Abstract: Corruption is characterized as the exploitation of entrusted authority for personal advantage, often taking the form of illegal acts, deceit, or bribery, and is broadly regarded as harmful to economic progress. Although some research indicates that corruption might enhance certain economic activities, it is primarily perceived as a major obstacle to sustainable development on a global scale. The research question of this study is: What is the effect of corruption on GDP per capita in South Asian nations between 1995 and 2016? This investigation examines the link between corruption, as assessed by the Corruption Perception Index (CPI), and GDP per capita in South Asia. By employing a Generalized Least Squares (GLS) model, the study seeks to analyze the impact of corruption on GDP per capita. The results reveal a significant negative association between corruption and GDP per capita, indicating that corruption hinders economic growth in the region. Therefore, it is crucial for the governments of these nations to adopt effective strategies to address corruption and foster sustainable economic development.
Abstract: National Bank for Agriculture and Rural Development (NABARD) formed in 1982 on 12th July is India's leading agricultural finance and rural development institution. This paper critically examines NABARD's development, financing, and supervisory roles with particular reference to the operations of its organizational hierarchies. NABARD performs as a support system for rural banking organizations' refinancing, financial inclusion, financing infrastructure operations, and promoting capacity-building schemes such as Self-Help Groups (SHGs), Farmer Producer Organizations (FPOs), and Primary Agricultural Credit Societies (PACS). Its departments such as Financial Inclusion and Development, Infrastructure and Development, and Supervision allow NABARD to support rural credit infrastructure and policy adherence. This paper assesses the performance of NABARD in rural development, climate resilient farming, and inclusive growth. Imbalanced credit flow to regions, over-reliance on government support, weak digital connectivity, and congruence of youth training skills remain issues despite these advancements. Despite these issues, NABARD remains a powerful instrument of sustainable rural development and farm advancement in India. This paper thus concludes the relevance of policy reforms, technology adoption, and greater autonomy to improve NABARD's long-term performance.
Abstract: This study examines pawnbroking's impact on social entrepreneurship and its implications for social development. It posits that Pawnbroking aids vulnerable entrepreneurs, often excluded from formal credit, in accessing quick financial resources, thereby enhancing social entrepreneurship. Through a meta-analysis and literature review, including three case studies from Bangladesh, the findings indicate that, despite exploitative practices, pawnshops are vital for providing the impoverished with financial access and supporting social welfare. However, risks such as asset loss, debt cycles, and exploitation of desperate borrowers are also highlighted. The study emphasizes the need for regulatory oversight and more accessible financial systems that protect borrowers while maintaining accessibility. Overall, pawnbroking offers both advantages and challenges for local communities in Bangladesh, necessitating a balance between quick cash access and consumer protections to promote healthier community dynamics.
Abstract: This study aims to measure the impact of the level of voluntary disclosure transparency on improving the quality of published financial reports in Jordanian business enterprises during the year 2024. The study adopted a combination of the inductive and positive approaches by extrapolating previous research and studies on voluntary disclosure and using the positive approach to analyze the quantity and quality of information disclosed in financial reports.
To achieve the study’s objectives, a model for measuring the level of voluntary disclosure was developed based on models previously used in studies conducted in environments similar to the Jordanian context. This model includes 134 elements encompassing strategic, financial, and non-financial information, with the aim of assessing the impact of these components on improving financial report quality. The study defines report quality in terms of the ability of disclosed information to influence the decision-making process of report users within the research population, which consists of publicly listed companies on the Amman Stock Exchange.
Additionally, the study sought to analyze the relationship between several variables—board independence, family ownership percentage, audit committees, and international exposure—and the level of voluntary accounting disclosure. The research sample consisted of 20 publicly listed companies on the Amman Stock Exchange, selected based on specific criteria that serve and contribute to achieving the study’s objectives.
The results revealed a statistically significant positive correlation between board independence, international exposure, audit committees, audit firm size, company size, and company performance and the level of voluntary disclosure transparency. Furthermore, the study found a statistically significant negative correlation between the percentage of family ownership in Jordanian public shareholding companies and the level of voluntary disclosure in financial reports.
Abstract: The COVID-19 pandemic accelerated digital adoption across sectors, rapidly restructuring Indian e-commerce. AI is a critical enabler of operational efficiency-from planning supply chains to automating customer support. The study attempts to understand post-COVID transformations in AI-related employment trends in various e-commerce subsectors in India. While AI threatens entry-level, routine applications, it creates a demand for professional jobs further involving AI development, data science, and digital operations. The study, thus, employs mixed methods, using secondary data sets and qualitative case studies, to comprehend the sectoral landscape of AI impacts on employment. It attempts to understand the potentials and challenges of AI, drawing on assessment of its socio-economic impact so as to arrive at recommendations on reskilling policies and inclusive employment strategies.