Supply chain resilience is vital for companies looking to reduce disruptions and preserve operational continuity. In this context, Pakistan and China’s industrial sectors, with their complex supply chains, require effective measures to boost resilience and reduce disruptions. This study takes an innovative approach that employs Partial least square structural equation modeling (PLS-SEM) and Necessary Condition Analysis (NCA) to identify the critical contributions of resilient suppliers (RSP), information sharing (INFM), inventory management (INVT), and flexibility (FLEX) as necessary conditions for optimizing Supply Chain Resilience (SPRE) through R-programming. A total of 546 valid responses were collected from Chinese and Pakistani manufacturing industry to evaluate this model. The results indicate that attaining 80% SPRE necessitates a harmonious relationship among RSP, FLEX, INFM, and INVT. RSP (53.4%) and FLEX (54.2%) are the primary components that guarantee supply consistency and responsiveness during disruptions. INFM (46.5%) improves coordination, and INVT (29.9%) offers buffers against demand-supply variations. Their synergistic impact enhances adaptability and risk management in supply networks. The research offers actionable insights for supply chain managers, highlighting the need of prioritizing resilience-enhancing solutions. By recognizing the necessary contributions of RSP, INFM, INVT, and FLEX, companies can more effectively manage interruptions and improve overall SPRE. This research enhances the literature by integrating PLS-SEM and NCA, providing an innovative analytical framework for identifying essential abilities required for achieving supply chain resilience in unstable contexts.
Aslam et al. (Wed,) studied this question.