Business Management

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  SUPPLY CHAINS OF PERISHABLE AGRI-FOOD PRODUCTS IN THE EAEU: CONCEPTUAL APPROACHES AND DEVELOPMENT OF LOGISTICS INFRASTRUCTURE

  The purpose of this study is to develop a conceptual approach to the formation of an integrated logistics platform for perishable agri-food products within the Eurasian Economic Union (EAEU). The methodological framework is based on systems and scenario analysis, SWOT assessment, comparative analysis of the logistics potential of EAEU member ... The purpose of this study is to develop a conceptual approach to the formation of an integrated logistics platform for perishable agri-food products within the Eurasian Economic Union (EAEU). The methodological framework is based on systems and scenario analysis, SWOT assessment, comparative analysis of the logistics potential of EAEU member states, and modeling of logistics chain efficiency under different levels of integration using panel empirical data for the period 2015–2023. Selected indicators of logistics infrastructure are employed to provide a descriptive assessment of the current state of agrologistics as of 2023. The modeling results demonstrate that coordinated investment policies and regulatory harmonization can significantly enhance the efficiency of agrologistics chains in the context of regional integration. The findings confirm that digitalization and the development of cold chain infrastructure are key determinants of logistics sustainability, while the coordination of regulatory and investment mechanisms substantially improves logistics efficiency across the EAEU member states. Based on the estimated parameters, a scenario-based forecast of agrologistics development up to 2030 is proposed. The study introduces a scalable model of an integrated agrologistics platform incorporating a cluster-based approach, a unified digital framework, and public–private partnership mechanisms adaptable to the specific conditions of EAEU countries. The scientific novelty of the research lies in substantiating a platform-based approach to cross-border agrologistics grounded in the synergy of digital and physical solutions, institutional coordination, and targeted infrastructure policy.

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  MEASURING THE LEVEL OF ORGANISATIONAL AMBIDEXTERITY OF MUNICIPAL ADMINISTRATIONS

  The research on organisational ambidexterity, understood as an ability to effectively solve current problems while ensuring long-term strategic development, is relatively recent. Very limited number of studies focus on ambidexterity in public organisations, or if any, it is considered primarily as an outcome rather than a strategy for achieving ... The research on organisational ambidexterity, understood as an ability to effectively solve current problems while ensuring long-term strategic development, is relatively recent. Very limited number of studies focus on ambidexterity in public organisations, or if any, it is considered primarily as an outcome rather than a strategy for achieving long-term success. This study aims to assess the organisational ambidexterity of a group of municipalities in two ways: by answering questions posed to municipal representatives and by calculating financial indicators that provide evidence of local governments’ preferences for funding current needs and investments for the future. The results were tested for statistically significant difference using the t-test. It is concluded that it is evident from their responses that municipal officials understand the need to achieve organisational ambidexterity, but the data from the analysis of the financial indicators of the studied municipalities clearly indicate a preference for spending on current needs over spending on investment and development.

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  A DUAL-LAYER HYBRID SECURITY FRAMEWORK: ANALYZING DIGITAL MODELS TO ENHANCE CYBERSECURITY MANAGEMENT FOR START-UPS AND SMES

  The rapid evolution of generative AI is transforming cybersecurity practices by providing advanced capabilities for threat detection and response. For start-ups and SMEs, these technologies offer a cost-effective way to defend against sophisticated online threats without the need for massive capital investment. While AI facilitates the ... The rapid evolution of generative AI is transforming cybersecurity practices by providing advanced capabilities for threat detection and response. For start-ups and SMEs, these technologies offer a cost-effective way to defend against sophisticated online threats without the need for massive capital investment. While AI facilitates the identification of anomalies and malicious behavior, it also introduces new risks, such as deepfakes, zero-day exploits, and the potential for attackers to manipulate AI models themselves. The study examines the impact of large language models and artificial intelligence on the software and architecture of cybersecurity systems. The main types of attacks on artificial intelligence systems and the changes in the software development paradigm that result from them are being considered. To address the evolving threat landscape, this study proposes a Dual-Layer Hybrid Security Framework that integrates high-speed algorithmic detection with cognitive analysis. We present an algorithm for building a security system using LLM models. We also propose a software application tailored explicitly for the comprehensive analysis of network traffic while detecting cybersecurity incidents using Python and the Pandas library. Furthermore, it leverages artificial intelligence to provide a comprehensive approach to detecting and mitigating cybersecurity threats. This will enable start-ups and small businesses to manage their cybersecurity in-house.