Review of Applied Management and Social Sciences (RAMSS) (E-Journal)
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Identifying Key Antecedents of Eco-Conscious Consumer Behavior: Mediating Role of Intentions to Purchase Green DC Inverter Air Conditioners
Get PDFThe study aims to explore the factors driving consumers' desire for environmentally friendly purchases and their impact on actual purchasing behavior. It uses a quantitative methodology, utilizing a structured questionnaire, to gather data from a diverse customer sample, reflecting the growing focus on green buying in both academic research and commercial operations. The study, involving 500 respondents from diverse demographic backgrounds and shopping habits, used structural equation modeling to analyze correlations among variables, revealing that numerous factors significantly influence green purchase intentions. The study reveals that environmental awareness and knowledge about sustainable practices are key predictors of green purchasing intention. Personal values and beliefs about environmental protection also positively influence green purchase intention. The study also examines the impact of green purchase intention on actual green purchase behavior, finding a strong positive relationship between consumers' intention to purchase green products and their environmentally responsible consumption practices. This research emphasizes the importance of understanding consumers' intentions in driving sustainable purchasing behaviors. It provides valuable insights for marketers and policymakers in developing effective strategies to promote green products and encourage environmentally conscious behaviors. By targeting the antecedents of green purchase intention, marketers can tailor their communication and promotional efforts to increase consumers' likelihood of making sustainable choices. The study also contributes to the existing body of knowledge by expanding our understanding of factors influencing green purchase intention and its impact on actual green purchase behavior. The findings highlight the importance of translating consumers' intentions to purchase eco-friendly products and emphasize the need to translate these intentions into actual behaviors
Economic Strain and Recovery Trajectories in Mental Health: The Role of Financial Stability in Mental Health Outcomes
Get PDFThis study explores the intricate relationship between financial stability and recovery from mental health, and clarifies how economic security constitutes an essential feature that enhances mental health results. The study has used SPSS in quantitative analysis for regression analysis, ANOVA, cluster analysis, and structural equation modeling to explore the determinants of influential predictors and patterns in linking financial stability with mental health recovery. The regression outcome showed that financial stability substantially predicts recovery (? = 0.52, p < 0.01), and ANOVA indicated large differences in the scores of recoveries among the financial groups (F = 8.15, p < 0.05). Cluster analysis also indicated a difference such that the average score of recovery for high-stability participants was 8.5, while for low-stability participants it was 4.1. Thus, SEM shows both direct and indirect effects as it manifests that financial stability indeed reduces stress and encourages treatment adherence. The study concludes that economic security indeed plays a multifaceted role ranging from the access of mental healthcare through income support programs to resilience and overall well-being through the promotion of living a financial stability life. Recommendations should include income support programs, financial literacy programs, and integrated financial and mental health support services to form sustainable recovery. Further longitudinal researches, with larger and more diverse samples, should be conducted to study the long-run impact of financial stability on mental health trajectories and tailor policy interventions accordingly
Youth Employment Challenges and Opportunities in Pakistan: An Econometric Analysis
Get PDFThe involvement of young people in Pakistan's job market is the subject of this dissertation. This work highlights two main benefits of the research conducted using micro data. First, it breaks out the labor market behaviors of teenagers in Pakistan by age group. Then, using econometric approaches, it explains what variables influence youth work chances in Pakistan. According to the research, several young people start working at a young age, which may affect their future productivity and income. At the beginning of their professions, young people frequently have a higher unemployment rate; nevertheless, this number decreases with time. In addition, there were notable disparities in the labor market outcomes for male and female teenagers based on area. Unemployment rates for young women are higher than those for young men in several regions of the nation. Although young people in Baluchistan are more prepared to enter labor than their counterparts in other regions, the study's main conclusion shows that their employment prospects are poorer. Several characteristics, the findings of a logistic regression analysis demonstrate that the job chances of youth in Pakistan are highly impacted by age, gender, marital status, emigration, geography, educational achievement, and family characteristics. In addition, studies show that Pakistani teenagers are a heterogeneous group, reflecting a wide variety of personal traits and perspectives on employment that are influenced by their home context. Policymakers should see Pakistani youth as something other than a monolithic entity. Unemployment is a problem in Pakistan due to several factors
Analyzing how Social Media Platforms, Driven by AI, can serve as Spaces for Teachers' Professional Development by Facilitating Networking, Knowledge Sharing, and Real-time Collaboration
Get PDFThis study assesses the impact of AI-facilitated social media on teachers' professional development in relation to networking, knowledge-sharing, and instant collaboration. Given that AI is increasingly incorporated into learning spaces, more often than not, the traditional means of PD have some of these disadvantages, including the lack of time, place, and the lack of room to collaborate with other teachers. The use of AI-based platforms like LinkedIn, Twitter, Edmodo, and Google Classroom supports personalized learning and connects teachers all over the world. This study was a quantitative design to gather information on the multivariate sample of teachers using these platforms in order to advance their professional development. Responses on usage patterns, perceived benefits, and effectiveness of AI were gathered from structured questionnaires. To interpret these, descriptive statistics, correlation analyses, and regression analyses were applied in the evaluation of data. Findings were concluded whereby AI-driven platforms greatly enable improvement in networking opportunities, support more efficient knowledge sharing than classical PD environments, and can contribute to developing real-time collaboration. In other words, what an AI might provide in terms of learning support brings with it opportunities with which teachers might have rich, accessible, and also personalized learning experiences. This requires further research into the particular features of AI that support PD and for educators, working with developers of platforms, to optimize AI for the enhancement of teacher effectiveness. These findings add to a growing literature on the role that AI plays in education through actionable insights for possible integration into education programs for teachers in the future
Voices of Resilience: Pakistani Artists Respond to War and Terror
Get PDFThis study investigates the impact of geopolitical incidents on Pakistani visual artists as they confront issues of war and terror. It focuses on individuals who transform pain into compelling visual narratives, illustrating how art can combat oppressive forces, document resilience, and foster a sense of hope and healing. Using qualitative research methods, data was gathered through interviews, primary and secondary sources, and an analysis of artworks from digital galleries, journals, and artists' social media profiles. The study highlights how artists such as Rashid Rana, Humaira Abid, and Abdullah M. Syed employ various mediums to explore themes of resilience, displacement and hope in response to terrorism. Furthermore, it outlines these artists and their works' crucial role in addressing the societal effects of war and terrorism. The study advocates for promoting art as a tool for peace-building and a means to raise awareness regarding socio-political issues
Influence of Digital Bank Services on the Financial Performance of the Commercial Banks
Get PDFIt is anticipated that the adoption of digitalization in Pakistan's banking industry will have an impact on how banks formulate financial services and products as well as how well these banks operate. This paper attempted to analyse the impact of the digital banking on Pakistani commercial banks' financial performance in order to achieve this goal. Quantitative research approach was utilized. Commercial banks were the target population of this research. There were 200 responders from Pakistani commercial banks in the sample. The study employed multiple regression analysis to examine how digital banking affects financial performance. According to this research, Pakistan's commercial banks' growing profitability was mostly because of an increase in digital customer deposits made through digital banking platforms. The research findings indicate that there was an rising trend in the ratio of digital bank transactions to total assets over the chosen study period. The overall percentage of assets while growing due to a further increase in information technology expenses, fees, and commissions. The research findings indicated that an increase in online banking transactions was favourably and strongly correlated with profitability. To boost digital banking and boost commercial banks' financial performance, the report advises bank management to improve it
Visitors’ Environmental Conservation Behaviour in the Mountain Tourism Destinations in Pakistan
Get PDFThis study investigates the environmental conservation behavior of visitors in mountain tourism destinations across Pakistan, with theoretical support drawn from the Theory of Planned Behavior (TPB), Norm Activation Model (NAM), and the Visitor Impact Management (VIM) Framework. With the growing popularity of mountain tourism, concerns regarding its environmental impact have become increasingly pertinent. Understanding the behavior of visitors towards conservation practices is essential for sustainable tourism management. Utilizing a mixed methodology, together with reviews and interviews, this research aims to explore the attitudes, motivations, and actions of tourists towards environmental conservation in Pakistan's mountainous regions. By analyzing data collected from both domestic and international tourists, this study seeks to identify key factors influencing visitors' conservation behavior, such as awareness levels, socio-cultural backgrounds, and perceptions of responsibility. Furthermore, it examines the ability of current conservation initiatives and the potential for enhancing environmental education and awareness among tourists. The findings of this research will add to the expansion of strategies and policies aimed at promoting sustainable tourism practices in Pakistan's mountain destinations, ensuring the preservation of natural resources and the long-term possibility of the travel industry
Impact of Total Productive Maintenance, Total Quality Management and Lean Practices on Operational Performance in Pharmaceutical Industry of Pakistan: An Empirical Study on Anti-Hypertensive Drugs
Get PDFReviewing the drugs can help the users to understand that how the individual patient factor in addition to age and other health needs can be treated with medication to manage the perspective of treatment. The study aims to review the impact of Total Productive Maintenance, Total Quality Management and Lean Practices on Operational Performance in the Pharmaceutical Industry for Anti-Hypertensive Drugs in Pakistan. It has used a sample of 100 respondents. The data has been analsyed using Smart PLS later. It has reviewed 10 hypotheses and all are approved as positive. The findings show that an autonomous maintenance involves operators taking responsibility for the basic maintenance of their equipment. It has been agreed that in order to reduce all these factors it is better to produce Anti-Hypertensive Drugs with more demand-appropriate equipment. It is recommended that the context of anti-hypertensive drugs can be supported using Total Productive Maintenance, Total Quality Management and Lean Practices. The managers and decision makers can use the study output to enhance their working plans
Portfolio Selection and Stock Returns: The Role of Machine Learning Algorithms in Asset Choices
Get PDFThe investigation has been made across various financial assets available globally to develop a portfolio that may generate higher returns with low risk and minimal drawdowns and even may perform well under stressful financial happening. The main objective of this study is to provide a strategically effective weighting process to build an efficient and optimally diversified portfolio by using various categories of financial assets classified into three samples. The machine learning algorithms have been applied to diversify and build a suitable portfolio by evaluating the suitability of the rebalancing approach. The last twenty years' daily data of various assets permits analysis of the dynamic behaviors and underlying patterns of the assets as a part of the portfolio. Although the long-run variations in asset returns are not an effective way to make good forecasts about their behavior in the future this makes it possible to test their resilience and response during financial stress-events. Findings suggest that portfolio diversification should incorporate some top-position assets from the main categories of financial markets to classify the ranking of various assets and assigning equal weights to each asset in the portfolio ensures remarkably high returns
Use of Artificial Intelligence in the Banking Industry: A Case Study of Pakistan
Get PDFThis study investigates the adoption and impact of Artificial Intelligence (AI) in Pakistan’s banking sector, with a focus on Habib Bank Limited (HBL), Faysal Bank, and Bank Alfalah. The objective is to understand the extent to which AI technologies have transformed core activities within customer service, operations, fraud detection, and risk management in these banks. Data were collected from semi-structured interviews with ten respondents, selected based on their experience with AI implementation. This qualitative methodology allows for in-depth insights into the functionality and challenges associated with AI in banking. Results reveal that AI has notably improved operational efficiency by streamlining risk management and enabling real-time fraud detection. Additionally, AI-driven chatbots and virtual assistants have enhanced customer experiences by offering faster and more personalized services. Despite these benefits, the study identifies significant challenges, particularly regarding data privacy and regulatory compliance, as well as the need for human resources to adapt to AI-enabled tools. Key pressures in the industry include building capabilities to work alongside AI while addressing concerns over automation. To maximize the advantages of AI, the study emphasizes the need for comprehensive policies that balance technological adoption with ethical considerations, data security, and staff training. Strategic planning in Pakistan’s banking sector will be crucial to harnessing AI’s potential while managing its risks