The Impact of Cross-Level Risks on Employee Performance Through Enhanced Crisis Management and Employee Resilience in Agricultural Entreprises in Northwest China

Abstract

As artificial intelligence (AI) rapidly reshapes the production and labor landscape of agricultural SMEs, this study, based on survey data from 418 practitioners in Northwest China, employs a hybrid approach of SEM and NCA to conduct an in-depth investigation. The empirical results reveal a key theoretical finding: professional identity threat and technological uncertainty have a significant negative inhibitory effect on employees’ crisis management capabilities (CMCs), while lack of transparency increases reliance on adaptive crisis responses. Furthermore, CMC indirectly influences performance through employee resilience, which exhibits the strongest positive effect on performance. The study also demonstrates that perceived organizational support not only strengthens resilience and performance, but also significantly moderates the effect of CMC on performance. The NCA results further contribute by showing that organizational transparency and resilience are necessary preconditions for achieving high performance, while CMC functions as a sufficient but non-essential driver. Grounded in risk perception theory and crisis management theory, this study contributes to theoretical advancement by developing a dual-level framework that explains how employees perceive AI-related risks, mobilize crisis management capabilities, and translate psychological adaptation into performance outcomes. This paper contributes to theoretical literature by expanding the interaction between psychological and organizational mechanisms in the context of AI-driven transformations. It offers actionable implications for building organizational capabilities and fostering supportive governance in agricultural SMEs.