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Abstract

This study aims to analyze the influence of sustainable supply chain management practices (SSCMP) on operational and environmental performance, with the mediation of big data analysis capabilities (BDAC) as a mediating variable. The research was conducted using a quantitative approach with a hypothesis testing method through Structural Equation Modeling based on Partial Least Squares (PLS-SEM), using primary data from 200 respondents in manufacturing companies. The results of the study show that PBRPB has a significant effect on the increase in BDAC, which then has a positive impact on operational performance. However, sustainability practices do not directly impact operational performance without the support of data technology. On the other hand, sustainable practices can directly improve environmental performance, even though BDAC does not significantly influence environmental aspects or act as a mediator. Other findings suggest that good operational performance significantly contributes to improving environmental performance. These results emphasize the importance of integrating sustainability strategies and analytics technology to drive operational efficiency while fulfilling environmental responsibility. As such, manufacturing companies need to build sustainable, data-driven supply chain systems to increase competitiveness amid market demands and regulations that increasingly emphasize sustainability.

Keywords

Sustainable Supply Chain Management Practices Big Data Analytics Capability Operational Performance Environmental Performance Smartpls Manufacturing Companies

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Camila, S. A., Santosa , W., Darasih, R., & Widowati , D. (2025). The Role of Big Data Analysis Capabilities in Mediating the Relationship between Sustainable Supply Chain Management Practices and Company Performance in Manufacturing Companies. Golden Ratio of Mapping Idea and Literature Format, 6(1), 57–72. https://doi.org/10.52970/grmilf.v6i1.1399
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