Investigating potential interventions on disruptive impacts of Industry 4.0 technologies in circular supply chains: Evidence from SMEs of an emerging economy

Hannan Amoozad mahdiraji*, Fatemeh Yaftiyan, Aliasghar Abbasi-Kamardi, Jose Arturo Garza-Reyes

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

As a transversal theme, the intertwining of digitalization and sustainability has crossed all Supply Chains (SCs) levels dealing with widespread environmental and societal concerns. This paper investigates the potential interventions and disruptive impacts that Industry 4.0 technologies may have on pharmaceutical Circular SCs (CSCs). To accomplish this, a novel method involving a literature review and Pythagorean fuzzy-Delphi has initially been employed to identify and screen categorized lists of Industry 4.0 Disruptive Technologies (IDTs) and their impacts on pharmaceutical CSC. Subsequently, the weight of finalized impacts and the performance score of finalized IDTs have simultaneously been measured via a novel version of Pythagorean fuzzy SECA (Simultaneously Evaluation of Criteria and Alternatives). Then, the priority of each intervention for disruptive impacts of Industry 4.0 has been determined via the Hanlon method. This is one of the first papers to provide in-depth insights into advancing the study of the disruptive action of Industry 4.0 technologies cross-fertilizing CE throughout pharmaceutical SCs in the emerging economy of Iran. The results indicate that digital technologies such as Big Data Analytics, Global Positioning Systems, Enterprise Resource Planning, and Digital Platforms are quite available in the Irans' pharmaceutical industry. These technologies, along with four available interventions, e.g., environmental regulations, subsidy, fine, and reward, would facilitate moving towards a lean, agile, resilient, and sustainable supply chain through the efficient utilization of resources, optimized waste management, and substituting the human workforce by machines.
Original languageEnglish
Article number108753
Number of pages18
JournalComputers & Industrial Engineering
Volume174
Early online date19 Oct 2022
DOIs
Publication statusPublished - Dec 2022

Keywords

  • Industry 4.0 technologies
  • Pythagorean fuzzy Delphi
  • Pythagorean fuzzy SECA
  • Hanlon method

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