The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.

Universities play a crucial role in supporting sustainable development. In recent decades, indicator-based assessment tools have emerged to quantify universities’ efforts towards sustainability. The most widely known is the UI GreenMetric World University Rankings (UI-GWUR): In our paper, we examine the sustainability performance of the three greenest Hungarian universities. The University of Pécs, the University of Szeged and the University of Sopron were among the top 200 higher education institutions (HEIs) in the UI-GWUR in 2023, which proves that they have successfully integrated sustainable development into the components of their system. The aim of the paper is to identify the sustainability measures implemented by the three-top Hungarian HEIs. Their experiences shed light on how it is possible to move forward in the UI GWUR for a Hungarian higher education institution. In order to evaluate the sustainability efforts of the universities, the UI GWUR database was first examined. The websites and sustainability reports of the three universities were also analyzed to gain insight into their activities. Identifying the sustainability actions of the three institutions will help other universities to successfully plan and implement their sustainability initiatives. In the last part of our paper, we evaluate how the three Hungarian universities communicate sustainability through their websites. The results show that advancement in the UI Green Metric World University Rankings primarily requires conscious planning, which means a deeper understanding of the ranking methodology on the one hand, and a clear strategy creation and implementation on the other hand.

Background and introduction: The East and Southeast Asian newly industrialized economies have shown spectacular economic development by their export-oriented development policies during recent decades, which resulted in not only economic wealth but enabled them to be technology exporters and investors. Their products, their flagship brands today are well-known and recognized throughout the world. It is not surprising that the Hungarian government—by its Hungarian Eastern Opening strategy—intended to focus on these economies, even though that with most of them there were intensive and broad co-operation in the fields of business, investment, culture, education and tourism. The new strategy gave a focus on increasing the diplomatic and trade relationship with the wider region, new embassies and trade representation offices were opened or re-opened in several locations with the view of intensifying the business and the people-to-people contacts. Even though the pandemic of Covid 19 and the energy crisis caused disruption in international trade, it can be said the trade and investment relations with these economies have still been growing, especially on the import side. The prospects of the growth of Hungarian exports to these destinations are modest which is hindered by the huge geographic distance, the peculiar consumer preferences, the merely different market conditions and the sharp competition. Objective: The aim of this paper to illustrate by statistical figures the state of the trade and investment relations between Hungary and the Republic of Korea, Taiwan, Singapore and Thailand. Methodology: Bibliographic and data analysis, focusing on the relevant international and Hungarian literature and databases, especially the trade and investment statistics of the Hungarian Central Statistical Office (HCSO/KSH).

This study investigated the variability of climate parameters and food crop yields in Nigeria. Data were sourced from secondary sources and analyzed using correlation and multivariate regression. Findings revealed that pineapple was more sensitive to climate variability (76.17%), while maize and groundnut yields were more stable with low sensitivity (0.98 and 1.17%). Yields for crops like pineapple (0.31 kg/ha) were more sensitive to temperature, while maize, beans, groundnut, and vegetable yields were less sensitive to temperature with yields ranging from 0.15 kg/ha, 0.21 kg/ha, 0.18 kg/ha, and 0.12 kg/ha respectively. On the other hand, maize, beans, groundnut, and vegetable yields were more sensitive to rainfall ranging from 0.19kg/ha, 0.15kg/ha, 0.22 kg/ha, and 0.18 kg/ha respectively compared to pineapple yields which decreased with increase rainfall (−0.25 kg/ha). The results further showed that for every degree increase in temperature, maize, pineapple, and beans yields decreased by 0.48, 0.01, and 2.00 units at a 5 % level of significance, while vegetable yield decreased by 0.25 units and an effect was observed. Also, for every unit increase in rainfall, maize, pineapple, groundnut, and vegetable yields decreased by 3815.40, 404.40, 11,398.12, and 2342.32 units respectively at a 5% level, with an observed effect for maize yield. For robustness, these results were confirmed by the generalized additive and the Bayesian linear regression models. This study has been able to quantify the impact of temperature on food crop yields in the African context and employed a novel analytical approach combining the correlation matrix and multivariate linear regression to examine climate-crop yield relationships. The study contributes to the existing body of knowledge on climate-induced risks to food security in Nigeria and provides valuable insights for policymakers, farmers, government, and stakeholders to develop effective strategies to mitigate the impacts of climate change on food crop yields through the integration of climate-smart agricultural practices like agroforestry, conservation agriculture, and drought-tolerant varieties into national agricultural policies and programs and invest in climate information dissemination channels to help consider climate variability in agricultural planning and decision-making, thereby enhancing food security in the country.

This paper conducts a bibliometric visual analysis of the application of the Unified Theory of Acceptance and Use of Technology (UTAUT) in education, using CiteSpace software. Drawing on data from the Web of Science, the study explores research trends and influential works related to UTAUT from 2008 to 2023. It highlights the growing use of educational technologies such as mobile learning and virtual reality tools. The analysis reveals the most cited articles, journals, and key institutions involved in UTAUT research. Furthermore, keyword analysis identifies research hot spots, such as artificial intelligence and behavioral intentions. This study contributes to the understanding of how UTAUT has been used to predict technology adoption in education and provides recommendations for future research directions based on emerging trends in the digital learning environment.

Leadership behavior is a critical component of effective management, significantly influencing organizational success. While extensive research has examined key success factors in road management, the specific role of leadership behaviors in road usage charging (RUC) management remains underexplored. This study addresses this gap by identifying and analyzing leadership behavior dimensions and their impact on management performance within the RUC context. Using a mixed-methods approach, focus group discussions with industry practitioners were conducted to define eight leadership behavior dimensions: Central-Level Leadership Guidance (LE1), Local-Level Leadership Guidance (LE2), Central-Level Leadership Commitment (LE3), Local-Level Leadership Commitment (LE4), Subordinate Understanding from Central-Level Leadership (LE5), Subordinate Understanding from Local-Level Leadership (LE6), Work Motivation (LE7), and Understanding Rights and Obligations (LE8). These dimensions were further validated through a quantitative survey distributed to 138 professionals involved in RUC management in Vietnam, with the data analyzed using structural equation modeling (SEM) and partial least squares (PLS) estimation. The findings revealed that LE3 (Central-Level Leadership Commitment) had the strongest direct impact on management performance (MP) and mediated the relationships between other leadership dimensions and management outcomes. This study contributes to the theoretical understanding of leadership in RUC management by highlighting the centrality of leadership commitment and offering practical insights for improving leadership practices to enhance organizational performance in infrastructure management.

The aim of the research is to prove that nowadays the role of higher education, its impact on “territorial capital” and the factors of their competitiveness measurement have changed. Competitiveness should no longer be measured only in terms of rankings between higher education institutions, but also in terms of their role in territorial capital. Examining the extension of a competitiveness measurement model developed for small and medium-sized enterprises to the field of higher education can be exciting because the competitive situation between higher education institutions is strengthening, and its aspects are not limited to winning tender funds and the competition for students. The subject of this study is the Central European higher education in general and the Hungarian higher education specifically. Higher education as it appears in regional strategic documents, and the regional, third mission role of higher education institutions appearing in their strategic documents. In terms of methodology: the first part of the paper is based on document and content analysis. In the second part of the paper, institutional characteristics that may influence competitiveness are identified in the case of a Hungarian higher education institution with SME characteristics. The research concludes that the impact on territorial capital, together with the traditional characteristics of higher education and its third missionary role, may constitute the competitiveness of a given institution. If the impact of higher education institutions on location could be measured uniformly, competition between institutions would be more transparent and the role of the region would be strengthened.

Traditional shipping plays a crucial role in the national sea transportation system, serving inland areas, remote areas, and outer islands that are widely distributed throughout the country. However, there is still limited research on the problems of traditional shipping empowerment and its implementation. This research aims not only to analyze the obstacles encountered in empowering traditional shipping but also the implementation of the traditional shipping grant program. This study employed a quantitative descriptive approach, utilizing a likert scale, to analyze the issues that arise in the empowerment of traditional shipping. Additionally, for policy implementation analysis, the Hellmut-Wollmann policy analysis was used. The findings indicate that the most significant issues arise in the area of human resource development, such as a lack of competent teaching staff, insufficient short courses, complicated testing procedures, and the lack of crew certification. In the ex-ante stage, the variable of empowering traditional shipping transportation programs experienced the highest implementation rate. During the ongoing stage, the variable empowering traditional shipping services achieved the highest implementation score. And in the ex-post stage, traditional shipping services had the highest implementation score. This paper emphasizes the significance of collaboration and coordination among all levels of government, from the central to the local, in order to effectively implement the traditional shipping empowerment program. These findings also highlight the necessity of extending the traditional shipping grant program while making improvements in areas such as ship safety management regulations, the management and supply of traditional shipping terminals, the division of transportation types, and route determination policies.