Paper Type
Complete
Paper Number
PACIS2026-1522
Description
This study examines how Industry 4.0 technologies activate distinct resilience capability mechanisms in supply chains. Drawing on dynamic capabilities theory, we position digital twin capability and AI-driven predictive analytics as technology-enabled capabilities that strengthen supply chain anticipation capability and recovery capability, which together enhance supply chain resilience performance. Using survey data from 289 supply chain executives in Taiwan’s electronics sector and PLS-SEM, all six direct-effect hypotheses are supported, while supply chain complexity significantly strengthens the four technology-to-capability relationships. Complementary fsQCA based on a 98-case complete-data sub-sample identifies three sufficient configurations for high resilience performance, including anticipation-dominant and capability-driven pathways. The findings extend proactive–reactive resilience research by clarifying the temporal and functional distinction between anticipation and recovery capabilities and by showing how differentiated digital investments support resilience under supply chain complexity.
Recommended Citation
Wu, Chih-Lun, "Digital Twin-Enabled Supply Chain Resilience: Anticipation and Recovery Capabilities in Taiwan's Electronics Manufacturing Sector" (2026). PACIS 2026 Proceedings. 5.
https://aisel.aisnet.org/pacis2026/dig_sec/dig_sec/5
Digital Twin-Enabled Supply Chain Resilience: Anticipation and Recovery Capabilities in Taiwan's Electronics Manufacturing Sector
This study examines how Industry 4.0 technologies activate distinct resilience capability mechanisms in supply chains. Drawing on dynamic capabilities theory, we position digital twin capability and AI-driven predictive analytics as technology-enabled capabilities that strengthen supply chain anticipation capability and recovery capability, which together enhance supply chain resilience performance. Using survey data from 289 supply chain executives in Taiwan’s electronics sector and PLS-SEM, all six direct-effect hypotheses are supported, while supply chain complexity significantly strengthens the four technology-to-capability relationships. Complementary fsQCA based on a 98-case complete-data sub-sample identifies three sufficient configurations for high resilience performance, including anticipation-dominant and capability-driven pathways. The findings extend proactive–reactive resilience research by clarifying the temporal and functional distinction between anticipation and recovery capabilities and by showing how differentiated digital investments support resilience under supply chain complexity.
Comments
08-Security