purpose of this paper is to help the financial institutions improve the predictability of business failure of supply chain finance (SCF) clients with the use of external big data set. Design/methodology/approach – A prediction model for the business failure of SCF clients was built upon different theoretical perspectives. Logistic regression method was deployed to test the model. Findings – The authors develop a model that illustrates several key determinants to predict the probability of business failure of SCF clients based on several theoretical perspectives. The results show that taxable sales revenue, frequency of making value added tax (VAT) payment, number of counterparty for VAT invoice issuance, frequency of VAT invoice issuance and firm age are negatively correlated with business failure of SCF clients while the VAT paid and industry clockspeed are positively correlated with their business failure. Practical implications – This paper shows how financial institutions can effectively leverage the external information sources through “unconventional” predictor variables in order to reduce the credit risks associated with business failure of SCF clients. Originality/value – This paper is one of the first to focus on the potential use of financial big data set from external sources to improve of predictability of financial institutions on the business failure of SCF clients. In addition, this paper is a pivotal study on the financial client risk assessment based on taxpaying behaviors, tax amount, firm and industry characteristics.

Purpose The purpose of this paper is to empirically investigate the joint effects of lead time, information sharing and the accounts receivable period on reverse factoring (RF) adoption from the suppliers’ perspective. Design/methodology/approach Supported by one of the largest commercial banks in China, survey data are collected from 424 Chinese manufacturing firms and analyzed using regression methods. Findings The results suggest that lead time positively affects suppliers’ RF adoption directly and indirectly through the accounts receivable period. Meanwhile, information sharing has a positive, direct and a negative, indirect influence on suppliers’ RF adoption. Originality/value The findings give suppliers and financial institutions a better understanding of how to leverage the benefits of RF.

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Purpose The purpose of this paper is to investigate the effect of human-computer interaction (HCI) on customers’ perceived electronic service (e-service) value and the mediating role of task-technology fit (TTF) in that effect. Design/methodology/approach This paper develops a model based on service-dominant logic (SDL) and TTF theory, and validates it using a hierarchical regression with the data collected from 634 online banking customers in Guangdong Province and Guangxi Zhuang Autonomous Region in China. Findings The findings reveal that HCI in e-service contexts comprises five components. Three fundamental components (i.e. technology functionality, customer technology readiness and task routine) contribute to value co-creation. Two core components (i.e. interaction between customer technology readiness and technology functionality, and interaction between task routine and technology functionality) are inhibitors, but the inhibitory effect of the former is only significant in the Guangdong sample. TTF takes a mediating role in these relationships, but the mediating effect of the former core component is only significant in the Guangdong sample. Originality/value This paper explains two basic questions about the trigger points of value co-creation in e-service contexts (i.e. what their operational definitions are and how to measure them) and unlocks the “black box” of value co-creation by taking TTF as a mediator. SDL and TTF theory are extended. The paper provides suggestions for how practitioners can efficiently advance value co-creation with customers.

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