A hybrid approach to explore the critical criteria of online supply chain finance to improve supply chain performance

Lu Zhang, Li Cui, Lujie Chen, Jing Dai, Ziyi Jin, Hao Wu

Research output: Journal PublicationArticlepeer-review

4 Citations (Scopus)

Abstract

With the rapid development of information and internet technologies, online supply chain finance is becoming increasingly important in improving supply chain performance from many perspectives, including capital and information. To fully understand the role of online supply chain finance, it is necessary to comprehensively assess the criteria of online supply chain finance that affect supply chain performance. Meanwhile, given the lack of relevant theoretical research and methodologies, this study proposes a hybrid approach that integrates fuzzy set theory, interpretive structural modelling and a Bayesian network to assess and identify the critical criteria. The results show that criteria such as the development of the supply chain industry, incentive mechanisms, e-commerce platforms and the quality of small and medium-sized enterprises are predominant in improving supply chain performance. Finally, some new findings and corresponding suggestions are also provided.

Original languageEnglish
Article number108689
JournalInternational Journal of Production Economics
Volume255
DOIs
Publication statusPublished - Jan 2023

Keywords

  • Bayesian network
  • Fuzzy set theory
  • Interpretive structural modelling
  • Online supply chain finance
  • Supply chain performance

ASJC Scopus subject areas

  • General Business,Management and Accounting
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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