Background: People who are financially literate are able to make sound decisions regarding their money since they have a firm grasp of the fundamentals of money and financial products. The significance of financial literacy has been acknowledged by numerous nations, prompting the formation of task teams to assess their populations and develop educational and outreach programs. The requirement to make educated decisions about ever-increasing financial goods necessitates a higher level of financial literacy. Aim: Being able to make sense of one’s personal financial situation is becoming an increasingly valuable skill in today’s world. One of the most essential components for making sure and successful decisions is having a good grip on one’s financial status. By contrast, financial literacy refers to an individual’s level of knowledge and awareness regarding financial matters, whereas investors’ decision-making is characterised by their understanding, prediction, investigation, and assessment of the various stages and transactions involved in making an investment decision. Risk, a decision-making framework and process, and investing itself are all components of investing. Method: Researchers will conduct a cross-sectional survey of Saudi Arabian investors. We used a structured questionnaire to gather data. Using “Cronbach’s a and confirmatory factors” analysis, we checked whether the data is reliable. The links between financial literacy and investment decisions was demonstrated using structural equation modeling (SEM) in IBM-SPSS and SmartPLS. Purpose: The purpose of this research is to look at how the investment choices of Saudi Arabians are correlated with their degree of financial literacy. Consequently, research on the connection between financial literacy, knowledge, behaviour, and investment choices is lacking. Researchers on this subject have already acknowledged the problem’s importance and intended to devote substantial time and energy to solving it. Findings: The study concluded that there was a significant relationship between financial literacy and financial knowledge with respect of investment decision of investors. Similarly, there was a significant relationship between financial behaviour and financial knowledge with respect of investment decision of investors. The discovery of the outcomes will enable regulatory authorities to aid investors in preventing financial losses by furnishing them with sufficient financial information.

This study addresses the crucial question of the macroeconomic impact of investing in railroad infrastructure in Portugal. The aim is to shed light on the immediate and long-term effects of such investments on economic output, employment, and private investment, specifically focusing on interindustry variations. We employ a Vector Autoregressive (VAR) model and utilize industry-level data to estimate elasticities and marginal products on these three economic indicators. Our findings reveal a compelling positive long-term spillover effect of these investments. Specifically, every €1 million in capital spending results in a €20.84 million increase in GDP, a €17.78 million boost in private investment, and 72 new net permanent jobs. However, these gains are not immediate, as only 14.5% of the output increase and 38.8% of the investment surge occur in the first year. In contrast, job creation is nearly instantaneous, with 93% of new jobs materializing within the first year. A short-term negative impact on the trade balance is expected as new capital goods are imported. Upon industry-level analysis, the most pronounced output increases are witnessed in the real estate, construction, and wholesale and retail trade industries. The most substantial net job creation occurs in the construction, professional services, and hospitality industries. This study enriches the empirical literature by uncovering industry-specific impacts and temporal macroeconomic effects of railroad infrastructure investments. This underscores their dual advantage in bolstering long-term economic performance and counteracting job losses during downturns, thus offering valuable public policy implications. Notably, these benefits are not evenly distributed across all industries, necessitating strategic sectoral planning and awareness of employment agencies to optimize spending programs and adapt to industry shifts.

Companies are impacted by toxic leadership phenomena, resulting in many dissatisfied employees, low morale, and reduced progress. The fundamental mismatch between good leadership and harmful actions of toxic leaders is the primary cause of the problem. Toxic leadership can also be developed from narcissistic behavior of considering personal interests or using humiliation to maintain power. In this context, employees are negatively affected, resulting in higher stress levels, poorer job satisfaction, and a significant decrease in trust. Therefore, this research aims to explore the impact of toxic leadership and other factors on companies. The sample consists of 187 senior employees in the accounting department who worked in manufacturing companies. The results showed that toxic leadership influences role stress, while role stress affects emotional exhaustion and reactive work behavior. Moreover, future research should be conducted using other samples such as hospital employees or pay attention to other aspects related to role stress.

Purpose: This research examines the intricate interplay between Business Intelligence (BI), Big Data Analytics (BDA), and Artificial Intelligence (AI) within the realm of Supply Chain Management (SCM). While the integration of these technologies has promised improved operational efficiency and decision-making capabilities, concerns about complexities and potential overreliance on technology persist. The study aims to provide insights into achieving a balance between data-driven insights and qualitative factors in SCM for sustained competitiveness. Design/methodology/approach: The research executed interviews with ten Arab Gulf-based consulting firms. These companies’ ability to successfully complete BI projects is well recognised. Findings: Through examining the interplay of human judgement and data-driven strategies, addressing integration challenges, and understanding the risks of excessive data reliance, the research enhances comprehension of the modern SCM landscape. It underscores BI’s foundational role, the necessity of balanced human input, and the significance of customer-centric strategies for lasting competitive advantage and relationships. Practical implications: The research provided information for organizations seeking to effectively navigate the complexities of integrating data-driven technologies in SCM. The research is a foundation for future studies to delve deeper into quantitative measurement methodologies and effective data security strategies in the SCM context. Originality: The research highlights the value of integrating BI, BDA, and AI in SCM for improved efficiency, cost reduction, and customer satisfaction, emphasising the need for a balanced approach that combines data-driven insights, human judgement, and customer-centric strategies to maintain competitiveness.

The paper examines the motivations, financing, expansion and challenges of the Belt and Road Initiative (BRI). The BRI was initially designed to address China’s overcapacity and promote economic growth in both China and in countries along the “Belt” and “Road” through infrastructure investment and industrial capacity cooperation. It took into account China’s strategic transition in its opening-up policy and foreign policy to pay more attention to the neighboring countries in Southeast Asia and Central and West Asia when facing greater strategic pressure from the United States in East Asia and the Pacific region. More themes have been added to the initiative’s original framework since its inception in 2013, including the vision of the BRI as China’s major solution to improve international economic cooperation and practice to build a “community of shared future for mankind”, and the idea of the Green Silk Road and the Digital Silk Road. Chinese state-owned enterprises and policy and commercial banks have dominated investment and financing for BRI projects, which explains the root of the problems and risks facing the initiative, such as unsustainable debt, non-transparency, corruption and low economic efficiency. Measures taken by China to tackle these problems, for example, mitigating the debt distress and improving debt sustainability, are unlikely to make a big difference anytime soon due to the tenacity of China’s long-held state-driven investment model.

This study investigates the changing nature of the psychological contract in the digital era, particularly how fluid work arrangements alter traditional employment dynamics. Utilizing a conceptual approach informed by a narrative review, this study examines the historical development of the psychological contract through foundational studies, while also integrating recent research that highlights the transformative influence of digital platforms in fluid work environments. The key contribution of this study is the innovative model it proposes, which captures the complexities of the psychological contract in modern digital and fluid work settings. This model provides a comprehensive theoretical framework to understand evolving employer-employee relationships and practical insights for organizations navigating these changes. It represents a significant advancement in both theory and practical application, connecting traditional employment principles with the dynamism of digital-era work.