Blockchain Papers

Vikas Khare, Monica Bhatia, Miraj Ahmed Bhuiyan

No abstract is available for this record.

Vikas Khare, Monica Bhatia, Miraj Ahmed Bhuiyan

No abstract is available for this record.

Martin Končár, Adel Aazami, Sebastian Kummer, Navid Mohammadi

Digital technologies are widely expected to reshape supply chains, yet the conditions under which they deliver operational and sustainability-related value in practice remain insufficiently understood. This study examines how digital technologies influence supply chain operations and performance, where performance is operationalized through demand forecasting accuracy, cost, lead time, visibility, and inter-organizational collaboration, and asks how these technologies can support more resilient, resource-efficient, and sustainable supply chain operations. The study adopts an exploratory qualitative design based on semi-structured interviews with eight supply chain professionals at manager level or above, drawn from the aluminum, elevator, railway, food, and consumer goods industries in Austria, Slovakia, and the Czech Republic, and conducted between March and June 2025. A structured literature review complements the interview evidence. Within this exploratory sample, Artificial Intelligence and Data Analytics were the most widely adopted technologies (five of eight participants each), followed by the Internet of Things (four of eight) and Automation (five of eight), while no participant reported active Blockchain deployment. Reported benefits concentrated on forecasting accuracy, operational efficiency, visibility, and collaboration, whereas high implementation costs, legacy system integration, skill shortages, and regulatory uncertainty formed the principal barriers. The central finding is a conditional relationship between adoption and competitiveness: internal operational gains did not automatically translate into competitive advantage among the professionals interviewed, but appeared to require strategic alignment, cross-functional integration, and performance measurement. Because digitally enabled forecasting, inventory positioning, and resource optimization also reduce waste and improve resource utilization, the findings link digital supply chain transformation to sustainable development objectives. This exploratory study of eight participants therefore provides practitioner-level propositions and a research agenda for digital and sustainable supply chain transformation rather than statistically generalizable findings.

S. Priyan, A. Brindha, Piratdin Atabayev, Bikash Paul

No abstract is available for this record.

Sinhika Deshmukh, Sujata Karve

Purpose This study aims to develop and evaluate a blockchain-enabled traceability framework capable of improving circular steel recovery and reducing embodied carbon within Tata Steel’s supply chain. Study Blockchain technology is increasingly being explored as a digital enabler for circular economy practices and low-carbon industrial supply chains. In the steel sector, fragmented documentation systems, limited material traceability and inefficient scrap recovery mechanisms continue to constrain circularity and embodied carbon reduction, particularly within the Indian construction industry. Despite growing interest in blockchain-enabled traceability, limited research has examined its application within steel supply chains using a case-grounded and quantitatively modelled approach linking traceability improvements with circular steel recovery and embodied carbon reduction. Design/Methodology/Approach A single-case explanatory research design combined with secondary-data-based scenario modelling was adopted using publicly available Tata Steel sustainability disclosures, industry benchmarks and validated emission factors. The proposed framework integrates QR/RFID-enabled batch identities, Internet of Things (IoT)-assisted verification systems, smart contracts and artificial intelligence (AI)-assisted dashboard visualisations to model improvements in traceability and closed-loop recycling performance. Findings Scenario modelling indicates that traceability coverage could improve from approximately 42% to 98%, while verified scrap reuse could increase from 60% to 88%. Using an emission avoidance factor of 1.35 tCO2 per tonne of recycled steel and a conservative annual scrap throughput assumption of 8.0 Mt, the framework estimates a feasibility-oriented embodied carbon reduction of approximately 3.0 MtCO2/year. Originality/Value The study proposes a Tata Steel-specific blockchain circularity framework demonstrating how digital provenance systems can strengthen transparent material governance, enhance circular steel recovery and support feasibility-oriented embodied carbon reduction pathways within industrial steel supply chains. Research Limitations/Implications The findings are based on secondary-data-driven scenario modelling and should therefore be interpreted as feasibility-oriented estimates rather than empirically validated operational outcomes. The framework provides a basis for future empirical assessment and sensitivity analysis under alternative industrial and policy conditions. Practical Implications The framework provides a conceptual decision-support approach for improving batch-level traceability, scrap verification, closed-loop recovery, environmental reporting and supply-chain accountability through blockchain-enabled systems. Social Implications Improved material provenance and verification can strengthen transparency and accountability among supply-chain actors and support more trustworthy circular material governance.

Nguyen Thi Thu Hoan, Le Ngoc Thang

Abstract The rapid integration of Industry 4.0 technologies is profoundly transforming global supply chains, impacting sustainability, economic efficiency, and competitiveness. This study economically analyzes the adoption of Industry 4.0-driven green supply chain management (GSCM) practices specifically within developing economies. Leveraging established economic theories, including transaction cost economics, resource-based view, and institutional theory, alongside empirical data and case studies, the authors assess how digital transformation enhances supply chain sustainability and economic performance. The authors employ a panel data regression model to examine the relationship between Industry 4.0 technologies (Internet of Things, blockchain, artificial intelligence, and additive manufacturing) and key sustainability metrics, including carbon footprint reduction, cost efficiency, and resilience. By leveraging case studies from developing nations, the authors highlight how digital adoption influences supply chain productivity and long-term economic gains while aligning with the United Nations Sustainable Development Goals (UNSDGs) 2030. The authors’ findings provide policy recommendations for governments and firms to optimize digital infrastructure investments, mitigate adoption barriers, and enhance regulatory frameworks for sustainable economic growth. This chapter contributes to the literature by bridging economic analysis with the practical application of Industry 4.0 technologies for supply chain sustainability in developing economies. It offers novel insights into how these nations can achieve economic and environmental resilience amid evolving global trade dynamics, particularly in the post-COVID-19 era.

Mariem Balti

Abstract This chapter examines how Industry 4.0 technologies enhance adaptive performance within the framework of Green Supply Chain Management (GSCM), drawing on the theoretical perspectives of Dynamic Capabilities, the Resource-Based View and Circular Economy principles. A systematic review of peer-reviewed literature from Scopus and Web of Science (2018–2025) was conducted, using defined inclusion and exclusion criteria to identify 126 relevant studies. The analysis highlights how key technologies – including the Internet of Things (IoT), Artificial Intelligence (AI), Blockchain, Robotics and Additive Manufacturing – enable real-time responsiveness, transparency and resource efficiency in sustainable supply chains. Findings indicate that the integration of these technologies not only strengthens operational flexibility and resilience but also accelerates progress toward United Nations Sustainable Development Goals (SDGs), particularly Goals 9, 12 and 13. This chapter provides theoretical contributions by linking adaptive performance to strategic technological capabilities and practical recommendations for policymakers and industry leaders to align digital transformation with net-zero carbon targets. Future research directions are proposed to empirically assess these relationships using both quantitative and qualitative approaches.

Katarina Dimić‐Mišić, Shailesh Singh Chouhan, Michael Gasik, Milica P. Marčeta Kaninski · 7 authors

Electronic waste (e-waste) is among the fastest-growing global waste streams, with 62 million tonnes generated in 2022 and only 22.3% formally recycled, while generation is projected to reach 82 million tonnes by 2030. Fragmented record-keeping, weak chain-of-custody controls, and limited transparency enable illegal dumping, fraudulent recycling claims, and loss of recoverable materials. This paper presents a narrative literature review of blockchain and distributed ledger technologies applied to electronics and e-waste management. Following a structured search and relevance screening of major scientific databases, publisher platforms and grey literature (last search was run on 15 July 2026), 110 sources published between 2017 and 2026 were thematically synthesized across four domains: technological developments, sustainability and circular-economy implications, traceability and compliance mechanisms, and e-waste management applications. Blockchain delivers value primarily through an auditable chain-of-custody built on three pillars: standardized item and batch identities, standardized lifecycle event schemas, and licensed-actor attestations supported by off-chain evidence anchored on-chain. Recurring design patterns include permissioned consortium networks, hybrid storage, and role-based access control. Persistent barriers include data-input integrity, scalability, governance, and cost. Blockchain immutability protects stored records but cannot correct falsified inputs, making trusted data capture and governance the decisive factors for reliability. Adoption should be evaluated against measurable indicators, such as traceability completeness, audit-time reduction, fraud rates, and verified material recovery, rather than assumed benefits.