Title
A fuzzy maturity-based method for lean supply chain management assessment
Document Type
Article
Publication Date
3-29-2021
DOI
https://doi.org/10.1108/IJLSS-08-2020-0123
Abstract
Purpose: This study aims to propose a method for measuring lean supply chain management (LSCM) maturity based on the main lean practices and existing waste of a supply chain.
Design/methodology/approach: A three-stage approach was developed. First, a thorough literature review was performed to raise concepts and previous findings on maturity models (MMs) and LSCM. This review’s outcomes were then validated by experts in the field using the fuzzy Delphi method (FDM). Subsequently, the proposed model was illustrated and assessed based on a multi-case study.
Findings: All companies attained high outcomes in the elimination of the waste pillar. The pillars of logistics management, continuous improvement and information technology management also stood out in the three organizations’ results. The company with the lowest maturity level operates in a make-to-order production policy, which may harm the lean supply in its supply chain.
Practical implications: The proposed model can reveal external opportunities and threats and internal strengths and weaknesses in supply chains (SCs). It is also capable of providing a clear roadmap for SC improvement in companies.
Originality/value: To the best of the authors’ knowledge, no study to date has proposed a MM in the LSCM context using FDM and considering the crucial relationship between lean practices and wastes.
Language
English
Recommended Citation
Soares, Gabriela Pereira; Tortorella, Guilherme; Bouzon, Marina; and Tavana, Madjid, "A fuzzy maturity-based method for lean supply chain management assessment" (2021). Business Systems and Analytics Faculty Work. 91.
https://digitalcommons.lasalle.edu/bsa_faculty/91
Comments
Pereira Soares, G., Luz Tortorella, G., Bouzon, M. and Tavana, M. (2021) ‘A Fuzzy Maturity-Based Method for Lean Supply Chain Management Assessment,’ International Journal of Lean Six Sigma, Vol. 12, No. 5, pp. 1017-1045.