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Title: Study on Investment Pattern of Salaried Class People with Special Reference to Dehradun City

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.

By Pankaj Kumar, Subhash Chandra
In Volume: 14,Issue: 1
Title: Artificial Intelligence and Employment Shifts in India’s E-Commerce Sector: A Sectoral Post-Covid Analysis

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.

By S.K.S. Yadav, Samreen Khan
In Volume: 14,Issue: 1
Title: Ethical AI Integration and the Future of Employee Rights at Work

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.

By Kanika Maheshwari
In Volume: 14,Issue: 1
Title: Social Intelligence and Burnout among Post Graduate Students

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.

By Pratiksha Rani, Manju Khokhar
In Volume: 14,Issue: 1
Title: Gender Dimension and Safety Issue of Female Workforce of the Garment Industries in Bangladesh

Abstract: Bangladesh is one of the most prominent developing country in the world, the RMG sector is one of the prime earning sources of Bangladesh. Now Bangladesh is listed one of the gigantic garment exporters of the world. The garment industry is around Eighty four percent of total exports zone of Bangladesh. In Bangladesh more than four million people are worked in this garments industry. Around eighty percent (that is, 3.2 million workers) of the garment workers are female in Bangladesh. According to Bangladesh Garment Manufacturers and Exporters Association (BGMEA), the female garments workers are victim of high prevalence of violence and injustice in the work place. The violence and injustice the female garments workers are faced are adversely affect their physical and mental state. This research paper discusses the complication of gender dimension, fitness, well being and protection matters and hurdle of female garment workers of Bangladesh. Here the author used regression analysis, chi-square test, pearson R test, independent T test in order to explain the factors affect safety issue of female garments workers and the injustice towards them.

By Samira- Binte- Saif
In Volume: 14,Issue: 1
Title: Electric Mobility Integration in Indian Urban Planning: Challenges, Opportunities, and Policy Implications

Abstract: India’s urban transport system is facing unprecedented challenges due to rapid population growth, vehicular congestion, and escalating pollution levels. Against this backdrop, the transition toward electric mobility (e-mobility) offers a promising pathway for sustainable urban development. This study investigates the extent to which electric mobility is being integrated into urban planning in Indian cities. It explores critical challenges such as inadequate charging infrastructure, limited policy coordination, and citizen hesitancy. Drawing upon both primary data collected through surveys in five urban centres—and secondary sources from government and institutional reports, the research applies statistical methods, including factor analysis and regression modelling, to examine the drivers of electric vehicle (EV) adoption. The findings reveal that infrastructure readiness and public policy awareness are strong predictors of urban EV acceptance. The study concludes by offering practical policy recommendations, such as zoning reforms and enhanced fiscal incentives, aimed at creating EV-supportive urban environments aligned with national climate goals.

By Shantam Babbar, Rajesh Kumar Raju, Monika Kumari
In Volume: 14,Issue: 1

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