https://gprjournals.org/journals/index.php/jpscm <p><strong>Journal of Procurement and Supply Chain Management</strong> (JPSCM) is a fast track and a peer-reviewed journal published by GPR Journals. The scope of JPSCM include, but not limited to, inventory Management, Procurement Contracting, Demand Forecasting, Inventory Management, Logistics &amp; Transportation, Materials Handling, Supplier Relationship Management, Sourcing &amp; Purchasing Services, Supplier Relationships, Supply Chain Finance, Supply Chain Mapping, Supply Chain Planning &amp; Scheduling, Supply Chain Scalability, Supply Chain Synchronization, etc. JPSCM is devoted to maintain its authenticity amongst scholars, business practitioners, and readers seeking an update on current experience and future prospects in procurement and supply chain management. Manuscripts submitted to this journal are published online and can also be printed as hard copies upon author’s request. Papers can be submitted via email to <a href="mailto:journals@gprjournals.org" target="_blank" rel="noopener">journals@gprjournals.org</a> or <a href="https://gprjournals.org/online-submission/">online submission.</a></p> Global Peer Reviewed Journals en-US Journal of Procurement and Supply Chain Management 2958-4078 <p><em>The authors retain the copyright and grant this journal right of first publication. This license allows other people to freely share and adapt the work but must give appropriate credit, provide a link to the license, and indicate if changes were made. They may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.</em></p> https://gprjournals.org/journals/index.php/jpscm/article/view/441 <p><strong>Aim:</strong> This study aims to evaluate the role of Artificial Intelligence (AI) in enhancing sustainable supplier assessment within ESG-focused procurement systems, ultimately demonstrating AI’s potential as a transparent, adaptive, and scalable tool for sustainable supplier evaluation.&nbsp;</p> <p><strong>Methods:</strong> The research adopts a mixed-methods approach combining qualitative analysis of international ESG standards (GRI, ISO 20400), an algorithmic review of AI techniques (Machine Learning, Natural Language Processing, Explainable AI), and an in-depth case study of Unilever. The core procedure involved developing an analytical matrix to systematically compare traditional and ESG-oriented supplier selection and formulating a framework for embedding ESG-by-design principles into digital procurement platforms.</p> <p><strong>Results:</strong> Findings reveal that AI-enabled procurement systems significantly improve transparency, scalability, and adaptability in supplier ESG assessments compared to traditional methods. The analytical matrix highlights AI’s superior predictive capabilities for risk mitigation, facilitating a shift from simple compliance checking to proactive risk management.</p> <p><strong>Conclusion:</strong> This work substantiates the need to combine AI tools with an ethical approach to supply chain management under conditions of uncertainty and risk, establishing ESG integration not just as an ethical imperative but a strategic necessity.</p> <p><strong>Recommendations:</strong> The main practical implication is the imperative for organizations to shift from reactive compliance to a proactive risk architecture, mandating the use of AI tools under strict ethical governance for reliable supply chain resilience. Strategic recommendations include embedding ESG criteria natively within digital procurement platforms and adopting the developed AI-driven classification matrix.</p> Yuliia Zorina Copyright (c) 2025 Yuliia Zorina https://creativecommons.org/licenses/by/4.0 2025-11-20 2025-11-20 4 3 1 13 10.58425/jpscm.v4i3.441 https://gprjournals.org/journals/index.php/jpscm/article/view/460 <p><strong>Aim:</strong> The study aims to examine the application of blockchain technology as a secure, reliable, and tamper-resistant solution for lifecycle record management of aircraft parts within the aviation Maintenance, Repair, and Overhaul (MRO) sector.</p> <p><strong>Methods: </strong>The study adopts a design-oriented and case-based approach to evaluate the integration of blockchain technology with existing MRO systems. A permissioned blockchain architecture is proposed, leveraging smart contracts for automated compliance verification and maintenance scheduling. Real-time aircraft telemetry is ingested using Apache Kafka and processed through Apache Spark to validate and enrich data before being recorded on the blockchain. A proof of concept and case study are used to assess system performance, auditability, and integration challenges with enterprise resource planning (ERP) systems.</p> <p><strong>Results: </strong>The findings demonstrate that blockchain implementation significantly improves auditability, data accuracy, and time efficiency in aircraft parts traceability among original equipment manufacturers (OEMs), MRO providers, and aviation authorities. The proof of concept highlights reduced risks of record tampering, improved regulatory compliance, and enhanced transparency across the aircraft parts lifecycle. However, challenges related to system integration, implementation costs, scalability, and market adoption barriers are also identified.</p> <p><strong>Conclusion: </strong>The study concludes that blockchain technology has strong potential to reshape trust, transparency, and productivity in aircraft parts record-keeping within the MRO environment. By providing a secure digital footprint for serialized parts, blockchain serves as a foundational technology for advancing the digital transformation of the aviation MRO ecosystem.</p> <p><strong>Recommendations: </strong>The study recommends adopting a phased, three-stage blockchain implementation strategy supported by regulatory alignment and cross-stakeholder collaboration among OEMs, MRO organizations, and aviation authorities. Future efforts should focus on cost optimization, ERP integration frameworks, scalability testing, and industry-wide standards to enable sustainable and widespread adoption of blockchain-based MRO solutions.</p> Saketh Kumar Vishwakarma Copyright (c) 2025 Saketh Kumar Vishwakarma https://creativecommons.org/licenses/by/4.0 2025-12-25 2025-12-25 4 3 1 4 31 10.58425/jpscm.v4i3.460