Optimizing supply chain performance through sustainable manufacturing practices and capabilities in emerging markets: an integrated linear (PLS-SEM) and non-linear (fsQCA) approach

Supply chain uncertainties are a key managerial concern because of their adverse influences on organizations and supply chain operations. Supply chain firms must establish a strategic construct: the capability to reconfigure, adapt, and respond during disruptive events. This study aims to empirically examine the impact of the dimensions of supply chain analytics capability and sustainable manufacturing practices, thereby achieving high levels of supply chain performance in emerging markets. The study combines the theoretical framework using dynamic capability theory to reconfigure supply chain firms’ resources and capabilities to respond to disruptive events, thereby attaining a competitive advantage in dynamic markets. By employing the proposed questionnaires, participants are collected from 333 senior supply chain professionals involved in various manufacturing industries in Bangladesh. Accordingly, the study proposed five hypotheses to test the empirical validation using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The results show that management capability, data-driven culture, supply chain management, and sustainable manufacturing process significantly impact supply chain performance using the PLS-SEM model. In the fsQCA model, the findings reveal that management capability and supply chain management are sufficient core conditions to achieve high supply chain performance. This substantial result identifies that deploying dynamic capabilities techniques for the implication of extant capabilities in combination with processes for expanding and employing new insights strengthens the supply chain’s capability to find potential uncertainties and respond to them rapidly.