Abstract: Investment patterns among salaried individuals are influenced by various factors, including income levels, financial awareness, risk appetite, and socio-economic conditions. This study aims to analyze the investment preferences of salaried professionals in Dehradun, focusing on their choice of financial instruments such as fixed deposits, mutual funds, stocks, insurance, and real estate. The research examines the factors affecting investment decisions, including risk tolerance, savings behavior, tax benefits, and long-term financial goals. A structured survey was conducted among salaried individuals from diverse professional backgrounds to gather primary data. The findings reveal a preference for low-risk investment options, with a significant inclination toward fixed deposits and insurance, while younger investors show a growing interest in mutual funds and equity markets. The study also highlights the role of financial literacy in shaping investment behavior. The insights from this research can help financial institutions, policymakers, and advisors tailor investment solutions that align with the financial goals of salaried individuals in Dehradun. Additionally, the study underscores the need for enhanced financial education programs to encourage informed investment decisions.
Abstract: Islamic banking is reshaping Bangladesh’s financial landscape by offering a Sharia-compliant alternative to conventional banking, particularly through innovative community-driven micro-savings and micro-investment models. This qualitative study analyzes First Security Islami Bank Limited (FSIBL), Bangladesh’s first full-fledged Islamic bank (est. 1999), to draw insights for India’s emerging Islamic banking sector. FSIBL’s success in applying profit-loss sharing (PLS) models—such as Mudarabah-based micro-savings pools converted into agricultural investments and Bai-mode financing for SMEs—alongside mobile banking-enabled societal banking initiatives, demonstrates how Islamic finance can bridge financial inclusion gaps in developing economies. The bank’s CSR-linked community investment programs, which transform small deposits into Waqf-funded local projects, offer a replicable template for India. However, recent governance lapses and liquidity crunches highlight systemic risks in scaling these models without robust safeguards. The study addresses two questions: (1) How does FSIBL’s integration of microfinance with Islamic principles validate its viability in emerging markets? (2) What lessons can India adopt to leverage societal banking wings for grassroots capital formation while avoiding governance pitfalls? Findings reveal that participatory micro-investment frameworks require three pillars: strong Sharia governance (e.g., community oversight committees), depositor protection mechanisms (e.g., taka ful-backed micro-savings), and adaptive asset-liability management (e.g., blockchain-tracked PLS ventures). By examining FSIBL’s journey, the paper proposes actionable strategies for India to harness Islamic banking’s dual social-commercial mandate, advocating for regulatory sandboxes to pilot community savings-to-investment chains and tax-neutrality for micro-investment products. The study concludes that India’s vast SHG networks and digital infrastructure position it to outperform Bangladesh’s model—if integrated with ethical resilience and operational transparency.
Abstract: Artificial Intelligence (AI) has become increasingly central to both economic progress and modern business practices. While much public discussion has centered on the societal and ethical dimensions of AI—particularly in relation to data privacy and human rights—there has been comparatively less attention on how AI is transforming traditional workplace dynamics, especially in the area of occupational health and safety. Although concerns about human rights and gig economy conditions are well-documented, the potential implications of AI for day-to-day worker safety remain underexplored. This paper seeks to fill that gap by introducing a conceptual framework for an AI Work Health and Safety (WHS) Scorecard. This tool is designed to help identify and manage workplace risks linked to AI deployment. Drawing from a qualitative, practice-oriented research project involving organizations actively implementing AI, the study outlines a set of health and safety risks derived from aligning Australia’s AI Ethics Principles and Principles of Good Work Design with the AI Canvas—a tool traditionally used to evaluate AI’s commercial value. The study’s key innovation lies in a newly developed matrix that maps known and anticipated WHS and ethical risks across each stage of AI adoption, offering a structured approach to evaluating AI’s workplace impact.
Abstract: This study was aimed to identify the effect of social intelligence on the academic burnout among college students who were studying in different faculties (Science, Commerce, Arts). The data was collected from different colleges situated in Meerut city. A total 300 students studying different colleges under CCS University were participated. Burnout was measured by Copenhagen(2012)’s Burnout Scale while Social Intelligence by Chadda and Ganeshan (2009). Multiple Regression was used to find our predictors for the burnout among college students. Regression Analysis revealed that social intelligence was emerged as important predictor of burnout. Further T test also revealed significance difference between groups. It was found that female students were having more burnout problems as compare to male participants. Students’ social intelligence is a Type a perceiving ability to understand social cues and effectively navigate social situations. It is ability to cope with burnout or stressors and maintain balance between academic and personal life. In this paper the present study has social applied application Academic Achievement, Mental health and general wellbeing can all be affected by social intelligence. Thus the present study is to examine low social intelligence affects college’s student abilities to handle their burnout problems.
Abstract: Artificial Intelligence (AI) has become increasingly central to both economic progress and modern business practices. While much public discussion has centered on the societal and ethical dimensions of AI—particularly in relation to data privacy and human rights—there has been comparatively less attention on how AI is transforming traditional workplace dynamics, especially in the area of occupational health and safety. Although concerns about human rights and gig economy conditions are well-documented, the potential implications of AI for day-to-day worker safety remain underexplored. This paper seeks to fill that gap by introducing a conceptual framework for an AI Work Health and Safety (WHS) Scorecard. This tool is designed to help identify and manage workplace risks linked to AI deployment. Drawing from a qualitative, practice-oriented research project involving organizations actively implementing AI, the study outlines a set of health and safety risks derived from aligning Australia’s AI Ethics Principles and Principles of Good Work Design with the AI Canvas—a tool traditionally used to evaluate AI’s commercial value. The study’s key innovation lies in a newly developed matrix that maps known and anticipated WHS and ethical risks across each stage of AI adoption, offering a structured approach to evaluating AI’s workplace impact.
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.