The article examines risk management as a strategic foundation for managing the economic activity of an enterprise under conditions of wartime instability, macroeconomic turbulence, and digital transformation. The relevance of the topic is driven by the growing level of environmental uncertainty, intensified competition, and the emergence of new digital and war-related risks that require the formation of an integrated system of strategic risk management. The purpose of the article is to substantiate the theoretical foundations and develop practical approaches to the formation of a risk management system as a strategic tool for managing the economic activity of an enterprise.The paper systematizes the main risk management instruments (risk acceptance, avoidance, transfer, and mitigation), identifies the structural elements of the risk management process, and proposes a model for organizing business processes within the framework of a risk management strategy. The concept of risk zones (risk-free, acceptable, critical, and catastrophic) is disclosed, enabling the assessment of risk concentration levels and ensuring timely adjustments of managerial decisions.Special attention is paid to digital risks arising from the implementation of cross-cutting digital technologies, including artificial intelligence, big data, robotics, and distributed ledger systems. The authors propose an original classification of digital transformation risks at the enterprise level, distinguishing economic, technical, organizational, and war-related risks, as well as identifying key risks associated with the use of artificial intelligence technologies (data privacy risk, infrastructure risk, statistical discrimination risk, incorrect managerial decision-making risk, workforce imbalance risk, etc.). The necessity of integrating digital risks into the corporate risk management system (ERM) is substantiated.The article also considers modern strategic approaches to risk management, including the “three lines of defense” model, the method of defining risk appetite and risk tolerance, and the development of risk culture and effective communication. It is proved that their integrated application creates a holistic risk management architecture aimed at preventive response, balancing profitability and sustainability, and enhancing the economic security of the enterprise. It is concluded that under modern conditions, risk management acts not only as a mechanism for minimizing threats but also as a strategic concept for ensuring long-term stability, innovative development, and competitiveness of an enterprise in the context of the digital economy and wartime challenges.
Martin Brennecke, Simon Mertel, Tobias Guggenberger, Johannes Sedlmeir · 6 authors
Zusammenfassung Auf dem Weg zu einer kreislauffähigen Wertschöpfung nimmt die lückenlose Dokumentation von Produktionsketten eine elementare Rolle ein: Sie erlaubt es, eingesetzte Ressourcen und Schritte im Wertschöpfungsprozess nachzuvollziehen und nachhaltigkeitsbezogene Angaben überprüfbar und somit vermarktbar zu machen. In diesem Kontext wird immer wieder über die Blockchain-Technologie diskutiert. Neben den Chancen, die eine Blockchain für eine verifizierbare Dokumentation und Interaktionen über Organisationsgrenzen hinweg bietet, werden in diesem Beitrag die Herausforderungen ihrer Nutzung aufgezeigt. Dabei wird auch auf komplementäre Technologien, insbesondere kryptographische Ansätze für digitales Identitätsmanagement und Zero-Knowledge Proofs, eingegangen und gezeigt, wie diese zur Bewältigung der Herausforderungen genutzt werden können.
Traditional and electronic voting systems face significant challenges in ensuring transparency, security, and voter trust. Issues such as centralized control, lack of auditability, vulnerability to tampering, and potential for fraud undermine the integrity of electoral processes. This paper proposes a novel blockchain-based electronic voting system designed to address these shortcomings through decentralized ledger technology and smart contracts. The system ensures vote integrity, voter anonymity, and public verifiability while preventing double voting and eliminating single points of failure. By employing cryptographic techniques such as zero-knowledge proofs and ring signatures, voter privacy is maintained without compromising transparency. The proposed architecture is evaluated through simulation, demonstrating scalability, reduced transaction costs, and robustness against common cyber threats. This work contributes to the advancement of trustworthy digital democracy and provides a feasible framework for real-world electoral deployment.
The concept of blockchain has transformed the trust concept by decentralizing, non-modifiable, and transparent, but there is a certain conflict between the principle of public verifiability and data privacy. As DeFi and cross-institutional data collaboration should grow, it has become a fundamental concern to have the confidentiality of this data without losing verifiability on-chain. The following paper will be a review of blockchain privacy technologies developed in 2020-2025, which will involve the history of zero-knowledge proofs and homomorphic encryption development at the cryptographic primitive level, as well as share new developments such as secure multi-party computation. It points out advances in recursive proof systems, distributed proof generation architectures and scalable multi-party computing systems to overcome bottlenecks in performance. There is a trade-off between privacy, system performance, regulatory compliance, and decentralization in a comparative analysis of technology integration in both public and permissioned chains. Lastly, research directions in the future are suggested in order to overcome issues associated with low proof efficiency, regulatory compliance problems, and migration of post-quantum cryptography. The review offers both theoretical and technical sources on how to develop trusted blockchain infrastructure that would strike the right balance between compliance, high-performance, and data sovereignty.
Advancements in networking applications increase the requirement for secure data storage and an efficient data access mechanism with robust networking characteristics. Consequently, the huge volume of data generated from the het-erogeneous networks, such as smart cities, healthcare, and smart energy trading systems, suffers from scalability issues and generates insights for secure data storage and effective data management. Therefore, the research proposes a secure data storage and access scheme named Multimodal Biometric-enabled Zero-Knowledge Proof of Stake(MBZKPS). The Multimodal Biometric Data Access(MBDA) ensures secure and robust access to the heterogeneous data with reduced computational overhead. The Distributed Storage System and the Zero Knowledge Protocol with Proof of Stake alleviate the storage pressure on the blockchain and regulate the heterogeneous data storage and access in the blockchain. The Message Digest 5(MD5) with Homomorphic Encryption enables computations on the encrypted data with better data confidentiality preserva-tion. The introduction of the blockchain eliminates the scalability issues with improved privacy preservation and data integrity. Simulation results validate the superiority of the MD5 with Homomorphic Encryption (HE) used in research by achieving 0.95ms decryption time, and 0.97 encryption time with 0.73 Genuine User Rate occupying 363.76KiloBytes of memory for 250 nodes. In addition, the proposed research performs secure data storage with a 1025.85 ms response time and 1.01ms transaction time using blockchain.
In the present times, Transformation finance has become a prominent approach for a systematic financial channel to facilitate the step-by-step decarbonization of carbon-intensive sectors. Such mechanisms rely on the accuracy of carbon emissions data to measure environmental performance and to inform capital decisions. The current carbon accounting methods are limited by inadequate data-collection provisions, slow verification processes, and low auditability, which undermine the reliability of emission-reduction claims and constrain the effectiveness of carbon asset markets. In the present research work, a blockchain-based framework is proposed that will create reliable carbon data accounting and facilitate structured carbon asset circulation within ecosystems of transformation finance. The framework establishes a single carbon lifecycle for data, integrating real-time emission tracking, multi-step verification, a secure registry, and computer-generated assets. The datasets of industrial emissions used to test the operation of the proposed system under multi-sector conditions include energy systems and manufacturing activities, logistics networks, and urban service infrastructure. The objective of the proposed framework is to measure the reliability of carbon accounting by normalizing emission intensities, estimating verification confidence, and scoring trust with uncertainty. In addition, a circulation model is proposed to describe the liquidity of carbon assets, the efficiency of their utilization, and the stability of decentralized transactions. The outcome of the present research is to regulate the creation and transfer of tokenized carbon assets, which guarantees the consistency of environmental performance and financial representation. The review shows a quantifiable increase in the visibility of emission records, a decrease in verification delays, and greater visibility into asset circulation processes compared with traditional centralized systems. The suggested framework establishes a logical link between verifiable carbon-reduction results and decentralized financial mechanisms, enhancing the operational feasibility of transformation finance.
Enabled by blockchain progress, ICOs emerged as an alternative to traditional equity financing, with global investor reach, decentralized governance, and reduced transaction costs. However, the performance of ICOs under competitive product market conditions remains underexplored. This paper develops a game theoretic Cournot competition model to compare firms' financing and operational strategies under two benchmark scenarios, depending on whether product value is insensitive or sensitive to managerial effort. The analysis examines how cost structure, market volatility, product substitutability, and managerial risk attitude jointly affect financing choices and production decisions. To ensure research rigor, we further analyze a generalized model and conduct robustness checks by varying key parameters, confirming the stability of the equilibrium outcomes beyond the benchmark settings. The results show that optimal financing choices depend critically on market structure. Greater product substitutability intensifies competition and widens the utility gap between financing modes, strengthening the dominance of the more suitable strategy. Equity financing is more favorable for risk averse firms or those operating in low innovation, high substitutability industries such as manufacturing and utilities, due to its risk sharing and operational flexibility. In contrast, ICOs are better suited for innovation driven ventures such as DeFi and NFTs, which benefit from incentive alignment and reduced equity dilution. This study provides managerial insights into the strategic selection of financing mechanisms under competition and contributes to a deeper understanding of token financing in modern capital markets.
Effective risk management has grown more and more crucial in the complex world of international trade finance, bolstered by security, trust, and openness. By creating an integrated system that blends Hyperledger Fabric blockchain technology, Supply Chain Finance (SCF) protocols, and Generative Adversarial Networks (GANs), this study seeks to improve the intelligence and dependability of financial risk assessment. Four interrelated steps make up the suggested approach: (1) preprocessing and encoding SCF datasets; (2) creating synthetic risk data with GANs to mimic uncommon or dishonest trade behaviors; (3) using Hyperledger Fabric to execute smart contracts and log transactions decentralized; and (4) using real-time SCF compliance modeling for dynamic risk assessment. While blockchain guarantees the transparency, immutability, and auditability of financial records, GAN integration improves the prediction model by adding value to the training corpus. Comparative studies show that the suggested system considerably lowers the likelihood of data tampering and improves risk prediction accuracy by 12% when compared to traditional machine learning models. The results demonstrate that integrating generative modeling with blockchain technology can significantly improve financial risk management, transparency, and adaptability in global trade settings.
The Vjosa River Basin, located in the heart of the Balkans, is one of Europe's last free-flowing wild rivers comprising a large number of pristine habitat types with a wealth of biodiversity. Widespread degradation of the forest ecosystem and unsustainable land use due to logging and livestock farming have led to an urgent need for effective conservation planning and sustainable management. This study applies the Ecosystem Service Opportunity (ESO) framework to provide a diagnosis of the social-ecological context and the current institutional and legal frameworks governing the Vjosa River in Permet area and its surroundings. Based on 15 semi-structured interviews with stakeholders from local government, NGOs, and a national government agency, we identify opportunities for policy and finance instruments to encourage ecosystem conservation and sustainable livelihoods. The results are compared to Integrated Management Plan (IMP) for the Vjosa Wild River National Park. Our results align with the IMP approach in several strategic areas (i.e., stronger law enforcement and patrolling, regulating illegal livestock grazing, improved staff management and collaboration between local agencies, incorporating traditional knowledge in conservation strategies), but further emphasizes the need for action beyond national park boundaries, decentralization with stronger municipal involvement, establishment of a collaborative platform, and the diversification of funding initiatives.
Open access
2 source records
Land Use and Ecosystem Services
Conservation, Biodiversity, and Resource Management
Enterprises are rapidly shifting from human-interpreted dashboards to Autonomous Analytical Entities (AAE) that execute decisions directly on production systems. This transition introduces a new failure mode—Agentic Divergence—where decentralized agents act on misaligned, drifted, or out-of-scope data products and metadata, leading to high-impact errors at scale. This paper proposes the Autonomous Analytical Coherence (AAC) framework, centered on an Analytical Control Plane (ACP) that inserts a mandatory, machine-enforced governance layer between AAEs and decentralized data products. The ACP mandates Agentic Data Contracts (ADC) as runtime dependencies and enforces Kullback–Leibler (KL) divergence-based drift checks within Trusted Execution Environments (TEE) to safeguard both analytical coherence and data sovereignty. Simulation-based experiments across finance and logistics workloads indicate that AAC reduces erroneous autonomous transactions by 77% compared with uncoordinated agent deployments, with only a 25 ms median increase in latency. These results demonstrate that treating governance as a runtime dependency is a practical path toward safe, high-stakes autonomous analytics in enterprise data meshes.
Radovan Vladisavljević, Aleksandra Zlatić-Tešić, Svetlana Marković
The aim of the work is to present a model of tax control automation using smart contracts, this is a relatively new application of blockchain technologies. The use of new technologies can greatly improve the operations of modern organizations that have digitized their operations. New technologies not only provide a high degree of automation but also provide a high degree of transparency. This leads to faster business with an increase in the level of trust of all participants in the business venture.
Abstract Many compilation stages of smart contracts on the Ethereum blockchain have been transitioned to the intermediate language . Tasks such as smart contract optimization and bytecode generation are—or will soon be—performed directly at the level in the compilers for the higher-level languages such as Solidity. In this paper, we develop a formal semantics of programs in Rocq, suitable for verification, which allows formal reasoning at the level of code or generation tools processing programs. Our semantics is expressive enough to be the basis for formal verification tools, and simple enough to make the development of such tools feasible. In order to prove its adequacy for verification, we develop in Rocq a checker (and associated soundness proofs), based on our semantics, able to verify the results of the liveness analysis stage of the official Solidity compiler , which opens the door towards formally verified Ethereum’s smart contracts compilation. Experiments on more than 1,500 smart contracts show that we are able to automatically verify ’s liveness analysis results in negligible time.
The incessant development and ubiquitous diffusion of information and communication technologies give rise to phenomena of considerable socio-economic and therefore legal significance. Among these, contractual relationships are strongly affected by technological evolution, which provides new tools for negotiating, concluding and executing contracts, with specific operating dynamics and unpublished legal issues. In this perspective, from a legal point of view, the contract-technology combination represents a topical issue for a comparative analysis, which provides the interpreter with an overall view of different local responses to common developments and problems deriving from the use of technology in contracts.