Analyzing the impact of inventory on EV supply chain performance: a system dynamics approach

• Main Author: Niu, Haoyu
• Other Authors: Chen Songlin
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Business::Operations management::Supply chain management
• Online Access: https://hdl.handle.net/10356/171845
• Institution: Nanyang Technological University

The widespread transition from Conventional Vehicles (CVs) to Electric Vehicles (EVs) is a multifaceted process that involves numerous influencing factors. The implementation of an effective inventory policy is an essential component of any successful business, as it is directly tied to the value realization of an organization. Inventory policy serves to maintain balance across various nodes, including production, transportation, and sales. However, it can be considered an idle resource that occupies capital. Companies establish inventory to handle unpredictable future demands, but this leads to several supply chain issues, such as order fulfillment shortages, high product costs, reduced liquidity, decreased turnover rates, slow market penetration, and inefficient transition from combustion vehicles to electric vehicles. Effective control of inventory is necessary to accelerate the adoption of electric vehicles by integrating operations among different nodes in the supply chain. This is especially crucial in industries such as the automotive sector with long supply chains and high capital requirements, where inventory has always been a critical concern. Therefore, researching effective inventory systems holds both theoretical and practical significance. This dissertation utilizes a systems dynamics methodology by choosing the EV automotive inventory network as its research focus and creating a system dynamics VI model to illustrate the intricate inventory system of the EV supply chain network. Firstly, the overall supply chain structure is analyzed systemically, followed by an examination of the feedback relationships among different factors within the EV automotive supply chain. The influential factors are methodically analyzed. The study establishes a causal relationship model and a stock-flow-feedback model. The dynamic equations of these models are determined, and appropriate parameters are assigned. A system dynamics (SD) approach is employed, using the Vensim simulation tool, to model the dynamics of inventory raw materials, supplier components, manufacturer inventory, distributor inventory, and retailer inventory. The objective of this study is to provide a thorough analysis of inventory status at different nodes within the EV automotive supply chain under varying demand scenarios. The study aims to clarify the contradictory performance of inventory fluctuations and assist in making strategic decisions related to optimizing supply- demand alignment, minimizing EV inventory waste, and promoting EV adoption from CVs. Ultimately, the dissertation aims to enhance the competitive advantage of the electric vehicle (EV) automotive industry over conventional vehicles (CVs) and yield valuable insights into its inventory control system.