To mitigate and respond to supply chain risks, previous research usually views supply chain risk management as the management of various activities concerning risk identification, assessment, mitigation, and responses. While supply chain risk information plays a crucial role in the implementation and decisions of many of these activities, the importance of a firm's information processing capability to its supply chain risk management effort has received very little attention in the literature. Using information processing theory as the theoretical lens, we argue that a firm's capability in processing supply chain risk information, which comprises supply chain risk information sharing and supply chain risk information analysis, can improve operational performance, and this capability's effectiveness in improving performance is contingent on product-specific uncertainty characteristics (i.e., product complexity and product customization) and environment-related uncertainty characteristics (i.e., technology turbulence and market turbulence). We test the proposed theoretical model using data collected from 350 manufacturing firms in China. The results support that supply chain risk information processing capability comprises two constituent elements and has a positive effect on operational performance. The results also suggest that except for product complexity, all the other posited product-specific and environment-related uncertainty characteristics positively moderate the relationship between supply chain risk information capability and operational performance. We contribute to the literature by developing a theory-driven empirical model that integrates the core concepts of supply chain risk management and information processing theory to generate research findings with theoretical and managerial implications.
- Information processing capability
- supply chain risk (SCR)
- uncertainty characteristics
ASJC Scopus subject areas
- Strategy and Management
- Electrical and Electronic Engineering