Industry 5.0 emphasises human-centric technologies (HCTs) as essential drivers of sustainable and resilient production. However, their specific contributions to Circular Economy (CE) strategies and the associated skill requirements are not well-defined. This paper investigates how HCTs support Circular Economy practices (CEPs) and which skills and competencies are needed for their effective implementation. A systematic literature review was conducted using Scopus and Web of Science, following established guidelines. The search employed a string that links Industry 5.0, human-centricity, and the 10 R framework of CE. After a multi-stage screening and snowballing process, 41 peer-reviewed contributions published between 2015 and 2025 were selected for analysis through a combination of bibliometric and qualitative content analysis. The review maps the main HCTs, such as AI, digital twin, XR, robotics, blockchain, and IoT, to CEPs and specific 10 R strategies. It identifies seven clusters of skills ranging from analytical and decision-making abilities to human-machine collaboration, CE-specific expertise, and green human resource management practices. A Sankey diagram visualises the primary linkages between technology and strategy. Then, the authors developed a framework (TSC framework) that links skill clusters, CE practices, and enabling technologies and validated it through an illustrative case study. Interpreting the findings through the Resource-Based View, the paper argues that value arises from socio-technical bundles that integrate technologies, circular practices, and human capabilities. The study concludes with implications for policymakers, educators, and practitioners and outlines potential avenues for future research on skills for human-centred circularity.
The rapid advancement of Large Language Models (LLMs) has established autonomous agents as the core vehicles for artificial intelligence applications. However, existing Internet infrastructures, primarily relying on TCP/IP and DNS, are designed for human-centric, host-to-host data transmission, inherently lacking the semantic awareness, dynamic capability discovery, and decentralized trust mechanisms required for autonomous agent interactions. To address these limitations and break the closed ecosystems of single vendors, this paper proposes AONA (Agentic Overlay Network Architecture), a novel overlay network architecture for the Internet of Agents (IoA). We first provide a multi-disciplinary scientific defense for multi-agent collaboration, demonstrating its theoretical necessity over single super-intelligence through the lenses of organizational economics, scaling principles, and the Price of Anarchy. AONA is then structured as a four-layer logical blueprint comprising the Base, Interconnection, Collaboration, and Application layers, which facilitates cross-protocol and cross-platform interoperability without disrupting the underlying physical network. To physically instantiate this blueprint, we design a distributed node infrastructure anchored by Management Root Nodes, Registry Service Nodes, Discovery Service Nodes, and Enterprise Intelligent Service Hubs for private domain integration. Finally, we detail the dynamic operational workflows-including zero-trust identity issuance, globally coordinated semantic taxonomy synchronization, intent-driven semantic discovery, and trusted metering for commercial settlement-that drive the network. This comprehensive architecture provides a robust, scalable, and secure foundation for the future of global agentic collaboration.
Decentralized Autonomous Organizations (DAOs) are an emerging development at the intersection of organizational governance and blockchain-based technology. DAOs are transparent, participant-driven systems that operate without central authority. This study addresses the lack of a unified understanding of DAO architecture and governance in existing research. It presents a structured five-layer framework integrating governance, technology, and operational components. The goal of DAOs is to build autonomous, community-driven organizations on blockchain platforms controlled by smart contracts. By using code rather than conventional authority to ensure trust, these contracts automatically execute predefined rules, eliminating the need for intermediaries. These virtual organizations operate without a central authority and are governed through participant agreement and smart contracts. They use digital tokens to allocate resources and support decision-making. By promoting open and autonomous systems, DAOs have gained attention for their potential to transform multiple sectors. This article examines the benefits of DAOs over traditional organizations, evaluates existing approaches, and presents key concepts, components, and characteristics. This study also emphasizes the growing importance of decentralized governance in modern digital ecosystems.
Este artigo apresenta um esboço estruturado sobre “Migração de Lógica de Negócio para Layer‑2: Desafios de Compatibilidade.”. O objetivo é analisar os fundamentos técnicos e econômicos relacionados à migração de contratos e aplicações da camada base (L1) para soluções de escalabilidade em Layer‑2, discutindo implicações para o ecossistema Web3 e tendências de mercado. A metodologia baseia‑se em revisão bibliográfica e análise de casos práticos, com foco em diferenças entre soluções L2 EVM‑equivalentes e apenas EVM‑compatíveis, modelos de segurança de bridges, padrões de liquidez multi‑chain e impactos em tooling, UX e governança. Argumenta‑se que a migração não é apenas um “lift‑and‑shift” de bytecode, mas um processo que envolve reavaliação de suposições de segurança, dependências de infraestrutura (oráculos, indexadores, sequencers) e design de incentivos em ambientes com finalização e custos distintos da L1. Casos práticos de migração de protocolos de DeFi e indexação evidenciam trade‑offs entre custo por transação, fragmentação de liquidez e complexidade operacional, bem como a importância de padrões de bridging, mensageria cross‑chain e governança multi‑domínio para manter coerência de lógica e de risco entre instâncias L1/L2. Conclui‑se que migrar lógica de negócio para Layer‑2 exige abordagem incremental e consciente de compatibilidade, com atenção especial à equivalência de EVM, à segurança de rollups e bridges, e à coordenação de liquidez e governança em um ecossistema crescentemente modular e multi‑chain.<br>
This study seeks to fill a gap in the understanding of how blockchain smart contracts may improve logistics service quality and investigate the drivers of blockchain smart contracts.Semistructured interviews were carried out with ten logistics professionals to collect data.According to the findings, the drivers of using blockchain smart contracts in the logistics industry comprised the strongest predictor amongst security, traceability, decentralization, transparency, efficient information sharing, and automation factors.The identified drivers of blockchain smart contracts could be used by logistics practitioners as a "road map" for the development of appropriate solutions to successfully strengthen logistics service quality within the logistics industry.The results indicate that blockchain smart contracts enhance payment transaction security, increase end-to-end visibility, and improve delivery timeliness.Moreover, this technology optimizes routing, advances fleet management, and reduces logistics costs.The existing literature focuses on the approaches to applying theoretical, technical, or operational benefits of blockchain smart contracts, but fails to propose a deep dive into logistics service quality.This research appraises blockchain smart contracts by assessing and suggesting how they can enhance logistics service quality.
The rapid expansion of enterprise-scale data ecosystems and AI-driven services has created an urgent need for autonomous governance mechanisms capable of operating across distributed, dynamic, and heterogeneous environments, where traditional centralized control models increasingly fail to provide the scalability, adaptability, and real-time compliance required by modern enterprises. In response to these limitations, this paper introduces the concept of Multi-Agent Autonomous Governance Networks (MAAGN), a novel architectural paradigm that leverages advances in multi-agent systems (MAS), policy-driven governance, and self-adaptive computing to enable truly self-regulating AI ecosystems. MAAGN is designed to distribute governance responsibilities across intelligent, cooperative agents that operate with contextual awareness, enabling localized decision-making while maintaining global policy alignment. By integrating cognitive agent models capable of perception, reasoning, and learning with layered governance frameworks that enforce regulatory, organizational, and operational constraints, the architecture supports continuous compliance and dynamic policy evolution. Furthermore, the incorporation of enterprise-scale coordination mechanisms such as decentralized consensus protocols, adaptive orchestration layers, and feedback-driven control loops ensures system-wide resilience and fault tolerance even in highly volatile environments. The study synthesizes foundational theories in MAS, contemporary developments in multi-agent reinforcement learning, and emerging governance-aware AI frameworks to propose a scalable, extensible, and future-ready model for enterprise AI control systems, positioning MAAGN as a critical enabler for trustworthy, transparent, and autonomous digital infrastructures.
Dec 23, 2025·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Oliver Alexy, Oliver Baumann, Ying-Ying Hsieh, Giorgia Sampó
Decentralized Autonomous Organizations (DAOs) represent a radical form of socio-technical systems, where rules are enforced by code and governance is conducted by a distributed network of stakeholders. A critical challenge in designing these systems is achieving consensus without centralized authority, yet how consensus ensures effective governance remains underexplored. This study investigates the design of DAO governance systems, utilizing data from 70 DAOs and applying Fuzzy Set Qualitative Comparative Analysis (fsQCA) to explore which consensus configurations lead to positive organizational outcomes. Our analysis challenges the notion of a single consensus model. Instead, we uncover 13 distinct configurations that characterize successful DAOs. Our key finding reveals a fundamental “ideation-legitimation trade-off”: successful DAOs optimize for broad participation in either the proposal (ideation) stage or the voting (legitimation) stage, but rarely both. These insights provide a nuanced framework for understanding and designing effective governance systems for DAOs.
Demand volatility, logistical interruptions, and linked worldwide networks define the remarkable complexity of modern supply chains. Classic centralized management solutions find difficulty in offering real-time solutions to changing operational problems. For designing distributed, intelligent, and self-organizing supply chain ecosystems, artificial intelligence agents combined with Model-Control-View (MCV) architectures provide transformational possibilities. These autonomous computational entities span three functional layers: view interfaces enable monitoring and interaction, control mechanisms govern decision-making and optimization, and model components represent digital twins of supply chain entities. Multi-agent coordination enables decentralized yet coherent operations through the negotiation and collaboration of agents representing suppliers, production, logistics, and retail, all of which adhere to standardized protocols. Applications include demand forecasting, intelligent logistics, stock optimization, supplier partnering, and flexible disruption response. While reducing reliance on centralized control systems, the framework enhances resilience, scalability, openness, and operational efficiency. Challenges in implementation include organizational adaptation needs, cybersecurity vulnerabilities, and data integration complexity. Future advances in autonomous and cooperative supply chain systems will include explainable artificial intelligence, quantum-enhanced optimization, edge computing powers, and blockchain-enabled trust mechanisms.
Sharmila Mary Joseph, Baseera A, Mayank Sharma, Prajal Mishra · 6 authors
This study presents an innovative framework integrating machine learning algorithms to enhance the operational efficacy of blockchain-based decentralized autonomous organizations (DAOs). By leveraging reinforcement learning, deep Q-networks, natural language processing (NLP), and genetic algorithms, the framework addresses core challenges in governance automation, decision optimization, and adaptive resource management within DAOs. The proposed method demonstrates superior performance across critical metrics such as accuracy, scalability, convergence speed, and energy efficiency. Additionally, domain-specific visualizations, such as real-time Q-value convergence and NLP-enhanced proposal analysis, are introduced to ensure interpretability and transparency. This multidisciplinary approach not only overcomes inherent limitations in traditional DAO structures but also introduces a scalable, intelligent, and fair governance model capable of dynamic adaptation in decentralized environments.
The rapid advancement of artificial intelligence (AI) has begun to challenge traditional assumptions of corporate organization, governance, and commerce. While AI is widely recognized as a tool for enhancing decision-making and operational efficiency, an emerging possibility lies in the concept of AI corporations—autonomous economic entities capable of engaging in trade, investment, and contractual relationships without direct human intervention. This paper explores the rise of AI corporations and their potential to redefine global commerce through autonomous economic agents. The study adopts a descriptive and analytical framework, drawing on secondary data, global case studies of decentralized autonomous organizations (DAOs), AI-driven financial institutions, and blockchain-enabled smart contracts. Findings suggest that AI corporations could significantly reduce transaction costs, enable borderless 24/7 trade, and enhance economic efficiency while simultaneously raising profound challenges concerning legal identity, accountability, taxation, and regulatory oversight. Unlike traditional corporations that rely on human managers and shareholders, AI corporations operate on algorithmic autonomy, raising questions about liability, ethical conduct, and governance in the absence of human decision-makers. The implications are both economic and policy-oriented: while the integration of AI corporations could accelerate global trade and investment, unchecked autonomy could lead to monopolistic control, systemic risks, and destabilization of labor markets. The paper argues for the urgent development of international regulatory frameworks, AI-specific corporate laws, and hybrid human–AI governance models to harness the opportunities while mitigating risks. By positioning AI corporations as the next stage in the evolution of commerce—from traditional enterprises to digital platforms and now autonomous entities—this study contributes to the discourse on the future of global business, law, and economic systems.
Abstract Agile fosters speed, autonomy, and innovation at the team level, but organizations often struggle to preserve these strengths as they scale. Coordination overhead increases, decision-making slows, and the agility that once fueled success begins to erode. This paper introduces an approach to scaling by drawing on Robotics Subsumption Architecture , a model originally developed to build adaptive, autonomous robots. Building on the late Mike Beedle ’s pioneering work in applying these robotics principles to organization design , we reimagine how to design systems that grow without sacrificing local autonomy or real-time responsiveness. This approach offers scalable agility by embedding sensing, decision-making, and action into every layer—resulting in organizations that are resilient, decentralized, and capable of surviving today’s VUCA market.
The relevance of this article lies in the existence of over 13,000 decentralized autonomous organizations worldwide, with a total capitalization exceeding 23 billion USD. Numerous projects exploit this form to circumvent regulatory frameworks. At both the international and Ukrainian levels, a coherent understanding of the phenomenon of decentralized autonomous organizations, their objectives, genesis, and legal nature remains absent. The purpose of this article is to explore the genesis and legal nature of decentralized autonomous organizations – from the inception of the technical idea to their transformation into sui generis legal entities. Applying comparative and formal legal methods to examine the development of the legal understanding of these organizations, and employing case study methodology to assess their implementation in practice, the article investigates the main stages of the formation of the modern concept of decentralized autonomous organizations, their differentiation from adjacent constructs – decentralized applications, autonomous agents, and decentralized organizations – by highlighting criteria of autonomy and decentralization, along with case studies from Bitcoin to The DAO. On the basis of a comparative legal analysis of regulatory models in the United States, Europe, and offshore jurisdictions, a conceptual mismatch is identified between classical corporate forms and the ontology of decentralized autonomous organizations. A two-component qualification test is proposed, alongside a typology dividing them into genuine, hybrid, and quasi forms. The findings of the study, together with the identification of practical challenges faced by such projects, substantiate the possibility of recognizing decentralized autonomous organizations as legal persons under Ukrainian law by means of the doctrinal construct of the “personalized purpose” (Zweckvermögen) developed by A. von Brinz, potentially implemented in the form of a foundation. This approach permits the integration of algorithmic will with legal personality without undermining their decentralized nature. The article provides a foundation for further inquiries into specific legal characteristics of decentralized autonomous organizations, including the “sorites paradox” and the prospects for legislative regulation within the Ukrainian legal order based on the doctrine of personalized purpose.
Nidhi Singh, Usama Awan, Sarah Basahel, Rsha Alghafes
This study addresses a gap in the current research by investigating the relationship between BC based financial solutions and SC recoverability and financial resilience. Previous research provides little empirical evidence on how and under what conditions Fintech improves the manufacturing firm's financial resilience. This empirical research draws on the resource base view (RBV) to investigate the role of Fintech as a driver of better relationship transparency and SC production risk management for financial resilience. The data was collected from 295 engineering manufacturers in India. A key contribution of this study is that it provides new insights by highlighting the role of Blockchain Technology (BCT), built on the Ethereum-based system, in strengthening SC recoverability and enhancing relationship transparency. We present a research framework grounded in the Resource-Based View (RBV) that illustrates how blockchain technology (BCT) can provide firms with critical competencies for developing relationship transparency and managing production risks, thereby enhancing financial resilience in the SC. Relationship transparency, essential for SC recoverability, is pivotal in establishing the link between BCT and SC recoverability. Our findings advise SC managers that relationship transparency improves SC recoverability and may be an important source of financial resilience.
Distributed ledger technologies (DLT) have been piloted in enterprises to improve transparency and trust relationships among multiple partners but have not managed to mature as planned. Even though most implementation projects demonstrate various opportunities for the involved partners, enterprises experience difficulties in assessing the technology’s impact on profitability in order to make valid investment decisions and improve productivity. This paper employs the dynamic capabilities theory to explore how enterprises can adapt and leverage DLT for improved profitability. It presents an applicable profitability assessment model and a collection of quantitative profitability factors of DLT in enterprise networks. The framework and its associated models are developed through an inductive Grounded Theory-based approach, composed of literature reviews and qualitative empirical studies from 40 participating mixed-industry blockchain, tangle, and hashgraph experts. To retrieve profitability factors in a structured manner, the framework features an integration model covering necessary assessment steps; a taxonomy and heat map characterizing the maturity and assessment situation of the DLT; as well as an assessment model to identify and monetize profitability factors.
Blockchain technology establishes trust among participants through technical means. However, some malicious nodes may compromise this trust through short-range reorganization attacks for their interest. This paper develops an agent-based model to systematically analyze Proof-of-Stake short-range reorganization attacks, where three types of agents interact through distributed consensus mechanisms with ex-ante, fine-grained, and ex-post reorganization attack strategies. Through rigorous simulation of agent decision-making dynamics, we identify that: (1) Compared with ex-ante reorganization, the ratio of malicious nodes required for ex-post reorganization is much larger. (2) Increasing the node number increases the difficulty of ex-ante and ex-post reorganization. (3) The number of nodes affects ex-post reorganization attacks more significantly than ex-ante attacks. (4) Fine-grained reorganization significantly reduces attack difficulty
The rapid expansion of digital twin (DT) applications in industrial settings has created a pressing need for robust interoperability solutions, particularly for blockchainsupported DT teams operating across heterogeneous platforms. Current blockchain frameworks struggle with seamless data exchange and operational efficiency due to interoperability limitations. In this study, we introduce an innovative cross-chain framework that leverages a relay-chain mechanism and dynamic non-fungible tokens (NFTs) to overcome these challenges. Through experimental validation on Ethereum and Hyperledger Fabric, we demonstrate the framework's effectiveness in ensuring scalability, security, and cost efficiency. The evaluation reveals minimal network latency for cross-chain transactions with a negligible impact on overall throughput. The comparative analysis further highlights the advantages of our approach over existing cross-chain solutions, offering enhanced interoperability while maintaining low deployment costs. By addressing key barriers to blockchain deployment, this work provides a practical solution for improving cross-chain collaboration and advancing industrial DT integration. Future research will focus on refining relay-chain consensus mechanisms and extending support to private blockchains to enhance adoption in multi-stakeholder environments.
Denis Shakhov, Руслан Вахаевич Баташев, Ilyоs Abdullayev
This study investigates the transformative impact of artificial intelligence on corporate communications, focusing on AI-powered personalization systems in business environments. Through a systematic literature review (2019-2024), the research establishes an empirical framework for evaluating these systems’ technological infrastructure. The findings reveal distinct sector-specific performance variations: the retail sector showing 58% enhanced engagement metrics, while B2B segments demonstrated 28% improvement in key performance indicators. The technological foundation comprises machine learning algorithms, natural language processing frameworks, and high-performance computing systems enabling real-time personalization. The methodology integrates the adaptive personalization framework (APF) with the multidimensional personalization model (MPM) to elucidate machine learning mechanisms. This framework supports user profiling, navigation optimization, and behavioral pattern modification, secured through distributed ledger technologies. Empirical analysis reveals the complementarity between AI and human capabilities. While AI systems excel in response velocity (mean: 4.92), human interactions demonstrate superior responsiveness (5.27) and professional competency metrics (5.32 vs. 4.87), suggesting the optimality of a hybrid model. The study culminates in a conceptual framework balancing communication scalability with personalized relevance while adhering to ethical imperatives of data protection, algorithmic fairness, and transparency protocol.
Decentralized Autonomous Organizations (DAOs) are a type of Decentralized Applications (DApps) that utilize smart contracts to support governance processes. To achieve a high degree of utility of the system, stakeholders need to identify a suitable organizational structure in the early stages of design. While Model-Driven Development (MDD) methods are established for DApp and smart contract design, they lack specialization for modeling the organizational structures of DAOs. To address this gap, we propose a modeling language and a method which support crucial DAO design and development phases. The method is evaluated through an in vivo case study. Unlike existing solutions, comprehensive stepwise guidance is provided by our method for both technical and non-technical stakeholders involved in DAO development from the initial stages of the project.
The question of how Decentralized Autonomous Organization (DAOs) achieve benevolent and sustainable decentralized self-governance has always been a focal point of attention both domestically and internationally. Existing research primarily focuses on addressing this issue from a technological and legal perspective. To further address the problems and dilemmas faced by DAOs in the process of self-governance, this paper, from a cultural perspective, reveals the deep and enduring efficacy of culture in participating in DAO autonomy from three aspects: theoretical logic, goal logic, and soft logic. Culture will profoundly influence the benign and sustainable development of DAOs in three aspects: the production of spiritual and cultural products, the consolidation of cultural consensus, and the construction of mechanisms for cultural products to reach the public directly.