A Multiple Criteria Decision Making Approach to Model Sustainable Supply Chain in Automotive Parts Industry

Wu Guanqiao

Abstract

Supply chain management is increasingly important with the intensified globalization and international trade and cooperation. The impacts of supply chain activities attract public’s attention due to the industry’s expansion and development. Thus, non-governmental organizations and related authorities advocate sustainable supply chain management to minimize the unnecessary harm to the environment. However, most of the reviewed literatures related to green supply chain management simplify the problem and its inherent complexity. With the purpose of developing a well-founded and practical recommendation for the management to assure the long-term success, the Thesis aims to construct multiple criteria decision making models that reveals the complexity caused by interdependency and feedback effects within decisive attributes.

Analytical Network Process (ANP) is selected as the most appropriate modeling strategy due to its unique capability of capturing the structural dependency. However, the modeling process is complicated. Therefore, the Thesis proposed a modeling procedure based on hierarchy thinking to reduce the initial modeling difficulty. With that, the model for sustainable supply chain management is constructed to explore the balance and optimal solution, which address both business and environmental sustainability requirements. The model is specifically designed for automotive parts industry and can be modified and applied to other industries of interests. Several commonly applied supply chain management strategies are evaluated under the proposed model and the most advantageous option is selected for managerial recommendation. According to the results, “Leagility Supply Chain” has the highest priority rating. “Leagility” emphasize on both Lean principle and business agility for the whole supply chain operation. With a balanced strategy, both business and environmental criteria are accessed and adjusted.