The article provides evidence on the effect of local public governance on the impact of public investment on local and regional economic growth, using spatial and regional logic. The research uses the spatial Durbin model and produces a panel data set that was conducted on 63 provinces of Vietnam from 2006 to 2022. Based on the interaction between public governance and public investment, the main findings indicate that their interaction plays an important role in adjusting the effects of public investment and public governance on economic growth not only in the locality but also spillover to neighboring localities in both the short and long terms. It suggests that local public governance not only hampers the impact of local public investment on local economic growth but also has spillover effects on the growth of neighboring provinces or regions in Vietnam. Additionally, the results of detailed analysis of PCI component indicators show that many aspects of local public governance are hindering local economic growth but contributing to promoting neighboring localities economic growth. Or, it has no effect the locality but promote or hinder the regional economic growth. The findings in this study implies that authorities of localities need to be cautious when using resources to improve the various aspects of public governance when designing strategies to enhance the quality of local public governance. It also suggests that this spillover effect is a crucial factor in advocating for more redistributive fiscal policies and regional governance policies aimed at reducing economic disparities caused by territorial boundaries. Therefore, authorities should prioritize regional cooperation strategies in their decisions regarding public governance and public capital allocation.

Social Services are vital for addressing adversity and safeguarding vulnerable individuals, presenting professionals with complex challenges that demand resilience, recovery, and continual learning. This study investigates Organizational Resilience within Community Social Services, focusing on strategic planning, adaptive capacity, and user perspectives. A cross-sectional study involved 534 professionals and service users from Community Social Services Centers in Spain. Centers were selected based on the characteristics of their population and the representativeness of their geographic location. The study utilized the Benchmark Resilience Tool (BRT) to evaluate Organizational Resilience and the SERVPERF questionnaire to gauge user-perceived service quality. The results demonstrate satisfactory levels of Organizational Resilience and user satisfaction, while also highlighting key areas for enhancing resilient strategies: reinforcement of personnel for thinking outside the box or in the resources available to the organization to face unexpected changes. These findings suggest the need to develop and optimize measures that improve the organization’s ability to adapt to and recover from adverse situations, ensuring a positive user experience. Emphasizing the importance of resilience in Social Services as a quality predictor, future research should explore innovative strategies to bolster Organizational Resilience. The findings emphasize the need to strengthen resilience in Social Services, enhancing practice, policy, and adaptability to support vulnerable populations.

The privacy of personal information is aimed at protecting human rights both under the international human rights regime and the Saudi Arabian constitution and other statutes and regulations, subject only to some exceptions that include the protection of public health. The coronavirus disease 2019 (COVID-19) pandemic has brought about certain challenges that necessitate strategies to augment the conventional surveillance of infectious diseases, contact tracing, isolation, reporting and vaccination. Several governments institutions, and agencies presently adopt mobile applications for collecting, analyzing, managing, and sharing critical personal data of individuals infected with or exposed to COVID-19. While the benefits of sharing private information for achieving public health needs may not be disputed, the risk of breach of personal privacy is enormous. This had forced the national governments into a dilemma of either succumbing to public health needs, strictly respecting and protecting the privacy of individuals, or alternatively, balancing the two conflicting demands. There is a massive body of literature on the security and privacy of such mobile applications, but none has adequately explored and discussed public interest justifications under Saudi Arabian laws for alleged privacy breaches. We examined the health surveillance mobile app technologies currently in use in Saudi Arabia with the aim of determining the potential risks of data breaches under extant data protection laws. The paper recommends, among others, that any potential risk of breach to right to privacy of personal information under the law must be (justified by) the public health needs to protect society during the COVID-19 pandemic.

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 research examines the interplay between human dignity and the pursuit of knowledge within Islamic thought, using insights from the Quran. It explores how Islamic epistemology emphasizes the harmonious integration of divine revelation and human reason, underscoring the importance of knowledge as a key factor in both intellectual and spiritual development. By analyzing the contributions of classical Islamic scholars, such as Al-Farabi, Ibn Sina, and Al-Ghazali, alongside Western epistemological traditions, the study highlights complementary and contrasting approaches to understanding knowledge and its role in shaping ethics and governance. Furthermore, the research draws on contemporary case studies, such as the Marrakesh Declaration and Masdar City, to illustrate how Quranic principles of cooperation, justice, and environmental stewardship can inform modern societal frameworks. Ultimately, the study argues for the continued relevance of Islamic thought in addressing contemporary global challenges, emphasizing that the pursuit of knowledge not only advances scientific discovery but also promotes human dignity, justice, and societal well-being.