Smart Value Chains: Integrating Big Data and Sustainability in Industry 4.0
Abstract
The integration of Big Data and Industry 4.0 technologies has been widely associated with improvements in operational efficiency and sustainability; however, there is limited empirical evidence explaining how data-driven capabilities simultaneously influence circularity, governance, and transparency within industrial value chains. This study analyzes the impact of Big Data integration on sustainable performance through a quantitative explanatory design based on survey data collected from industrial organizations between May and October 2024. The analysis combines exploratory factor analysis, multiple linear regression, and Pearson correlation to examine three key dimensions: real-time data integration, operational efficiency and circularity, and algorithmic governance and transparency. The results reveal high levels of implementation in real-time data integration (M = 4.12) and operational circularity (R² = 0.42), with strong positive correlations between data integration and sustainability indicators (r = 0.68; p < 0.01). Additionally, algorithmic governance explains 35% of the variance in sustainable governance outcomes, highlighting the role of data governance in ensuring transparency and accountability. These findings demonstrate that Big Data capabilities act as a structural enabler of both operational and environmental performance. Based on this evidence, the study proposes a smart value chain framework that integrates analytics, governance, and circularity as core dimensions of sustainable Industry 4.0 systems. This research contributes empirical evidence on the systemic role of data-driven transformation in advancing sustainable industrial ecosystems.Downloads
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