Abstract

Transparency in procurement and supply chain management has emerged as a critical determinant of efficiency, accountability, and trust in both public and private sector operations. Inadequate visibility into procurement processes often fuels inefficiencies, fraud, corruption, and inequitable supplier relationships, undermining organizational competitiveness and stakeholder confidence. Recent technological advancements, particularly the development of integrated digital platforms, offer promising avenues for enhancing transparency by enabling real-time information sharing, standardized documentation, automated auditing, and multi-stakeholder collaboration. Such platforms combine digital procurement systems, blockchain-enabled traceability, data analytics, and artificial intelligence to provide comprehensive oversight and reduce opportunities for malpractice. This paper presents a literature-based review of scholarly and applied research on the development and deployment of integrated digital platforms for procurement and supply chain transparency, focusing on works published up to 2024. The review traces the evolution of transparency as a strategic goal, identifies the main technological enablers of digital platforms, and critically assesses challenges of implementation, ranging from interoperability and cybersecurity to institutional resistance and capacity gaps. By synthesizing existing knowledge, the study contributes to the academic discourse on digital procurement transformation and highlights practical pathways for organizations seeking to adopt integrated systems. The findings emphasize that while digital platforms offer significant benefits in improving procurement efficiency, reducing corruption, and strengthening supply chain resilience, their success depends on cross-sectoral collaboration, robust governance frameworks, and context-specific design. This review lays the groundwork for future studies to explore the integration of emergent technologies such as blockchain, big data analytics, and machine learning into procurement transparency frameworks, while providing actionable insights for policymakers, practitioners, and supply chain leaders.