Background: According to the 2023 World Economic Forum report, the impact of Artificial Intelligence (AI) and automation on the job market was more significant than originally projected. Although 2018 research forecasted significant job losses balanced by job creation, current data indicates otherwise. Between 2023 and 2027, it is anticipated that 69 million new jobs will be created due to advancements in AI, however, this will be offset by the loss of 83 million jobs, leading to a net decrease of 14 million jobs worldwide. Roles related to AI, digitalization, and sustainability, such as AI specialists and renewable energy engineers are expected to grow, while those in clerical and administrative sectors are most at risk of decline. This shift underscores the need for reskilling and adapting to evolving fields, as nearly 44% of workers skills will face disruption by 2027. The demand for analytical thinking, technological literacy, and adaptability will grow as companies increasingly adopt frontier technologies. Objectives: (1) identify key variables influencing adaptability of college graduates in Indonesia, (2) quantify the strength of relationships between these variables to understand the combined effect on graduate adaptability. The research also aims to (3) develop theoretical and practical recommendations to strengthen ICIL policy and equip students with the relevant skills needed to thrive in an ever-changing job market. Methodology: The research focuses on predicting future employment trends, adaptability, and learning agility (LA), along with the implications for improving the Independent Campus Independent Learning (ICIL) policy. It focused on the significant unemployment rate among college graduates, along with the lack of research on the relationship between job change predictions, graduates’ adaptability, and the impact on graduates’ general well-being. The mixed-method strategy with quantitative analysis was used to conduct this research with data collected from 284 ICIL participants through online survey. The gathered data was evaluated using Structural Equation Modeling (SEM) with Lisrel version 10. Results: The result showed that job trend projections significantly influence responsiveness, which demonstrated a robust association between employment trend predictions and LA. Responsiveness significantly influenced learning agility which indicated no significant direct association between job trend projections and graduate adaptability. Conclusion: The research emphasized the need to consider adaptability as a concept with multiple dimensions. It proposed incorporating these factors into strategies for education and human resources development in order to better equip graduates for the demands of a constantly changing work market. Unique contribution: This research focused on adaptability as a multifaceted concept that consist of the ability to forecast job trends, be sensitive, and possess LA. It offered a deeper understanding of the relationships between these variables as discussed in the human resources literature. Technology, corporate culture, and training played a critical role in connecting employment trend prediction with the ability to respond effectively. Key recommendation: Institutions should implement a comprehensive approach to the development of human resources, with emphasis on fostering critical thinking, analytical abilities, and the practical application of information. By employing these tactics, higher education institutions may effectively equip graduates with both academic proficiency and the ability to adapt and thrive in quickly changing organizational environments, leading to the production of robust and versatile workers.

SMEs are characterized by a number of flaws that threaten their survival and counteract them from reaching high levels of growth and development. Access to finance is the primary problem facing these companies in the Moroccan context. Aware of the effective and potential impacts of SMEs on the country as a whole, the Moroccan Government through a variety of actors has mobilized its efforts in a number of ways to support this population of companies. This study assesses the extent to which actors within the Moroccan SMEs’ financing ecosystem align to support these companies and develop their ability to access external financing. Using the MACTOR model, based on an in-depth contextual analysis and expert interviews, our findings suggest that Morocco’s SMEs’ financing ecosystem is skewed, with high levels of convergence between its components.

Ancestral knowledge is essential in the construction of learning to preserve the sense of relevance, transmit and share knowledge according to its cultural context, and maintain a harmonious relationship with nature and sustainability. The objective of this research is to study and analyze the management of ancestral knowledge in the production of the Raicilla to provide elements to rural communities, producers, and facilitators in decision-making to be able to innovate and be more productive, competitive, sustainable, and improve people’s quality of life. The methodological strategy was carried out through Bayesian networks and Fuzzy Logic. To this end, a model was developed to identify and quantify the critical factors that impact optimally managed technology to generate value that translates into innovation and competitive advantages. The evidence shows that the optimal and non-optimal management of knowledge, technology, and innovation management and its factors, through the causality of the variables, permits us to capture the interrelationship more adequately and manage them. The results show that the most relevant factors for adequate management of ancestral knowledge in the Raicilla sector are facilitators, denomination of origin, extraction and fermentation, and government. The proposed model will support these small producers and help them preserve their identity, culture, and customs, contributing greatly to environmental sustainability.

Bali is the most famous tourist destination in the world, and this popularity has led to a significant rise in the island’s economy. The rise in income has also driven an increase in demand for infrastructure. Moreover, the Bali regional competitiveness index, in the infrastructure pillar, shows a lower figure compared to the national level. So that the Bali Provincial Government focuses on building an infrastructure strategy. This research uses the Input-Output Table (IOT) model, namely the 2016 Bali Province IOT which will be released in 2021. This analysis was chosen because IOT assumes that one sector can be an input for other sectors, in terms of this this is the construction sector. With investment in strategic and monumental infrastructure marking the New Era of Bali, it will result in additional Gross Regional Domestic Product (GRDP) of IDR 18.7 trillion, or in other words Bali’s GRDP will increase by 9.71% from the condition of no investment. This shows that infrastructure development is able to boost Bali’s economy. Further research is needed to be able to qualitatively analyze development infrastructure strategies in Bali. Remembering that a qualitative approach is also important to be able to analyze in depth.