Just Published – Data-driven Decision-making Research for Supply Chain Finance

Industrial Management & Data Systems

Guest Editors

Jie Wu, School of ManagementUniversity of Science and Technology of China, Hefei, China

Ron Fisher, Griffith University, Brisbane, Australia


Data-driven decision-making research for supply chain finance has developed dramatically in recent years and until now has lacked relevant research attention. The purpose of this special issue is to present innovative research methodologies from the perspective of data-driven analysis of supply chain finance considering social influence.

The papers featured in this special issue focus on topics such as: rural supply chain finance problems; blockchain-driven 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.

Table of Contents

Guest editorial
Jie Wu, Ron Fisher

Performance of China's rural supply chain finance: from the perspective of maximization of intermediate output
Xiaohong Liu, Yue Du, Jiasen Sun, Rui Yang, Feng Yang

A blockchain-driven cyber-credit evaluation approach for establishing reliable cooperation among unauthentic MSMEs in social manufacturing
Jiajun Liu, Pingyu Jiang

How monetary policies and ownership structure affect bank supply chain efficiency: a DEA-based case study
Yelin Hu, Bingjing Li, Ying Zha, Douqing Zhang

Centralized selection of standardized modular containers: a multi-criteria method considering freight behavior and shipper segment
Xiang Ji, Bingru Guan, Guowei Liu

A data-driven and network-aware approach for credit risk prediction in supply chain finance
Mohammad Rishehchi Fayyaz, Mohammad R. Rasouli, Babak Amiri

A data envelopment analysis approach by partial impacts between inputs and desirable-undesirable outputs for sustainable supplier selection problem
Mohammad Nemati, Reza Farzipoor Saen, Reza Kazemi Matin

Agricultural loan efficiency in centralized bank supply chains with fairness concern: a DEA-based analysis
Jianguo Zhuo, Yuwei Hu, Min Kang

Impact of data-driven online financial consumption on supply chain services
Lei Li, Yaxuan Dai, Yudong Sun

Data-driven approach to find the best partner for merger and acquisitions in banking industry
Qingyuan Zhu, Xingchen Li, Feng Li, Alireza Amirteimoori

Assessing the efficiency of financial supply chain for Chinese commercial banks: a two-stage AR-DEA model
Guangcheng Xu, Zhixiang Zhou

Analysis of two financing modes in green supply chains when considering the role of data collection
Nenggui Zhao, Qiang Wang

Bank supply chain efficiency analysis based on regional heterogeneity: a data-driven empirical study
Yu Jiang, Mingjun Li, Panpan Xia