Matching functions of supply chain management with smart and sustainable Tools: A novel hybrid BWM-QFD based method

Abstract

In recent years, there is a noticeable increase in interest in supply chain smartness and sustainability since a growing number of companies are adopting smart technologies and sustainable practices in the functions of supply chain management. Therefore, scholars and practitioners seek to make sense of how this phenomenon can be addressed concerning companies’ maturity level of supply chain smartness and sustainability. This paper proposes a novel hybrid methodology combining the Best-Worst Method (BWM) and Quality Function Deployment (QFD) to assess the level of maturity for supply chain smartness and sustainability by weighting the functions of supply chain management. A twin-QFD technique is used to obtain a conceptual design to determine the relationship between the functions of supply chain smartness tools and sustainability indicators to assess the level of maturity, whereas the BWM is used to determine the weights of the functions of supply chain management. A case study in the automotive manufacturing industry is applied to demonstrate the applicability of the proposed approach. The findings disclose the prominent smart technologies (simulation, big data analytics, cloud computing) and sustainability indicators (costs, lead time, and damage and loss) in integrating Industry 4.0 technologies and sustainable supply chain practices. Findings also suggest a guideline to compare the current and targeted levels of smartness and sustainability maturity. This study provides insights for scholars and practitioners and contributes to the body of knowledge by evaluating companies’ maturity of digital transformation and sustainable practices in the supply chain functions.