The events of the last five years have had a huge effect on the healthcare supply chain. The system has encountered challenges such as the COVID-19 pandemic and political conflicts. At the same time, sustainability pressures are increasing. These disruptive incidents have revealed weaknesses in the supply chain and lack of resilience. As a result, changes in resilience models have begun to be planned and implemented. The article looks at the main changes in resilience models, emphasizing new models, measures, and attitudes to ensure healthcare logistic. Factors such as risk forecasting, diversification of supply sources, the impact of digitalization, timely inventory management, and strengthening cooperation with suppliers are analyzed. Models that are oriented toward greater flexibility and systemic resilience assessment in general are also discussed. Based on the literature review, it can be concluded that the development of dynamic, predictive, and technology-based robustness models can minimize the harm caused by supply chain disruptions and ensure the stability of the healthcare system. The results of the review indicated that the newest direction for models is the flow of smart technologies. This is expensive, but digitalization can ensure a robust supply chain in the healthcare sector.

The rapid growth of global air cargo demand has intensified the need for more efficient and intelligent storage allocation within airport cargo terminals. Traditional static allocation and rule-based systems struggle to adapt to dynamic cargo flows, leading to operational inefficiencies. This study aims to develop a hybrid decision support system that optimizes storage allocation by integrating machine learning and multicriteria decision-making techniques. A Random Forest Classifier was trained using historical cargo data, including weight, quantity, size, priority, and cargo type, to predict optimal storage zones. To enhance interpretability and expert control, the Analytic Hierarchy Process AHP was used to derive feature weights, while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed to rank the best storage alternatives. The model was tested on real-world data from Almaty International Airport involving 1,500 cargo orders. Results show that the system reduced average storage time by 14%, minimized cargo redistributions by 22%, increased storage density by 9%, and improved on-time delivery for priority cargo by 17% compared to traditional FIFO-based methods. The integration of data-driven learning with expert judgment offers a robust and transparent decision-making framework. These improvements confirm the value of combining machine learning with AHP–TOPSIS methods in logistics operations. This system presents significant implications for airport terminal managers seeking to enhance operational throughput, academic researchers exploring hybrid intelligent systems, and policymakers promoting digital logistics infrastructure. Future studies may include adaptive learning, seasonal cargo flow modelling, and digital twin-based scenario testing to further generalize the solution.

The rise of e-commerce has intensified the demand for logistics services, emphasizing the need for research on service quality to enhance efficiency and customer satisfaction, ultimately fostering loyalty. This study explores the impact of Logistics Service Quality (LSQ) on customer satisfaction and loyalty in the dynamic logistics market of Ho Chi Minh City, Vietnam. Employing an extended SERVQUAL model, this study investigates six dimensions of Logistics Service Quality (LSQ): tangibility, reliability, responsiveness, assurance, empathy, and the newly added dimension of fairness, thereby providing a more comprehensive and nuanced understanding of logistics service quality. A quantitative approach was employed, analyzing data from 409 logistics service users using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings indicate that all the service quality dimensions positively influence customer satisfaction, except for reliability, suggesting a potential misalignment between customer expectations and the consistency of service performance in this market. Additionally, customer satisfaction was found to be a strong and positive predictor of customer loyalty. These results provide practical insights for logistics providers to prioritize service attributes that most effectively enhance customer satisfaction and loyalty. The study contributes to the literature by validating an extended LSQ model in a key Southeast Asian context and offers a managerial framework for improving customer relationships and sustaining a competitive advantage. This research is highly relevant for both scholars and practitioners in logistics, offering a solid empirical foundation for improving service quality and fostering customer loyalty in the sector.

The paper analyses barriers to the implementation of green manufacturing in industrial enterprises in Slovakia, focusing on financial, technological, and organizational barriers. Based on a questionnaire survey, the main obstacles were identified, including insufficient investment, a lack of skilled labour, and limited access to green resources. To evaluate regional and size-related differences, the Chi-square test was applied to determine whether the occurrence of barriers varies according to the geographical location or size of the enterprise. The results of the analysis did not show statistically significant differences between regions in Slovakia or between enterprise size categories, indicating that the barriers to implementing green manufacturing have a nationwide character. However, the most frequent barriers were found to be insufficient financial resources, a shortage of qualified employees, and limited availability of raw materials and technological infrastructure. These factors negatively affect the eco-innovation performance of enterprises, reducing their ability to implement green manufacturing principles and respond effectively to identified barriers. A comparison with the Eco-Innovation Index 2024 further confirmed Slovakia’s below-average performance within the European Union, highlighting insufficient investment in eco-innovation, weak cooperation between the public and private sectors, and limited government support. The findings suggest that overcoming these obstacles requires the development of targeted financial mechanisms, stronger institutional support, and the integration of environmental training programs for employees. This paper aims to identify the main barriers to the implementation of green manufacturing in industrial enterprises in Slovakia and to analyse their differences between regions and individual enterprise size categories.

As the market becomes more globalized and competitive, businesses are under increasing pressure to enhance efficiency, cut costs, and focus on what they do best. One strategy that has gained traction in both practice and research is logistics outsourcing, where companies hand over logistics functions to specialized third-party providers (3PLs). This approach allows businesses to tap into expert capabilities, utilize cutting-edge technology, and scale their operations more effectively. This paper offers a comprehensive review of research on logistics outsourcing decisions, delving into key concepts, theoretical frameworks, and emerging trends. To support this, the study employs VOSviewer, a powerful bibliometric analysis tool that helps visualize and map out the structure of research in this area. By analyzing co-authorships, keyword connections, and citation patterns, VOSviewer uncovers important topics, identifies leading researchers, and highlights new trends in the field. Ultimately, the goal of this paper is to provide insights that deepen our understanding of the evolving landscape of logistics outsourcing research and help shape future studies in this space.

The main purpose of the paper is the analysis of specific logistical requirements when transporting companion animals. Attention is focused to the obstacles that need to be addressed in the field of animal transport and the logistics associated with their commercial and non-commercial transport. The general conditions and requirements of companion animals transport within the European Union have led to unjustified administrative burdens and costs. The main goal of the contribution is to point out the circumstances on which the safe transport of animals depends, based on the selection of the correct logistics management and the selection of the correct logistics process. Special rules are applied depending on the species and quantity of transported animals. In the process of transporting companion animals, it is important to ensure that live animals entering and leaving the EU, or third countries are healthy, well-being and that the specific import and export conditions are fulfilled in European Union legislation, including all related mandatory acts, documents and data centralization. The article presents sequence of logistic activities in the transportation of companion animals for non-commercial purposes. Logistic activities are divided into two phases. The first phase (preparatory phase) includes activities that the owner of the animal is obliged to perform if he performs the transportation himself or uses a business partner for transportation. The second phase includes activities from loading to unloading the animal. The article presents selected statistics for the transportation of companion animals, too.

Nowadays, due to rapidly changing customer needs, product life cycles are getting shorter, while the number of product variants is increasing, so continuous innovation of the product and the technology related to its production is an important task. Not only the product itself needs to be renewed, but also flexible production technology needs to be developed in accordance with changing customer needs, as a large number of product variants are being produced, which require individual settings, different production operations and real-time tracking. In the case of diversified manufacturing requirements, the application of Industry 4.0 technologies can increase efficiency. The aim is to maintain the smoothness of the manufacturing process, for which matrix production offers a suitably flexible solution. The main tasks of production logistics are the in-plant movement of workpieces between workstations and the supply of workstations with the raw materials, parts, etc. required for the actual production step. The larger workpieces are transported by dedicated AGVs. In the production area, several AGVs can perform their tasks simultaneously, so several material handling tasks occur at the same time. This paper deals with the route planning issues emerging during the movement of AGVs between the workstations in a multi AGV environment. We are following a holistic approach during design, aiming to simultaneously optimize layout, production sequence, and AGV routing.

The main goal of a manufacturing company is to make a profit, which requires efficient in-house processes and smooth process flow. The key tools for increasing productivity and optimizing production are process standardization, workflow efficiency, and the application of the theory of constraints (TOC). Process standardisation leads to the standardisation of workflows and the elimination of variability. TOC focuses on identifying bottlenecks in the process and optimizing them, resulting in cost reduction, increased productivity, and improved enterprise profitability by enhancing process flow. The presented paper describes a case study aimed at analysing selected processes at robotic welding workstations in a selected industrial enterprise. The aim of the paper is to identify opportunities to improve production efficiency at robotic welding workplaces, focusing on standardization of work procedures, more efficient use of production equipment capacity, and improvement of the remuneration system, which has a direct impact on workflow efficiency, process optimization, and the financial performance of the enterprise. The results of the research point to a lack of standardisation of working practices, low utilisation of the equipment capacity (30% below the planned value) and limitations in the remuneration system that hinder the achievement of the full productivity potential. The combination of inefficient use of equipment and working time increases financial costs and limits profitability. An effective bonus system can increase employee motivation, support productivity improvements and contribute to cost reduction. To address these issues, the implementation of standardised work practices, optimisation of equipment utilisation and effective workforce management are needed.

The subject of consideration is to discuss key aspects related to the ergonomics and efficiency of IT systems, particularly in the context of Transport Management Systems (TMS). TMS supports the planning, control, analysis and optimization of flow processes, which translates into better technical resource management and cost reduction. Ergonomic design of IT systems aims to create intuitive and easy-to-use tools that minimize employee effort and reduce the number of mistakes made. This approach leads to increased work efficiency, which is crucial for companies, where process automation can significantly reduce the time needed to complete tasks and increase the efficiency of work. The article is based on the example of the TMS system from AndSoft and presents proposals for improvements of selected aspects of the system operation. The proposed improvements relate to the issue of planning and the creation of a unique feature allowing for cascading replenishment of resources, reducing the time needed to perform daily planning operations. In addition, it is proposed to synchronize two tabs “Orders” and “Availability resources” in order to find unplanned resources faster and assign them to specific transport ordersMoreover, an alert system was proposed to inform about errors made, which will allow for their quick detection and correction. In addition, a vehicle self-diagnosis system is proposed to monitor the technical condition of vehicles in real time. These innovative technological solutions contribute to increasing efficiency, reducing errors, and improving overall management of logistics elements.

This study aimed to assess the efficiency of the railway industry in Central Asia Regional Economic Cooperation (CAREC) 10 member countries. Using data from 2016 to 2018, we set the ten CAREC countries as DMUs and applied the DEA (Data Envelopment Analysis) method to analyze the relative efficiency of each country's railway industry. Input factors considered were railway extension length, number of workers, freight cars, and expenses. Output factors included revenue and total cargo volume. The results revealed that the China Railway Corporation and the Afghanistan Railway Authority consistently demonstrated efficiency over three years, with an efficiency value of 1(100%). Kazakhstan and Uzbekistan also achieved 100% efficiency for one year each. While the Mongolian railway industry showed a slightly higher efficiency index, it was less efficient than China, Afghanistan, Kazakhstan, and Uzbekistan. Findings reveal that the Mongolian railway sector faces significant challenges due to outdated infrastructure, rolling stock, and equipment, which hinders profitability. According to the results of DEA's analysis, it is helpful for Mongolia to choose optimal benchmarking targets to reduce operating costs, improve infrastructure and facilities, and optimize operations to enhance railway efficiency.