Instability is inherent in global capitalism, impacting all countries, particularly those directly reliant on this economic framework. The USA shapes tourism metrics in dependent nations and influences inbound tourism spending. Using logarithmic models and power tests, the study delineated four dynamic fields (Cn) supporting the thesis of the fusion of tourism and temporary residency. This study demonstrates that tourism and migration correlate with political, economic, and social instability, as evidenced by high statistical correlations. Variance increases during instability, leading to more residency petitions per tourist entry. This pattern is repeated during three major crises: the 2008–2009 financial crisis, the 2011–2013 conflicts in the Middle East and Africa, and the 2016–2017 regional political turmoil and Venezuelan migration. Economic classification tests confirm the association between instability, armed conflict, and heightened tourism and residency tendencies. Tourism income rises steadily, and residency averages increase, especially during periods of regional instability. The study highlights the tight link between tourism and migration with political, economic, and social instability. The statistical analysis reveals significant correlations, showing higher residency pressure during unstable periods. The applied tests confirm that countries in turmoil exhibit heightened tourism and migration tendencies.

Using the United Nations’ Online Services Indicator (OSI) as a benchmark, the study analyzes Jordan’s e-government performance trends from 2008 to 2022, revealing temporal variations and areas of discontent. The research incorporates diverse testing strategies, considering technological, organizational, and environmental factors, and aligns with global frameworks emphasizing usability, accessibility, and security. The proposed model unfolds in three stages: data collection, performing data operations, and target selection using the Generalized Linear Model (GLM). Leveraging web crawling techniques, the data collection process extracts structured information from the Jordanian e-government portal. Results demonstrate the model’s efficacy in assessing accessibility and predicting web crawler behavior, providing valuable insights for policymakers and officials. This model serves as a practical tool for the enhancement of e-government services, addressing citizen concerns and improving overall service quality in Jordan and beyond.

Nowadays, urban ecosystems require major transformations aimed at addressing the current challenges of urbanization. In recent decades, policy makers have increasingly turned their attention to the smart city paradigm, recognizing its potential to promote positive changes. The smart city, through the conscious use of technologies and sustainability principles, allows for urban development. The scientific literature on smart cities as catalysts of public value continues to develop rapidly and there is a need to systematize its knowledge structure. Through a three-phase methodological approach, combining bibliometric, network and content analyses, this study provides a systematic review of the scientific literature in this field. The bibliometric results showed that public value is experiencing an evolutionary trend in smart cities, representing a challenging research topic for scholars. Network analysis of keyword co-occurrences identified five different clusters of related topics in the analyzed field. Content analysis revealed a strong focus on stakeholder engagement as a lever to co-create public value and a greater emphasis on social equity over technological innovation and environmental protection. Furthermore, it was observed that although environmental concerns were prioritized during the policy planning phase, their importance steadily decreased as the operational phases progressed.

Amidst an upsurge in the quantity of delinquent loans, the financial industry is experiencing a fundamental transformation in the approaches utilised for debt recovery. The debt collection process is presently undergoing automation and improvement through the utilisation of Artificial Intelligence (AI), an emergent technology that holds the potential to revolutionise this sector. By leveraging machine learning, natural language processing, and predictive analytics, automated debt recovery systems analyse vast quantities of data, generate forecasts regarding the likelihood of recovery, and streamline operational processes. Debt collection systems powered by AI are anticipated to be compliant, precise, and effective. On the other hand, conventional approaches are linked to increasing expenditures and inefficiencies in operations. These solutions facilitate efficient resource allocation, customised communication, and rapid data analysis, all while minimising the need for human intervention. Significant progress has been made in data analytics, predictive modelling, and decision-making through the application of artificial intelligence (AI) in debt recovery; this has the potential to revolutionize the financial sector’s approach to debt management. The findings of the research underscore the criticality of artificial intelligence (AI) in attaining efficacy and precision, in addition to the imperative of a data-centric framework to fundamentally reshape approaches to debt collection. In conclusion, artificial intelligence possesses the capacity to profoundly transform the existing approaches utilized in debt management, thereby guaranteeing financial institutions’ sustained profitability and efficacy. The application of machine learning methodologies, including predictive modelling and logistic regression, signifies the potential of the system.

This study explores the impact of Project-Based Learning (PBL) and locally sourced reading materials on improving speaking proficiency in English as a Foreign Language (EFL) learners. The participants consist of college students aged 18 to 19 years. Forty-four participants from two groups—experimental and control—were evaluated using pre-and post-tests. The experimental group engaged with local cultural reading materials and followed a PBL framework, while the control group used standard commercial textbooks from Western publishers. The findings reveal that the experimental group demonstrated significantly improved fluency, vocabulary, and speaking confidence compared to the control group, with 37.04% showing improvement. PBL facilitated collaborative learning in real-life scenarios, reducing anxiety and fostering more significant participation in speaking tasks. In contrast, the control group showed minimal improvement, highlighting the limitations of traditional lecture-based methods. This study concludes that integrating PBL and locally relevant content into language instruction can enhance speaking proficiency, learner motivation, and engagement. The results suggest that PBL is a dynamic approach that supports developing linguistic and collaborative skills, providing a more holistic learning experience.

In recent years, information technology and social media has developed very rapidly and has had an impact on government services to the public. Social media technology is used hugely by several developing countries to provide services, information and promote information disclosure in its government to improve its performance. This study aims to build role of social media technology concept as a public service delivery facilitator to the public. Furthermore, it discusses the potential impact of social media use on government culture. To achieve the goal, this study combines two theories, namely government public value theory and green smart city with four variables, namely quality of public services, user orientation, openness, and greenness. These variables are used as the foundation for data collection through in-depth interviews and group discussion forums. In-depth interviews are utilized as data search and direct observation. The informants consist of several government elements, including heads of regional apparatus organizations, heads of public service malls and Palembang city government employees. The study revealed that the Palembang government has several social media-based public services that have quality of services, user-orientation, openness, and environmental friendliness.