Blockchain Papers

Nitya Agrawal, Manisha Nayak, Tannistha Maharana, Stutimayee Swain · 6 authors

No abstract is available for this record.

Pasam Beulah, Rajender S

The proliferation of counterfeit products in various industries, including pharmaceuticals, electronics, and luxury goods, poses a significant threat to consumer safety, brand reputation, and economic integrity. Traditional verification methods often fail due to centralized control and limited traceability. This research proposes a block chain-based system to identify fake products by leveraging the decentralized, immutable, and transparent nature of block chain technology. The system records product information such as manufacturing details, origin, and ownership history on a distributed ledger, ensuring secure and tamper-proof tracking across the supply chain. Each product is tagged with a unique QR code that links to its block chain record, allowing end-users to verify authenticity through a mobile application. The system incorporates distinct login modules for administrators, sellers, and customers to ensure secure interactions and streamline product management. Simulation results validate the system’s capability to detect counterfeit products with high accuracy and real-time verification speed. The proposed solution provides a scalable and efficient framework for enhancing supply chain integrity and protecting consumers against fake goods

N. Sindhu, K. Krishna Veni

Abstract Counterfeit and stolen goods seriously threaten the reliability of modern supply chains. They affect consumer trust, brand reputation, and economic stability. To tackle this issue, this paper presents a blockchain-based smart supply chain framework. It combines Non-Fungible Tokens (NFTs) with dual-layer Anti-counterfeiting mechanisms such as RFID tags and holographic labels [2], [6]. Each physical product connects to a unique NFT, creating a secure digital twin on a private blockchain network [3], [8]. This setup ensures traceability, verifies authenticity, and keeps transaction records safe from tampering [1], [5].. The proposed system includes a new Supply Chain Consensus (SCC) algorithm, designed specifically for supply chains. It classifies nodes by trust and stake to allow for efficient and scalable transaction validation. Also, a collateral-based incentive mechanism encourages honest participation among all involved, including manufacturers, transporters, buyers, and arbitrators [7]. Furthermore, a decentralized dispute resolution model features a transparent voting process that ensures fairness and accountability during conflicts [8]. A conceptual framework and simulation-based analysis were carried out to assess the system's performance in terms of transaction efficiency, security, and counterfeit reduction [1], [5]. The findings show that this approach significantly boosts supply chain transparency, lowers verification costs, and improves product authentication compared to traditional centralized systems [4]. This framework provides a scalable and secure solution for the next generation of supply chains, particularly in sectors like pharmaceuticals, luxury goods, and electronics. Keywords: Blockchain, Smart Supply Chain, Non-Fungible Tokens (NFTs), Anti-Counterfeiting, Digital Twin, RFID, Smart Contracts, Supply Chain Security.

K. Venkata Reddy

Demand volatility, logistical interruptions, and linked worldwide networks define the remarkable complexity of modern supply chains. Classic centralized management solutions find difficulty in offering real-time solutions to changing operational problems. For designing distributed, intelligent, and self-organizing supply chain ecosystems, artificial intelligence agents combined with Model-Control-View (MCV) architectures provide transformational possibilities. These autonomous computational entities span three functional layers: view interfaces enable monitoring and interaction, control mechanisms govern decision-making and optimization, and model components represent digital twins of supply chain entities. Multi-agent coordination enables decentralized yet coherent operations through the negotiation and collaboration of agents representing suppliers, production, logistics, and retail, all of which adhere to standardized protocols. Applications include demand forecasting, intelligent logistics, stock optimization, supplier partnering, and flexible disruption response. While reducing reliance on centralized control systems, the framework enhances resilience, scalability, openness, and operational efficiency. Challenges in implementation include organizational adaptation needs, cybersecurity vulnerabilities, and data integration complexity. Future advances in autonomous and cooperative supply chain systems will include explainable artificial intelligence, quantum-enhanced optimization, edge computing powers, and blockchain-enabled trust mechanisms.

Aravindh Sekar, Deb Tech, Cherie Noteboom

The convergence of Artificial Intelligence (AI) and Blockchain Technology (BCT) is transforming supply-chain ecosystems by enhancing transparency, intelligence, and automation. However, existing research lacks a unified theory explaining how these technologies jointly create resilience across organizational levels. This paper extends the Strategic–Decentralized Resilience Theory (SDRT), originally developed to guide effec-tive blockchain implementation, by integrating Agentic AI capabilities to form the SDRT–Agentic AI framework. The framework conceptualizes how predictive, adaptive, and agentic (autonomous) AI capabilities reinforce SDRT’s three pillars: Strategic, Or-ganizational, and Decentralized Resilience. The framework draws on three AI modali-ties—predictive AI for strategic foresight and agility, adaptive AI for organizational learning and flexibility, and agentic AI for self-governed, trustless coordination within blockchain ecosystems. Together, these mechanisms explain how intelligent and de-centralized systems co-evolve to generate dynamic, multi-level resilience. This con-ceptual paper develops a comprehensive model and propositions describing interac-tions between AI capabilities and blockchain-based organizational structures. It con-tributes to information systems and supply-chain research by unifying two fragmented domains, AI and blockchain, under a resilience-oriented mid-range theory. Practically, the framework provides managers with a roadmap to align AI investments with de-centralized governance mechanisms, enabling proactive decision-making, adaptability, and sustainable competitiveness in increasingly autonomous digital environments.

Quang Huy Duong, Carlos F.A. Arranz, Mao Xu, Li Zhou · 5 authors

The rapid transition to electric vehicles has intensified challenges in electric vehicle battery (EVB) closed-loop supply chains (CLSC), particularly regarding material traceability, supply chain transparency, and recycling efficiency. While decentralised technologies, particularly Web3 and Metaverse, offer promising solutions, their integration into EVB CLSC remains fragmented and insufficiently examined. We introduce an Operational Decentralisation Framework enabling a systematic analysis of centralised operations and a critical evaluation of decentralised alternatives as transformational forces. By adopting a holistic perspective, the framework equips firms with strategic guidance for transitioning from centralised structures to decentralised ecosystems. We analyse 588 academic articles and 1,168 industry documents through two advanced text mining techniques – Dynamic Latent Dirichlet Allocation and Burst Detection. Web3 and metaverse can potentially reconfigure the design, manufacturing, end-of-life diagnostics, procurement, waste management, load balancing, capacity planning, inventory management and service operations of two key areas: (1) EVB CLSC operations and (2) EVB circular energy/grid operations. We also found that while blockchain and digital twins show established applications, Web3 and Metaverse applications face significant barriers, including scalability, technology complexity, and expertise gaps, despite their great potentials. Therefore, we propose four visionary models integrating Web3, Metaverse, and AI technologies that have the potential to overcome existing barriers and enable transformative decentralisation. Extending the TOE framework, the study contributes to the theory by developing an integrated framework for evaluating decentralised technology adoption in EVB CLSCs. For practitioners, we provide actionable insights and pathways for technology implementation across different CLSC stages and guidance for addressing key adoption barriers.

Alexander Samuels

Background Global supply chains are increasingly challenged by disruptions, environmental pressures, and evolving market demands, necessitating a strong digital transformation. This study explores how the integration of Artificial Intelligence (AI), Blockchain, and the Internet of Things (IoT) is revolutionizing supply chain management (SCM) by improving operational efficiency, transparency, resilience, and sustainability. Methods Adhering to the PRISMA framework, a systematic review of literature published between 2010 and 2024 was undertaken. Comprehensive searches were conducted in Scopus database. The collected literature was rigorously screened and analyzed using Atlas-ti software to identify recurring themes and assess the synergistic impact of AI, Blockchain, and IoT on supply chain operations. Results The review reveals that digital transformation significantly improves SCM through improved demand forecasting, optimized inventory management, and real-time decision-making capabilities. AI provides predictive insights that mitigate risks and streamline processes, Blockchain offers secure, transparent, and immutable records that improve trust and traceability, and IoT enables real-time monitoring and connectivity across the supply chain network. Despite these benefits, challenges remain, including cybersecurity vulnerabilities, interoperability with legacy systems, and the need for workforce upskilling. Conclusion The integration of AI, Blockchain, and IoT into SCM presents a compelling pathway toward creating more resilient and sustainable supply chains. The paper offers a comprehensive analysis of the benefits and challenges associated with these digital technologies and provides strategic recommendations for practitioners and policymakers to encourage a balanced, technology-driven, and sustainable supply chain ecosystem. JEL codes O33, M11, M15

Yiming Zhao, Christopher Hayes

The complexity of modern supply chain networks requires sophisticated approaches to inventory management that can effectively handle demand uncertainty and coordinate decisions across multiple organizational levels. This paper proposes a novel hierarchical multi-agent reinforcement learning framework for dynamic inventory allocation in multi-echelon supply chains facing stochastic demand patterns. The hierarchical architecture decomposes the inventory control problem into strategic and operational decision layers, where high-level agents coordinate allocation policies across distribution networks while low-level agents optimize local replenishment decisions. The framework integrates Centralized Training with Decentralized Execution paradigm, enabling autonomous agents to learn coordinated policies through shared experience while maintaining operational independence during deployment. Experimental results demonstrate that the proposed approach achieves significant reductions in total system costs compared to traditional base-stock policies and single-agent reinforcement learning methods, while effectively mitigating the bullwhip effect in supply chains with high demand variability.

Vadym Derkach

As global pressure increases for sustainable and transparent supply chains, logistics organisations are exploring ways to strengthen environmental, social and governance (ESG) performance. This article examines how artificial intelligence (AI) and distributed ledger technologies (DLT) contribute to ESG integration in logistics. The study applies a qualitative desk research approach based on secondary data from 2017–2025, including sustainability reports, port authority publications, and the industry press. The comparative case analysis covers four Baltic logistics actors: the Port of Klaipėda (Lithuania), Vlantana (Lithuania), the Freeport of Riga/ Baltic Container Terminal (Latvia), and HHLA TK Estonia (Estonia). The findings show that Klaipėda’s LNG, OPS, and hydrogen projects enhance environmental outcomes; the Vlantana Norge case exposes social and governance compliance risks; and Riga and Tallinn demonstrate governance-oriented digitalisation through 5G networks and blockchain documentation. AI primarily supports efficiency and risk detection, while DLT secures the transparency and auditability of ESG data. Together, they function as complementary enablers of ESG reporting, though broader adoption requires regulatory alignment, interoperability, and investment in the digital infrastructure.

SANJAY V S, R.V Suganya

Abstract The digital transformation of global supply chains presents unprecedented opportunities, yet it concurrently exacerbates the existing gap in financial inclusion for Micro, Small, and Medium Enterprises (MSMEs). Traditional supply chain finance (SCF) models often fail to serve these small suppliers due to high information asymmetry, lack of verifiable collateral, and manual, paper-intensive processes, leading to significant liquidity constraints. This study proposes and empirically investigates blockchain technology as a foundational solution to mitigate these challenges. Specifically, it examines how blockchain-enabled traceability fosters greater trust and transparency, which in turn facilitates more accessible and inclusive supplier financing mechanisms. Employing a mixed-method approach (Quantitative N=150−180 survey and Qualitative interviews) with a cross-sectional design, the research analyzes relationships using descriptive statistics, regression, and factor analysis. Preliminary findings are expected to demonstrate a significant positive impact of blockchain adoption on financial inclusion metrics for MSMEs. The research contributes by providing a rigorous framework for practitioners and policymakers aiming to leverage decentralized technology to create a more equitable and sustainable global trade ecosystem. Keywords: financial inclusion, blockchain enabled supply, micro, small, and medium enterprises,

Pallab Haldar

Global supply chains are essential to world trade, but they harbor profound inequities- challenges that are manifestations of, and exacerbate, social inequalities. Lack of information, ambiguous procurement practices, and biased risk models relegate small suppliers, developing states, and underrepresented laborers. Artificial intelligence and blockchain with data governance come together in the form of AI-Driven Access and Transparency Networks (AI-ATNs), which make global value networks more equitable and accountable. Explainable AI is used together with fairness-conscious optimization and distributed ledger transparency in AI-ATNs.The outcome? Supply chain participation based on merit and need rather than location or connections. Agriculture, manufacturing, and humanitarian logistics provide real examples of AI systems turning equity into both a social goal and economic necessity. The digital revolution needs to move past efficiency targets and embrace equity intelligence, transforming global supply chains into ethical systems that balance business success with social justice.

Diyan Putranto, Fransiscus Amonio Halawa, Rintis Eko Widodo, Fahmi Setiawan · 5 authors

The competitive hospitality sector faces a growing credibility crisis, where rising consumer skepticism regarding "greenwashing" severely limits the ability of hotels to capture the Sustainable Revenue Premium. This research addresses a critical gap in Sustainable Supply Chain Management (SSCM) literature by empirically modeling the "Credibility Mechanism"—the process by which digital technology resolves information asymmetry to monetize sustainability claims. Focusing on the complex Food and Beverage (F&B) supply chains of emerging archipelagic economies, the study employs a rigorous sequential mixed-methods design. First, Design Science Research was utilized to architect a permissioned cross-chain blockchain framework integrating Zero-Knowledge Proofs (ZKPs) for verifiable, private provenance. Subsequently, Partial Least Squares-Structural Equation Modeling (PLS-SEM) confirmed that blockchain-enabled transparency significantly mitigates perceived greenwashing risk, which in turn fosters Customer Trust. Critically, the study validates financial outcomes using a Stochastic Frontier Bayesian Model (SFBM) applied to longitudinal hotel data. Results demonstrate that adopting this traceable framework yields an 8.4% increase in F&B revenue efficiency and sustains a 5.1% price premium for ethically sourced items. These findings provide profound theoretical advancements by redefining SCM risk mitigation through Information Governance rather than material redundancy. Managerially, the research offers a data-driven justification for high-tech investment, proving that verifiable transparency is a direct revenue driver essential for competitive advantage in opaque markets.

Aguirre Ortiz, Sofía, Parrado Carreño, Gary Yeffet, Zamora, Jairo

Accelerated global digitalization is threatened by a profound crisis of digital trust, marked by systemic data breaches and eroding confidence in centralized intermediaries. This article investigates Distributed Ledger Technology (DLT) as a foundational solution, examining its capacity to replace institutional trust with cryptographic assurance through decentralized verification. Through a rigorous comparative case study methodology analyzing cross-border finance and supply chain traceability, the research assesses how DLT mitigates counterparty risk while generating new forms of economic value. The core analysis focuses on critical implementation tensions between operational scalability requirements and ideological decentralization goals, alongside the challenge of reconciling immutable systems with evolving global regulatory frameworks. Empirical findings confirm DLT's tangible economic value through significant reductions in financial verification costs and settlement timeframes, while simultaneously generating measurable consumer trust premiums in supply chain applications through verifiable provenance. However, evidence reveals a fundamental trade-off: practical enterprise adoption consistently favors high-throughput permissioned ledgers, compromising decentralization ideals for operational scalability and governance control. Significant regulatory friction further necessitates hybrid data architectures, positioning DLT as a crucial assurance layer within broader compliance ecosystems rather than a standalone solution. This underscores the need for future research developing integrated trust frameworks that balance technological potential with implementation pragmatism across diverse sectoral contexts.

Ziling Wu, Xiaohan Liu, Ruiting Zhang

No abstract is available for this record.

Azz-eddine Meafa, Abla Chaouni Benabdellah, Kamar Zekhnini, Surajit Bag

The automotive supply chain (ASC) in Northern Africa faces many challenges related to traceability, trust deficits, data integrity, heavy workloads and intermediary involvement in its sourcing process (SP). These challenges can hinder this process’s efficiency and sustainability while sourcing suitable suppliers for the supply chain (SC). Thus, digitalization stands as a powerful facilitator in managing complex processes and blockchain technology (BT) is promoted to effectively address similar issues. In this regard, this article aims to build a smart SP model guided by lean practices and green principles using BT and smart contracts to achieve operational excellence (OE) in the automotive SP in the Northern Africa context. To do so, this study conducts interviews with experts to investigate contextual issues and identify the main challenges faced by the current automotive SP. Then, it proposes the smart SP as a solution for these challenges. The proposed solution uses an algorithmic approach to develop the smart contract algorithms for six sub-processes of the smart SP. Furthermore, the study offers multiple business implications on the digitalization of the SP to reduce higher workloads of the sourcing team, cost related to intermediary elimination and decentralized data management to deal with integrity, traceability and trust challenges while searching for potential partners.

Sorina Geanina Stănescu, Constantin Aurelian Ionescu, Maria Cristina Ștefan, Luiza Ionescu · 6 authors

The agri-food sector is currently undergoing a significant digital transformation, driven by climate change, frequent supply chain disruptions, and increasing demand for transparency and food safety. This article, based on a systematic review of 113 recent studies (in line with the PRISMA guidelines), delves into how emerging digital technologies, particularly blockchain, are reshaping agri-food supply chains towards sustainability, a circular economy, and complete product traceability from production to the final consumer. The paper identifies the main enabling factors, barriers, and implementation models of blockchain and other technologies associated with Industry 4.0 (IoT, artificial intelligence, smart contracts), highlighting their role in increasing the resilience of supply chains, optimising quality control, and sustainable resource management. A key contribution of the study is the introduction of the CTSAF (Converging Technologies for Sustainable Agri-Food Chains) conceptual framework, which provides practical implications for policymakers and organisations, enabling them to make informed decisions. The results also provide valuable insights for future research, supporting the transition to a more transparent, resilient, and sustainable global food system.

Tan Gürpinar, Mehmet Akif Gulum

Global supply chains face increasing disruptions from cyber threats, geopolitical instability, extreme weather events, and a range of economic, social, and environmental sustainability challenges. As these disruptions intensify, enhancing Supply Chain Resilience (SCR) has become a strategic priority. This study investigates how Distributed Ledger Technology (DLT) can contribute to SCR by mitigating vulnerabilities and strengthening key capabilities within global supply chains. A qualitative research approach is employed, utilizing expert evaluations to examine DLT’s impact on supply chain vulnerabilities and capabilities. Five workshops were conducted with 25 industry professionals from logistics, IT, procurement, and risk management. Experts examined how DLT could address disruptions stemming from supplier instability, poor traceability, and regulatory and environmental pressures, while highlighting its potential to drive ethical sourcing and environmentally responsible practices. The structured discussions were guided by theoretical frameworks and expert evaluations were synthesized into two analytical matrices illustrating DLT’s influence on SCR. The findings reveal that the contribution of DLT to SCR and sustainability is highly context-dependent, with its effectiveness hinging on how it is embedded within governance structures and aligned with the interplay of complementary technologies. Building on these insights, the study presents the DLT-LFL (Distributed Ledger Technology–Learning Feedback Loop) framework, which integrates sensing, decision-making, adaptation, and predictive learning from distributed operational data, allowing supply chains to better anticipate disruptions, adjust processes dynamically, and continuously strengthen resilience and sustainable practices. The study also develops a practical checklist to assess how effective DLT applications and their integration with predictive and AI-driven analytics reduce vulnerabilities, strengthen capabilities, mitigate risks, and support adaptive decision-making.

Jinho Cha, Young‐Chul Kim, Junyeol Ryu, Sangjun Park · 6 authors

This study develops a strategic procurement framework integrating blockchain-based smart contracts with bounded demand variability modeled through a truncated normal distribution. While existing research emphasizes the technical feasibility of smart contracts, the operational and economic implications of adoption under moderate uncertainty remain underexplored. We propose a multi-supplier model in which a centralized retailer jointly determines the optimal smart contract adoption intensity and supplier allocation decisions. The formulation endogenizes adoption costs, supplier digital readiness, and inventory penalties to capture realistic trade-offs among efficiency, sustainability, and profitability. Analytical results establish concavity and provide closed-form comparative statics for adoption thresholds and procurement quantities. Extensive numerical experiments demonstrate that moderate demand variability supports partial adoption strategies, whereas excessive investment in digital infrastructure can reduce overall profitability. Dynamic simulations further reveal how adaptive learning and declining implementation costs progressively enhance adoption intensity and supply chain performance. The findings provide theoretical and managerial insights for balancing digital transformation, resilience, and sustainability objectives in smart contract-enabled procurement.

Ejielo Ogbuefi, Stephen Ehilenomen Aifuwa, Jennifer Olatunde-Thorpe, David Akokodaripon

Resilience in critical infrastructures (CIs) has emerged as a pressing global concern, as societies become increasingly dependent on tightly interconnected systems that support communication, energy, finance, and healthcare. These infrastructures, once considered largely independent, now operate within a convergent ecosystem where disruptions in one domain can propagate rapidly across others, leading to cascading failures with severe societal and economic consequences. Conceptual frameworks addressing resilience in such interdependent systems emphasize the need to move beyond traditional robustness toward adaptive, absorptive, and restorative capacities that account for dynamic risks, systemic vulnerabilities, and emergent behaviors. The convergence of communication technologies with energy, financial, and healthcare services introduces both opportunities and challenges. While digital integration enhances efficiency, situational awareness, and service delivery, it also amplifies exposure to cyber threats, systemic shocks, and supply chain fragilities. For instance, a cyberattack on a power grid can simultaneously disrupt healthcare delivery and financial transactions, while communication failures may impede crisis coordination. To address these risks, resilience frameworks increasingly adopt network-centric, socio-technical, and complex adaptive systems perspectives, highlighting interdependencies and the need for multi-level governance. Key strategies include embedding redundancy and decentralization in communication systems, deploying microgrids and storage in energy infrastructures, integrating distributed ledgers and systemic risk monitoring in finance, and strengthening telemedicine and emergency preparedness in healthcare. At a broader level, resilience planning requires cross-sector interoperability standards, public–private collaboration, and ethical prioritization of vulnerable populations. Emerging tools such as AI-driven predictive analytics and digital twins offer promising avenues for resilience assessment and proactive adaptation. Ultimately, resilience in convergent critical infrastructures demands an integrated, multidisciplinary approach that bridges engineering, policy, and social dimensions. By adopting conceptual frameworks that embrace interdependency, adaptability, and inclusivity, societies can enhance preparedness, mitigate cascading risks, and ensure continuity of vital services under conditions of uncertainty.

Hakeem Mustapha Attau, Oluwaseun Adeniyi Ojerinde, John Kolo Alhassan, Kabiru Abdullahi

No abstract is available for this record.

Zhaoqian LIU

Sustainable trade requires verifiable, granular, and trustworthy data across multi-jurisdictional supply chains. This paper argues that blockchain’s binding constraints are institutional, not technical, and proposes the Green Trade Blockchain Governance Trilemma: no design can simultaneously maximize (i) transactional efficiency, (ii) regulatory verifiability, and (iii) decentralized governance with commercial privacy. Comparative cases—TradeLens, IBM Food Trust, Everledger, and Power Ledger—show divergent institutional choices and outcomes: TradeLens faltered under perceived hegemonic control; Food Trust succeeded via a buyer mandate; Everledger thrived through symbiosis with trusted authorities; Power Ledger scaled within a regulatory sandbox. We further analyze the Oracle Problem as the key limit to verifiability and assess privacy-enhancing technologies, especially zero-knowledge proofs, as partial mitigations that protect sensitive data while enabling compliance checks. We conclude that success hinges on context-specific institutional design—certified oracles plus verifiable computation—rather than a one-size-fits-all stack, offering actionable guidance for policymakers, consortia, and firms building credible green-trade infrastructure.

Jing Zhao

As global economic integration deepens, supply chain finance plays a crucial role in optimizing corporate cash flow and promoting the coordinated development of industrial chains. However, issues such as information asymmetry and credit assessment difficulties in traditional models have hindered its growth. Blockchain technology, with its decentralized nature, data immutability, and automated smart contracts, offers innovative solutions for credit risk management in supply chain finance. This article systematically analyzes the application logic, typical scenarios, and implementation effects of blockchain technology in credit risk management within supply chain finance. It also explores the technical bottlenecks, regulatory challenges, and coordination issues faced by the practical implementation of these technologies, and propose targeted optimization strategies. The aim is to provide theoretical support and practical references for the deep integration of blockchain technology with supply chain finance.

Madhu Kaushik

Globalized supply chains are strained by fragmented data, multi-tier opacity, counterfeit risks, and costly disputes. Blockchain—a shared, append-only ledger—has been proposed to enhance transparency, traceability, and operational efficiency, yet real-world adoption reveals both breakthroughs and bottlenecks. This paper develops a deploymentminded view that integrates GS1 EPCIS/CBV standards for interoperable event data, permissioned ledgers for governance, and privacy-preserving proofs (zero-knowledge) to reconcile transparency with business confidentiality. We synthesize evidence from systematic reviews and flagship pilots (e.g., Walmart–IBM Food Trust) and contrast them with lessons from initiatives that wound down (e.g., TradeLens), extracting adoption patterns, KPI impacts, and failure modes. We then describe a reference methodology—data acquisition via EPCIS events, Fabric-based channels, and role-based access—plus an evaluation rubric for trace time, recall precision, dispute cycle time, and data-reconciliation costs. Results from literature-anchored benchmarks indicate orders-of-magnitude traceability lead-time (TLT) reductions (days → seconds) and measurable reductions in manual reconciliation, with gains contingent on standards compliance and high-quality “oracle” data. Finally, we map future directions—zk-proof rollups, interoperable digital product passports, and policy-aligned sustainability metrics—alongside candid limitations around ecosystem incentives, privacy, scalability, and data veracity. We conclude that blockchain can shift chains from reactive to verifiable and auditable networks when combined with data standards, sound governance, and selective privacy technologies rather than “full transparency” alone.

Mohamed Al-Ali, Mohammad Miftaur Khan

No abstract is available for this record.