Matching functions of supply chain management with smart and sustainable Tools: A novel hybrid BWM-QFD based method. (December 2021)

• Record Type: Journal Article
• Authors: Gunduz, Mehmet Akif; Demir, Sercan; Paksoy, Turan
• Is Part Of: Computers & industrial engineering. Volume 162(2021)
• Publication Date: 2021-12
• Subjects: Best-Worst Method -- Quality Function Deployment -- Supply Chain Management -- Smartness -- Sustainability; RAS Robotics and autonomous systems -- AM Additive manufacturing -- AR Augmented reality -- S Simulation -- HVSI Horizontal and vertical system integration -- IoT The Internet of things -- CC Cloud computing -- CS Cybersecurity -- BDA Big data and analytics -- AI Artificial intelligence -- ML Machine learning -- BCT Blockchain technology -- C Costs -- LT Lead time -- IT Inventory turnover -- DL Damage & loss -- EU Energy use -- P Pollution -- W Waste -- E Emission -- SR Social responsibility -- PB Perks & benefits -- LA Labor abuse -- HS Health & safety; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2021.107676
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Assessing the level of maturity for the supply chain is critical for enterprises. Investigating the smartness and sustainability dimensions is of great importance. A twin QFD method leads to achieving a high degree of customer satisfaction. Comparing the current states and targets of smartness and sustainability is crucial. Digital transformation and sustainable practices should be explored simultaneously. 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.