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.

The global significance of the energy crisis and the need for a sustainable European electricity system have intensified interest in renewable energy sources. This study aims to explore the attitudes toward solar energy systems among the population of the North Transdanubian region, which is crucial for companies in the region specializing in solar system installation. The research sheds light on trends in energy prices, potential strategies for addressing the energy crisis, and the regulatory environment for solar systems in Hungary and Austria, focusing on the Burgenland region. The study is divided into two main sections: secondary and primary research. The secondary research presents various applications of renewable energy sources, especially solar energy, and examines energy pricing trends in the two countries, with particular emphasis on the payback period and the impact of changes in energy prices. The primary research is also divided into two parts: the first examines the satisfaction of customers who already use solar systems, and the second focuses on the attitudes of potential customers toward solar investments. The findings provide a comprehensive view of both current users’ and prospective investors’ perspectives on solar energy systems. The practical significance of this research lies in identifying development opportunities for companies, advancing energy efficiency goals, and supporting sustainability efforts.

Energy systems face serious difficulties due to economic policy uncertainty, which affects consumption trends and makes the shift to sustainability more difficult. While adjusting for economic growth and carbon emissions, this study examines the dynamic relationship between economic policy uncertainty and energy consumption (including renewable and nonrenewable) in China from 1985Q1 to 2023Q4. The research reveals the frequency-specific and time-varying relationships between these variables by employing sophisticated techniques such as Wavelet Cross-Quantile Correlation (WCQC) and Partial WCQC (PWCQC). Economic policy uncertainty and energy consumption do not significantly correlate in the short term; however, over the long term, economic policy uncertainty positively correlates with renewable energy consumption at medium-to-upper quantiles, indicating that it may play a role in encouraging investments in sustainable energy. On the other hand, EPU has a negative correlation with nonrenewable energy usage at lower quantiles, indicating a slow move away from fossil fuels. These results are confirmed by robustness testing with Spearman-based WCQC techniques. The study ends with policy recommendations to maximize economic policy uncertainty’s long-term impacts on renewable energy, reduce dependency on fossil fuels, and attain environmental and energy sustainability in China.

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.

The study examines the acceptance and sustainability of vegetarian, vegan, and flexitarian diets, focusing on the health and environmental benefits of reducing animal-derived proteins. Our objective was to investigate the level of acceptance of these dietary trends across different age groups and health statuses and understand how sustainability awareness and health consciousness impact dietary decisions. We used a mixed-method approach to achieve this, conducting eight in-depth interviews and a survey with 329 participants from various demographic backgrounds. Our qualitative analysis revealed that individual and family health consciousness, along with sustainability considerations, play a significant role in dietary choices, particularly among younger generations who are more open to sustainable eating. Quantitative results show that access to information and educational resources strongly influences dietary decisions, further supporting the spread of environmentally conscious eating habits. The practical significance of our research lies in highlighting the importance of educational campaigns and public health policies that can foster broader societal acceptance of sustainable diets. Educational institutions and community organizations can help facilitate the transfer of knowledge necessary for adopting such diets. Our findings emphasize the role of targeted communication strategies in increasing awareness of the benefits of plant-based diets. Furthermore, these insights underline the potential of policy interventions to make sustainable food choices more accessible and appealing to a wider population. Future research could focus on exploring economic incentives and examining long-term health and environmental outcomes associated with these diets.