As supply chains (SCs) become more complex globally, businesses are looking for efficient business analytics (BA), business intelligence (BI), and artificial intelligence (AI) tools for managing supply-chain risk. The tools and methodologies proposed by the supply-chain risk management (SCRM) literature are mostly based on experts’ judgments, their knowledge, and past data. The expert evaluation-based approach could be partly or fully replaced by AI solutions, increasing objectivity, impartiality, and impersonality, reducing sources of human mistakes, biases, and inefficiencies in SCRM. However, the transition from BA to AI in SCRM is not a self-contained process; though attractive as a vision, it is not straightforward as a management or implementation process. The purpose of this research is to explore and define the conceptual grounds for transitioning from BA to AI in SCRM. The conceptual SCRM structure, its AI suitability, and implementation terms are defined theoretically based on a literature review. A single, in-depth business case study is employed to explore the theoretically defined terms of AI-based SCRM implementation. The proposed conceptual AI-suitable SCRM structure is defined by five principal building blocks: risk events, risk-event indicators, data-processing rules and algorithms, analytical techniques, and risk event probability forecasts. The study concludes that the business environment meets AI-based SCRM-implementation terms of data existence and access. Since data on risk events and negative outcomes are limited for machine learning, experts’ experience and knowledge might be utilised to build initial rules and data-processing algorithms for AI.

The research analysis shows that children in mainstream schools suffered from psychological deterioration (aggressive behaviour, depressive moods, despair about academic underachievement, etc.) when governments implemented measures to manage the COVID-19 pandemic, and children’s education took place remotely for a significant period. This was caused by the lack of social contact, which in turn contributed to the lack of knowledge in individual subjects, a deterioration in physical condition (spinal problems, visual impairment, insufficient muscle development), and the development of specific illnesses related to low physical activity. The research aims to identify the factors of distance learning that may affect student learning achievements. The research methods included an analysis of the scientific literature, and document and content analysis. A summary of the research findings found that the COVID-19 school quarantine had adverse effects on the students’ knowledge, social skills, socialisation, and psychological and physical health. It also caused macro- and micro-economic problems. In summary, the research demonstrated that distance education resulted in a decline in the students’ achievements and knowledge, miscommunication with their peers and conflict situations. Because of that, there are health-related concerns and additional financial challenges for parents and educational institutions organising distance education. Households also experienced additional expenditure on the infrastructure necessary for distance learning and tutoring services.

Baltic Seaports are a part of the sustainable global transport infrastructure. The main competitors of the Baltic countries in Baltic Sea region are the ports of Lithuania, Latvia, and Estonia. The ports of all three Baltic States are important transit corridors, connecting not only East and West, but also South and North. Periodical investments, modernization, and the construction of new terminals allow the Port of Klaipeda to successfully compete with neighbouring ports and strive for leadership positions. Thus, the aim of our study is to investigate the competitive environment of the Baltic Sea region. We use systematization, grouping, summarization of the scientific literature, data collection, comparison, financial analysis, and capacity calculation. The main results show that the Port of Klaipeda, a seaport on the eastern Baltic coast, is an important hub of the East-West (IXB) transport corridor, connecting roads and sea routes in this direction. With the accession of new members, including Lithuania, to the EU in 2004, the Baltic Sea became the internal Sea of the Union. Many Baltic seaports belong to the same system and organizations (ESPO, BPO). EU ports policy provides them with equal requirements for security, transport regulation, environmental protection, anti-air pollution, and sustainable development. The results obtained enable exploration perspectives. This includes a feasibility study for port development and attracting new investment from foreign capital markets in the Baltic Sea region.

For more than two decades, scholars have been escalating asymmetric information issues in megaproject management linking them to enhanced public debt concerns. Most megaprojects turn out to be a burden on economy when constructions are completed. Authorities, meanwhile, continue to promote the advancement of megaprojects with overly optimistic public messages on expected socio-economic benefits. A combination of expertise in the topic, in-depth literature analysis, independent cost-benefit reassessment, and empirical survey of related documentation of three EU transport megaprojects shows political implications to be the essential causes of information asymmetries in megaproject management. Socio-economic over-estimations imply to be useful for obtaining and securing funding commitments at the political level, but then the real project value is often omitted from the assessment. This work takes a wider, strategic approach beyond the usual socio-economic reasoning. The article argues that socio-economic assessment practice is too narrow to grasp the full potential impact of a megaproject. Therefore, a strategic assessment should be performed by public authorities along with an appropriate funding mechanism. This work contributes to science by suggesting a direction to more constructive discussions between scholars and politicians that could lead to more effective future decisions on the overall sustainability of economies.

Distance education has influenced the organization of education at the level of systems and schools, the change in the specificity of teachers’ activities, the change in pupils’ learning, and, undoubtedly, the attainment of learning outcomes. The aim of this study is to determine what factors have affected pupils’ learning outcomes in the course of distance learning during the COVID-19 pandemic, from the perspective of pupils, pupils’ parents, and teachers. A quantitative study was conducted in order to reveal the impact of distance learning. The positive and negative aspects of distance education became clear. As regards the negative consequences of distance teaching/learning, the results of the study showed that in the teachers’ opinion, the pupils’ learning outcomes generally deteriorated. The positive factors of distance learning influencing the learning process and thus learning outcomes were a comfortable environment, the possibility to use a variety of learning aids available at home, and the possibility to view the lesson records at a time convenient for pupils.

This study analyzed the widespread distance teaching/learning impact in the context of the COVID-19 pandemic and assessed distance teaching/learning’s effects on students’ intelligence. The distance teaching/learning impact results were evaluated based on the extensive sample tests conducted by applying the Wechsler Abbreviated Scale of Intelligence (WASI) methodology. The tests conducted in January–September 2022 were compared with those conducted in the same age groups in 2017, 2018, 2019, and 2021. The research data were processed in the following three stages: Stage I. Overview of the general situation of the research data concerning the variables. The descriptive statistics method was applied when calculating the percentages representing the students’ verbal, non-verbal, and general IQ. Stage II. Estimation of the statistically significant differences between the independent variables. Stage III. Review of the research data. The descriptive statistics method was applied, and the WASI methodology was used to assess the effects of distance teaching/learning on the IQ of 1–12-grade students in the 2017–2019 and 2021–2022 periods. The test sample size was over 2000 respondents who engaged in the study questionnaires and surveys. The effects of distance teaching/learning were assessed in many relevant aspects to identify which factors considerably impacted students’ intelligence during distance teaching/learning. Also, a more extensive analysis of these factors was performed to reveal which of them, during the period of distance teaching/learning, (1) greatly influenced students’ verbal IQ, (2) significantly impacted students’ non-verbal IQ, and (3) had a substantial impact on students’ general IQ. The results of the 2021 tests, conducted after the announcement of the official end of distance teaching/learning due to the pandemic, showed that distance teaching/learning affected students’ IQ positively. Such results can be associated with an increased number of self-study independent tasks, which in turn influenced the growth of creativity. The IQ tests of students born in 2009 revealed that the total IQ of test participants gradually decreased in 2018, 2019, 2021, and 2022 respectively. These results might have been influenced by the then-prevalent education system, favoring educational programs that do not promote IQ development. It is believed that the parents of children born in Lithuania in 2009 were provided more favorable conditions for raising children than the EU standards. Notably, the IQ of students of aged 6–15 tended to grow from 2017 to 2021, but in 2022, a dramatic drop was observed. The restricted socialization and deficiency of live communication could pose one of the primary reasons for the drop in their IQ. The analysis also showed that distance teaching/learning negatively affected all student groups by age. Age groups differed to a positive and negative extent; e.g., during the research, the most considerable negative effect in the student group aged 6–10 years and the uniqueness of students born in 2009, i.e., the overall highest average IQ of students born that year (134 in 2018), were noticed. However, during the five years afterward, students’ IQs decreased (119 in 2022). The analysis of the socio-economic environment allowed for determining a positive trend that could have been influenced by the most favorable program for families established by the government at that time. Furthermore, the study concluded that distance learning had an apparent adverse effect on the IQ of individuals in the 6–19 age group.