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.
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.
Gurkan Akalin, Birsen Karpak, Y. İlker Topçu, Emel Aktaş
Purpose The pandemic, disruptions to transportation networks, geopolitical conflicts and trade restrictions over the past five years have intensified attention to supply chain resilience (SCRes) from both academia and industry. At the same time, rapid digitalisation is transforming traditional supply chains. Although numerous studies have examined digital technologies or SCRes independently, limited attention has been given to the reciprocal interrelationships among digital technologies and SCRes dimensions. Given the interconnected nature of digital technologies and the multidimensional characteristics of SCRes, examining these reciprocal interrelationships is essential for capturing their collective influence. Therefore, this study aims to identify the digital technologies that influence SCRes and examine their interrelationships with the dimensions of SCRes, thereby clarifying the relative roles and influence of both digital technologies and SCRes dimensions in strengthening more resilient and sustainable supply chains. Design/methodology/approach We conducted a structured literature review (SLR) and consulted a hybrid panel of seven academic and industry experts to identify the key dimensions of SCRes and the digital technologies influencing them. We then worked with experts to prioritise these factors using the analytic network process (ANP), an extension of the analytic hierarchy process (AHP) that is well-suited to modelling the strong interdependencies and feedback relationships among digital technologies and SCRes dimensions. Data were collected in both 2023 and 2025 from the same experts to capture the changes in expert judgements over time. Findings We found that collaboration and Internet-of-Things (IoT) have exerted the strongest relative influence on SCRes. In particular, collaboration becomes the highest priority factor overall, whereas IoT is the highest priority digital technology within the proposed decision framework. Visibility and velocity follow as the next most influential resilience dimensions, while AI and blockchain, although lower ranked, exhibit increasing relative influence across the two assessment periods. We also argue that no single digital technology on its own is sufficient to achieve supply chain resilience. Successful adoption and implementation require an understanding of how these technologies mutually interact with SCRes dimensions. By explicitly accounting for these interdependencies, the proposed decision framework prioritises both digital technologies and SCRes dimensions according to their relative influence on supply chain resilience, providing practical guidance for organisations seeking to strengthen resilience. Originality/value This study advances the SCRes literature by proposing an integrated ANP-based framework that models the interdependencies and feedback relationships between digital technologies and SCRes dimensions. Unlike prior studies that examine technologies in isolation or treat resilience dimensions as independent constructs, the present study evaluates both the combined and individual influence of digital technologies within a multidimensional resilience framework. The study further contributes by organising the literature around digital technologies and SCRes dimensions, revealing their interplay through expert judgement and providing a temporal comparison of evolving priorities between 2023 and 2025. The findings further demonstrate that SCRes emerges through reciprocal interdependencies between digital technologies and multiple resilience dimensions rather than through isolated technological effects.
Open access
Supply Chain Resilience and Risk Management
Infrastructure Resilience and Vulnerability Analysis
To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This model is constructed within the context where consumers’ low-carbon preferences influence product demand, and a government carbon cap policy is implemented. By comparing decentralized and centralized equilibria, we verify that centralized collaboration achieves dual gains: higher carbon reduction levels and greater overall supply chain profits, which strengthens sustainability and resilience. To address efficiency losses from three types of information asymmetry, we propose a two-stage dynamic coordination mechanism adapted to evolving cooperation transparency. At the initial stage with opaque information, a bargaining-power-weighted profit-sharing contract is adopted, where negotiation weights are quantified by enterprise scale, resource control and industry influence. After data transparency improves, the system switches to a Nash bargaining framework supported by blockchain carbon data sharing to realize stable long-term collaboration. Numerical cases and sensitivity analysis demonstrate that manufacturer cost information asymmetry is the primary constraint on coordination efficiency. The proposed dynamic coordination scheme effectively mitigates systemic complexity, balancing economic benefits and carbon reduction targets. This study provides practical pathways for supply chain participants to navigate complex low-carbon environments and advance sustainable, resilient supply chain operation.
Under China's strategic commitment to peak carbon emissions by 2030 and achieve carbon neutrality by 2060 (the "Dual Carbon Goals"), renewable energy enterprises face unprecedented pressure to simultaneously expand capacity, reduce costs, enhance supply chain resilience, and minimize carbon footprints. This study systematically investigates supply chain synergy optimization for wind and solar power enterprises within the Dual Carbon policy framework. Employing a multi-method approach integrating literature review, system analysis, and a case study of LONGi Green Energy, this research identifies three core synergy barriers: geographic fragmentation and policy decoupling, carbon traceability credibility crises, and inherent conflicts among efficiency, decarbonization, and resilience objectives. A three-tier collaborative optimization framework is proposed, comprising: (1) an information synergy layer based on blockchain-enabled carbon data pools; (2) an operational synergy engine integrating multi-objective optimization models with dynamic carbon taxation and shared warehousing; and (3) a carbon synergy mechanism incorporating tiered supplier incentives and green transition funds. Empirical validation through the LONGi case demonstrates significant improvements: total supply chain costs reduced by 15.3%, lifecycle carbon emissions per watt decreased by 39.6%, and disruption recovery time shortened by 58.3%. This research contributes a "policy-geography-technology" three-dimensional synergy blockage theory, a tri-objective dynamic equilibrium model, and a responsibility-sharing carbon governance framework, offering both theoretical advancements and practical pathways for sustainable energy supply chain management. Keywords: Dual Carbon Goals, Renewable Energy, Supply Chain Synergy, Carbon Traceability, Supply Chain Resilience, Blockchain, Multi-Objective Optimization, Green Supply Chain.
Felipe Bastos dos Reis, Adriana Marotti de Mello, João Valsecchi Ribeiro de Souza
Industry 4.0 technologies are increasingly recognized as important contributors to the transition toward a circular economy, yet their association with circular business models (CBMs) remains poorly understood. This paper examines how Industry 4.0 technologies contribute to CBM implementation. Drawing on a systematic literature review of 34 papers and an analysis of 13 illustrative cases from the Circular X and Ellen MacArthur Foundation databases, the study maps the relationship between technologies, applications, and CBM patterns. The findings identify seven core technologies, Artificial Intelligence, Big Data, Cloud Computing, Internet of Things, Additive Manufacturing, Augmented Reality, and Blockchain, and 14 key applications linked to circular business models, such as data integration, predictive maintenance, smart energy management, and supply chain traceability. The results suggest that technology adoption alone is not necessarily associated with circular outcomes. Most applications correspond to efficiency-oriented strategies, particularly the reduction of material and energy consumption, indicating that current uses of Industry 4.0 in CBMs remain strongly oriented toward digital optimization. When technologies are not aligned with circular value propositions, efficiency gains may generate rebound effects, potentially increasing environmental impacts. This study advances the circular economy literature by providing a configurational perspective on the implementation of Industry 4.0 technologies within CBMs and by mapping how digital capabilities contribute to specific circular applications. Practically, the findings offer guidance for managers seeking to prioritize technology investments and move circular business strategies beyond operational efficiency toward circular transformation. Overall, the study contributes to a more comprehensive understanding of how the association between Industry 4.0 technologies and circular transformation, rather than digital optimization alone, appears stronger when their applications align with CBM patterns and circular value propositions.
Circular economy (CE) has become prevalent worldwide due to its economic and environmental benefits. More and more practitioners have deployed CE in supply chains to improve operational efficiency and sustainability. Thus, the integration of CE and supply chain has developed a new concept: circular supply chain (CSC). In particular, the CE model could remarkably reduce food waste within food supply chains (FSCs) and diminish the environmental impact from FSCs. Such a FSC that adopts CE principle is known as circular food supply chain (CFSC). However, lack of technical support for effective communication is a significant difficulty in developing CFSCs. Blockchain technology (BCT) could be the potential solution to this problem because of its decentralisation, public information sharing, high traceability and transparency, high security etc. Although many researchers have studied CFSCs in recent years, few studies investigate BCT as an impetus for CFSC development. Therefore, this research will fill this gap, focusing on the feasibility of BCT-based CFSCs, how BCT can establish CFSCs, and possible barriers. In addition, a few recommendations on developing BCT-based CFSCs will be provided.
This study investigates the theoretical foundations, practical applications, and optimization strategies of financial big data analysis and network security optimization in support of Sustainable Development Goals (SDGs). A comprehensive framework is developed to integrate sustainable financial management, environmental cost-benefit analysis, socially responsible investment decision-making, and sustainable supply chain management. The study further proposes a network security optimization architecture incorporating multi-level data encryption, access control, real-time threat monitoring, intelligent defense mechanisms, and blockchain-based data protection. The proposed framework is particularly applicable to communication-intensive environments, including wireless communication infrastructures and antenna-supported information transmission networks, where secure and reliable financial data exchange is essential. Experimental analyses demonstrate that the integration of financial big data technologies and network security mechanisms enhances data protection, operational efficiency, and sustainable decision-making capabilities. The results provide a practical reference for secure financial data governance and sustainable development in complex digital and communication-oriented systems.
C. N. He, H. D. Chen, H. J. Tian, J. Zhang · 5 authors
This study investigates low-carbon investment strategies in power supply chains under the combined influence of carbon quota mechanisms (CQM) and blockchain technology (BCT). A two-echelon system consisting of a power generator and an electricity retailer is modeled, and four decision scenarios are constructed by considering blockchain adoption under both the grandfathering method (GFM) and benchmarking method (BMM). A Stackelberg game framework is employed to analyze the interactions among low-carbon technology investment, low-carbon electricity promotion, market demand, and enterprise profitability. Results show that the BMM consistently induces higher low-carbon investment levels, stronger market demand, and greater retailer profitability than the GFM, regardless of blockchain adoption. Furthermore, blockchain-enabled information traceability exhibits a significant threshold effect: when implementation costs remain below a critical level, trusted information transmission enhances consumer green trust, stimulates demand for low-carbon electricity, and improves the economic performance of supply-chain participants. Sensitivity analysis further demonstrates that consumer green trust, low-carbon preference, and responsiveness to low-carbon promotion positively influence both emissionreduction efforts and enterprise profitability, whereas excessive blockchain deployment costs weaken these benefits. The proposed framework provides a quantitative methodology for analyzing information-enabled lowcarbon decision making and coordinated investment strategies in modern power systems.
Ms. Gunavarthani S, Dr. Princy J, Ms. Samyuktha S K
The textile industry has undergone a dramatic change in recent times because organizations are incorporating digital technology solutions for addressing issues related to sustainability and fast-tracking the journey toward a circular economy. These include Digital Product Passports (DPP), blockchain, Radio Frequency Identification (RFID), the Internet of Things (IoT), Artificial Intelligence (AI), and Industry 4.0 technologies, among others. The current research intends to conduct a systematic review of the literature on the topic of digital transformation and sustainability in the textile industry. A Systematic Literature Review (SLR) was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. In all, 55 peer-reviewed journals from 2020 to 2026 have been reviewed based on a structured selection process and analyzed using the thematic analysis approach. Six themes have been identified in the literature, which are as follows: Digital Product Passport, Digital Traceability Technologies, Industry 4.0 & Artificial Intelligence, Circular Economy Practices and Circular Supply Chains, Sustainability and Environmental, Social & Governance (ESG), and Barriers, Challenges and Future Research Directions. The results show that digital technology greatly improves the traceability of products, efficiency, and resource recycling, facilitating sustainability along the supply chain. Yet, issues such as costly digital technology implementation, inadequate digital infrastructure, the absence of standardization in digital data structures, and organizational readiness hinder digital technologies' broader application. This research fills a gap in the literature in that it identifies a consolidated thematic framework explaining the role of digital technologies in transforming the industry sustainably. The results provide insights useful for academic studies, industry professionals, and policymakers working on sustainable textile ecosystems powered by digital technology.
This study develops and validates an ecological economics framework integrating green logistics practices to enhance supply chain resilience in Southeast Asia's automotive sector. Using mixed-methods analysis of 272 firms across Thailand, Indonesia, and Malaysia, structural equation modelling confirms three hypotheses: green logistics adoption significantly predicts resilience (β=0.38, p<0.001); ecological economics tools (full-cost accounting, ecosystem service valuation) double these gains through heightened environmental cost awareness; and the hybrid framework yields superior economic returns compared to standalone practices. Thailand leads (SCR=65.3) due to BCG policies, while Indonesia lags (ROI=9.1%) amid nickel dependency. Simulations project +34% resilience under carbon pricing scenarios. Qualitative interviews reveal disaster-driven adoption and SME capex barriers, with ECA>4.0 thresholds flipping green logistics from cost to profit centre. Findings advance dynamic capabilities theory with biophysical limits, resolve triple bottom line tensions, and deliver managerial roadmaps (rail pilots→FCA training→blockchain Scope 3) plus ASEAN policy blueprints (CBAM harmonisation, $500M capacity fund). The framework positions the ASEAN automotive sector for regenerative leadership, converting natural capital from externality to competitive asset amid global decarbonisation pressures. These findings offer actionable insights for managers, investors, and policymakers seeking to align profitability with ecological resilience in emerging economies.
Open access
Supply Chain Resilience and Risk Management
Sustainable Supply Chain Management
Infrastructure Resilience and Vulnerability Analysis
Against the background of the global "dual carbon" goal and the EU Carbon Border Adjustment Mechanism (CBAM), targeting problems such as missing trust in emission reduction and insufficient technological collaboration in cross-border low-carbon supply chains, this paper incorporates blockchain technology, vertical spillover of emission reduction and consumer low-carbon preference into a unified analytical framework. It constructs a two-echelon cross-border supply chain model consisting of a single supplier and a single manufacturer, builds Stackelberg game models under centralized decision-making and decentralized decision-making respectively, comparatively analyzes the optimal emission reduction levels, pricing strategies and profit distributions under two scenarios with and without vertical spillover, and verifies the conclusions through numerical simulation. The research shows that the EU CBAM carbon tax, vertical spillover of emission reduction and consumer low-carbon preference form a positive synergistic incentive, which significantly lifts the supply chain's emission reduction level and overall profit, and the synergistic effect is more prominent under centralized decision-making. A rising emission reduction cost coefficient will restrain enterprises' investment in emission reduction, and vertical spillover will aggravate this restraining effect. Whether vertical spillover is considered or not, centralized decision-making outperforms decentralized decision-making in both emission reduction efficiency and total supply chain profit; the higher the carbon tax rate and vertical spillover rate, the wider the gap between the two. This paper further puts forward management insights from the aspects of enterprise technology sharing, decision-making mode selection and government policy guidance, so as to provide theoretical reference and decision support for cross-border supply chains to respond to CBAM regulations and realize low-carbon transformation.
This study investigates the multidimensional impacts of the Industry 5.0 paradigm on logistics and supply chain management, focusing primarily on human-centric digitalization and sustainability dynamics. Within this scope, aspects of operational efficiency, resilience, and financial performance are analysed as complementary dimensions within the thematic synthesis. Emphasising human-centric digitalization, it examines how the integration of advanced technologies with social responsibility principles reshapes supply chain strategies, fosters organisational transformation, and creates competitive advantages in the context of sustainable development. Following the PRISMA protocol, and using the Web of Science Core Collection as the primary database, a systematic literature review of 47 peer-reviewed studies was conducted, mapping thematic linkages among digitalization, resilience, financial outcomes, and sustainability. The synthesis identifies a conceptual framework that positions human–machine collaboration as a central enabler for sustainable transformation, enhancing decision-making, adaptability, energy efficiency, carbon footprint reduction, green innovation, and financial outcomes. Findings highlight interconnected pathways through which digitalization generates both operational gains and long-term strategic resilience. This study contributes an original analytical lens that unites human-centric digitalization, sustainability, resilience, and financial performance within a single framework, offering actionable insights for aligning technological innovation with sustainable supply chain strategies. In particular, the study points to practical pathways such as the use of digital twins for resource optimisation, blockchain for supply chain transparency, and AI-driven solutions for emission reduction.
Shahreza Shauqi Ismail, Nura Abubakar Allumi, Yousif Munadhil Ibrahim
Purpose: The aim of this study is to analyze the evolution of research trends in green supply chain management (GSCM) in agriculture, constructing an intellectual framework to improve the efficiency and environmental sustainability of the supply chain with smart agricultural technologies. Design/methodology/approach: The review used the bibliometric approach with two science mapping approaches (i.e., co-citation and co-word analysis) were perfomed to analyze 381 articles published in the Web of Science (WoS) database to investigate past and future research direction in GSCM using the VOSviewer software. Findings: Previous studies mainly focused on CE integration, sustainable agri-food supply chain design, and blockchain in supply chain management, whereas future research is expected to emphasize green logistics, low-carbon supply chains, smart circular systems, and digital innovation in green agri-SCM. Limitations and Research implications: This study is limited to the WoS database and two bibliometric techniques. Future research should validate the identified themes through additional bibliometric and empirical studies. Practical Implications: This study provides practical insights for managers, policymakers, and researchers to support the development of sustainable agricultural supply chains through circular economy, green logistics, and digital technologies. Originality/value: This study provides a comprehensive knowledge map of GSCM in agriculture by identifying past research themes and future research directions through bibliometric analysis
The accelerating adoption of Electric Vehicles (EVs) has intensified the need for efficient and sustainable life-cycle management of Lithium-Ion Batteries (LIBs). However, the complexity of battery supply chains, data fragmentation, and varying technological characteristics among distributed ledger platforms create significant uncertainty in selecting an appropriate infrastructure for implementing Digital Battery Passports (DBP). This study proposes a structured decision-support model to evaluate and differentiate among Distributed Ledger Technologies (DLT) under an uncertain decision environment. The proposed framework integrates the plithogenic set theory to capture expert uncertainty and inconsistency, the Best–Worst Method (BWM) to determine the relative importance of evaluation criteria, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank alternative platforms. The model is applied to assess eight leading DLT platforms for DBP implementation in the automotive context. The results indicate that Hedera is the most suitable platform, achieving the highest TOPSIS closeness coefficient (0.8223), followed by IOTA and EOS. The findings confirm that incorporating contradiction-aware uncertainty modeling into a hybrid MCDM framework enhances the robustness and transparency of DLT platform selection for DBP-oriented applications.
Rouwaida Abdallah, Guillermo Toyos Marfurt, Sara Tucci-Piergiovanni
This work has been accepted for publication in the proceedings of 3SCEA 2026 conference. The deposited manuscript corresponds to the author-accepted version presented at the conference. The final published version will appear in the official conference proceedings. Abstract: Traceability remains a critical challenge in modern supply chains, particularly as industries transition towards sustainability and circular economy models. The Digital Product Passport (DPP) emerges as a vital tool to consolidate and share comprehensive product information across its lifecycle. In this paper, we propose a decentralized, customizable, and self-deployable DPP system, leveraging blockchain technology and an extension of the Fractional Non-Fungible Token (F-NFT) model. This approach enables fine-grained traceability of individual product components and events across the supply chain, ensuring transparency and verifiability. A key strength of our system lies in its flexibility, enabling businesses to deploy tailored solutions without reliance on centralized service providers. The proposed system empowers stakeholders with greater control over product data while supporting selective information sharing. We present a functional implementation of the system and discuss the crucial design decisions that support its real-world applicability.
Tomi Setiawan, Muhammad Farras Samith, Muhammad Hammam Mughits, Aulia Fitrah Uswatun Hasanah · 5 authors
This study synthesizes Web3-based governance strategies in closed supply chains for electric vehicle batteries in Indonesia, focusing on reducing environmental impacts and improving resource efficiency. It includes a theoretical framework and case studies to address the overall issues in empirical validation and contextual adaptation. This paper aims to expand the governance framework, compare digital product passport implementations, identify incentive mechanisms including CSR integration, quantify regulatory models, and analyze practical case studies. An integrated analysis of multidisciplinary literature, using theoretical modeling, game theory, and empirical case studies, reveals that blockchain-based digital product passports improve transparency and lifecycle traceability but face challenges in large-scale implementation and data standardization. Incentive mechanisms based on game-theoretic frameworks and CSR promote resource efficiency, although empirical evidence in Indonesia remains limited and its social dimensions remain underexplored. A comparative regulatory analysis highlights the relevance of EU policies as a benchmark while also highlighting regulatory gaps and enforcement challenges in Indonesia. The case studies demonstrate the feasibility of Web3 technologies in improving environmental outcomes and operational efficiency, but scalability and stakeholder coordination require further investigation. These findings highlight the need for an integrated, multi-stakeholder governance model that bridges theoretical innovation with practical implementation in Indonesia's unique socio-regulatory context. This study informs future research and policy development to optimize sustainable battery supply chains through digital governance and circular-economy principles.
This study aimed to examine the role of blockchain technology in transforming digital marketing within the emerging Web3 environment, with a specific focus on its impact on consumer trust and marketing efficiency. The research primarily investigated the relationship between blockchain technology as the independent variable and digital marketing transformation as the dependent variable, while also considering consumer trust and marketing efficiency as key outcome variables. A quantitative research design was adopted, and data were collected from 250 respondents, including digital platform users and marketing professionals, using a structured questionnaire based on a 5-point Likert scale. Statistical analyses, including reliability, correlation, and regression, were conducted to test the proposed hypotheses and evaluate the relationships among variables. The findings revealed that blockchain technology had a significant positive impact on digital marketing transformation (β = 0.68, p < 0.001) and consumer trust (β = 0.72, p < 0.001). Digital marketing transformation significantly influenced marketing efficiency (β = 0.70, p < 0.001). The results also indicated that consumer trust played a mediating role in enhancing marketing efficiency, highlighting the importance of transparency and data security in digital environments. The study provides practical implications for organizations by emphasizing the adoption of blockchain-based marketing systems to improve transparency, reduce operational inefficiencies, and strengthen consumer trust. It also highlights the strategic importance of decentralized platforms in shaping the future of digital marketing. References Basal, M., & Şarkbay, Ö. F. (2026). Web3-driven digital marketing and consumer protection. 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Effective demand forecasting is crucial for reducing food waste. However, data privacy concerns often hinder collaboration among retailers, limiting the potential for improved predictive accuracy. In this study, we explore the application of Federated Learning (FL) in Sustainable Supply Chain Management (SSCM), with a focus on the grocery retail sector dealing with perishable goods. We develop a baseline predictive model for demand forecasting and waste assessment in an isolated retailer scenario. Subsequently, we introduce a Blockchain-based FL model, trained collaboratively across multiple retailers without direct data sharing. Our preliminary results show that FL models have performance almost equivalent to the ideal setting in which parties share data with each other, and are notably superior to models built by individual parties without sharing data, cutting waste and boosting efficiency.
The construction industry is a major global consumer of energy and a leading source of greenhouse gas emissions, underscoring the need for transparent, data-driven, and energy-efficient supply chain strategies. This study develops an integrated mixed-integer linear programming (MILP) model for a multi-echelon, multi-product construction supply chain that explicitly incorporates differentiated building energy efficiency levels ( A +, A ++, A +++) as exogenous determinants of material requirements, production processes, and logistics flows. By embedding blockchain-enabled smart contracts, the model automates supplier governance and ensures compliance with delivery reliability, quality standards, and CO 2 performance through predefined incentives and penalties, thereby enhancing transparency and accountability. The framework jointly optimizes facility location, material and product flows, supplier selection, and reverse logistics operations under a CO₂ emission cap, while simultaneously capturing the implications of greenfield and brownfield project conditions. A real-scale numerical case study demonstrates the model’s ability to evaluate the economic–environmental trade-offs arising from increasingly stringent sustainability requirements. The results reveal that although higher energy efficiency levels incur greater initial supply chain costs due to advanced materials and more complex logistics, they lead to substantial reductions in long-term operational energy consumption, rendering the A +++ option the most economically favorable from a lifecycle perspective. Furthermore, the integration of blockchain-enabled smart contracts partially offsets cost escalations by penalizing non-compliant suppliers and rewarding high-performing ones. Overall, the proposed model provides a rigorous and transparent decision-support framework that enables contractors to align supply chain design with energy-efficiency targets, CO 2 -reduction policies, and circular-economy objectives while preserving operational feasibility and supply reliability.
Christian Finke, Tamino Marahrens, Matthias Schümann
As supply chains (SCs) face increasing pressure from ecological demands, ethical expectations, and global disruptions, Distributed Ledger Technology (DLT) is gaining attention as a potential enabler of transparent, secure, and automated processes, helping to meet the expectations of customers and regulatory authorities. Nevertheless, the lack of generally valid design recommendations hinders its implementation. Therefore, we adopted grounded theory principles within a design science research approach to address this gap. Subsequently, we derived 11 overarching expert insights for developing a DLT operating model in SCs and 15 for its implementation by conducting 16 expert interviews. These insights were finally used to extract 19 generally valid design recommendations for applying DLT in SC processes that contribute to practical implementations and the framing of realistic adoption expectations by guiding researchers and practitioners.
The Digital Product Passport (DPP) is a cross-sectoral framework for sharing data across value chains to promote circular economy practices such as repair, reuse, and recycling. A key challenge is ensuring trust and integrity in DPP data, which is often fragmented among multiple stakeholders. Distributed ledger technologies (DLTs) ofer a promising solution by enhancing data integrity, transparency, and reliability. However, a comprehensive understanding of how DLTs can support DPPs remains underexplored. This paper reviews academic and industrial initiatives using DLTs to build trustworthy DPP infrastructures. It identifies three core benefits of DLTs for DPPs: (1) tamper-proof data integrity for traceability, (2) peer-to-peer private data sharing without central authority, and (3) decentralized DPP lifecycle management, from creation to deactivation. Based on these findings, the paper proposes design guidelines to inform the development of DLT-based DPP systems that can support long-term trust and collaboration in circular economy ecosystems.
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.
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.