Axiomatic Design and Sustainable Balanced Scorecard Application for LARG Supply Chain Design in a Hesitant Fuzzy Environment

Much has been written about various approaches which pay attention to supply chain from specific angles. One of the new approaches is an integration of Lean, Agile, Resilient, and Green (LARG) that benefiting from the advantages of different approaches and avoiding their disadvantages. This study aims to present a model for analyzing LARG supply chain using Axiomatic Design (AD) and Sustainable Balanced Scorecard (SBSC) in a Hesitant Fuzzy (HF) environment in automaker industry. The study process consisted of two stages: designing stage and evaluating stage. In the first stage, the Functional Requirements (FR) and chain Design Parameters (DP) identified in the LARG supply chain based on the Delphi technique and literature review. In the second stage an integration of information axiom, the Best-Worst Method (BWM), SBSC and hesitant fuzzy logic was used to analyze supply chain in Iran automaker industry. The results showed all 21 indicators are met in both independence and information axioms. Among LARG supply chain criteria, customer requirements, and timely delivery of the car to the customer is the most important and the use of multi-purpose labor and up-to-date machinery is the least important. Among sustainable balanced scorecard perspectives, growth and learning perspectives are the most important and internal processes perspective is the least important. The model with integrating LARG supply chain using AD and SBSC in a hesitant fuzzy environment has caused the designed model to have many capabilities compared to the existing models.