## 2 Theoretical Foundation  
### Organizational Information Processing Theory  
As global supply chains face increasingly complex and uncertain environments, supply chain resilience (SCR) has become a critical capability for enterprises to maintain competitiveness and achieve sustainable development. SCR refers to an enterprise's ability to rapidly adjust, recover, and optimize supply chain operations when confronted with external disruptions. In recent years, the rapid advancement of digital technologies has made the role of digital capabilities in enhancing SCR a key research focus [13,20]. Organizational Information Processing Theory (OIPT), first proposed by [PERSON] (1973) [21], emphasizes that firms respond to environmental uncertainty and complexity through information processing capability. When faced with increasing task uncertainty, enhancing real-time information processing capability enables firms to achieve optimal performance outcomes [22]. Information processing needs may arise from uncertainties within the supply chain or from external environmental factors. When a firm's information processing capability matches its information needs, it can attain optimal performance [23]. In the field of supply chain management, information processing capability is reflected in a firm's ability to utilize digital technologies--such as big data, the Internet of Things (IoT), and artificial intelligence (AI)--to collect, analyze, and transmit information to support decision making and operations [24]. OIPT posits that when information processing capability aligns with information needs arising from supply chain uncertainties, firms can achieve optimal operational performance. Supply chain operations are inherently uncertain, with sources of uncertainty stemming from social, natural, and human factors [25]. These uncertainties mainly arise from internal and external factors, such as fluctuating customer demand, inter-organizational complexity, natural disasters, and \"black swan\" events [26,27]. Neglecting such events exacerbates supply chain vulnerabilities, particularly as weak links often become primary sources of risk [10]. Therefore, identifying and mitigating these critical vulnerabilities, along with enhancing supply chain risk management capability, is essential for shaping supply chain resilience. According to OIPT, enterprises require robust information processing capabilities to support risk management [28]. Risk management enhances firms' adaptability by dynamically monitoring risks, analyzing uncertainties, and facilitating emergency decision making [29]. Efficient risk information processing helps firms collect essential data, ensure transparency among supply chain partners, and translate data analytics into actionable insights [6]. Additionally, collaborative mechanisms among supply chain enterprises foster risk information sharing, thereby improving overall response capabilities. These practices strengthen supply chain stability, enabling firms to swiftly recover and optimize operations in the face of external disruptions. Digital capability refers to a firm's ability to leverage digital technologies--such as AI, blockchain, and big data analytics--to enhance information processing capacity [17]. Digital capability not only improves the efficiency of risk management but also amplifies its positive impact on SCR [29,30]. By increasing information transparency and traceability, digital capability enhances firms' ability to identify and respond to supply chain risks. For example, AI and big data analytics can analyze supply chain data in real time, predict potential risks, and provide decision-making support [18]. Meanwhile, digital technologies facilitate information sharing and collaboration across enterprises, strengthening the adaptability of various supply chain segments [17; 31]. The application of blockchain technology ensures data authenticity and immutability [32], thereby reinforcing trust mechanisms and enhancing risk management effectiveness.