The Trade Tensions and Sustainability in Indonesia’s Nickel Industry: a System Dynamics View for Electric Vehicle Development

Geopolitical tensions between the United States and China are reshaping global investment flows, particularly within critical mineral supply chains essential to electric vehicle (EV) development. As the world's largest producer of nickel (a key material in EV battery chemistries) Indonesia has emerged as a strategic hub in this global realignment. This study investigates how trade conflict, industrial policy, and environmental regulation jointly influence nickel demand and supply dynamics in the EV context. A hybrid methodology is employed, integrating a Systematic Literature Review (SLR) and Content Analysis, guided by the PRISMA 2020 framework. From 21 selected publications, key variables and causal linkages were extracted and synthesized into a system dynamics-based Causal Loop Diagram (CLD). The model reveals that U.S.-China tensions catalyze investment relocation, resulting in increased foreign direct investment (FDI) in Indonesia and stimulating domestic nickel demand through downstream expansion. This reinforcing dynamic is counterbalanced by environmental regulations and macroeconomic factors such as interest rate sensitivity. The analysis identifies three strategic intervention points: (1) mandating downstream integration in FDI-related projects, (2) establishing and enforcing measurable environmental thresholds, and (3) embedding systems-thinking tools in national development planning. The findings underscore that Indonesia's long-term role in the global EV supply chain will depend on its ability to balance economic growth with environmental stewardship and cross-sector policy alignment. For EV developers and policymakers, the proposed CLD offers a structured framework to assess sourcing risks and inform sustainable procurement strategies. This work advances system-based approaches in mineral governance and lays the groundwork for future quantitative modeling of long-term EV supply scenarios.