Driving big data success: a comparative analysis of critical factors in services and manufacturing

This work identifies critical factors for the successful adoption of Big Data technologies, assesses their impact on firm performance, and explores sectoral differences in these factors and impacts. Based on a sample of 163 medium and large Portuguese enterprises in the manufacturing and services sectors (classified by NACERev.2), data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Partial Least Squares Multi-Group Analysis (PLS-MGA). Governance-related factors, such as Data Privacy Management, Cybersecurity, and Government legislation, alongside Big Data Utilization – measuring its depth, extent, and data characteristics – emerged as key drivers. Findings confirm these factors significantly enhance financial and market performance, with consistency across sectors. This study contributes a refined Technology-organization-Environment (TOE) framework, providing practical insights for managers and policymakers to prioritize critical areas influencing Big Data adoption and performance. This is the first study to explore sectoral disparities in Big Data adoption.