The study’s purpose is to investigate the relationship effect of innovation on online organizational learning applications and employees’ engagement in the Jordanian public sector. Quantities and descriptive analytical approach were used, and the population was covered (10) Jordanian public departments in Amman capital. Convenience method was used, which covered all departments’ managers and assistances in the Jordanian public services department’s headquarters, with (284) employee. Electronic survey set used. The SPSS-V20 and AMOS-V24 were used for hypotheses statistical analysis testing. The study found a significant impact of online organizational learning applications in its dimensions (Zoom, Teams, Goto Meeting, and Google Meet) on employee’s engagement, and a significant relationship of innovation between online organizational learning applications and employee’s engagement in Jordanian public services departments. The study contributions show that employees are willing to engage with their occupied work to achieve work goals, and to control over of how they undertake the employees career development, empowerment, communication skills, and work completion competences. The study implications for organizations management to conduct more future studies concerning online organizational learning applications by other dimensions as well as social media and other digital workshop and training in different organizations environments.

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.

Raising public awareness of maritime risk and disseminating information about disaster prevention and reduction are the most frequent ways that the government incorporates citizens in marine disaster risk management (DRM). However, these measures are deemed to be insufficient to drive the participation rate. This study aims to understand the participation trend of citizens in marine DRM. On the basis of the theory of citizen participation’s ladder, public participation within marine DRM is categorized into non-participation, tokenistic participation, and substantive participation. Using organization theory, the government’s strategies for encouraging participation are classified into common approach (raising awareness), structural approach (innovating instruments), and cultural approach (developing citizenship). Considering the vignette experiment of 403 citizens in a coastal city of China that has historically been subject to marine disasters, it was found that effectiveness of the strategies, from highest to lowest, are citizenship development, risk education, and instruments innovation. At the individual level, psychological characteristics such as trust in the government, past disaster experience, and knowledge of marine DRM did not significantly influence citizens’ participation preferences. At the government level, even when citizens are informed about new participatory mechanisms and tools, they still tend to be unwilling to share responsibilities. However, self-efficacy and understanding the beneficial outcomes of their participation in marine (DRM) can positively impact the willingness to participate. The results show that to encourage public participation substantively in the marine DRM, it is important to cultivate a sense of civic duty and enhance citizens’ sense of ownership, fostering a closer and more equitable partnership between the state and society.

New technologies always have an impact on traditional theories. Finance theories are no exception to that. In this paper, we have concentrated on the traditional investment theories in finance. The study examined five investment theories, their assumptions, and their limitation from different works of literature. The study considered Artificial Intelligence (AI) and Machine Learning (ML) as representative of financial technology (fintech) and tried to find out from the literature how these new technologies help to reduce the limitations of traditional theories. We have found that fintech does not have an equal impact on every conventional finance theory. Fintech outperforms all five traditional theories but on a different scale.

Indonesia has ratified United Nations Convention on the Law of the Sea 1982 (UNCLOS 1982) through Law No. 17 of 1985 concerning the ratification of the 1982 Law of the Sea Convention, thus binding Indonesia to the rights and obligations to implement the provisions of the 1982 convention, including the establishment of the three Northern-Southern Indonesia’s Archipelagic Sea Lane (ALKI). The existence of the three ALKI routes, including ALKI II, has led to various potential threats. These violations not only cause material losses but, if left unchecked and unresolved, can also affect maritime security stability, both nationally and regionally. The maritime security and resilience challenges in ALKI II have increased with the relocation of the capital, which has become the center of gravity, to East Kalimantan. The research in this article aims to identify and analyze the factors influencing the success of maritime security and resilience strategies in ALKI II. The factors used in this research include conceptual components, physical components, moral components, command and control center capabilities, operational effectiveness, command and control effectiveness, and the moderating variables of resource multiplier management and risk management to achieve maritime security and resilience. This study employed a mixed-method research approach. The factors are modeled using Structural Equation Modeling (SEM) with WarpPLS 8.0 software. Qualitative data analysis used the Soft System Methodology (SSM). The results of the study indicate that the aforementioned factors significantly influence the success of achieving maritime security and resilience in ALKI II.

The development of artificial intelligence (AI) and 5G network technology has changed the production and lifestyle of people. AI also has promoted the transformation of talent training mode under the integration of college industry and education. In the context of the current transformation of education, AI and 5G networks are increasingly used in the education industry. This paper optimizes and upgrades the training mode of skilled talents in higher vocational colleges by using its advanced methods and technologies of information display. This means is helpful to analyze and solve a series of objective problems such as the single training form of the current talent training mode. This paper utilizes the principles and laws of industry university research (IUR) collaboration for reference to construct and optimize the talent training mode based on the analysis of the requirements of talent training and the role of each subject in talent training. Then, the ecological talent training environment can be realized. In the analysis of talent training mode under the cooperation of production and education, the correlation coefficients of network construction, environment construction, scientific research funds, scientific research level, and policy support were 0.618, 0.576, 0.493, 0.785, and 0.451, respectively. This showed that the scientific research level had the greatest impact on talent training in the talent training mode of IUR collaboration, while policy support had less impact on talent training compared with other factors. The combination of AI and 5G network technology with the talent training mode of IUR cooperation can effectively analyze the influencing factors and problems of the talent training mode. The hybrid method is of great significance to the talent training strategy and fitting degree.