RETRACTED: An integrated Industry 4.0-Sustainable Lean Six Sigma framework to improve supply chain performance: a decision support study from COVID-19 lessons
Journal of Global Operations and Strategic Sourcing
ISSN: 2398-5364
Article publication date: 18 January 2023
Issue publication date: 27 April 2023
Retraction statement
The publisher of Journal of Global Operations and Strategic Sourcing wishes to retract the article by Jaypalsinh Ambalal Rana and Suketu Y. Jani, “An integrated Industry 4.0-Sustainable Lean Six Sigma framework to improve supply chain performance: a decision support study from COVID-19 lessons”, published in Journal of Global Operations and Strategic Sourcing, Vol. 16 No. 2, pp. 430-455, https://doi.org/10.1108/JGOSS-04-2022-0032.
It has come to our attention that a large portion of this article is taken, without attribution, from an earlier, unpublished original work by Manoj Palsodkar, Madhukar Nagare, and Gunjan Yadav, “Enhancing manufacturing supply chain performance through integrated Industry 4.0-ANPD practices: A decision support study from COVID-19 lessons”. The submission guidelines for Journal of Global Operations and Strategic Sourcing make it clear that articles must be original. The authors would like it to be noted that they are not in agreement with this retraction. The publisher of the journal sincerely apologizes to the readers.
Abstract
Purpose
The COVID-19 pandemic era has severely hampered the economy over the globe. However, the manufacturing organizations across all the countries have struggled heavily, as they were among the least who worked on online mode. The organizations are adopting various innovative quality methodologies to improve their performance. In this regard, they are adopting the Sustainable Lean Six Sigma (SLSS) concept and Industry 4.0 technologies to develop products at a faster rate. The use of Industry 4.0 technologies may reduce material movement and supply chain disruptions with the help of smart intelligent systems. There is a strong synergy between SLSS and Industry 4.0 technologies, resulting in an integrated approach for adoption. This study aims to develop a framework that practitioners can use to adopt Industry 4.0-SLSS practices effectively.
Design/methodology/approach
This study portrays 31 Industry 4.0-SLSS practices and 22 performance metrics identified through a literature review to improve the manufacturing supply chain performance. To compute the weights of these practices, the Robust Best–Worst Method (RBWM) is used. The Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method is used to rank performance metrics.
Findings
According to the RBWM results, “Process Development Practices (PDP)” are first among the major criteria, followed by “Organizational Management Practices (OMP)” at second, “Technology Adoption Practices (TAP)” at third, “Strategy Management Practices (SMP)” at fourth and “Executive Management Practices (EMP)” at fifth, whereas the PF-CoCoSo method resulted in the performance metric “On time product delivery” ranking first.
Research limitations/implications
The identified practices have the potential to significantly improve the performance of the manufacturing supply chain. Practices that encourage a sustainable manufacturing supply chain and the usage of emerging technology will benefit organizational effectiveness. Managers can assess performance using prioritized performance metrics.
Originality/value
During the COVID-19 pandemic era, this is one of the unique attempts to provide a framework to improve the manufacturing supply chain performance. This study integrates and identifies Industry 4.0-SLSS practices and performance metrics for enhancing overall performance.
Keywords
Acknowledgements
The authors would like to thank all experts for providing their inputs for multicriteria decision-making analysis that helped them to generate the desired results.
Conflict of interest: The authors declare no potential conflict of interest.
Citation
Rana, J.A. and Jani, S.Y. (2023), "RETRACTED: An integrated Industry 4.0-Sustainable Lean Six Sigma framework to improve supply chain performance: a decision support study from COVID-19 lessons", Journal of Global Operations and Strategic Sourcing, Vol. 16 No. 2, pp. 430-455. https://doi.org/10.1108/JGOSS-04-2022-0032
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Group Publishing Limited