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.

Under the concept of independent maintenance proposed by the Meteorology, Climatology, and Geophysics Agency (BMKG) for operational equipment, a thorough analysis of its management processes is necessary. Leadership involvement at various levels can affect maintenance outcomes, impacting sustainability. This research creates a thinking model that connects responsible leadership (RL) with sustainable performance (SP) through agile organization (AO) mediation and maintenance management implementation (MMI) in the management of leading operations equipment. The method used was a survey of 366 respondents who were BMKG employees, and explanatory analysis was analyzed based on descriptive statistical analysis using SmartPLS. The research results show that the third hypothesis proposed is acceptable, and the two mediator variables are partial mediation. The discussion of the study results shows some theoretical and practical implications for achieving the goals of SP, where organizations should encourage RL behavior that can implement current practices regarding AO and MMI. The test results show that AO and MMI have a significant role as mediators in encouraging the influence of RL on SP. This study is the first step in examining the relationship of RL to SP using AO and MMI mediation. Furthermore, this model can be developed and analyzed in other sectors or fields to increase knowledge.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.

The need for strategic alignment within HR management increased managers' concern about individual behavior and how this behavior was related to the achievement of goals. In public management, effectively managing employees' performance has been necessary since Weber's bureaucratic administration. The individual performance appraisal is the right tool to assess employees' competencies. Thus, we proposed the following research question: Which factors, as pointed out by theory, have the most significant influence on the individual performance appraisal process? The quantitative method was applied to answer this question, developing and testing a scale via EFA and a hypothetical model via SEM-CB. The results indicated a scale with 25 items able to access the main points of the IPA process and a hypothetical model with 7 constructs that indicate the influence on employee engagement. The main finding is the significant influence of feedback on the whole process. The main theoretical contribution was the construction of the MIPAS scale, and the practical contribution was to identify the points where managers should focus on improving the IPA process with their subordinates.

The purpose of this research is to estimate the differences in sales levels between businesses owned by individuals who self-identify as Indigenous (IE) and those who do not (NIE), as well as between males (ME) and females (WE), and how this intersection may affect their sales levels. To accomplish this, an Analysis of Variance (ANOVA) is used to compare the means between the groups analyzed, and Tukey’s Honestly Significant Differences (HSD) is used to determine the magnitude and direction of these differences. The results of the study show that indigenous-owned businesses have sales that are 26% lower than the general average, while women-owned businesses have sales that are 70.6% lower in the same comparison. In addition, businesses run by indigenous women have sales that are 93.5% lower on average. These findings suggest that the challenges faced by entrepreneurs reflect the structural inequalities observed in other areas of society and highlight the need for public and private policies focused on reducing these gaps.

Organisational culture stands as a fundamental prerequisite for the efficacious operation of any given organisation. The primary aim of this study is to discern potential alterations within the dimensions of organisational culture across the pre-COVID-19, contemporary, and favoured paradigms within the realm of public administration. The data set was obtained from a cohort of 1189 officials in the Czech Republic. The Organisational Culture Assessment Instrument (OCAI) was deployed for the purposes of conducting an online survey. The dominance of the clan archetype across all examined time frames has been corroborated. In addition, a statistically significant manifestation of these dimensions has been determined. In relation to pertinent variables, specifically gender, age, tenure, manager gender, and the dimensions typifying organisational culture, no statistically significant correlations have emerged. Respondents have not reported a sense of work-life imbalance in the aftermath of the pandemic. In summary, it is deduced that the pandemic has not exerted a drastic influence on the metamorphosis of organisational culture within the ambit of public administration. This study provides invaluable information on the repercussions of the pandemic within a sphere that, as an intangible constituent, often goes under-recognised. Mastery of the positioning of dimensions across diverse archetypes is of paramount significance for managers, as it can provide guidance in the cultivation of an apt organisational culture.