This study examines how AI-based reverse logistics improves net-zero-based green performance through circular economy practices and how tariff policy uncertainty constrains these effects. Drawing on dynamic capability theory, it frames AI-based logistics and circular practices as adaptive capabilities under trade-policy volatility.
Data were collected through a three-wave survey of 209 ISO 14001-certified high-tech manufacturing firms. Hayes’ PROCESS macro was used to test mediation and moderated mediation, while fsQCA identified configurations associated with high green performance.
AI-based reverse logistics positively affect circular economy practices and net-zero-based green performance. Circular economy practices mediate this relationship. However, tariff policy uncertainty weakens the direct effects of AI-based reverse logistics on circular practices and green performance, as well as the indirect effect through circular practices. fsQCA confirms that strong green performance is most likely when AI-based reverse logistics and circular practices coexist, especially under low tariff uncertainty.
The study extends dynamic capability theory by showing that digital and circular capabilities support net-zero goals, but their effectiveness depends on trade-policy stability.
