How big data and green supply chains advance circular economy in Saudi pharma sector

Big data analytics (BDA), when combined with sustainable performance metrics and green supply chain practices, forms a powerful triad for enabling circular economic goals in Saudi Arabia's pharmaceutical industry, says a new study published in Sustainability. Titled “Big Data Analytics as a Driver for Sustainable Performance: The Role of Green Supply Chain Management in Advancing Circular Economy in Saudi Arabian Pharmaceutical Companies”, the study proposes a dual-mediation model explaining how BDA contributes to the circular economy (CE) both directly and indirectly.

The research provides empirical evidence on how digital transformation, driven by data intelligence, enhances environmental performance and green supply chain management, serving the nation’s Vision 2030 goals. Based on a dataset from 275 industry professionals, the research delivers practical strategies for integrating digital tools into sustainability efforts in a heavily regulated sector.

How does big data analytics advance circular economic outcomes?

The study establishes a strong direct relationship between big data analytics and the implementation of circular economy strategies in the pharmaceutical sector. It asserts that BDA is not merely a technological asset but a dynamic organizational capability that enables firms to adapt, innovate, and reconfigure their operational structures. By integrating advanced analytics, companies can identify resource inefficiencies, improve material flow traceability, and extend product life cycles through predictive maintenance and waste mitigation.

In the context of circularity, BDA enhances system-wide visibility, allowing decision-makers to monitor material consumption and respond proactively to demand fluctuations and production challenges. This data-enabled responsiveness supports key CE pillars such as reduce, reuse, and recycle. The study reinforces the idea that digital transformation must be coupled with a strategic sustainability agenda to optimize long-term resource value and reduce environmental degradation.

Empirical results from the structural equation modeling confirm that BDA exerts a statistically significant and robust effect on CE indicators. The findings challenge conventional views that emphasize regulatory pressure as the primary driver of sustainability, positioning digital capability instead as a strategic enabler of green transformation. This shift is particularly salient in emerging markets like Saudi Arabia, where industrial sectors are rapidly digitalizing in alignment with national development plans.

What role do sustainable performance and green supply chains play?

Beyond the direct influence of BDA on CE, the research identifies two critical mediators: sustainable performance (SP) and green supply chain management (GSCM). The dual mediation framework proposed in the study confirms that these two variables significantly channel the benefits of data analytics into circular economic outcomes.

Sustainable performance is conceptualized as the organization’s commitment to environmental, social, and economic goals. The study finds that BDA enhances sustainable performance by optimizing resource use, reducing emissions, and reinforcing stakeholder engagement. These improvements in turn create a conducive environment for implementing CE practices. Notably, sustainable performance aligns closely with multiple UN Sustainable Development Goals, particularly SDG 7 (Affordable and Clean Energy) and SDG 12 (Responsible Consumption and Production), reinforcing its strategic importance.

Green supply chain management, on the other hand, acts as a mechanism through which BDA facilitates environmentally responsible sourcing, manufacturing, distribution, and end-of-life product management. By leveraging data-driven insights, companies can adopt reverse logistics, green procurement, and waste management systems that align with CE goals. The study finds that GSCM has a slightly stronger mediating effect than SP, suggesting that operational strategies tied to supply chain processes are pivotal in realizing the full potential of big data initiatives.

Together, these two mediators offer a dual pathway: SP provides internal organizational readiness, while GSCM ensures external ecosystem alignment. This integrated approach helps companies move beyond fragmented sustainability projects toward systemic circular transformation.

What are the implications for industry and policy in emerging markets?

The research delivers significant implications for both corporate decision-makers and policymakers in Saudi Arabia and similar emerging markets. At the industry level, the study advises firms to invest in digital infrastructure and human capital to fully harness big data’s potential. It recommends embedding analytics into core operational and strategic processes, with a particular focus on supply chain transparency and waste reduction. Specialized training programs for employees and managers are highlighted as essential for improving data literacy and sustainability awareness.

For policymakers, the study suggests that public–private collaboration is essential to scale CE initiatives. Governmental support in the form of regulatory frameworks, tax incentives, and sustainability certification can drive wider adoption of green practices. The research also calls for an enhancement of national data governance strategies to support responsible data use in industrial sectors.