This article examines aspects of implementing energy efficiency monitoring for an electric vehicle fleet operating in an urban environment. Monitoring is considered as a tool of intelligent energy management for a motor transport enterprise. The electric vehicle fleet is viewed not only as an active consumer of electricity, but also as a participant in the energy market. The monitoring task is considered from the perspective of ensuring sustainable e-mobility and efficient enterprise operation. In addition, issues related to the integration of the electric vehicle fleet into the power grid and its impact on the electrical load of the energy system are also taken into account. A set of tasks for monitoring the energy efficiency of an electric vehicle fleet has been formulated to support managerial decision-making aimed at improving the energy efficiency of motor transport enterprise operations. The system of information and analytical support for monitoring the energy efficiency of an electric vehicle fleet is considered as a set of complex subsystems focused on data collection, processing, and storage, as well as data analysis, modeling, and energy efficiency control. A stratified representation approach for complex systems has been applied to solve the problem of multitasking in energy efficiency monitoring. This made it possible to simplify the description of the components of the information and analytical support system. Data collection, preprocessing, and storage are implemented on the basis of IoT technology. The analytical support subsystem consists of computational agents, each of which ensures the solution of a specific monitoring task. Object-oriented technology has been applied to formalize the system of information and analytical support for monitoring the energy efficiency of an electric vehicle fleet. The system objects are represented through three categories of classes. These class categories have integrated properties and ensure the functioning of the monitoring subsystems. The description of data structures and class functions has been developed taking into account the formulated monitoring tasks.

Construction waste transportation (CWT) is a tightly regulated urban activity central to urban development, traffic operations, and environmental governance. As an underexamined yet policy-sensitive segment of intra-city freight transportation, CWT exhibits complex operational logics that warrant systematic analysis for effective supervision and management. This study adopts a dynamic complex network perspective, leveraging large-scale GPS data from over 8,000 construction waste transport trucks in Chengdu, China. Dynamic community detection is applied to characterise the temporal evolution of network structures, revealing a clear two-phase daily operational pattern and community structures dominated by different transportation enterprises. In addition, a motif-based node importance identification method tailored to CWT networks is developed to uncover critical motifs and structurally important nodes. These insights provide managerial guidance for regional governance of construction waste transport and targeted supervision of key nodes within urban transportation networks.

The dynamic development of the food delivery sector and the resulting increase in last-mile distribution operations generate the need to simultaneously improve the efficiency of delivery processes and reduce the environmental impacts of urban logistics. In this context, shortening delivery time contributes not only to higher service quality and competitiveness but also to lower energy consumption and carbon dioxide emissions, which are key elements of sustainable urban mobility and logistics. Therefore, the aim of this study is to develop a delivery time optimization algorithm for the food delivery sector using selected machine learning methods, supporting the implementation of sustainable development principles in the operations of transport enterprises. This study presents an integrated approach to modelling delivery time in food distribution as a tool for building the competitive advantage of logistics enterprises under the conditions of implementing sustainable development principles. The study combines a literature review on sustainable last-mile logistics and data-driven optimization with an empirical analysis using traditional methods such as multiple regression and selected machine learning methods: decision trees, the Gradient Boosting Machine (GBM) method, and the XGBoost algorithm. The operational data include parameters related to delivery execution, such as supplier characteristics, vehicle type, order execution date, weather conditions and traffic situation. The developed mathematical models enable high-accuracy prediction of delivery time and the identification of the most important factors affecting both timeliness and potential energy consumption in the delivery process. The comparative assessment of the applied methods makes it possible to indicate the algorithms that provide the best forecast quality and practical usefulness in logistics decision-making. The proposed delivery time optimization algorithm supports data-driven decision-making that leads to shorter delivery times and lower energy intensity and thus to a reduction in the carbon footprint of last-mile operations, simultaneously strengthening the competitiveness and environmental responsibility of logistics enterprises. The results contribute to the development of sustainable urban logistics by linking predictive modelling with the economic, environmental and operational dimensions of efficiency in last-mile transport processes. Overall, this study offers an original, high-quality contribution to sustainable last-mile food delivery by integrating large-scale operational data with advanced machine learning models to deliver practically relevant, highly accurate delivery time predictions for logistics enterprises.

The rapid advancement of digital technologies is fundamentally reshaping the global economy, and transport logistics stands at the forefront of this transformation. In an era where speed, transparency, and resilience define competitive advantage, the ability of transport companies to adopt and integrate digital tools has become a critical determinant of their long-term viability. This is particularly relevant for Ukraine, where the sector operates under the compounding pressures of global digitalization trends and the devastating consequences of full-scale military aggression that began in February 2022. The urgency of researching digital technologies in transport logistics is driven by several interconnected factors. First, the global logistics industry is undergoing a structural shift driven by the proliferation of artificial intelligence, the Internet of Things, blockchain, digital twins, and cloud-based management systems. These technologies are no longer experimental – they have become operational standards for leading logistics operators worldwide, redefining how freight is tracked, routed, documented, and managed. Second, Ukraine's transport and logistics sector faces a uniquely challenging environment in which traditional supply chains have been disrupted, infrastructure has been partially destroyed, and established routes have been fundamentally altered. In this context, digitalization is no longer a strategic aspiration but an immediate operational imperative. The article examines a range of pressing issues that remain insufficiently addressed in the existing scholarly literature. These include the absence of a comprehensive systems-level analysis of how various digital technologies interact as a unified platform under wartime constraints such as personnel shortages, energy instability, and route reorientation. Furthermore, the practical mechanisms through which small and medium-sized transport enterprises, which form the backbone of Ukraine's freight market, can realistically implement digital solutions remain underexplored. The prospects for integrating Ukraine's transport and logistics infrastructure into European digital standards, particularly in the context of EU accession, also represent a significant gap in current research. By addressing these questions, the article contributes to a broader understanding of how digital transformation can serve not only as a tool for operational efficiency but also as a means of building sectoral resilience in times of profound uncertainty.

The article determines that the turbulence of the operating environment of railway transport enterprises, caused by digitalization processes, increased interspecific competition, as well as crisis and war risks, actualizes the need to form a new model of development of the industry. Based on the analysis of the activities of railway transport enterprises, it is determined that the depleted material and technical base, intensification of competition from other types of transport, digital transformation of transport systems, increased requirements for environmental friendliness and energy efficiency, socio-economic challenges and post-war recovery, the importance of integration into international transport corridors require innovative and digital transformation of the system of functioning of enterprises in the industry. A system of key factors that determine the expediency of their innovative transformation is determined. It is argued that political, economic, socio-cultural, technological and environmental factors comprehensively determine the directions of innovative transformation of railway transport enterprises, forming requirements for modernization, digitalization and greening of the industry. A theoretical model for ensuring the innovative and digital development of railway transport enterprises has been formed, which defines the goal, principles, tasks and tools for implementing innovative and digital transformations in order to transform enterprises in the industry into an integrated and highly automated platform that provides world-class logistics and passenger services. The key tasks of innovative and digital development of railway transport enterprises within the framework of the model are: creation of a modern, effective and sustainable transport system; digital transformation of management; innovative renewal of production processes and funds; integration into the international transport space; ensuring sustainability and safety; personnel management and HR transformation. It has been proven that the implementation of this model at railway transport enterprises will create an opportunity not only to optimize business processes, increase operational efficiency and safety, but also to increase the competitiveness of Ukraine in the international transport services market.

It is established that the current dynamics of the development of the world economy are characterized by the aggravation of environmental challenges, increased resource constraints and the intensification of the global transformation of economic systems towards the implementation of the principles of sustainable development. It is substantiated that under such conditions, the environmental component of enterprise activity acquires strategic importance and is transformed from an auxiliary element of management into a key factor in the formation of long-term competitive advantages. It is proven that these processes acquire particular relevance in the transport sector, which is characterized by a high level of resource and energy intensity and belongs to the sectors of the economy with a significant anthropogenic impact on the environment. It is argued that the strengthening of international environmental standards, the integration of the principles of the “green” economy into business practice, as well as the orientation of global markets towards the formation of environmentally responsible value chains necessitate the transformation of approaches to the strategic management of the development of transport enterprises. In this context, the feasibility of forming environmental value as an integral characteristic of an enterprise's activities has been proven, reflecting its ability to create added value by minimizing negative impact on the environment, increasing the efficiency of resource use, implementing environmental innovations and developing environmentally friendly business models.Strategic principles for managing the environmental value of transport enterprises have been developed, within which the key elements of the relevant strategy have been identified. The stages of its formation and implementation have been highlighted, a set of measures and management tools aimed at integrating environmental priorities into the enterprise's strategic management system has been systematized. The tools for implementing the strategy for managing the environmental value of transport enterprises in the context of ensuring their competitiveness have been detailed.

The article examines marketing logistics as an integrated management system within transport enterprises, emphasizing its role in creating sustainable competitive advantages through the effective management of flows and delivery of services that preserve consumer value. In modern economic conditions, traditional isolated application of marketing and logistics tools often fails to ensure the achievement of strategic objectives, particularly under circumstances of high uncertainty, resource limitations, and disruptions in supply chains, such as those experienced during martial law. Marketing logistics emerges as an integrative mechanism that combines market-oriented approaches with process- and flow-oriented logistics, aligning demand generation with the enterprise’s operational capabilities. A critical review of domestic and international literature reveals a lack of unified conceptual understanding of marketing logistics. Foreign studies tend to interpret it from a logistics perspective, emphasizing operational efficiency and physical distribution, while domestic research increasingly views it as a comprehensive, integrative system that coordinates marketing and logistics decisions to achieve long-term competitive advantages. The article classifies approaches to marketing logistics into three groups: functional-distributional, integration-oriented, and value-oriented (synthetic), reflecting its evolution from a narrowly operational function to a strategic management concept. The study offers a conceptual generalization of marketing logistics as an integrated management system under conditions of high uncertainty. The study identifies key objectives and tactical tasks of marketing logistics, including ensuring full and timely satisfaction of consumer demand, optimizing logistics costs, maintaining service quality, enhancing resilience, and supporting sustainable development and digital transformation. The article further delineates the core functions of marketing logistics — analytical, planning, organizational, coordination, control, and value-oriented — demonstrating their integrative nature in harmonizing marketing and logistics processes. Comparative analysis highlights that marketing logistics not only delivers physical products but also generates additional value for the consumer by balancing service levels with operational efficiency. The findings underscore the relevance of marketing logistics as a holistic management tool for transport enterprises operating in dynamic and uncertain environments. Prospects for further research include the development of digital, data-driven, and adaptive approaches to enhance efficiency, resilience, and sustainability in marketing logistics processes.

The article summarizes and develops the theoretical aspects of managing urban transport enterprises, taking into account the current conditions of their operation, and also identifies the main approaches to improving the efficiency of managerial activities in the sector. It is noted that urban transport, as a management object, has a number of specific characteristics that distinguish it from other sectors of the economy. It is emphasized that management principles and functions play a key role in ensuring managerial efficiency. It has been found that implementing innovative approaches and digital technologies makes it possible to enhance management efficiency, optimize resources, and improve the quality of passenger services. It is noted that urban transport enterprises today face a number of significant problems and challenges affecting the efficiency of organizational, economic, and technological processes. Their analysis has shown that the issues of urban transport enterprises require a comprehensive approach. Indeed, theoretical conceptions – system, process, and situational approaches, the integration of ESG principles, and adaptive management – provide a scientifically grounded basis for decision-making. It has been concluded that urban transport enterprises today face a range of problems that significantly impact the efficiency of their operations, including financial constraints, aging infrastructure, increasing urbanization, stricter environmental requirements, and the need for digital transformation. The analysis indicated that applying system, process, and adaptive approaches, along with integrating ESG and smart transport conceptions, establishes a scientifically grounded foundation for managerial decisions, enhances the quality of transportation, optimizes resources, and minimizes risks in the operations of enterprises. At the same time, implementing these theoretical approaches in practice requires the use of modern tools such as economic-mathematical modeling, technical condition forecasting, big data analytics, and digital management platforms. The combination of a conceptual foundation and practical methods allows urban transport enterprises to develop efficient strategic and tactical decisions even in conditions of uncertainty and dynamic external changes.

The article addresses the issues of interaction among transport enterprises based on the distribution of orders for freight transportation through the calculation of proposed indicators that determine the degree of order compatibility. In the context of increasing demand for road freight transportation and limited production capacities of individual carriers, cooperation between motor transport enterprises becomes an important tool for improving the efficiency of transport processes. The study substantiates the feasibility of organizing such interaction by taking into account organizational and technological compatibility of transportation orders. It has been established that the compatibility of freight transportation orders depends on the sequence of their execution within the transport process and on their concentration within a given transport network. The article proposes analytical indicators that make it possible to quantitatively assess the degree of compatibility and concentration of orders, which allows transport enterprises to form rational priorities for order execution. These indicators can be used to determine the expediency and level of interaction among motor transport enterprises, including the redistribution of orders and the joint use of vehicle fleets. The proposed methodology for distributing freight transportation orders makes it possible not only to solve the problem of planning the transport process under conditions of a large volume of incoming transportation orders, but also to ensure a reduction in unproductive mileage, downtime, and inefficient use of vehicles. As a result, interaction among motor transport enterprises contributes to an increase in the overall efficiency of freight transportation and to the achievement of a higher total profit for all cooperation partners. The object of the research is the process of interaction among motor transport enterprises in the execution of freight transportation orders. The aim of the study is to determine the criteria that form the basis for planning and distributing freight road transportation orders among cooperating road transport enterprises. The research method is analytical and is based on the analysis of time parameters of order execution and spatial characteristics of transportation networks. The practical significance of the research lies in the possibility of applying the proposed approach in the operational planning of freight transportation by motor transport enterprises, especially under conditions of limited resources and high market competition.

Topicality. The article substantiates a conceptual approach to optimizing logistics costs of motor transport enterprises by integrating camera monitoring systems (CMS) into digital twins. The relevance of the study is driven by the need for digital transformation of logistics and the shift from reactive to predictive fleet management amid resource price volatility and geopolitical risks. The purpose of the work is to develop and validate a scientific-methodological approach to intelligent management of logistics costs based on the synergy of visual telemetry and dynamic modeling. The research applies methods of systems analysis, simulation modeling, and expert assessments. The following results were obtained. The architecture of a digital twin of the enterprise is formed, with CMS serving as the primary data source on vehicle movement, technical condition, and psychophysiological behavior of drivers. A predictive management matrix incorporating 13 key indicators (grouped into safety, operation, and economics categories) has been developed. A model is proposed that accounts not only for internal fleet parameters but also for external determinants (resource prices, weather conditions, regulatory requirements), enabling real-time adaptation of logistics operations. Conclusion. Validation results based on industry data (2022–2025) confirmed the economic efficiency of the approach. Implementation of the system yields a return on investment (ROI) of 277% in the base scenario with a payback period of 4–6 months. Sensitivity analysis under a pessimistic scenario (10% deviation of factors) demonstrated model robustness with an ROI of 134% and payback within 9 months. The practical significance of the work lies in providing specific recommendations for reducing transportation unit costs, minimizing unplanned downtime, and lowering risks, thereby contributing to the sustai nable development and investment attractiveness of modern transport enterprises.

ABSTRACT This study investigates the effects of environmental, social, and governance (ESG) practices on the financial and operational efficiency of international container shipping enterprises (CSEs) from 2019 to 2023. Using data envelopment analysis to measure firm efficiencies and truncated regression to examine ESG relationships, results reveal that financial efficiency improved, largely driven by technological change and favorable market conditions, while operational efficiency declined, indicating price-driven profitability gains. Scale efficiency is a key determinant of financial performance, with leading carriers achieving full efficiency and smaller firms facing persistent inefficiencies. Environmental initiatives enhance financial efficiency but reduce operational efficiency, highlighting a trade-off between long-term financial gains and short-term operational constraints. Social and governance dimensions show no significant effects, suggesting delayed or indirect impacts. The findings emphasize the need for strategically timed environmental investments, resource allocation, fleet modernization, and long-term planning of social and governance initiatives to optimize CSEs’ performance.

This research paper examines the nexus between digital transformation and investment activity across a diverse economic spectrum, encompassing the rapid growth of the BRICS bloc, the advanced industrial framework of Germany, and the resilient, IT-driven economy of Ukraine. As global logistics networks shift toward "Industry 4.0" standards, the traditional investment model, historically focused on physical fleet expansion, is being restructured to prioritize digital infrastructure, AI-driven logistics, and Big Data analytics. Utilizing a structural-analytical framework, this research evaluates how these digital investments enhance the financial sustainability of transport firms by optimizing asset utilization and reducing operational risks. The findings demonstrate that digital transformation acts as a catalyst for institutional change, enabling firms to achieve higher capital productivity and long-term economic resilience. In the context of transitional markets, the shift toward digitalized investment activity serves to mitigate macroeconomic vulnerabilities by lowering logistics costs and improving regional trade integration. The study concludes that for transport enterprises, digital-led structural reforms are not merely technological upgrades but are essential strategies for ensuring fiscal stability and competitive advantage in an increasingly volatile global economy. Practical recommendations for managers and policymakers focus on balancing CAPEX between physical assets and digital innovation to ensure sustainable growth.Copyright© 2026 The Author(s). This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited.Article’s history: Received 29th of October, 2025; Revised 9th of December, 2025; Accepted 12th of January, 2026; Available online: 15th of March, 2026. Published as article in the Volume XXI, Special Issue, 1(91), 2026.

The Role of Supply Chain Finance and Carbon Trading in Asset Allocation Decisions of Transportation Enterprises

The process that improves decision-making for prioritizing the implementation of digital technologies at a transport enterprise under the conditions of uncertainty associated with war and European integration has been investigated in this study. The objective need to improve the efficiency of decisions is predetermined by resource constraints faced by enterprises, especially under conditions of martial law. To solve the problem, it has been proposed using a methodological approach based on the hierarchy analysis method. A system of criteria for assessing the priority of digital technologies for transport enterprises was built, which consists of the following groups: economic, technological, organizational-managerial, social-security, and strategic. It was established that the most significant criteria for evaluating digital technologies for the studied enterprises are operational stability (0.4214), technological reliability (0.2621), physical security of infrastructure (0.2987), management flexibility under risk conditions (0.4237), protection of life and health of employees (0.4593), as well as compliance with the legislation of Ukraine and EU norms (0.2713). The priority of implementing digital technologies for the studied group of transport enterprises was justified based on the construction of a multi-criteria model and the application of the Analytic Hierarchy Process. The following digital technologies were considered to be of the highest priority: transport monitoring and telematics systems, electronic document management, digital contracts and digital interaction platforms. The objectivity and consistency of the results is attributed to the fact that the evaluation was based on substantiated criteria that provided a multidimensional reflection of the impact of digitalization on the activities of enterprises. A feature of the improved methodological approach is its higher universality. It is suitable for practical application in various modes of transport and for a wide continuum of digital technologies

The article explores the digitalization of risk management as a strategic factor in enhancing the competitiveness of transport enterprises within the framework of sustainable development. The study substantiates that the growing uncertainty of the external environment, intensified by digital transformation, global logistics disruptions, environmental requirements, and operational risks, necessitates the revision of traditional risk management approaches in transport enterprises. It is argued that the integration of digital technologies into risk management systems enables a shift from reactive to proactive and predictive management models. The research systematizes key digital risk management tools used in the transport sector, including Big Data analytics, automated monitoring systems, decision support systems, digital dashboards, and geographic information systems. Their functional role in identifying, assessing, monitoring, and mitigating operational, financial, infrastructural, logistical, and environmental risks is analyzed. Particular attention is paid to the ability of digital tools to ensure real-time data processing, improve forecasting accuracy, and enhance the quality and timeliness of managerial decision-making. The article proposes a conceptual model that reflects the causal relationship between digitalization of risk management, improvement of management efficiency, formation of competitive advantages, and achievement of sustainable development of transport enterprises. The model is based on a phased logic of digital transformation, where digital technologies form an information foundation for risk management, which in turn increases operational efficiency and leads to sustainable competitive positioning in the transport services market. Based on the proposed model, a system of research hypotheses is formulated, describing the managerial and economic effects of digitalization at each stage of enterprise transformation. These hypotheses provide a theoretical basis for further empirical verification and quantitative assessment of the impact of digital risk management on competitiveness and sustainability indicators. The practical significance of the research lies in the applicability of the proposed approach for developing digital transformation strategies, improving risk management systems, and strengthening the long-term economic, social, and environmental sustainability of transport enterprises.

Purpose. The work is aimed at developing a methodology for experimental research into the influence of reduced supply voltage on the operating and mechanical characteristics of squirrel-cage induction motors with a power of up to 5 kW. The research is focused on critically important technological equipment of railway transport enterprises (locomotive depots, repair plants), which in modern conditions is often operated in power supply modes with low quality indicators. Methods. The work uses a comprehensive analysis of the technical equipment of railway enterprises, analytical methods for studying the properties of asynchronous machines, and methods for mathematical analysis of test results. The experimental part is based on the method of direct loading on a mutual load stand, where a DC machine with independent excitation is used as a braking device. The process includes preliminary measurement of the characteristics of idling and non-working speed for calibrating the measuring system. Results. A scheme of an experimental stand has been developed and practically tested, allowing to fix the coordinates of the electric drive (torque, speed, current) in a wide range of loads. It has been established that the use of a P-42 type generator as a loading device allows to create a regulated braking torque from 0 to 35 N∙m. This provides the possibility of modeling the operating modes of asynchronous motors with a capacity of up to 5 kW with a variation of the supply voltage. The described metrological base confirms the high accuracy of the obtained data for the further construction of real mechanical characteristics. Originality. The author first proposed to use a mutual load stand with a DC generator of proportional power to the engine, operating on a network with regulated voltage, specifically to assess the stability of non-traction railway consumers in conditions of unstable power supply. The method of direct loading of low-power machines has also been further developed, which, unlike analytical models, allows taking into account real electromagnetic processes in conditions of deviation of network parameters from nominal values. Practical significance. The obtained methodology and bench test results are the initial data for predictive modeling of the stability of industrial equipment operation at railway repair enterprises. The practical application of the results will allow developing technical recommendations for protecting critical equipment from the negative impact of low-quality electricity, as well as justifying the implementation of voltage compensation measures and the use of renewable energy sources for the uninterrupted operation of locomotive depots.

The article presents a systematization and justification of the organizational and economic principles for managing the viability of maritime transport enterprises, and identifies key directions for improving management mechanisms, taking into account modern challenges and industry development trends. The methodological foundation of the study is based on a comprehensive integration of classical and contemporary scientific approaches, ensuring a multidimensional understanding of the processes of managing the viability of maritime transport enterprises. This led to the application of research methods such as analysis and synthesis, comparative analysis, the systems approach, and expert assessment. The study’s results indicate that the comprehensive development of organizational and economic principles of viability management is a necessary prerequisite for the stable functioning of shipping companies, fleet operators, and maritime cargo transportation enterprises amid the transformation of the global logistics system. It is demonstrated that improving the management mechanisms of maritime transport enterprise viability should focus on the following key areas: increasing the adaptability of organizational structures to quickly respond to changes in market conditions and external risks; integrating strategic and operational planning, risk management, shipping safety, and logistics operations; optimizing financial and economic mechanisms, including cash flow management, diversification of funding sources, economically justified tariff policies, and investment efficiency assessment considering industry-specific risks; implementing digital and analytical management tools to enhance decision-making speed and accuracy; developing monitoring systems. This means improving how we measure viability, review management decisions, and adjust company strategies to outside challenges. The study's value is in finding steps that build viability at the linked levels of a maritime transport company—systemic, target, and resource levels. These levels are connected: choices about resources influence reaching goals (target level), and good teamwork between company subsystems keeps the whole company running smoothly (systemic level).

ABSTRACT Intermodal transport is an important part of international trade, and poor connectivity between transport modes can significantly increase costs. To minimize these costs, we propose a novel two-stage optimization model that combines transport mode selection and route planning. However, previous studies often ignore the uncertainty of node detention service time. To address this issue, we extend the robust optimization theory and introduce a two-stage robust planning model. The model is illustrated based on a simulation case. The study shows that even if the transport mode remains unchanged, uncertain parameter changes can lead to a significant drop in service levels. Based on a deep reinforcement learning algorithm, two improvement strategies are combined to improve the algorithm efficiency. In addition, optimizing transport mode selection can reduce carbon emissions without sacrificing transportation efficiency. This study provides valuable theoretical support for the low-carbon transformation of intermodal transport enterprises.

The article examines the economic strategies for the development of railway transport enterprises in Ukraine in the context of deep structural transformations of the national economy, military risks, intensification of European integration changes, and digitalization of management and production processes. The role of railway transport as a strategically important component of the state's transport system, which ensures transport and economic ties, population mobility, national security, and sustainable socio-economic development of regions, is noted. The current state of railway enterprises is analyzed and the main problems of their functioning are identified, in particular, the critical level of depreciation of fixed assets, limited investment resources, low level of innovation activity, increased operating costs, imperfect management systems, and financial instability. The paper systematizes key areas for the formation of economic strategies for the development of railway transport enterprises, which include increasing the efficiency of financial, material, and labor resource management, as well as cost optimization, the introduction of modern digital and innovative technologies, diversification of funding sources, and the development of logistics services and mechanisms of public-private partnership. Additionally, attention is paid to the need to adapt strategic management to the conditions of martial law, to carry out post-war recovery (reconstruction) of the Ukrainian economy, taking into account the needs of rebuilding transport infrastructure and strengthening its competitive positions. A set of measures and recommendations is presented that are directly aimed at ensuring financial stability, investment attractiveness of enterprises, and increasing the competitiveness of railway transport. The implementation of such recommendations will contribute to the sustainable development of the industry, improving the quality of transport services, more effective use of transit potential, and deepening Ukraine's integration into the European transport space in the long term.

Marine data assets are increasingly recognized as important drivers of value creation in the blue economy, yet their valuation remains challenging due to difficulties in isolating data-related earnings in capital-intensive maritime enterprises. This study proposes a methodological valuation framework that integrates the multi-period excess earnings method with the Analytic Hierarchy Process (AHP) and the Fuzzy Comprehensive Evaluation (FCE) approach, incorporating both financial and non-financial dimensions. The framework follows a “total synergistic return–data contribution separation” logic to isolate data-related excess earnings and applies an AHP–FCE-based adjustment coefficient to account for data quality, application value, and risk. A representative container shipping enterprise is used as an illustrative application to demonstrate the implementation logic of the framework. The results indicate that marine data assets can constitute a non-negligible component of enterprise value under reasonable parameter settings, while sensitivity analysis highlights the influence of key parameters such as the data contribution coefficient and discount rate. The proposed framework provides a transparent methodological reference for marine data asset valuation and supports sustainability-oriented research and practice in the blue economy.