This study addresses the present limited understanding of the complex relationship between ethical leadership, job stress, and employee job performance in the hotel business. This study shows that job stress moderates the association between ethical leadership and employee job performance, underlining the necessity for more research in the industry. The present study fills a crucial research void in our understanding of the complex interaction between these factors. The study utilizes a sample of 292 employees in the accommodation and hotel industry. Prior to commencing data collection, the questionnaire underwent thorough validation and reliability testing to ensure that the instrument met all specified criteria and demonstrated robustness. Using hierarchical regression analysis, the study reveals substantial findings. It has been discovered that ethical leadership has a direct and positive effect on employee job performance. Notably, job stress emerges as a significant moderating variable that affects the relationship between ethical leadership and employee job performance. This highlights the crucial role that job stress plays in determining outcomes. The research indicates that reducing workplace stress and fostering ethical leadership can result in improved employee job performance. In addition, the study highlights the importance of social learning theory in enhancing employee job performance, with job stress and ethical leadership serving as significant moderating factors.

This article addresses the complex challenge of defining the concept and principles of juvenile justice within the realm of legal science: juvenile justice is a specialized legal framework that focuses on addressing legal issues involving minors, emphasizing rehabilitation over punishment. The article explores the evolution of juvenile justice, examining its theoretical foundations, legislative developments, and practical applications across different legal systems. By dissecting various definitions and principles proposed by scholars and practitioners, this article aims to clarify the core components of juvenile justice and propose a coherent conceptual framework. This article seeks to analyze and elucidate the concept and principles of juvenile justice by examining its historical development, theoretical underpinnings, and current practices. Through a comprehensive review of existing literature and comparative analysis of various legal systems, the article seeks to provide a robust framework for understanding juvenile justice, to offer clarity on “juvenile justice” definition and principles, thereby enhancing the effectiveness of juvenile justice systems and contributing to more informed policy-making and legal reform. The analysis underscores the importance of protecting minors’ rights while balancing the interests of society, thereby contributing to a more nuanced understanding of juvenile justice in contemporary legal discourse. Based on the research, it is suggested to define juvenile justice as a comprehensive system of legal norms and institutions, state and other bodies that protect the rights of minors, as well as a complex of preventive and other measures in this area.

While infrastructure provides necessary public services and is vital for the socio-economic development of a nation, public funds alone cannot finance all infrastructure needs in society, especially after the COVID-19 pandemic, where many countries are facing budget deficits. Although private financing schemes, such as public-private partnerships (PPPs) and land value capture, have been considered intensively, they have yet to produce adequate private capital flows to infrastructure projects due to a lack of incentives for private investors. Against the background, this paper proposes a new financing mechanism in which governments might divert some of the increased tax revenue from the spillover effects of newly constructed infrastructures to fund the private sector through grants or subsidies. The empirical work in Vietnam shows a significant increase in tax revenues after completing two expressways, supporting our idea about spillover effects, which includes small- and medium-sized enterprise (SME) development. This study’s results suggest that spillover effects can bring new opportunities for governments and multilateral development banks (MDBs) to implement infrastructure projects with greater private sector involvement in the region. It also proposes some financial schemes, such as land capture and financing for business startups, including SMEs, to enhance the spillover effects of infrastructure.

This study explores the advancement of ethical practices and environmental sustainability in Thai banking through an in-depth case analysis of Siam Commercial Bank (SCB), the country’s first indigenous bank founded in 1907. SCB has significantly influenced ethical banking practices and sustainability initiatives. The research provides a unique comparative analysis of SCB’s ethical frameworks and sustainability policies, assessing their impact on key stakeholders, including customers, employees, the community, and the environment. Employing a qualitative case study methodology, this study utilizes secondary data from SCB’s reports and CSR documents, analyzed through thematic analysis and descriptive statistics. The findings reveal SCB’s substantial progress in aligning ethical considerations with environmental sustainability, contributing new insights into ethical decision-making processes and the balance between profit and responsibility. Recommendations are provided to enhance ethical and sustainable practices in banking, adding to the discourse on corporate responsibility, environmental stewardship, and sustainable development.

The tourism sector is exponentially expanding across the globe. Despite different forms of tourism, community-based tourism has evolved with new dimensions of development. Assessing the sustainable development of the sector is a top priority in order to adopt the new forms. Therefore, in this study, the association between community-based tourism and its sustainable development was measured under the lens of collaborative theory and social exchange perspective. Non-probabilistic judgmental sampling techniques were applied, and 201 respondents were assessed. Data analysis was conducted using structural equation modeling (SEM). The study grounded with residents’ perspectives and attested that community-based tourism directly enhanced residents’ economic conditions with a better environment, and the relationship between residents and tourists enhanced the tourism industry’s sustainable development. Stakeholders like government and local administrations play a significant role in exploring community-based tourism. This outcome of the research will be a substantial resource for local administrations, governments, researchers, policymakers and practitioners.

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.