Consumer satisfaction can be defined as the user’s response to a service or experience compared to the user’s expectations and perceived practical benefits. After reviewing consumer satisfaction models, it can be argued that there is no single model of consumer satisfaction assessment that is suitable for every service and every region of the world, as the causes and outcomes of satisfaction often vary. The research is original in its methodology: at the beginning, a theoretical research model is presented, then hypotheses are formulated, and correlation, factorial, regression analyses were made, which results confirmed hypotheses. The crop insurance system consists of relations between the state institution regulates insurance activities, farmers, insurers and insurance intermediaries. The aim of this article is to identify the factors that determine consumer satisfaction with crop insurance and to assess their impact. The empirical study found that consumer satisfaction is determined by the factors of recognizable value, functional (process) and technical (result) quality, consumer expectations, and image. The most important factors that determine consumer satisfaction of crop insurance are recognizable value, functional quality, and consumer expectations. Consumer satisfaction can be assessed by the cost paid and the quality received, the quality expected, and the consumers’ evaluation of the services. It was found that the socio-demographic elements of consumers do not have a decisive influence on the factors that determine service satisfaction and consumer satisfaction. It is also established that socio-demographic elements of consumers (farmer experience and insurance experience) have direct statistically significant but weak links with consumer satisfaction.

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.

Local community members play a critical role in the success of conservation projects, which in turn have the potential to influence the perceptions of local people. Relationships matter when it comes to sustainable long-term conservation and community well-being. The study aims to establish the relationship between local communities and wildlife conservation organizations in the context of Phinda Private Game Reserve and the Mnqobokazi community, located in South Africa. Data was collected using the qualitative methods of interviews and focus group discussions. The findings show that a symbiotic relationship between conservation organizations and local community members is critical in conserving the environment. The research indicates that both participation and benefits result in improved perceptions towards the protected area and a strong positive relationship. The accrual of benefits also appears to result in pro-environmental consciousness amongst community members. Several existing studies examine participation or benefit-sharing in community-based tourism in developing nations. However, less is known about the relationships between local communities and conservation organizations and the effect of participation and beneficiation on these relationships. This research narrows this gap in the body of knowledge by qualitatively examining a single case study. The findings add value to global collaborative efforts aimed at achieving positive relationships between communities and conservation management.

This article explores the implications of directive change management, characterized by top-down leadership and minimal employee involvement, on organizational dynamics, employee morale, and job security. This approach's psychological and operational impacts are underscored, emphasizing the imperative of addressing employee perceptions and fostering trust. Strategies for rebuilding trust and enhancing morale post-directive change management are presented, including transparent communication, participative decision-making, and recognition of employee contributions. The significance of enhancing job security through clear policies, open dialogue, and robust mental health and well-being support systems is highlighted. Practices that encourage job dedication are introduced, emphasizing goal alignment, meaningful work design, and a culture of innovation and continuous improvement. Long-term strategies for cultivating a healthy workplace, such as establishing feedback mechanisms, investing in leadership development, and maintaining organizational adaptability, are also discussed. This brief article is an introductory resource for business leaders, managers, and change practitioners seeking to be better equipped with the necessary tools and strategies to navigate the post-implementation effects of directive change management. It is anticipated that this information can assist leaders and organizations in navigating the challenges of directive change management, promoting resilience, employee well-being, and sustainable organizational success.