How does artificial intelligence capacity enhance the production system resilience and operational performance? A human-organization-technology fit perspective

Artificial Intelligence (AI) capabilities are increasingly pivotal for enhancing production system resilience in today's volatile business environments. However, the integration of AI technologies with established organizational information processing and decision-making frameworks remains inadequately understood. Grounded in the Human-Organization-Technology (HOT) fit theory, this study investigates how AI capacity positively influences a firm's operational performance. Using multi-wave survey data collected from 305 manufacturing firms via a professional online platform during the COVID-19 pandemic, we identify critical factors that reinforce this positive effect and elucidate its underlying mechanisms, with particular emphasis on how AI reconfigures organizational information flows and knowledge practices. Partial least squares-based structural equation modeling was employed to test the hypothesized model. The findings reveal a significant positive impact of AI capacity on production system resilience. Furthermore, production system resilience itself exerts a strong positive influence on operational performance. Crucially, production system resilience serves as a key mediating mechanism, through which AI capacity indirectly enhances operational performance. Finally, the degree of fit, conceptualized across task-tool, human-tool, and data-tool dimensions, moderates the positive effect of AI capacity on production system resilience. This research is contextualized within the Chinese manufacturing sector, a major global production hub, and enriches the theoretical discourse on AI capacity and production system resilience from an information management perspective, highlighting its transformative role in organizational information flows, knowledge creation, and data-driven decision processes.