The role of Industry 4.0 technologies on performance measurement systems of supply chains during global pandemics: an interval-valued intuitionistic hesitant fuzzy approach

Purpose This paper aims to investigate Supply Chain (SC) Performance Measurement Systems (PMSs) (SCPMSs) that are suitable and applicable evaluate SC performance during unexpected events such as global pandemics. Furthermore, the contribution of Industry 4.0 Disruptive Technologies (IDTs) implement SCPMSs Black Swan is investigated in this study. Design/methodology/approach The research methodology based upon a novel qualitative quantitative mixed-method. A Systematic Literature Review (SLR) was initially employed identify two complete lists IDTs. Then, Interval-Valued Intuitionistic Hesitant-Fuzzy (IVIHF)-Delphi method firstly developed screen extracted SCPMSs. Afterward, Propriety, Economic, Acceptable, Resource, Legal (PEARL) indicator Hanlon innovatively applied prioritize identified IDTs for each finalized SCPMS. Findings Two high-score including operations reference (SCOR) model sustainable SCPMS were recommended improve measuring pharmaceutical emerging economies Iran which societal, biological economic issues undeniable, particularly events. Employing nine simulation, big data analytics, cloud technologies, etc., would facilitate implementing from distinct perspectives. Originality/value one first papers provide in-depth insights into determining priority applying different Proposing multi-layer mixed-methodology involving SLR, IVIHF-Delphi, PEARL another originality offered by paper.