In today’s rapidly evolving organizational landscape, understanding the dynamics of employee incentives is crucial for fostering high performance. This research delves into the intricate interplay between moral and financial incentives and their repercussions on employee performance within the dynamic context of healthcare organizations. Drawing upon a comprehensive analysis of 226 respondents from three healthcare organizations in Klang Valley, Peninsular Malaysia, the study employs a quantitative approach to explore the relationships between independent variables (career growth, recognition, decision-making, salary, bonus, promotion) and the dependent variable of employee performance. The research unveils that moral incentives, including career growth, recognition, and decision-making, significantly impact employee performance. Professionals motivated by opportunities for growth, acknowledgment, and participation in decision-making demonstrate heightened engagement and commitment. In the financial realm, competitive salaries, performance-based bonuses, and transparent promotion pathways are identified as crucial factors influencing employee performance. The study advocates a holistic approach, emphasizing the synergistic integration of both moral and financial incentives. Healthcare organizations are encouraged to tailor their incentive structures to create a supportive and rewarding workplace, addressing the multifaceted needs and motivations of healthcare professionals. The implications extend beyond academia, offering practical guidance for organizations seeking to optimize workforce dynamics, foster job satisfaction, and ensure the sustainability of healthcare organizations.

This study delves into the role of pig farming in advancing Sustainable Development Goal (SDG) 8—Decent work and economic growth in Buffalo City, Eastern Cape. The absence of meaningful employment opportunities and genuine economic progress has remained a significant economic obstacle in South Africa for an extended period. Through a mixed-method approach, the study examines the transformative impact of pig farming as an economic avenue in achieving SDG 8. Through interviews and questionnaires with employed individuals engaged in pig farming in Buffalo City, the study further examines pig farming’s vital role as a source of decent work and economic growth. The study reveals inadequate government support and empowerment for pig farming in Buffalo City despite pig farming’s resilience and potential in mitigating socio-economic vulnerabilities and supporting community’s livelihoods. To enhance pig farming initiatives, this study recommends government’s prioritization of an enabling environment and empowerment measures for the thriving of pig farming in Buffalo City. By facilitating supportive policies and infrastructures, the government can empower locals in Buffalo City to leverage pig farming’s potential in achieving SDG 8.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

The introduction of artificial intelligence (AI) marks the beginning of a revolutionary period for the global economic environments, particularly in the developing economies of Africa. This concept paper explores the various ways in which AI can stimulate economic growth and innovation in developing markets, despite the challenges they face. By examining examples like VetAfrica, we investigate how AI-powered applications are transforming conventional business models and improving access to financial resources. This highlights the potential of AI in overcoming obstacles such as inefficient procedures and restricted availability of capital. Although AI shows potential, its implementation in these areas faces obstacles such as insufficient digital infrastructure, limited data availability, and a lack of necessary skills. There is a strong focus on the need for a balanced integration of AI, which involves aligning technological progress with ethical considerations and economic inclusivity. This paper focuses on clarifying the capabilities of AI in addressing economic disparities, improving productivity, and promoting sustainable development. It also aims to address the challenges associated with digital infrastructure, regulatory frameworks, and workforce transformation. The methodology involves a comprehensive review of relevant theories, literature, and policy documents, complemented by comparative analysis across South Africa, Nigeria, and Mauritius to illustrate transformative strategies in AI adoption. We propose strategic recommendations to effectively and ethically utilize the potential of AI, by advocating for substantial investments in digital infrastructure, education, and legal frameworks. This will enable Africa to fully benefit from the transformative impact of AI on its economic landscape. This discourse seeks to offer valuable insights for policymakers, entrepreneurs, and investors, emphasizing innovative AI applications for business growth and financing, thereby promoting economic empowerment in developing economies.

Using a qualitative research methodology and exploratory approach to collect data, this study assessed the effects of dependency syndrome within Africa’s international relations and its repercussions for achieving sustainable development. The collected data were analysed using document and content analysis techniques. The study revealed that dependency syndrome within Africa’s international relations has led to aid dependency, political violence, and poverty. It has promoted laziness and an inferiority complex that affects the working conditions of Africans. Further, it has promoted corruption and affected the rule of law for good governance; yet, sustainable development cannot occur without it. Moreover, dependency syndrome has inhibited innovation and led to the destruction of the local industries that are key to achieving sustainable development. The results of the study found that dependency syndrome has prevented the development of a robust transport network system that could promote African trade relations, which would lead to sustainable development. The results also posited that chronic poverty and underdevelopment in Africa are perpetuated by the dependency syndrome within Africa’s international relations. The study recommended that Africa needs to overcome dependency syndrome and reform her international relations with external world. This would require establishing a continental sovereignty that enables the continent to have one common foreign policy within its planning diplomacy endeavours.

Pattaya City is a well-known tourist destination in Thailand, famous for its beautiful beachfront, lively nightlife, and stunning natural scenery. Since 2019, the Eastern Special Development Zone Act, the so-called EEC (Eastern Economic Corridor), has positioned the city as a focal point for Meetings, Incentives, Conferences, and Exhibitions (MICE), boosting its tourism-driven economy. Infrastructure improvements in the region have accelerated urban development over the past decade. However, it is uncertain whether this growth primarily comes from development within existing areas or the expansion of urban boundaries and what direction future growth may take. To investigate this, research using the Cellular Automata-Markov model has been conducted to analyze land use changes and urban growth patterns in Pattaya, using land use data from the Department of Land for 2013 and 2017. The findings suggest an upcoming city expansion along the motorway, indicating that infrastructure improvements could drive rapid urbanization in coastal areas. This urban expansion emphasizes the need for urban management and strategic land use planning in coastal cities.