Digital transformation readiness and big data analytics in laying hen supply chains

Digital transformation (DT), driven by a set of enabling technologies such as Big data analytics (BDA), Internet of Things (IoT), cloud computing, and mobile platforms, has become a pivotal catalyst for improving supply chain performance (SCP), especially in volatile and resource-constrained environments like the laying hen farming sector in Indonesia. This study investigates the relationships between DT, SCP, behavioral intention (BI), supply chain agility (SCA), operational supply chain transparency (OSC), and supply chain uncertainties (SCU). Employing a quantitative approach with multivariate analysis using Structural Equation Modeling (SEM) Partial Least Squares (PLS), data from 205 respondents were analyzed. The results reveal that DT significantly enhances BI and SCA but does not directly affect SCP or OSC. BI and SCA serve as mediators, connecting DT to SCP, while SCU moderates the BI-SCP relationship. These findings emphasize the critical roles of agility and behavioral readiness—particularly in the context of adopting big data analytics (BDA) in translating digital transformation into tangible supply chain benefits. The study also underscores the need for targeted interventions to foster digital literacy, infrastructure development, and collaboration among smallholder farmers. By advancing the contingent resource-based view (CRBV) and Technology Acceptance Model (TAM), this research contributes to the theoretical understanding of DT’s impact in developing countries. Practical implications include policy recommendations for supporting digital adoption—especially BDA and enhancing supply chain resilience among livestock-based MSMEs. Future research should explore broader regional contexts, structural ownership influences, and long-term effects of DT on SCP.