Material Economy and Logistics 01/2023

Nowadays one of the biggest challenge for modern business entities is the introduction of solutions and assessments of environmental optimization in the supply chain (reducing the resource-intensiveness of the economy) and the search for waste-free solutions (facing the issues of losing the status of waste, by-products or accompanying products). These challenges are built in relation to the goals and scope of the circular economy (CE), which is conducive to the implementation of solutions aimed at sustainable development. The aim of this work is to identify the possibilities of achieving environmental optimization due to the use of digital technologies and the concept of digital supply chains in the conditions shaped by the CE. The adopted research question is: "To what extent can digital supply chains affect the development of CE?"

The article presents the results of research reflecting the essence of optimization in logistics and the requirements related to it. In practice – in the author's opinion – this term is overused due to the lack of awareness that in most decision-making situations, the aim is to rationalize logistics activities and optimization in logistics decisions should consist in clearly defining the criterion and using specific computational model. The article consists of three parts. In the first of them, common features and differences of rationalization and optimization were presented. The second part contains the results of research reflecting the place of optimization models against the background of model typologies. The third part presents logistic optimization models most often used in practice by logistic managers.

One of the priorities of logistics managers is to strive to increase the economic efficiency of logistics processes. The multidimensionality of logistics somehow naturally complicates decision-making and the search for an optimal solution – the optimal logistics decision – is not an unambiguous, obvious undertaking. It is therefore reasonable to define the conditions that must be met in order to talk about making optimal decisions. The described situation is a problematic situation that fundamentally determined the research and the arrangement of the content of the article as the result of this research.

The success of supply chains depends primarily on integrating and coordinating the activities of network participants. Many supplier companies are shifting toward team-based structures to manage the boundaries with their customers. One of the possibilities of the operational implementation of cooperation in the supply chain is the appointment of teams in the network structure. Teamwork is a specific social group, consisting of at least two people, subject to the same impact, consciously interacting with one another, perceiving themselves as members of a specific group and identifying with it, as well as having a common goal, shared norms and creating a characteristic structure (fulfilling complementary roles). Situation caused by COVID-19 forced a change in defining and functioning of supply chains. It is also a moment of very dynamic development of work and cooperation in a remote environment, which impacted the functioning of teamwork in the supply chain. The paper is composed of two parts and aims to orient researchers who are new to collaborative work in supply chain research. The first article is structured as follows: the systematic literature review procedure is presented, then the bibliometric analysis is conducted, an in-depth analysis of journals and articles is performed with use of the Treecloud tool and VOSviewer software to analyse the selected papers.

The aim of the article is to indicate the difference between a publicly available forecasting indicator used in supplier planning and one created specifically for a given company. The authors based on the results of comparative research in the operation of chain stores, forecasting deliveries and their value with the use of various systems supporting the forecasting of product supply. A research hypothesis was adopted that reliable forecasts are crucial in improving order fulfillment and are an important factor influencing customer satisfaction and gaining a competitive advantage.

The subject of consideration in this article are issues related to the need to introduce changes in the management of the European Union's external border with Ukraine in connection with the Russian invasion. The section of the Polish-Ukrainian border has been characterized and border crossings for pedestrian and goods traffic have been indicated. A temporary procedure introduced by the Chief Veterinary Officer regarding the handling of animals accompanying travelers entering the European Union from Ukraine during the armed conflict was presented. The introduction of shortened procedures for crossing the border and importing endangered species of fauna from Ukraine into the European Union was discussed. Available statistics on the number of confiscated CITES species imported from Ukraine in 2019–2022 were analyzed in order to determine the scale of their smuggling from this country. The aim of the article is to indicate the need to introduce changes in the management of the external border of the European Union in connection with the outbreak of war in Ukraine on selected examples.

The aim of the paper is to discuss reasons and barriers to Tier 1 suppliers and customers of the SME sector in Poland focusing on the Łódzkie Province. The first part of the work provides theoretical approach to the identification of circumstances conditioning the development of logistics networks relying on subject-matter literature and data from the reports of Bundesvereinigung Logistik (BVL). The second part of the paper contains author's questionnaire based studies of reasons and barriers to the development of logistics networks in the SME sector in the Łódzkie Province and the characteristics of companies from the SME sector participating in the studies.

The transport demand is increasing year by year. This is because of the increase in production and consumption. The longer the supply chain is, the more likely it is to be disrupted, as all operations involve risks. However, risk in the context of the supply chain and its management has recently been discussed. Unfortunately, no industry is immune to predictable and unpredictable disruptions that affect losses (e.g. loss of goods). From the point of view of carriers, it would be important to be able to predict the occurrence of, for example, damage to the goods. The article focuses on the use of machine learning methods to predict the risk of damage to goods (such as electronics, household appliances or telephones/computers) in road transport. The research used five intelligent methods such as: logistic regression; support vector machine (SVM); decision tree; naive Bayesian classifier; AdaBoost. The aim of the paper is to present the concept and the above-mentioned methods of machine learning, measures assessing the performance of models and the results related to the conducted research. The set goal determined the choice of the research methods – literature analysis and programming were used. The last part of the article presents the results obtained from the analysis of five models. The research established that AdaBoost has the best predictive ability.