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

Purpose Sustainable supply chain finance (SSCF) is a fascinated consideration for both academics and practitioners because the indicators are still underdeveloped in achieving SSCF. This study proposes bibliometric data-driven analysis from literature to illustrate clear overall concept of SSCF that reveals hidden further improvement. Design/methodology/approach A hybrid quantitative qualitative approach combining analysis, fuzzy Delphi method (FDM), entropy weight (EWM) decision-making trial evaluation laboratory (FDEMATEL) employed address uncertainty context. Findings The results show blockchain, cash flow shortage, reverse factoring, risk assessment triple bottom line (TBL) play significant roles comparison challenges gaps among different geographic regions provided advanced local perspective global state-of-the-art assessment. There 35 countries/territories being categorized into five regions. Of regions, two, Latin America Caribbean Africa, needs more improvement, exclusively collaboration strategies financial crisis. Exogenous impacts wars, natural disasters disease epidemics implied as inevitable attributes enhancing sustainability. Originality/value contributes (1) boundary foundations by data driven, (2) identifying critical providing knowledge directions references examination (3) addressing provide viewpoint diagnose comprehensive state art