Artificial Intelligence, Robotics and its Impact on Society
Volunteer Traveling In India: Budget Friendly Travel and Exploration for Youth in India
Risk Estimation in Textile Industries using Tri-Risk Matrix
Customer Satisfaction Analysis on Dabur Toothpaste using Hypothesis Testing
Consumer Spending Patterns and Savings: A Descriptive Analysis
Likes, Shares, Buys: Understanding Social Media's Role in Consumer Decision-Making
Likes, Shares, Buys: Understanding Social Media's Role in Consumer Decision-Making
Risk Estimation in Textile Industries using Tri-Risk Matrix
Customer Satisfaction Analysis on Dabur Toothpaste using Hypothesis Testing
Artificial Intelligence, Robotics and its Impact on Society
Volunteer Traveling In India: Budget Friendly Travel and Exploration for Youth in India
Volunteer Traveling In India: Budget Friendly Travel and Exploration for Youth in India
Artificial Intelligence, Robotics and its Impact on Society
Consumer Spending Patterns and Savings: A Descriptive Analysis
Customer Satisfaction Analysis on Dabur Toothpaste using Hypothesis Testing
Risk Estimation in Textile Industries using Tri-Risk Matrix
Artificial intelligence (AI), known by some as the Industrial Revolution (IR) 4.0, is going to change not only the way tasks are performed, how individuals relate to one another, but also what is known about ourselves and society. This paper will first examine what AI is, discuss its impact on industrial, social, and economic changes on humankind in the 21st century, and then propose a set of principles for AI bioethics. The IR1.0, the IR of the 18th century, impelled a huge social change without directly complicating human relationships. Modern Robotics in AI involves integrating AI technologies into robotic systems to enhance their capabilities and enable them to perform more complex tasks. AI in robotics allows robots to learn from experience, adapt to new situations, and make decisions based on data from sensors. This can involve machine learning, computer vision, natural language processing, and other AI techniques.
Volunteer travel, frequently referred to as voluntourism, has emerged as a significant aspect of contemporary tourism, combining travel experiences with community service. This research paper examines the effects of volunteer travel on both the participants and the host communities, highlighting its advantages, challenges, and ethical considerations. Using a combination of qualitative and quantitative research methods, the study assesses how voluntourism facilitates cultural exchange, skill development, and long-term community engagement. The paper also explores the role of digital platforms in enhancing access to volunteer opportunities and the importance of government regulation in ensuring ethical practices. Findings offer actionable insights for stakeholders aiming to promote responsible and impactful volunteer tourism in India.
The textile industry in India significantly contributes to the country's economic growth and provides employment opportunities for both rural and urban people. However, workers in the industry face various health hazards, including exposure to cotton dust, chemicals, excessive noise, and ergonomic issues. This study aims to evaluate the health hazards present in a textile company using the Tri-Risk Matrix, an integrated approach that combines AHP (Analytic Hierarchy Process), FMEA (Failure Mode and Effects Analysis), and FTA (Fault Tree Analysis) to identify, assess, and mitigate health risks. The Tri-risk matrix utilizes AHP to assess the potential failure modes associated with these hazards, FMEA to prioritize health hazards based on their significance, and FTA to identify their root causes. This integrated approach offers a comprehensive framework for managing health risks in textile manufacturing. This work has been performed in one of the leading textile industries in southern Tamil Nadu, India. As a result, the implementation of this approach has led to a reduction in health-related incidents, improvement in safety protocols, enhanced worker well-being, and a significant increase in overall workplace safety.
In today's competitive oral care market, customer satisfaction is key to brand success and loyalty. This study examines satisfaction with Dabur Toothpaste, known for its Ayurvedic formulation, using statistical hypothesis testing to assess consumer perceptions and the impact of demographic factors, particularly gender. This study was designed to explore critical dimensions of customer satisfaction by formulating specific hypotheses related to consumer perceptions, product effectiveness, and brand loyalty. The analysis provided meaningful insights into consumer behavior, revealing trends influenced by variables such as gender. These findings serve as a valuable foundation for strategic decision- making at Dabur, offering direction for refining product features, enhancing customer engagement, and tailoring marketing efforts to better align with consumer expectations and preferences.
Understanding consumer spending patterns is vital for businesses and policymakers to tailor products and policies effectively. To study spending patterns, a group of individuals was selected, and quantitative data was collected to analyze how they distribute their income across categories such as food, transportation, clothing, entertainment, and savings. The main objective was to investigate the impact of gender and age on spending behavior and savings. Descriptive statistics, including means, Standard deviation, and graphical representations, were used alongside hypothesis testing to examine differences between groups. The findings reveal that food and entertainment account for the largest share of expenditures, with notable variations related to demographic factors such as gender and occupation. These results provide valuable information on consumer priorities and budgeting practices, offering practical implications for market segmentation and policy formulation.
This study explores how social media platforms are shaping the way consumers make purchase decisions, with a specific focus on users in Kurnool District, India. As platforms like Facebook, Instagram, and YouTube become powerful tools in digital marketing, more businesses are turning to social media to influence consumer behavior. To understand this impact, we used a quantitative approach, gathering responses from 120 participants through a structured questionnaire. The data was analyzed using multiple regression to examine the role of three key factors: site design, information quality, and trust. The findings reveal that both site design (β= X, p < 0.05) and trust (β= Y, p < 0.01) significantly influence consumer decisions, while information quality had little to no effect. The overall model accounted for about 63% of the variation in purchase behavior (R² = 0.629), underscoring the crucial role social media plays in shaping buying habits. These insights are particularly valuable for marketers looking to enhance platform usability and build trust with their audience. However, the study is limited by its geographic focus and reliance on convenience sampling. Future research could benefit from exploring a broader and more diverse demographic to validate and expand upon these findings.
