The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI’s capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.

With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.

This study explores the dynamic relationship between ethical human resources management (HRM) strategies, the level of commitment an employee feels towards their organization, and their job performance, paying particular attention to how employees’ perceptions of the support they receive from their organization can influence these interactions, especially during challenging times. Drawing on a sample of full-time non-executive Indonesian employees, the research employs descriptive statistics for initial data analysis, followed by structural equation modeling (SEM) to test the proposed hypotheses rigorously. The investigation reveals a positive relationship between ethical HRM and employee performance (EP) and organizational commitment (OC). Additionally, OC emerges as a pivotal mediator in the ethical HRM-EP link. Notably, employees’ organizational support perception (EOSP), often assumed to enhance positive organizational outcomes, displays a surprising negative moderating effect when combined with OC, suggesting a more intricate relationship than traditionally posited. These findings enhance our comprehension of how ethical HRM practices function in times of crisis, questioning conventional beliefs regarding the influence of organizational support. The study’s methodological approach, combining descriptive and advanced statistical analyses, provides a robust framework for understanding these complex relationships. This research holds significant implications for HRM practices, particularly in crisis response and management, indicating a need for nuanced support strategies that reflect the complexity of employee-organization dynamics.

This bibliometric review evaluates the research progress and knowledge structure regarding the impact of supporting facilities on halal tourism development. Using the Scopus database and bibliometric analysis with the “bibliometrix” package in R, the study covers the period from 2016 to 2023. The search, employing keywords like “halal tourism,” “facilities,” “infrastructure,” and “local support,” identified 26 relevant publications. The findings highlight a limited body of research, with the Journal of Islamic Marketing being the most active publisher in this area, contributing six articles. Indonesia emerges as a leading contributor to halal tourism research, driven by its significant Muslim population and the economic potential of this niche market. Key facilities, such as mosques, musholla, and high-quality halal food options, are identified as crucial factors influencing Muslim travelers’ destination choices. This review provides a comprehensive overview of the current research landscape on supporting facilities in halal tourism and highlights opportunities for future investigation to further enrich the field.

Concerns about public food safety are comparatively common in the Chinese food distribution industry. A dearth of expertise and scarce resources lead to frequent instances of incapacity and inadequate oversight, which negatively affect stakeholders in the circulation industry. The main challenges to food supervision are the need for more alignment between the technical specifications, comprehensiveness, and continuity of the existing food safety supervision legislation and the real circumstances facing the regulatory agencies. Despite the circulation field’s critical position in food safety regulation, its complex and variable characteristics make it challenging to implement and manage. There exist notable concerns over inadequate food safety standards and supervisory frameworks, vagueness in enforcing rules, and insufficient workforce and technical know-how in food safety supervision. The opportunities for regulating the food business with the government’s focus and attention considerably outweigh the obstacles that lie ahead. The growth of the food business needs to be viewed in the larger framework of the country’s economic development. Professional involvement and collaboration with technical departments can help regulatory bodies tackle non-compliant actions in the market circulation process in a timely way, resulting in a more evidence-based and responsive regulatory approach. Establishing a healthy equilibrium and elucidating the relationship between oversight and the food business will be crucial in the future.

This study aims to structure guidelines for an intervention model from the perspective of Integral Project Management to improve the competitiveness level of cacao associations in south region of Colombia. The research followed a mixed-method approach with a non-experimental cross-sectional design and a descriptive scope. The study employed a stage-based analytical framework which included: identifying the factors influencing the competitiveness of the cacao sector; grouping these factors under the six primary determinants of competitiveness with reference to Porter’s Diamond Model; and proposing guidelines for an intervention model to enhance the competitiveness of the studied associations through project management. The first stage was conducted via literature review. The second stage involved primary data collected through surveys and interviews with the associations, members, and cacao sector experts in Huila. The third stage entailed grouping the factors within the main determinants that promote and limit the competitiveness of the cacao sector in the context of Porter’s Diamond Model. Based on the analysis of the corresponding restrictive and promoting factors, strategic recommendations were formulated for the various sector stakeholders on the measures that can be adopted to address restrictive factors and maintain promoting factors to enhance and sustain the sector's competitiveness.