Title: An Enhanced Framework for the Integration of Data Governance into Collaborative Supply Chain Management model
Authors: Naseer Sanni Ajoge (PhD), Abubakar Balarabe & Muhammad Haruna Isa
Volume: 9
Issue: 4
Pages: 222-231
Publication Date: 2025/04/28
Abstract:
In the era of digital transformation and Industry 4.0, supply chain networks are evolving into complex, data-driven systems that demand improved collaboration, visibility, and decision-making. This study proposes an enhanced collaborative supply chain framework that integrates data governance as a strategic component to address persistent challenges related to data accuracy, security, and transparency across supply chain operations. Drawing from the Resource-Based View (RBV) theory, the framework incorporates key data governance dimensions-data sharing, frequency, data anonymization, shared analytics, and conflict resolution mechanisms-into the existing collaborative supply chain model. The research identifies gaps in traditional supply chain systems, particularly the lack of coordinated data handling policies and technologies capable of ensuring secure, reliable, and meaningful data exchange between stakeholders. Using a mixed-method approach involving a structured survey and multi-level regression analysis, the study validates the effectiveness of the enhanced framework in improving supply chain collaboration, performance, and resilience. Empirical results from the analysis confirm that data governance variables, especially data sharing, conflict resolution, and data anonymization, have significant positive impacts on collaborative supply chain performance. This integration not only improves operational efficiency but also fosters trust, mitigates risks, and enables real-time analytics for proactive decision-making. The findings offer valuable contributions to both academic literature and industry practice by presenting a robust and scalable framework adaptable to modern supply chain ecosystems. The study concludes by recommending the adoption of emerging technologies such as blockchain and artificial intelligence to further support data governance, thereby fostering sustainable, secure, and intelligent supply chains.