Comparing world regional sustainable supply chain finance using big data analytics: A bibliometric analysis

Ming-Lang Tseng, Tat-Dat Bui, Ming Lim, Feng Ming Tsai, Raymond R. Tan

Research output: Contribution to journalArticlepeer-review

1 Downloads (Pure)

Abstract

Sustainable supply chain finance (SSCF) is a fascinated consideration for both academics and practitioners due to the indicators are still underdeveloped in achieving sustainable supply chain finance. This study proposes a bibliometric data-driven from the literature to illustrate a clear overall concept of sustainable supply chain finance that reveals hidden indicators for further improvement.
Original languageEnglish
Pages (from-to)(In-Press)
JournalIndustrial Management and Data Systems
Volume(In-Press)
Early online date17 Feb 2021
DOIs
Publication statusE-pub ahead of print - 17 Feb 2021

Keywords

  • Sustainable chain finance
  • Big data
  • Fuzzy Delphi method
  • Entropy weight method
  • Fuzzy decision-making trial and evaluation laboratory

Fingerprint Dive into the research topics of 'Comparing world regional sustainable supply chain finance using big data analytics: A bibliometric analysis'. Together they form a unique fingerprint.

Cite this