Blockchain Papers

Marc Hübschke, Marius Gros, Benedikt Latos, Elmar Holschbach · 5 authors

Purpose Blockchain technology is widely discussed as an enabler of transparency, efficiency and trust in supply chain management (SCM). However, empirical evidence on which blockchain-related success dimensions translate into value perceptions remains limited. This study aims to examine how the perceived relevance of blockchain success dimensions relates to realized benefits and whether these benefits contribute to overall perceived blockchain value. Design/methodology/approach A quantitative survey of 41 companies with blockchain experience in SCM is conducted. Success dimensions are prioritized using best–worst scaling (MaxDiff). Relationships between perceived relevance, dimension-specific benefits and overall perceived value are analyzed using partial least squares structural equation modeling (PLS-SEM). Exploratory analyses assess company characteristics. Findings Contrary to dominant expectations in academic and practitioner narratives, even highly prioritized blockchain success dimensions fail to translate into measurable firm-level value perceptions. While transparency and traceability are associated with significant dimension-specific benefits, these improvements do not produce statistically significant direct or indirect effects on overall perceived blockchain value. This suggests that localized operational gains alone may be insufficient to generate overall perceived value and indicates that blockchain benefits may depend on broader organizational and technological complements. Originality/value The study moves beyond identifying potential blockchain benefits by empirically differentiating which success dimensions matter and which do not. By combining MaxDiff with PLS-SEM, it offers a structured, mechanism-oriented framework for evaluating blockchain success and highlights boundary conditions for value realization in SCM.

Zhengguo Wang, Jingru Liu, Wenjuan Wang, Wenyu Zhao · 5 authors

With the standardization of the logistics market and advancements in innovation, trust issues arising from information asymmetry among supply chain participants have become increasingly prominent. This paper examines a blockchain-enabled collaborative regulatory system for logistics service supply chains involving the government, logistics enterprises, and the logistics market. Using evolutionary game theory, a three-party evolutionary game model is constructed and validated through system dynamics simulations to explore the impacts of various factors on the collaborative regulatory system. The results indicate that, during the system’s evolution, logistics enterprises stabilize first, followed by the government, with the logistics market converging the slowest. The added value of logistics services is identified as the core factor driving logistics enterprises to adopt blockchain, exhibiting a significantly stronger impact compared to regulatory benefits or improvements in quality and safety. While robust incentive policies can rapidly increase enterprises’ willingness to adopt blockchain technology, they concurrently weaken the government’s enthusiasm for regulation.

Zui Xu, Mei Sha, Dayong Yu, Shuang Li · 6 authors

Introduction Shippers may undeclare maritime dangerous goods as general cargo to avoid the preparation time, documentation burden, and freight premium associated with dangerous goods transportation, creating serious risks for vessel safety, port operations, and the marine environment. This paper examines whether blockchain-enabled documentation can mitigate such undeclaration by improving provenance information and shortening preparation and verification time in the dangerous goods channel. Methods We develop a game-theoretic model with one carrier and a continuum of heterogeneous shippers who differ in their marginal willingness to pay for service level, and in which the carrier endogenously sets the dangerous goods transportation price. We characterize the equilibrium declaration behavior under a benchmark scenario and under blockchain adoption, and extend the model to settings with carrier competition and enhanced detection. Results Undeclaration motives vary with the service environment: when dangerous goods service is relatively low, service-sensitive shippers undeclare to access the faster generalcargo channel; when service is sufficiently high, price-sensitive shippers undeclare to avoid the dangerous goods tariff. The carrier’s profit-maximizing price therefore does not generally coincide with the regulatory objective of zero undeclaration. Blockchain adoption introduces two opposing forces: a service-enhancement effect that encourages truthful declaration and a cost-escalation effect that raises the dangerous goods price. As a result, blockchain reduces undeclaration only when documentation-time savings dominate the price premium induced by adoption costs; when this condition fails, adoption may increase undeclaration and reduce compliant shipper surplus. Discussion Blockchain-enabled documentation is not a universal safety remedy. Its effect on undeclaration depends on the interaction between documentation-time savings and the adoption-driven price increase, and the extensions with carrier competition and enhanced detection show that blockchain deployment should be evaluated jointly with pricing, detection, competition, and regulatory policies.

Mo Zhang, Qianying Gu, Ruoqi Geng

Maritime supply chains (MSCs) are pivotal to the global economy yet face persistent challenges from external volatility, fragmented collaboration, and sustainability mandates. While consortium blockchain technology is heralded as a transformative solution, its adoption remains underexplored and lacks a holistic analytical framework. This study addresses this gap by conducting a systematic literature review of 81 studies to develop a comprehensive framework. The findings reveal that consortium blockchain adoption is not a binary event but a dynamic process shaped by the interplay of technological, organizational, and environmental factors. The analysis demonstrates that heterogeneous actors—governments, shipping lines, ports, and freight forwarders—assume distinct roles as drivers, pioneers, followers, or skeptics based on absorb capacity costs versus capture value within the emerging ecosystem. The successful transition from a technical platform to an operational system depends on a structured, multi-stage workflow encompassing identity authentication, smart contract collaboration, execution monitoring, and disintermediated payment settlement. Furthermore, this study identifies dual effects. While blockchain enhances efficiency, transparency, and sustainability, it simultaneously introduces power imbalances, systemic rigidity, and market concentration risks. By elucidating the strategic dynamics of adoption, operational implementation mechanisms, and paradoxical outcomes, this study provides a nuanced understanding of how consortium blockchain revolutionizes MSCs.

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.

Asabi Anthony Oluyemi

Abstract This study explores the transformative impact of artificial intelligence (AI) on enhancing demand forecasting and procurement efficiency within health commodity supply chains. It highlights the integration of advanced AI algorithms, including machine learning (ML), natural language processing (NLP) and optimisation techniques, which facilitate more accurate predictions, streamlined sourcing and improved inventory management. The analysis emphasises the essential interplay between technological innovation and ethical practices, underlining the importance of data privacy, transparency, fairness and accountability as foundational elements for trustworthy AI deployment in healthcare procurement. Implementation strategies take into account infrastructure requirements, change management and potential barriers to adoption. The investigation further examines organisational and workforce implications, scalability, sustainability and comparative experiences on both global and local scales, illustrating the complex challenges and opportunities presented by AI in health commodity procurement. Future directions suggest the convergence of AI with Internet of Things, blockchain and cloud computing, advocating for responsible innovation that adheres to ethical standards to optimise supply chain resilience, equity and operational performance in healthcare delivery.

Gulden Zhalbirova, Zhalgaskali Arystanov, Kateryna Zupanets, Zaru Kapassova · 6 authors

Background Scientific output on digital transformation in healthcare and pharmaceutical supply chains increased substantially after 2020, indicating growing research attention to resilient and digitally integrated logistics systems. However, the literature remains fragmented across technologies such as blockchain, artificial intelligence, Internet of Things, predictive analytics, cold chain monitoring and healthcare logistics optimization. Methods This study conducted a bibliometric analysis of scientific publications related to digital transformation and emerging technologies in healthcare and pharmaceutical supply chains. Data were retrieved from Scopus, PubMed and Web of Science databases following PRISMA 2020 screening principles. After duplicate removal and eligibility assessment, 83 peer-reviewed English-language journal articles published between 2015 and 2026 were included in the final analysis. Bibliometric mapping and thematic analysis were performed using VOSviewer and Bibliometrix/Biblioshiny. Results Within the analyzed corpus, the results showed a substantial increase in scientific publications after 2020, consistent with growing research attention to resilient and digitally integrated healthcare supply chains. Blockchain showed the highest visibility in keyword and citation-based analyses, particularly in relation to traceability, transparency and anti-counterfeit systems. Additional major research areas included artificial intelligence, predictive analytics, IoT-based cold chain monitoring and healthcare logistics optimization. Thematic analysis identified strong literature-based associations between digital technologies, supply chain resilience and pharmaceutical traceability systems. Conclusions Digital technologies are increasingly represented in research on healthcare and pharmaceutical supply chain transformation. The findings suggest that blockchain, AI and IoT technologies may support transparency, traceability and operational resilience. However, implementation barriers related to interoperability, infrastructure costs, data privacy and regulatory complexity remain significant challenges. These findings should be interpreted as bibliometric and thematic patterns within the analyzed English-language journal literature rather than direct evidence of technology implementation effectiveness.

Alifta Dicasani, Galih Mahardika Munandar, Muhammad Nur Wahyu Hidayah, Faradhina Azzahra

Post-disaster aid logistics is frequently affected by fragmented data, mismatches between needs and availability, distribution delays, and weak accountability. This study integrates a systematic literature review (SLR) and a proof-of-concept (PoC) to examine how blockchain can support data governance and aid traceability. Articles published in 2020-2025 were retrieved from ScienceDirect and Scopus, selected using PRISMA principles, and synthesized thematically from 31 eligible studies. The synthesis identified coordination and information alignment, along with traceability of goods, funds, beneficiaries, and delivery status, as the dominant issues. Frequently reported mechanisms included distributed ledgers, smart contracts, audit trails, cryptographic identities, and role verification. These findings were translated into a Solidity-based smart-contract PoC on a local Ganache network covering requests, stock, allocation, shipment, receipt validation, and event logs. Three synthetic scenarios and an access-control test showed that valid transactions were recorded, over-allocation was rejected, receipt discrepancies were flagged, and unauthorized operations were reverted. Blockchain is therefore better positioned as an infrastructure for data governance and transaction validation than as a standalone solution to all disaster-logistics problems.

Ugochukwu Damian Umeakubuike

Blockchain and distributed ledger technology (DLT) have been proposed for humanitarian operations because their shared-ledger characteristics may support transparency, traceability, accountability and coordination across organisations. This systematic evidence review synthesises research on operational benefits, adoption barriers, implementation conditions and evidence gaps in humanitarian supply chains. The evidence includes systematic reviews, empirical pilot research, expert-based barrier analysis, case-based design research and implementation-framework studies. Across the literature, the most consistently reported potential benefits are visibility, traceability, transparency, auditability, trust and inter-organisational information sharing. The empirical base is smaller than the conceptual literature, and barriers include regulatory uncertainty, skills and training, sustainability costs, privacy, infrastructure, scalability, interoperability and governance. The review proposes an eight-stage implementation pathway centred on problem diagnosis, technology justification, governance, privacy-aware architecture, piloting, capacity building, evaluation and controlled scaling. The framework is a synthesis proposed by the author from the reviewed evidence, rather than a tested causal model. The review concludes that blockchain should be selected conditionally, where multiple independent actors need a shared auditable record and where the expected coordination value justifies the additional technological and governance complexity.

Riktesh Srivastav

No abstract is available for this record.

Yassin Selouani, Ikram El Hachimi, Driss Ouslimane

Le management de la chaîne logistique connaît aujourd'hui de profondes mutations, dans lesquelles la transformation digitale s'impose comme un levier essentiel pour améliorer la traçabilité, renforcer la résilience et accroître la compétitivité des organisations. Si cette évolution est largement documentée dans les économies développées, les connaissances restent encore limitées en Afrique, où les contextes infrastructurels, institutionnels et socio-économiques présentent des spécificités importantes. Cette étude propose une revue systématique de la littérature afin de dresser un état des lieux des recherches consacrées à la transformation digitale des chaînes logistiques sur le continent. En suivant le protocole PRISMA, une recherche menée dans sept sources de recherche documentaire a permis de retenir 56 études parmi 742 références initialement recensées. Les résultats montrent un champ de recherche encore émergent, principalement centré sur l'Afrique du Sud, le Nigeria, le Ghana et le Kenya, ainsi que sur les secteurs agricole et pharmaceutique. La blockchain et l'Internet des objets dominent les travaux, tandis que l'intelligence artificielle et le big data demeurent encore peu mobilisés. Malgré une accélération de l'adoption sous l'effet de la pression concurrentielle et de la COVID-19, des obstacles persistants, telles que l’insuffisance des infrastructures, les coûts élevés, le déficit de compétences et la faiblesse des cadres réglementaires, limitent les bénéfices attendus. Cette étude fournit ainsi une synthèse structurée en langue française d’un corpus principalement anglophone et met en évidence plusieurs pistes pour la recherche et les politiques de digitalisation des chaînes logistiques africaines.

David Chikwere, Deborah Chikwere

Abstract The integration of Industry 4.0 technologies into supply chains (SCs) such as blockchain, artificial intelligence (AI), robotics, additive manufacturing and the Internet of Things (IoT), has transformed sustainability, operational efficiency and transparency. This enhances green supply chain management’s (GSCM) integrity and resilience which enable the achievement of sustainability objectives in line with the 2030 United Nations Sustainable Development Goals (UNSDGs) agenda. However, the accelerated digital adoption post-COVID-19 in developing countries came with increased SC vulnerabilities which undermine its integrity, resilience and sustainability goals. This study aims to determine the main SC cybersecurity risks and to recognise strategies that can be adopted to counter SC cybersecurity risks in developing countries. A search for literature was done in the Scopus, Google Scholar and ProQuest databases between 2018 and 2025 using a systematic literature review (SLR). The common SC cyber vulnerabilities findings were phishing incidents, breach of confidentiality, SC software attacks owing compromised open-source components and data theft. Consequently, this chapter proposed the use of monitoring and intrusion detection systems, collaborations for risk intelligence sharing, developing standardised cyber security protocols, use of firewalls and data encryption. These cybersecurity measures aim to equip SC managers and practitioners in developing countries with tools to protect data integrity and support sustainable Industry 4.0 operations by seamlessly integrating cybersecurity protocols with sustainability strategies, thereby enhancing resilience against digital disruptions. This chapter ends with proposing areas for further research and conclusion.

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.

Sharma V A, Shinde S M, Harle S M

The convergence of AI, Blockchain, IoT, Digital Twins, quantum computing, and FKF spectral methods constitutes a decisive research direction for next-generation logistics, especially when examined through the lens of Smart Mobility and Intelligent Transportation Systems [9]. Future work must prioritize real-time fusion of connected-vehicle and smart-infrastructure data streams, construction of scalable multi-resolution Digital Twin environments that span both supply chains and urban mobility networks, development of trustworthy AI models for predictive and prescriptive control, realization of practical hybrid quantum–classical optimizers for the combinatorial problems that dominate intelligent transportation and logistics, and computationally efficient multi-scale spectral analysis of complex temporal dynamics. Empirical validation across transportation, inventory, energy, and disruption scenarios incorporating advances in battery technologies [5], [10], solar-assisted and hybrid vehicle architectures [12], [28], and Industry 5.0 human-centric automation [27]will be indispensable. Realizing these advances will transform intelligent logistics from a conceptual integration into operational, sustainable, and resilient supply-chain systems that fully exploit the emerging capabilities of smart mobility ecosystems [1]–[28].

Sharma V A, Shinde S M, Harle S M

The content should be logically organized in a single paragraph, maintaining coherence and clarity throughout. Ensure that the abstract captures the research context, problem statement, approach, key results, and final conclusions in a balanced manner. It should provide enough detail to help readers quickly understand the scope and value of the study while encouraging them to read the full paper. The recommended length is between 150 and 250 words; however, it may extend up to 500 words if necessary to clearly communicate the research objectives, methods, findings, and significance. Keywords— Sustainable Logistics; Green Supply Chain Management; Artificial Intelligence; Smart Transportation; Digital Twins; Blockchain; Energy-Efficient Logistics; Quantum Computing; Supply Chain Resilience; FKF Analysis.

Sharma V A, Shinde S M, Harle S M

A convergent supply-chain architecture is proposed by integrating Digital Twins with Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), quantum computing, and FKF spectral analysis to address the growing complexity, uncertainty, and disruption risks in modern logistics. Digital Twins enable real-time virtual representation, simulation, monitoring, and disruption-response analysis, while AI extracts predictive and prescriptive intelligence from continuous IoT-generated data. Blockchain strengthens data integrity, transparency, security, and end-to-end traceability across supply-chain transactions. Quantum annealing supports computationally intensive logistics optimization problems, including routing, resource allocation, scheduling, and ULD configuration. FKF-based spectral features provide a mathematical representation of shifts, modulation effects, lead-time behavior, transient variations, and multiscale supply-chain dynamics. The integration of these complementary technologies enables information to flow from real-time sensing and trusted data management to spectral analysis, predictive intelligence, simulation, and advanced optimization. Together, the proposed architecture provides an adaptive, intelligent, sustainable, and resilient framework for monitoring supply-chain conditions, anticipating disruptions, evaluating alternative decisions, and improving overall logistics performance.

Shinde SM, Harle SM

This study introduces an FKF-enabled intelligent supply-chain framework that integrates Artificial Intelligence (AI), Blockchain, Internet of Things (IoT), Digital Twins, and quantum optimization into a unified architecture. The FKF transform provides a mathematical spectral representation of supply-chain signals, enabling the identification of temporal shifts, modulation effects, multiscale patterns, demand fluctuations, and lead-time dynamics. These spectral features can be supplied to AI and machine-learning models to improve forecasting, anomaly detection, disruption prediction, and resilience assessment. IoT devices continuously provide real-time operational data from transportation, inventory, production, and logistics processes, while Blockchain supports secure data sharing, traceability, and transaction transparency across supply-chain participants. Digital Twins complement these technologies by creating dynamic virtual representations of physical supply-chain systems, allowing alternative scenarios, disruptions, and recovery strategies to be simulated before implementation. Quantum annealing is incorporated to address selected computationally intensive combinatorial decisions, such as routing, scheduling, resource allocation, and logistics configuration. By connecting FKF-based mathematical spectral intelligence with AI-driven analytics, trusted digital infrastructure, simulation capabilities, and emerging quantum optimization, the proposed framework provides an integrated pathway toward more predictive, adaptive, transparent, sustainable, and resilient supply-chain management. The content should be logically organized in a single paragraph, maintaining coherence and clarity throughout. Ensure that the abstract captures the research context, problem statement, approach, key results, and final conclusions in a balanced manner. Keywords— Quantum Computing; Quantum Annealing; Logistics Optimization; Unit Load Device Configuration; Supply Chain Management; Artificial Intelligence; Digital Twins; Blockchain; Supply Chain Resilience; FKF Transform.

Kanade U V, Shinde S M, Harle S M

This study proposes a convergent framework integrating AI, Blockchain, IoT, Digital Twins, quantum computing, and FKF spectral analysis for sustainable and resilient supply chains. AI supports prediction and optimization, Blockchain improves transparency and traceability, IoT enables real-time sensing, and Digital Twins facilitate simulation and adaptive disruption management. Quantum annealing addresses selected combinatorial logistics problems, including ULD configuration, while FKF methods characterize temporal shifts, modulation, multiscale dynamics, and lead-time variations. The integration establishes a closed-loop architecture linking sensing, spectral analysis, intelligence, simulation, trust, and optimization for adaptive logistics decision-making.

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.

Jinde Jiang, Junding Yang, W Liu, Yingjing Gu · 6 authors

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.

Issam Qrunfleh, Russ Merz, Sufian Qrunfleh

Purpose This study systematically maps the intellectual structure and evolution of food supply chain research over three decades (1995–2026), identifying key themes, influential sources, and emerging trends to guide future research directions. Design/methodology/approach A comprehensive bibliometric analysis was conducted on 2,125 documents from 628 sources contributed by 6,903 authors. Four advanced bibliometric techniques were systematically employed: Bradford's Law analysis to identify core publication sources, keyword co-occurrence mapping to reveal thematic clusters, citation network analysis to determine influential works, and temporal trend examination to track research evolution. All analyses were performed using the R-based bibliometrix package (version 4.1.0), ensuring methodological transparency and reproducibility. Findings The analysis reveals a sustained 9.3% annual growth rate in publications and an average of 34.13 citations per document, confirming the field's scholarly impact. Two primary research clusters emerged: a sustainability-oriented cluster focusing on food waste, circular economy, and supply chain resilience; and a technology-oriented cluster emphasizing blockchain, traceability, and food safety. Temporal analysis demonstrates the emergence of digital technologies—particularly blockchain, artificial intelligence, and machine learning—after 2020, alongside heightened attention to COVID-19 impacts and supply chain resilience. Originality/value This is the first comprehensive bibliometric study spanning three decades of food supply chain research. The study makes three distinct contributions: it provides a systematic science map of the field's intellectual structure; generates empirical evidence for the convergence of technology and sustainability paradigms in food supply chain scholarship; and delivers a structured, evidence-based research agenda identifying specific gaps for future inquiry. These contributions offer researchers, practitioners, and policymakers a rigorous foundation for evidence-based decision-making in this critical domain.

Jiachang Yuan

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.

Shinde SM

This study proposes a unified framework integrating AI, Blockchain, IoT, Digital Twins, quantum computing, and FKF spectral analysis for sustainable, transparent, and resilient supply chains. AI enables prediction and optimization; Blockchain ensures trusted traceability; IoT provides real-time sensing; Digital Twins support simulation; and quantum annealing addresses complex logistics optimization. FKF analysis captures temporal shifts, modulation, multiscale dynamics, and lead-time variations for AI-based spectral intelligence. The resulting sensing–analysis–intelligence–simulation–optimization architecture provides an adaptive pathway for efficient and resilient next-generation logistics Keywords— Artificial Intelligence; Sustainable Logistics; Green Supply Chain; Blockchain; Digital Twins; Internet of Things; Quantum Computing; Quantum Annealing; FKF Transform; Supply Chain Resilience.