Global transformational processes associated with the geopolitical fragmentation of the world, changes in supply chains, and the emergence of threats to food, energy, logistics security, etc. have impacted the increase in the freight traffic volumes through the Ukraine-European Union (Ukraine-EU) land border section. In this context, the transport and logistics infrastructure on this section of the border was inadequate for the growing demand for international freight transport, leading to huge economic, social, and environmental damage to all participants in foreign trade. The aim of this paper is to study the efficiency of the functioning of the transport and logistics infrastructure on the Ukraine-EU border section. The taxonomy used in the paper made it possible to look into economic, security, geopolitical, logistics, transport, legal, and political factors shaping the freight traffic volumes, structure, and routes; their key trends and impact on the generation of freight traffic are described. Statistical analysis of freight traffic by border sections and with respect to border crossing points allowed the identification of bottlenecks in the functioning of the transport and logistics infrastructure and outlining ways to address them. The results of the study will be helpful both to researchers working on the issues of freight transport and to policymakers involved in transport and border infrastructure development.

International logistics supply chain is an important guarantee to support the country to build a new development pattern, this paper aims to propose a new strategy to promote the development of international logistics supply chain through the case study of Ningbo City. On the basis of supply chain theory and international logistics theory, this paper constructs SWOT model to study the case of Ningbo City, and draws the following conclusions: The international logistics supply chain of Ningbo city has the advantages of superior geographical location, perfect logistics infrastructure and strong port resources, and the disadvantages of low logistics informatization level and logistics management mode to be optimized. At the same time, it faces the opportunities of “One Belt and One Road” initiative and the competitive threat of other logistics centers. Adopting strategies such as policy support, strengthening logistics informatization construction and optimizing logistics management mode can ensure the stable development of foreign trade, which is conducive to accelerating the construction of a new development pattern and modern economic system in which domestic and foreign cycles promote each other.

This study aimed to examine and assess the impact of the logistics industry’s environment, entry-level graduates’ characteristics and the logistics and supply chain management (LSCM) program design on the transformation of knowledge and skills at Sohar port in the Sultanate of Oman. The study employed a pragmatic research philosophy involving a structured questionnaire. The sample size included 49 mid-managers from the logistics industry who were working at Sohar Port. The study found that entry-level graduates’ characteristics and LSCM program design positively and significantly influenced the transformation of knowledge and skills. However, the organisational environment had a negative and insignificant impact on the transformation. This study revealed several dimensions that may require further research. It is pertinent to broaden the research scope to other towns, ports, and other countries in the Gulf Council Countries (GCC) to broaden the scope and generalisability of the results. According to the study findings, several recommendations are proposed for the logistics and supply chain sector in Oman to enhance the transformation of knowledge and skills by entry-level graduates, as well as for higher education institutions (HEIs). To meet the sector requirements, HEIs may improve the current university-industry collaborations by increasing the inputs of the industry in designing and developing the LSCM program. The organisational environment must reconsider the knowledge and skills transformation by entry-level graduates in their strategic plan of resources management, which must be emphasised by the remuneration system and career paths incentive. While other studies have explored knowledge and skill transformation in the context of employee training, this study aims to fill a specific research gap by focusing on the transformation of knowledge and skills by entry-level graduates, an area which has not been extensively studied before. Furthermore, this study is unique as it examines the impact of the industry’s environment, entry-level graduates’ characteristics and the LSCM program on the transformation of knowledge and skills within the unique context of Oman. This novel approach provides an opportunity to understand the specific challenges and opportunities faced by entry-level graduates in Oman and suggests strategies for addressing them.

Finding the right technique to optimize a complex problem is not an easy task. There are hundreds of methods, especially in the field of metaheuristics suitable for solving NP-hard problems. Most metaheuristic research is characterized by developing a new algorithm for a task, modifying or improving an existing technique. The overall rate of reuse of metaheuristics is small. Many problems in the field of logistics are complex and NP-hard, so metaheuristics can adequately solve them. The purpose of this paper is to promote more frequent reuse of algorithms in the field of logistics. For this, a framework is presented, where tasks are analyzed and categorized in a new way in terms of variables or based on the type of task. A lot of emphasis is placed on whether the nature of a task is discrete or continuous. Metaheuristics are also analyzed from a new approach: the focus of the study is that, based on literature, an algorithm has already effectively solved mostly discrete or continuous problems. An algorithm is not modified and adapted to a problem, but methods that provide a possible good solution for a task type are collected. A kind of reverse optimization is presented, which can help the reuse and industrial application of metaheuristics. The paper also contributes to providing proof of the difficulties in the applicability of metaheuristics. The revealed research difficulties can help improve the quality of the field and, by initiating many additional research questions, it can improve the real application of metaheuristic algorithms to specific problems. The paper helps with decision support in logistics in the selection of applied optimization methods. We tested the effectiveness of the selection method on a specific task, and it was proven that the functional structure can help the decision when choosing the appropriate algorithm.

In response to the increasing global emphasis on sustainability and the specific challenges faced by small and medium-sized enterprises (SMEs) in China, this study explores the integration of green reverse logistics within these enterprises to enhance their sustainability and competitiveness. The aim of this study is to understand the relationship between reverse logistics, green logistics, and sustainable development. Data analysis was conducted utilizing a combination of descriptive statistics and correlation analysis. A survey of 311 participants examined SMEs’ performance in reverse logistics practices and their initiatives in green logistics and sustainable development. The empirical findings reveal significant progress in reverse logistics practices among SMEs, reducing environmental impact and improving resource efficiency. Moreover, a notable positive correlation was identified between reverse logistics promotion and advancements in green logistics and sustainable development. SMEs’ investment in reverse logistics is closely linked to their efforts in environmentally conscious and sustainable supply chain management. These insights benefit SMEs and supply chain practitioners and offer a valuable reference for future research and practical applications in this field.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.