Guest editorial

Abstract

Data-driven decision-making research for supply chain finance Data-driven decision-making research for supply chain finance develops dramatically in recent years. However, the relevant research work is still lack of attention. The purpose of this special issue is to innovative research methodologies from the perspective of data-driven analysis of supply chain finance considering social influence Supply chain finance (SCF) has played an increasingly important role in operational and financial practices and attracted growing attention from academia and industry alike (Yan et al., 2016; Milder, 2008). Supply chain finance not only involves the production and operation decisions of traditional suppliers and retailers facing capital constraints but also banks and some financial institutions play a key role in it (Babich and Kouvelis, 2018;Xu et al., 2018). It is particularly important to evaluate the efficiency of banks and other financial institutions. The current literature on supply chain finance involves many aspects, batch ordering (Shang et al., 2009), buyer intermediation (Tunca and Zhu, 2018), factoring and reverse factoring (Kouvelis and Xu, 2021), sourcing and risk management, (Tang et al., 2018) etc. At present, the development of mobile Internet makes the communication between members of the supply chain more timely (Akpakwu et al., 2017;Zhang et al., 2019), and the data of enterprises, consumers and banks also present massive and complex data (Li et al., 2019(Li et al., , 2018. Given that the previous literature rarely studies supply chain finance from these two dimensions, this special issue aims to fill this gap.This special issue of industrial management and data systems contains 12 research papers. These papers focus on recent advances topics of data-driven decision-making research for supply chain finance including rural supply chain finance problem, blockchaindriven cyber-credit evaluation system (BCCES), the two-stage data envelopment analysis model under meta-frontier and group frontier, optimal selection of standardized modular containers (SSMC) issues, the credit risk of collaboration in a supply chain finance network, sustainable supplier selection problem, a two-stage fairness concern efficiency model, supply chain integration with online financial consumption, merger and acquisitions (M&A), DEA model with assurance region (AR) restrictions, optimal financial and ordering strategies with environmental protection and the two-stage meta-frontier DEA model.The study by Liu et al. proposes a two-stage data envelopment analysis model to evaluate the performance of rural supply chain finance (RSCF) service systems in China. This twostage model considers not only the technical gap between RSCF systems but also the maximization of intermediate output. First, the paper shows the overall efficiency of China's RSCF systems is low, and there remains great potential for improvement. Second, the relationship between rural residents' disposable income and the efficiency of RSCF systems is U-shaped, and the ...