Background: The automotive industry is one of the most important industries in the
world as well as in our country. Supply chain management (SCM) of such large
industries requires design and evaluation.
Aims: The purpose of this study is better managing of supply chain in the automotive
industry; and seeks to answer questions about: what is the structure of the design and
evaluation approach of the LARG supply chain using the Axiomatic Design (AD)
technique & Best-Worst Method (BWM) in a Hesitant Fuzzy (HF) environment?
Methodology: The study process consisted of two stages: In the first stage, a
conceptual design for the LARGE supply chain in the automotive industry is proposed as
a desirable supply chain using the Axiomatic Design and Delphi techniques and its design
matrix is formed to test the independence axiom. In the second stage, a model is proposed
using an information axiom and its integration with Best-Worst Method (BWM) in
hesitant fuzzy environment as a way to evaluate LARG supply chain; and based on the
proposed model, the current and favorable situation of four automotive supply chains
(Iran Khodro, Saipa, Bahman Motor and Kerman Motor) will be evaluated and the
superior supply chain will be identified.
Conclusions: The results of this study in the first phase showed that the optimal
LARG supply chain of the automotive industry consists of 13 indicators. A design matrix
was formed to design the relationship between the mentioned indicators (tools) and
defined goals (performance requirements), and the semi-independent design of the LARG
supply chain design matrix was approved as the optimal supply chain in the automotive
industry.
In the second phase of this study, first the weighting of the introduced indicators and
all four strategies of the LARG supply chain were conducted using the technique of the
Best-Worst Method (BWM) in hesitant fuzzy environment; and the results showed that
the most important criteria of the LARG supply chain is the use of st