Administrative Sciences

The global maritime and logistics sectors are undergoing rapid digital transformation driven by emerging technologies such as automation, the Internet of Things (IoT), and blockchain. Artificial Intelligence (AI), with its ability to analyze complex datasets, predict operational patterns, and optimize resource allocation, offers a transformative potential beyond the capabilities of conventional technologies. However, mixed results are shown in its implementation. This study examines the current state of AI applications to unlock higher levels of efficiency and competitiveness in logistics firms. A mixed-methods approach was employed, combining surveys from logistics companies with in-depth interviews from key stakeholders in ports and logistics firms to triangulate insights and enhance the validity of the findings. Our results reveal that while technologies such as automation and digital tracking are increasingly utilized to improve operational transparency and cargo management, AI applications remain limited and largely experimental. Where implemented, AI contributes to strategic decision-making, predictive maintenance, customer service enhancement, and cargo flow optimization. Nonetheless, financial conditions, data integration challenges, and a shortage of AI-skilled professionals continue to impede its wider adoption. To overcome these challenges, this study recommends targeted investments in AI infrastructure, the establishment of collaborative frameworks between public authorities, financial institutions, and technology-driven Higher Education Institutions (HEIs), and the development of human capital capable of sustaining AI-enabled transformation. By strategically leveraging AI, Oman can position its ports and logistics sector as a regional leader in efficiency, innovation, and sustainable growth.

In this paper, we examine the existing artificial intelligence policy documents in aviation for the following three regions: the United States, the European Union, and China. These global economic leaders were selected for their dominance in economic activity; as a result, their influence on aviation policy direction is a logical assumption. Historically, the aviation industry has always been a first mover in adopting technological advancements. This early adoption offers valuable insights because of its stringent regulations and safety-critical procedures. Consequently, the aviation industry provides an optimal platform to address AI vulnerabilities through its stringent regulations, standardized processes, and certification of new technologies. Our research aims to compare AI regulations across these regions to guide other sectors in shaping effective policies. The findings of our comparative analysis show that there are vastly differing approaches to the application of AI regulations in the aviation sector, thus weakening desired prospects for global cooperation and worsening existing geopolitical tensions. Therefore, we propose a hybrid model approach as a way forward. Under this model, regions maintain their distinctive AI policies but collaborate on high-risk aviation applications through joint working groups, shared safety intelligence, or mutual recognition agreements. This would preserve incentives for innovation but also reduce regulatory friction.

This study examines outcomes associated with a short-term intensive pedagogical experience aimed at developing social entrepreneurship competencies among university students at an Ashoka U–affiliated institution in Mexico. The program, Semana Tec de Agencia de Cambio, is a five-day experiential learning experience grounded in the SEL4C (Social Entrepreneurship Learning for Complexity) framework and designed to promote changemaking through interdisciplinary collaboration, reflection, and action. Using a quantitative quasi-experimental pre–post design (n = 210), data were collected through the validated Social Entrepreneur Profile (SEP), which assesses four dimensions: self-control, leadership, social awareness and social value, and social innovation and financial sustainability. Paired-samples t-tests indicated statistically significant increases (p < 0.001) across all dimensions, with small to medium effect sizes (Cohen’s d = 0.40–0.63). Multiple regression analysis showed that changes in social awareness and social value (β = 0.33, p < 0.001), leadership (β = 0.27, p = 0.004), and innovation and sustainability (β = 0.24, p = 0.006) were most strongly associated with overall changes in self-perceived competencies, explaining 58% of the variance (R² = 0.58). Overall, the findings suggest that short-term intensive educational experiences grounded in active and interdisciplinary pedagogical approaches may contribute to measurable changes in students’ self-perceived social entrepreneurship competencies. Rather than evidencing consolidated transformation, the results are best interpreted as early indicators of competency activation within changemaker-oriented learning environments. The study contributes empirical insight into the use of intensive formats in social entrepreneurship education and situates the SEL4C framework as a coherent pedagogical reference within the Ashoka U context, without implying causal validation.