Optimizing Supply Chain Traceability: A Hybrid MCDM Approach (BWM–ANP) for Blockchain Platform Selection in Pharmaceutical and Healthcare Systems

Abstract

The pharmaceutical and healthcare supply chain faces growing risks, including falsified or substandard drugs, complex global sourcing, and stringent data protection regulations. Although digital track-and-trace tools, mobile authentication, and data analytics offer potential solutions, many current systems remain isolated and vulnerable to manipulation. Blockchain and other distributed ledger technologies provide decentralized, tamper-evident infrastructures suitable for drug traceability, yet selecting an appropriate platform is a complex and stakeholder-dependent decision.

This study proposes a hybrid multi-criteria decision-making framework that integrates the Best–Worst Method (BWM) with the Analytic Network Process (ANP) to guide platform selection for pharmaceutical traceability. Criteria are organized into five groups: technical performance, privacy and security, traceability and anti-counterfeiting quality, regulatory and compliance requirements, and organizational-economic-ecosystem factors. Expert evaluations from operations, regulatory, IT/blockchain, and strategic roles are first synthesized through BWM to derive consistent criterion weights, while ANP captures interdependencies among criteria through a weighted supermatrix. The framework is applied to four platform configurations: a Fabric-based consortium blockchain, an enterprise Ethereum network (Besu/Quorum), a sector-specific traceability platform inspired by PharmaLedger, and a public Ethereum plus Layer-2 setup. Results indicate that the sector-specific consortium solution holds the highest overall priority, emphasizing the importance of regulatory fit, identity management, and tamper-evident traceability in platform selection.