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Electronic garbage, or “e-waste,” which includes outdated or discarded electronic appliances, has increased in tandem with the exponential expansion in the use of electronic devices. Lead, mercury, and brominated flame retardants are among the dangerous materials found in e-waste that can leak into the environment and pollute the soil, water and air while also posing major health concerns to people and wildlife.
At almost 2 million metric tons per year, India is currently the world’s third-largest producer of electronic garbage, or “e-waste.” Computer machines produce the majority of this waste, followed by telephones and other electronic equipment. Significant geographic differences were highlighted by the approximately 150% increase in e-waste volumes during the six-year period (2017–2024), with the majority of the waste concentrated in about 65 urban areas and 10 states.
Only a small portion of e-waste is collected and recovered by the formal sector, regardless of current legislation. The informal recycling sector in India, which manages more than 95% of e- waste using crude techniques that emit harmful chemicals, makes the e-waste situation worse.
This paper highlights the present scenario of e-waste in various parts of India in comparison to world while highlighting the challenges.
In the end this paper also offers various sustainable strategies aligned with circular economy principles to enhance resource efficiency and practice the sustainable development strategies.

The way customers experience the automotive industry has changed dramatically in recent years, and artificial intelligence (AI) lies at the heart of this shift. This systematic review examines how AI-enabled technologies ranging from advanced driver assistance systems (ADAS) and predictive maintenance to natural language processing (NLP)-powered assistants and IoT-connected services are reshaping customer experience (CX) across the entire vehicle ownership lifecycle. Drawing on peer-reviewed literature published between 2021 and 2025, as well as evidence from leading automotive firms including Tesla, BMW, and Mercedes-Benz, this paper argues that AI does not merely improve existing services; it fundamentally alters how trust, satisfaction, and loyalty are formed. The review also highlights the barriers that slow AI adoption, notably consumer trust deficits, data privacy risks, and implementation costs and proposes actionable strategies for automotive firms navigating this landscape. A pictorial conceptual framework is developed to map AI capabilities onto trust mediators and customer outcomes in a visually accessible format

Man by nature mobile in pursuit of place, profession, promotion, publicity, political mileage, and pleasures. Mobility is a fundamental right. Transportation contributed to the progress of the world to a considerable extent. The world would be less exciting if there is no transportation. Transportation improves urbanization. Therefore, transportation is the driving force for the development of any nation. The performance of transportation systems can be measured through qualitative and quantitative factors. One of the essences of service quality in transportation is reliability. The causes of non-reliability in public transportation would be breakdowns, traffic congestion, and unexpected demand. Reduced breakdowns result in the reliability of transportation. The present study has been taken up to study the impact of causes for breakdowns. Four State Transport Corporations are operating in Karnataka State: KSRTC, BMTC, NWKRTC and NEKRTC. The present study found that BMTC and KSRTC had more opportunities to reduce the breakdowns. Whereas, NWKRTC and NEKRTC had moderate opportunities to reduce the breakdowns.

The growth of artificial intelligence and online task platforms has significantly increased the importance of crowd work within the global digital economy. The present study explores the determinants of career advancement and development among crowd workers engaged in online labor platforms. The study examines the influence of digital skills, platform reputation, and platform support on career growth opportunities in crowd work environments. A quantitative research design was adopted, and primary data were collected from 200 crowd workers through a structured questionnaire. Snowball sampling was used due to the dispersed and digitally connected nature of the target population. Statistical tools such as Pearson correlation, Independent Sample t-test, and One-Way ANOVA were employed to analyze the collected data. The study indicates that digital competencies, positive platform reputation, and supportive platform practices significantly influence career advancement among crowd workers. The research highlights the growing importance of professional development, skill enhancement, and ethical platform governance in digital labor systems. The findings provide useful implications for platform operators, policymakers, and researchers in promoting sustainable career development and inclusive employment opportunities within AI-driven online work ecosystems.

This study examined the impact of macroeconomic factors on stock prices in the pharmaceutical industry utilizing monthly data for the period January 2015 through December 2025. The autoregressive distributed lag (ARDL) modeling approach and bounds testing were used to evaluate whether or not there is a long-term relationship between macroeconomic variables and stock prices in the pharmaceutical sector, and the evidence found no long-term stable cointegration between macroeconomic variables and stock price movement, thus the focus of this study was on short-run dynamics. Empirical findings of this study document that inflation has a significant effect on stock returns, and the sensitivity of stock returns to inflation is increased by changes in the foreign exchange rate (i.e., a devaluation of the rupee). Furthermore, the interaction of inflation with changes in the foreign exchange rate provides evidence for transmission mechanisms which impact the performance of the pharmaceutical sector at the macroeconomic level. Also, the GARCH (1,1) volatility model indicates a short-lived event driven volatility which exhibits a high level of mean reversion. Results of structural break tests also indicate beginning in 2020 that there are issues with instability resulting primarily from global events (such as the COVID-19 pandemic), however these newly found structural breaks do not alter any of the conclusions drawn from this study’s models. Finally, the findings of this research indicate that the derived models demonstrated strong forecasting capabilities which outperformed the benchmark models employed. In conclusion, this study demonstrates that inflation and the value of the US dollar/euro exchange rate significantly influence the determination of stock returns in the pharmaceutical sector and provide useful insights to investors and policymakers for managing macroeconomic risks.

Digital financial inclusion has emerged as a vital factor in promoting inclusive economic growth by enhancing the accessibility of financial services among rural communities. This study focuses on analysing the challenges and opportunities associated with digital financial inclusion in the rural regions of Idukki district, Kerala. The research is primarily based on data collected from 100 rural respondents through a structured interview schedule. Respondents were selected using the purposive sampling method, considering individuals who regularly utilise digital financial services such as mobile banking, internet banking, UPI platforms and digital wallets. For the purpose of analysis, statistical techniques including percentage analysis, mean and standard deviation, Chi-square test, and One Sample t-test were employed. The results of the study indicate that digital financial inclusion has considerably enhanced financial access and encouraged greater participation in formal financial activities among rural residents. At the same time, several barriers continue to limit the effective adoption of digital financial services. These challenges include inadequate digital literacy, unstable internet connectivity, concerns regarding cybersecurity and insufficient awareness about digital financial platforms. The study concludes that the development of digital infrastructure together with effective financial literacy programmes is essential for achieving sustainable and inclusive digital financial growth in the rural areas of Idukki district, Kerala.

India’s Fin Tech sector, valued at USD 51.3 billion in 2026, has emerged as one of the world’s fastest-growing digital finance ecosystems, with an adoption rate of 87% — well above the global average. The Unified Payments Interface (UPI) alone processed over 8 billion transactions per month in 2025, while UPI accounted for over 80% of all retail digital payments in India in FY 2025–26. The Indian financial technology (Fin Tech) ecosystem has experienced exponential growth over the past decade, driven by government initiatives such as Digital India and Jan Dhan Yojana, widespread smartphone penetration and a young, digitally-native population. This study investigates the multifaceted influence of Fin Tech on India’s economy, with a specific focus on its differential impact across entrepreneurs, investors and consumers. Using a structured survey administered to 120 respondents across tier-1, tier-2 and tier-3 Indian cities, the study employs descriptive statistics, chi-square tests and regression analysis. Key findings reveal that Fin Tech adoption has significantly reduced transaction costs, improved access to institutional credit and democratised investment opportunities. However, cybersecurity concerns, digital literacy deficits and regulatory ambiguity remain substantial barriers. The study concludes with actionable policy recommendations for regulators, Fin Tech firms and financial institutions.

This study examines consumer behaviour toward eco-friendly products with particular emphasis on the gap between purchase intention and actual buying behaviour. The research also investigates the influence of product visibility and eco-label awareness on consumer trust and purchase decisions. A combination of descriptive and analytical research designs was adopted. Primary data were collected from 100 respondents in Kozhikode district using a structured questionnaire, and analysed using SPSS. Statistical tools including paired sample t-test, multiple regression, and Spearman correlation were employed to test the hypotheses. The findings reveal a significant gap between consumers’ intention to purchase eco-friendly products and their actual buying behaviour, indicating that positive attitudes do not always translate into action. The regression results show that product visibility, in terms of availability and display, does not significantly influence purchase behaviour. However, eco-label awareness is found to have a significant positive relationship with consumer trust and purchase decisions, highlighting the importance of credible and transparent labelling. The study concludes that trust plays a crucial role in promoting sustainable consumption. It suggests that policymakers and marketers should focus on enhancing consumer awareness and strengthening trust mechanisms to bridge the intention–behaviour gap and encourage environmentally responsible purchasing practices

The article examines the transformation of end-to-end automation in large organizations driven by generative and agentic AI. The aim of the work is to conceptualize the gap between formal regulations and actual process execution and, on this basis, to propose architectural principles for multi-agent orchestration. The relevance of the topic is determined by the limitations of classical robotic automation and workflow management systems when confronted with rich context, high variability, and stringent requirements for decision traceability. The novelty of the article lies in synthesizing research on intelligent automation, BPM, and human-in-the-loop approaches into a foundational multilayer architecture, in which agents function as specialized executors with explicit I/O contracts, decoupled from the orchestrator; policies and knowledge formalize the boundaries of autonomy; and human participation is treated as a regularized risk-management procedure. It is shown that such an architecture shortens process cycle times, reduces errors at role interfaces, supports reuse of agent roles, and shifts process management toward a regime of observable execution. It also provides an industry-grounded illustration of these principles through an enterprise-scale clinical service launch in which a new treatment modality was evaluated, governed, and rolled out across distributed sites under strict evidence discipline, risk controls, and measurable financial outcomes. This case exemplifies how multi-agent orchestration, contractual handoffs, and formalized escalation can translate into accelerated adoption, reduced execution friction at interfaces, and auditable value creation. The article is intended for AI system architects, process owners, and digital transformation leaders.

The impact of AI personalization of social media advertising on customer behaviour and its implications for sustainable brand engagement. This research examines the influence of social media advertising and artificial intelligence on sustainability and consumer trust and consumer involvement with the organization. The data from secondary data source is quantitative and the received data is subjected to descriptive statistics correlation and regression analysis and SEM calculated.