The maize commodity is of strategic significance to the South African economy as it is a stable commodity and therefore a key factor for food security. In recent times climate change has impacted on the productivity of this commodity and this has impacted trade negatively. This paper explores the intricate relationship between climatic factors and trade performance for the South African maize. Secondary annual time series data spanning 2001 to 2023, was sourced from an abstract from Department of Agriculture, Land Reform and Rural Development (DALRRD) and World Bank’s Climate Change Knowledge Portal. Autoregressive Distributed Lag (ARDL) cointegration technique was used as an empirical model to assess the long-term and short-term relationships between explanatory variables and the dependent variable. Results of the ARDL model show that, average annual rainfall (β = 2.184, p = 0.056), fertilizer consumption (β = 1.919, p = 0.036), gross value of production (β = 1.279 , p = 0.006) and average annual surface temperature (β = −0.650, p = 0.991) and change in temperature for previous years, (β = −0.650, p = 0.991) and the effects towards coefficient change for export volumes, (β = 0.669, p = 0.0007). In overall, as a recommendation, South African policymakers should consider these findings when developing strategies to mitigate the impacts of some of these climatic factors and implementing adaptive strategies for maize producers.

This study investigates how financial cognitive abilities influence individual investors’ intentions to engage in the stock market, particularly considering the mediating role of financial capability. It seeks to address the gaps in understanding the factors that drive investors’ participation in emerging markets like Pakistan, highlighting the importance of financial knowledge, financial planning, and financial satisfaction and financial capability. Data were collected from 377 individual investors through a self-administered questionnaire using a cross-sectional design and non-probability convenience sampling approach. Results reveal that financial knowledge affects investors’ intentions both directly and indirectly, with financial capability serving as a partial mediator. Financial planning influences intentions indirectly through complete mediation, while financial satisfaction affects intentions in both direct and indirect ways, with partial mediation. The study provides valuable insights for the researchers, individual investors, governmental officials, policymakers, and stock market regulators in context of emerging economies like Pakistan, highlighting key determinants of stock market participation.

This paper explores the ritual practices associated with Beiyuan Tribute Tea production in Jianzhou, Fujian, China. Beiyuan Tribute Tea, a historically significant tea, originated in the Tang Dynasty, flourished during the Song Dynasty, and experienced a decline in the Ming Dynasty, reproduced in contemporary times. The tea’s production involved intricate rituals that not only enhanced its quality but also embedded it deeply into the socio-cultural and religious fabric of the time. These rituals, encompassing aspects of religious reverence, craftsmanship, and social etiquette, played a crucial role in the tea’s esteemed status as a tribute to Chinese emperors in history. The study utilized ethnographic methods, including participant observation, in-depth interviews with 17 people, and document analysis, to capture the rich, contextual details of the tea production process. The study delves into the historical context, production techniques, and symbolic meanings of the rituals, highlighting their impact on the broader cultural heritage of Chinese tea. The recent revival efforts of these traditions underscore their enduring significance and offer insights into the cultural continuity and adaptation in contemporary tea practices.

This research addresses environmental, ethical, and health concerns related to high meat consumption, and aims to identify key predictors that encourage a shift towards sustainable diets among young adults. A cross-sectional survey involving 340 students from ten Malaysian universities was conducted using a structured questionnaire. The findings indicate that attitudes, subjective norms, perceived behavioral control, and personal norms significantly predict the intention to adopt plant-based diets. These results have practical implications, suggesting that policymakers, educators, and health professionals should create supportive environments and educational programs that emphasize the benefits of plant-based diets and equip students with the necessary knowledge and skills. Theoretically, the study reinforces the TPB framework’s applicability in understanding dietary behaviors and underscores the importance of personal and social factors in shaping dietary intentions. Ultimately, promoting plant-based diets among university students necessitates a comprehensive approach and strategy addressing attitudes, social norms, perceived control, and personal values. By leveraging these insights, stakeholders can foster sustainable and healthy eating practices among young adults, contributing to broader environmental and public health objectives for sustainable development.

Electricity consumption in Europe has risen significantly in recent years, with households being the largest consumers of final electricity. Managing and reducing residential power consumption is critical for achieving efficient and sustainable energy management, conserving financial resources, and mitigating environmental effects. Many studies have used statistical models such as linear, multinomial, ridge, polynomial, and LASSO regression to examine and understand the determinants of residential energy consumption. However, these models are limited to capturing only direct effects among the determinants of household energy consumption. This study addresses these limitations by applying a path analysis model that captures the direct and indirect effects. Numerical and theoretical comparisons that demonstrate its advantages and efficiency are also given. The results show that Sub-metering components associated with specific uses, like cooking or water heating, have significant indirect impacts on global intensity through active power and that the voltage affects negatively the global power (active and reactive) due to the physical and behavioral mechanisms. Our findings provide an in-depth understanding of household electricity power consumption. This will improve forecasting and enable real-time energy management tools, extending to the design of precise energy efficiency policies to achieve SDG 7’s objectives.

The Agriculture Trading Platform (ATP) represents a significant innovation in the realm of agricultural trade in Malaysia. This web-based platform is designed to address the prevalent inefficiencies and lack of transparency in the current agricultural trading environment. By centralizing real-time data on agricultural production, consumption, and pricing, ATP provides a comprehensive dashboard that facilitates data-driven decision-making for all stakeholders in the agricultural supply chain. The platform employs advanced deep learning algorithms, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to forecast market trends and consumption patterns. These predictive capabilities enable producers to optimize their market strategies, negotiate better prices, and access broader markets, thereby enhancing the overall efficiency and transparency of agricultural trading in Malaysia. The ATP’s user-friendly interface and robust analytical tools have the potential to revolutionize the agricultural sector by empowering farmers, reducing reliance on intermediaries, and fostering a more equitable trading environment.