Mental health is a significant part of the total well-being, and the interest in alternative and non-pharmacological approaches promoting psychological health is increasing. Laughter therapy has become a very easy and viable way of facilitating emotional balance and alleviating stress. The current observational analysis looks at the efficacy of laughter therapy in improving the mental health of adults. The participants that were targeted in the study were adults aged between 22 and 45 years old, who were attending the sessions of laughter therapies regularly. The 25 participants who participated in the study were selected using the purposive sampling method and had been practicing laughter therapy at least a month. The data were gathered in interactive sessions and semi-structured interviews, whereby participants were enabled to give their experiences in terms of emotional and psychological changes after the laughter exercises. Data was coded into a standardized data collection table and the analysis of the data was done through a qualitative thematic analysis technique. The findings showed that a consistent attendance of laughter therapy made a significant contribution to reducing stress, enhancing mood, raising the level of energy, and improving emotional health among the participants. Better socialization and a more positive attitude towards life were also a commonly reported outcome of many respondents. The research concludes that laughter therapy is an affordable, accessible, and useful intervention that can be integrated in the community wellness programs to enhance psychological health and overall quality of life of adults.

The rapid transformation of the retail sector has shifted competitive advantage from product-centric strategies toward customer-centric experiences supported by digital integration. Existing retail frameworks address service quality or store environment in isolation, offering limited integrated models for the multidimensional nature of modern retail. Addressing this gap, the present study proposes the SERVICE framework — a seven-dimension strategic model comprising Seamlessness, Engagement-Driven Personalization, Reliability, Value-Centricity, Interactivity, Connectivity, and Experience — to explain the key drivers of experiential and omnichannel retail excellence. A quantitative survey design was employed, collecting primary data from 72 retail customers and 21 retail employees using a structured five-point Likert-scale instrument. Statistical analysis — including descriptive statistics, Cronbach's Alpha, Pearson correlation, and multiple regression — was conducted to examine the relationship between SERVICE dimensions and customer satisfaction. Findings confirm that all seven dimensions significantly influence customer satisfaction, with Experience (r = 0.724) and Interactivity (r = 0.721) emerging as the primary drivers. The regression model explains 62.3% of satisfaction variance. The SERVICE framework offers academics and practitioners a structured, empirically validated model for designing customer-centric retail ecosystems that enhance engagement, trust, and loyalty.

Financial performance analysis plays a crucial role in evaluating the operational efficiency, profitability, and financial sustainability of organizations. The transportation and tourism sector in India has witnessed significant growth in recent years, particularly with the digital transformation of railway services. The Indian Railway Catering and Tourism Corporation (IRCTC) has emerged as a key public sector enterprise responsible for catering services, tourism operations, and online railway ticket booking. Despite its strategic importance, systematic evaluation of its financial performance remains limited in academic literature. The present study aims to analyze the financial performance of IRCTC using selected financial ratios and trend analysis over a specific period. The study focuses on assessing profitability, liquidity, and operational efficiency indicators to understand the company's financial stability and growth trajectory. The research is based on secondary data collected from annual reports, financial statements, and stock exchange disclosures of IRCTC. The analysis employs financial ratio analysis, correlation techniques, and trend analysis to evaluate performance patterns. Hypothetical findings indicate that IRCTC demonstrates strong profitability and operational efficiency supported by its monopoly in online railway ticketing services and diversified tourism operations. The study contributes to existing literature by providing an analytical perspective on the financial strength of a major government enterprise in the Indian railway ecosystem. The findings may assist investors, policymakers, and financial analysts in understanding the financial sustainability and strategic position of IRCTC within the public sector framework.

The increasing complexity of financial markets and the exponential growth of data have necessitated the adoption of advanced analytical tools for accurate forecasting. Artificial Intelligence (AI) has emerged as a transformative technology in financial forecasting by enabling data-driven decision-making and predictive analytics. This study investigates the role of AI in enhancing the accuracy, efficiency, and reliability of financial forecasting models. The primary research problem addressed in this study is the limitation of traditional forecasting methods in handling large datasets and capturing non-linear market dynamics. The study aims to examine the relationship between AI techniques and forecasting accuracy and to analyze the impact of AI-driven models on financial decision-making. A quantitative research design is adopted using secondary data collected from financial reports and AI-based forecasting applications. Statistical tools such as correlation and regression analysis are employed to test the hypotheses. The findings suggest that AI significantly improves forecasting accuracy and provides timely insights compared to conventional methods. The study contributes to the existing literature by offering empirical evidence on the effectiveness of AI in financial forecasting and highlights its implications for investors, financial analysts, and policymakers.

The implementation of the Goods and Services Tax (GST) marked a significant reform in the indirect taxation system, aiming to unify fragmented tax structures and enhance economic efficiency. Despite its macroeconomic advantages, the transition posed considerable challenges for Small and Medium Enterprises (SMEs), which form the backbone of developing economies. This study investigates the impact of GST on SMEs, focusing on compliance burden, operational efficiency, cost structure, and overall financial performance. The research problem arises from the disparity between the intended benefits of GST and the actual challenges faced by SMEs in adapting to the new tax regime. The primary objectives are to examine the relationship between GST implementation and SME performance and to analyze its impact on compliance and profitability. The study adopts a quantitative research design using secondary data collected from government reports, financial databases, and industry publications over the period 2017–2024. Statistical tools such as correlation and regression analysis are employed to derive insights. The findings suggest that while GST has improved transparency and reduced cascading taxes, it has also increased compliance costs and technological dependence, particularly affecting smaller enterprises. The study contributes to policy discourse by identifying structural gaps and recommending measures to enhance GST efficiency for SMEs.

This project presents the design and development of an advanced AI-powered fitness and diet recommendation system aimed at delivering highly personalized health and wellness guidance. In contrast to traditional fitness applications that rely on generic plans, this system leverages artificial intelligence, fitness science principles, and data-driven methodologies to tailor workout routines and nutritional strategies according to individual user profiles. The system collects comprehensive user data, including demographic information (age, gender), physiological metrics (height, weight, Body Mass Index), medical conditions, injury history, lifestyle patterns, and previous exercise routines. Using this data, the application employs rule-based AI algorithms combined with analytical models to generate customized fitness plans that align with user goals such as weight loss, muscle gain, or general fitness improvement. A key feature of the system is its ability to continuously monitor user progress through periodic data updates and performance tracking. It incorporates intelligent mechanisms to detect training plateaus, performance stagnation, and muscle imbalances, enabling dynamic adjustments to workout intensity, volume, and dietary intake. This adaptive approach ensures sustained progress and reduces the risk of injury or burnout. The system is implemented using Python and Flask for backend processing, ensuring scalability and efficient handling of user requests. SQLite is utilized for lightweight and reliable database management, while the frontend is developed using HTML and CSS to provide a user-friendly and responsive interface. Additionally, AI modules analyze real-time and historical user data to refine recommendations, making the system increasingly accurate over time.

Corporate Social Responsibility (CSR) has emerged as a pivotal framework for businesses to contribute to societal well-being, particularly in the realm of sustainable educational development. This research paper explores the intricate relationship between CSR initiatives and the advancement of education systems that align with the United Nations' Sustainable Development Goals (SDGs), with a special focus on SDG 4 (Quality Education). Drawing from a comprehensive review of literature spanning 2014 to 2023, the study analyzes how higher education institutions (HEIs) integrate CSR principles into their curricula, operations, and community engagements to foster sustainable practices. Key themes include the role of CSR in enhancing educational equity, promoting ethical management education, and addressing environmental and social challenges through interdisciplinary approaches. The analysis reveals that European HEIs lead in CSR-SDG integration, with peaks in research output during 2020-2021, driven by global sustainability agendas. Practical implications highlight how CSR-embedded education equips students with responsible values, boosts institutional performance, and generates societal benefits such as reduced inequalities and improved environmental governance. However, challenges persist, including language biases in research (e.g., English-only focus) and the need for broader multidisciplinary collaborations. By examining case studies and bibliometric data from 64 peer-reviewed articles, this paper underscores CSR's potential to transform educational development into a sustainable, inclusive process. Recommendations advocate for policy reforms that encourage public-private partnerships, culturally sensitive curricula, and longitudinal impact assessments. Ultimately, CSR serves as a bridge between corporate strategies and educational sustainability, paving the way for resilient societies in the face of global crises like climate change and social disparity.

Financial inclusion has emerged as a critical component of sustainable economic development, particularly in emerging economies where a significant proportion of the population remains outside the formal financial system. The rapid advancement of digital banking services has created new opportunities to bridge this gap by providing accessible, affordable, and efficient financial solutions. However, despite technological progress, disparities in access, digital literacy, and infrastructure continue to hinder the effectiveness of such initiatives. This study aims to examine the role of digital banking services in enhancing financial inclusion and to analyze the impact of technological accessibility and user adoption on financial participation. The research adopts a quantitative approach based on secondary data collected from global financial databases, government reports, and institutional publications over the period 2015–2024. Statistical tools such as correlation and regression analysis are employed to assess relationships between variables. The findings suggest a significant positive relationship between digital banking penetration and financial inclusion indicators, particularly in terms of account ownership, transaction frequency, and credit accessibility. However, structural challenges such as digital illiteracy and regional disparities remain key constraints. The study contributes to the existing literature by providing empirical insights into the effectiveness of digital financial services and offers policy implications for enhancing inclusive growth through technology-driven financial ecosystems.

The rapid digitization of financial services has significantly transformed payment systems in emerging economies, particularly in India. The introduction of mobile-based digital payment platforms such as Paytm has revolutionized transactional behavior, especially after policy interventions like demonetization and the promotion of a cashless economy. Despite the widespread adoption of digital payment systems, there remains a need to systematically examine the growth trajectory and influencing factors of Paytm transactions in India. The primary objective of this study is to analyze the growth pattern of Paytm transactions and evaluate the factors influencing its adoption. The study employs a quantitative research approach using secondary data collected from reports published by RBI, NPCI, and Paytm. Statistical tools such as correlation and regression analysis are used to interpret the data and test hypotheses. The findings indicate a significant increase in Paytm transactions post-demonetization and during the COVID-19 pandemic, driven by factors such as internet penetration, smartphone usage, and government initiatives. The study also finds a strong positive relationship between digital infrastructure development and transaction growth. This research contributes to the existing literature by providing empirical insights into digital payment adoption trends and offers practical implications for policymakers and fintech companies.

The banking sector plays a crucial role in promoting economic growth, financial inclusion, and capital mobilization in developing economies. In India, both public sector banks and private sector banks contribute significantly to the stability and efficiency of the financial system. However, differences in governance structure, operational efficiency, and technological adoption often lead to variations in financial performance between these two categories of banks. The present study aims to conduct a comparative analytical assessment of the financial performance of public and private sector banks in India. The study focuses on examining profitability, liquidity, and solvency indicators using selected financial ratios. Secondary data has been collected from annual reports of selected banks and financial databases for the study period of the last ten years. Analytical tools such as ratio analysis, correlation analysis, and regression techniques have been employed to evaluate financial performance trends and relationships among key financial indicators. Hypothetical findings suggest that private sector banks demonstrate relatively higher profitability and operational efficiency due to technological adoption and flexible management practices, whereas public sector banks maintain stronger financial stability due to government support and wider outreach. The study contributes to the existing literature by offering a structured comparative analysis of financial indicators and providing insights for investors, policymakers, and banking regulators to understand performance differentials within the banking sector.

The rapid expansion of the start-up ecosystem in India has positioned the country as one of the leading global innovation hubs. However, fluctuations in funding patterns, changing investor sentiment, and macroeconomic uncertainties have raised concerns regarding the sustainability of start-up financing. This study investigates the evolving trends in start-up funding in India, focusing on funding stages, sectoral preferences, and investment patterns over recent years. The primary objective is to examine the relationship between funding inflows and macroeconomic as well as ecosystem-level factors, and to analyze the impact of investor behavior on funding dynamics. The study adopts a quantitative research design using secondary data collected from venture capital databases, industry reports, and financial publications. Statistical tools such as correlation and regression analysis are employed to derive insights. The findings suggest that while early-stage funding has remained relatively resilient, late-stage investments have shown volatility due to global economic conditions. Additionally, sectors such as fintech, edtech, and SaaS continue to attract significant investor attention. The study contributes to the existing literature by providing an updated and structured analysis of funding trends, offering valuable insights for investors, policymakers, and entrepreneurs.

Financial literacy has become a critical determinant of retail investor behaviour in modern financial markets. With the rapid expansion of financial products and increasing participation in capital markets, investors require adequate financial knowledge to make informed decisions. In emerging economies such as India, mutual funds have gained prominence as an accessible investment avenue due to their diversification benefits, professional management, and regulatory oversight by the Securities and Exchange Board of India (SEBI). Despite this growth, limited financial awareness among many investors continues to influence investment preferences, fund selection, and long-term investment orientation. This study investigates the relationship between financial literacy and mutual fund investment trends among retail investors. Using secondary data from the Association of Mutual Funds in India (AMFI), financial literacy surveys, and capital market databases, the study applies correlation and regression analysis to examine the impact of financial knowledge on investment participation, SIP adoption, and overall industry growth. The results indicate a strong positive relationship between financial literacy and mutual fund investments, with higher literacy levels significantly enhancing investor participation and systematic investment behaviour. The study contributes to the literature by demonstrating the importance of financial awareness in shaping investment decisions and provides policy insights for strengthening investor education programs and promoting sustainable capital market participation.

Digital transformation has become a significant catalyst for improving efficiency, transparency, and strategic decision-making in financial institutions. The integration of advanced technologies such as cloud computing, artificial intelligence, blockchain, and big data analytics has fundamentally transformed Accounting Information Systems (AIS) by enabling automated transaction processing, real-time data analysis, and enhanced financial reporting mechanisms. However, despite rapid technological progress, many financial institutions continue to face challenges in effectively integrating digital solutions within their traditional accounting infrastructures, creating a need for empirical investigation. The present study examines the impact of digital transformation on the performance and efficiency of Accounting Information Systems in selected financial institutions. The research uses secondary data collected from annual reports, financial databases, and institutional disclosures of major Indian banks. Statistical tools including descriptive statistics, correlation analysis, and multiple regression analysis were applied to examine the relationship between digital transformation indicators, AIS automation, and financial reporting efficiency. The data analysis reveals a strong positive relationship between digital technology adoption and AIS performance, indicating that institutions with higher digital transaction levels, IT investment, and automated accounting processes demonstrate superior financial reporting accuracy, transparency, and operational efficiency. The regression results further confirm that digital transformation significantly influences financial reporting quality and accounting system effectiveness. The study concludes that digital innovation is a critical driver of modern accounting systems, enhancing internal control mechanisms, financial transparency, and organizational decision-making. The findings provide valuable insights for financial institutions, policymakers, and accounting professionals seeking to strengthen digital accounting infrastructure and improve financial governance.

Financial inclusion has emerged as a critical policy priority across developing and developed economies, particularly in the context of rapid digital transformation. Despite significant advancements in digital financial services, disparities in access and usage persist due to limited financial literacy among individuals. This study investigates the role of financial education in promoting digital financial inclusion by enhancing individuals’ ability to understand, access, and effectively utilize digital financial platforms. The primary research problem centers on the gap between technological availability and user adoption driven by inadequate financial knowledge. The study aims to examine the relationship between financial education and digital financial inclusion and analyze the impact of financial literacy on the adoption of digital financial services. A quantitative research design is adopted using secondary data from global financial databases and institutional reports. Statistical tools such as correlation and regression analysis are employed to evaluate relationships between variables. The findings (hypothetical) indicate a significant positive association between financial education and digital financial inclusion, suggesting that improved financial literacy enhances digital adoption. The study contributes to the literature by bridging the gap between financial knowledge and technological adoption, offering insights for policymakers and financial institutions to design effective inclusion strategies.

Financial literacy has emerged as an essential competency in modern economies where individuals are increasingly responsible for managing their personal finances and investment decisions. Among young adults, particularly college students, financial knowledge plays a crucial role in shaping saving behavior, risk perception, and investment planning. Despite the increasing availability of financial products and digital investment platforms, many students lack adequate financial literacy to make informed financial decisions. This study investigates the impact of financial literacy on investment decision-making among college students. The primary objective of the research is to examine the relationship between financial knowledge and investment behavior and to analyze how financial awareness influences students’ investment choices. The study adopts a quantitative research design using structured questionnaire-based data collected from college students. Statistical techniques such as correlation and regression analysis are used to examine the relationship between financial literacy and investment decisions. Hypothetical findings suggest that students with higher financial literacy demonstrate greater confidence in investment decisions and are more likely to engage in diversified financial investments such as mutual funds, equities, and systematic investment plans. The study contributes to the existing literature by highlighting the importance of financial education among youth and provides insights for policymakers, educational institutions, and financial educators to design effective financial literacy programs that can promote responsible investment behavior among young investors.

Insurance plays a crucial role in financial planning by providing risk protection and promoting long-term financial security. Despite the growing expansion of financial markets and the increasing availability of insurance products, a significant portion of individuals still demonstrate limited awareness regarding insurance as an investment and risk management tool. Lack of financial literacy, misinformation, and inadequate awareness campaigns often lead to suboptimal investment decisions and underutilization of insurance services. The present study aims to examine the level of insurance awareness among individuals and analyse its influence on their investment behavior. The study employs a quantitative research approach using secondary and survey-based analytical insights to evaluate the relationship between insurance awareness and investment decisions. Statistical tools such as correlation and regression analysis are applied to understand the strength and direction of the relationship between awareness levels and insurance investment behavior. Hypothetical findings suggest that individuals with higher insurance awareness are more likely to adopt diversified investment portfolios and show greater participation in insurance-based financial instruments. The study contributes to the growing literature on financial literacy and investment decision-making by highlighting the importance of insurance awareness in shaping rational financial behavior. The findings may assist policymakers, financial institutions, and regulators in designing effective financial literacy programs and awareness campaigns to improve insurance penetration and promote informed investment decisions.

The mutual fund industry in India has experienced significant growth over the past decade, driven by increasing financial awareness, technological advancements, and regulatory support. Despite this expansion, investor behaviour remains heterogeneous and often influenced by psychological, demographic, and economic factors. This study aims to analyse the investment behaviour of mutual fund investors with specific reference to SBI Mutual Fund, one of India’s largest asset management companies. The research problem centres on understanding how investor perceptions, risk tolerance, and financial literacy shape investment decisions. The study adopts a quantitative research design using secondary data sources, including annual reports, industry publications, and financial databases. Statistical tools such as correlation and regression analysis are employed to examine relationships among variables such as risk perception, return expectations, and investment patterns. Hypothetical findings suggest that investor awareness and risk appetite significantly influence mutual fund investment decisions, while demographic factors such as age and income also play a moderating role. The study contributes to the existing literature by offering insights into behavioural finance within the Indian mutual fund context and provides practical implications for fund managers and policymakers to enhance investor engagement and financial inclusion.

This study explores the practicality and acceptance of alternative fuels in India’s commercial vehicle industry, which is crucial for freight transport and economic development. Even with more stringent emission standards and increasing environmental worries, diesel remains the primary fuel in this sector because of its high energy content, dependability, and established refueling system. The research assesses the viability of alternative fuels like Compressed Natural Gas (CNG), Liquefied Natural Gas (LNG), battery electric vehicles (BEVs), and hydrogen, while also pinpointing the major factors and obstacles affecting their implementation in the logistics sector. Employing a descriptive research approach, primary data was gathered via a structured survey from 24 experienced professionals engaged in freight transport activities, including fleet managers and logistics executives. The results indicate that while knowledge of alternative fuels is widespread, actual implementation is still restricted due to substantial upfront expenses, insufficient charging and refueling facilities, and operational ambiguities. The study determines that a phased shift supported by a multi-fuel strategy, infrastructure expansion, and robust policy backing will be needed to foster sustainable and low-emission freight transport in India.

The rapid evolution of financial technology has significantly transformed consumer credit systems, with Buy Now Pay Later (BNPL) services emerging as a prominent alternative to traditional credit mechanisms. This study examines the growth trajectory of BNPL services, focusing on their adoption patterns, underlying drivers, and financial implications. The research problem centers on understanding whether BNPL growth is driven by genuine financial inclusion or by unsustainable consumer borrowing behavior. The primary objectives of the study are to evaluate the growth trend of BNPL services and to analyze the impact of technological and behavioral factors on their adoption. The study employs a quantitative research design using secondary data collected from financial reports, fintech databases, and market surveys. Statistical tools such as correlation and regression analysis are applied to identify relationships between variables such as user adoption, digital payment infrastructure, and consumer spending behavior. The findings indicate a strong positive relationship between digital payment penetration and BNPL adoption, while also highlighting concerns regarding consumer indebtedness and regulatory gaps. The study contributes to the existing literature by providing a comprehensive analytical framework for understanding BNPL growth and its implications for financial stability, policymakers, and investors.

This study examines the impact of influencer credibility on Generation Z’s purchase decisions, with a focus on the Indian market. As influencer marketing continues to shape digital consumer behavior, the research analyzes how credibility factors such as trustworthiness, authenticity, expertise, attractiveness, and relatability influence Gen Z’s buying choices. A quantitative research approach was adopted using a structured online questionnaire, supported by observational analysis of social media engagement trends. Findings reveal that Instagram and YouTube are the most preferred platforms for product discovery among Gen Z. A significant number of respondents reported purchasing products promoted by influencers, confirming the effectiveness of influencer marketing. However, Gen Z consumers demonstrate selective trust, often verifying influencer recommendations through additional sources before making purchase decisions. Among the credibility dimensions, trust, authenticity, and relatability were identified as the strongest determinants of influence.

The rapid transformation of the E-world has significantly influenced many business sectors, including online share trading. The equity cash segment in India has shown significant growth. According to reports from the National Stock Exchange, equity cash turnover reached ₹23.9 lakh crore in January 2026 (24% year-on-year increase), with average daily turnover rising to ₹1.2 lakh crore. The increasing volume of online stock market transactions highlights the need for a better understanding of the ever-evolving requirements and expectations of traders. This secondary research study presents a comparative analysis of day trading operations of major stock market platforms - Zerodha, Upstox, Groww, and Angel One. The study serves as a guiding reference for fintech companies seeking to enhance intra-day trader engagement and loyalty, while also helping intra-day traders select the most suitable mobile application for share trading.

Equity mutual funds have emerged as a significant investment avenue for both retail and institutional investors seeking long-term capital appreciation and portfolio diversification in modern financial markets. With the rapid expansion of the mutual fund industry, the need for systematic evaluation of fund performance in terms of risk and return has become increasingly important. Despite the wide availability of mutual fund schemes, investors often face challenges in determining whether these funds generate adequate returns relative to the level of risk undertaken. This study examines the risk–return characteristics of selected equity mutual funds using secondary market data obtained from published financial reports, mutual fund fact sheets, and financial databases. The study adopts a quantitative research design and evaluates key performance indicators such as average return, standard deviation, and beta to measure return performance and market risk exposure. Descriptive statistics, correlation analysis, and regression analysis are employed to investigate the relationship between risk and return. The empirical analysis reveals a strong positive association between risk indicators and mutual fund returns, indicating that funds with relatively higher volatility tend to generate superior returns over the study period. The findings highlight the importance of risk-adjusted performance evaluation in mutual fund investment decisions. The study concludes that equity mutual funds generally provide competitive market-linked returns, but their performance significantly depends on risk management and portfolio strategy. The research contributes to capital market literature by offering empirical insights into mutual fund performance evaluation and provides practical implications for investors, portfolio managers, and policymakers.

This study examines the role of information technology (IT) in smart city energy management, focusing on digital innovations that enhance sustainable urban development. Rapid urbanization has intensified energy demand in metropolitan regions, necessitating efficient energy governance systems. Smart cities leverage advanced technologies such as Internet of Things (IoT), artificial intelligence (AI), smart grids, and big data analytics to optimize energy production, distribution, and consumption. The study is based on secondary data analysis of energy management initiatives in Mumbai, India, including smart metering, renewable energy integration, and digital monitoring platforms. Quantitative assessment demonstrates improved energy efficiency, reduced transmission losses, and enhanced renewable energy adoption through digital interventions. Statistical testing indicates a significant positive relationship between IT implementation and sustainable energy management outcomes. The findings confirm that digital innovations contribute substantially to improved energy performance indicators in urban systems. The study concludes that strategic deployment of information technology is essential for sustainable urban transformation and energy resilience in developing metropolitan contexts.

Microfinance has emerged as a significant financial instrument for promoting inclusive economic growth and supporting entrepreneurial development among marginalized communities. In developing economies such as India, access to formal credit remains a critical barrier for women aspiring to establish and expand entrepreneurial ventures. Microfinance institutions (MFIs) play an important role in bridging this financial gap by providing small loans, financial literacy, and business support services to women entrepreneurs who are traditionally excluded from formal banking systems. The present study examines the role of microfinance in facilitating women entrepreneurship development and evaluates its impact on entrepreneurial growth and financial empowerment. The study focuses on identifying the relationship between microfinance accessibility and the growth of women-led enterprises. Using secondary data sources such as reports from microfinance institutions, government publications, and research databases, the study employs correlation and regression analysis to examine the influence of microfinance on women entrepreneurship outcomes. Hypothetical analytical results indicate that access to microfinance significantly enhances women’s entrepreneurial participation, income generation capacity, and business sustainability. The findings suggest that microfinance contributes not only to economic empowerment but also to social empowerment by improving women's decision-making capacity and financial independence. The study contributes to the growing body of literature on financial inclusion and entrepreneurship by providing insights into the effectiveness of microfinance programs in supporting women-led businesses. The research also highlights policy implications for strengthening microfinance frameworks to promote sustainable women entrepreneurship development.

The global tourism industry has undergone a radical paradigm shift from traditional brick-and-mortar agencies to digital-first ecosystems, where Online Travel Agencies (OTAs) serve as the primary gateway for millions of travellers worldwide. However, this rapid digitization has birthed a significant "Trust Crisis" characterized by systemic friction, choice overload, and algorithmic opacity. Modern travellers are increasingly plagued by deceptive "Drip Pricing"—the incremental revelation of mandatory fees—and a dangerous reliance on subjective, often unverified user reviews for safety assessments. These "Dark Patterns" lead to significant consumer detriment, high booking abandonment rates, and a measurable deficit in long-term brand loyalty as users feel "tricked" by hidden costs. This research introduces Explora, a technological response designed to restore consumer confidence through a "Transparency-First" architecture. Developed using a robust Model-View-Controller (MVC) pattern with a PHP and MySQL backend, the Explora framework implements a real-time upfront pricing engine and an objective Safety Verification Module. Unlike traditional aggregators that prioritize listing volume and subjective feedback, Explora utilizes data-driven safety metrics based on objective infrastructure parameters, such as proximity to police stations and emergency services. By shifting the industry standard from "Subjective Reviews" to "Objective Metrics," the system effectively addresses the information asymmetry that currently leaves travellers, particularly solo and female tourists, vulnerable. Empirical validation of the Explora framework was conducted through a structured survey of frequent travellers ($n=100$), focusing on metrics of financial frustration and safety demand. Data analysis confirms a critical market need for transparency, with 72.5% of respondents indicating that official verified safety scores would significantly influence their platform trust. Furthermore, hypothesis testing using a one-sample proportion Z-test yielded a Z-value of 4.80 ($p < 0.001$), providing strong statistical evidence to reject the null hypothesis and conclude that consumers significantly prefer platforms offering "Verified Safety and Price Transparency" over traditional non-transparent models. The study concludes that ethical design prioritizing honesty is not merely a moral imperative but a viable and necessary business strategy for the modern, safety-conscious traveller.

The rapid advancement of financial technology has significantly transformed the structure and operational dynamics of modern financial institutions. Technology-driven financial institutions, including digital banks, fintech platforms, and technology-enabled financial service providers, increasingly rely on sophisticated digital infrastructures, automated financial systems, and data-driven governance frameworks. While these innovations enhance operational efficiency, financial accessibility, and digital financial inclusion, they simultaneously raise critical concerns related to corporate governance effectiveness and financial transparency. In technologically complex financial environments, weak governance structures may increase the risk of financial misreporting, information asymmetry, and regulatory oversight challenges. The present study examines the relationship between corporate governance mechanisms and financial transparency in technology-driven financial institutions. Specifically, the research evaluates the influence of governance structures such as board independence, audit committee effectiveness, and ownership concentration on financial disclosure practices. The study adopts a quantitative research design using secondary data collected from annual reports and financial disclosures of selected technology-driven financial institutions over a defined study period. Statistical techniques including correlation analysis and multiple regression models are applied to assess the relationships between governance variables and transparency indicators. The empirical analysis demonstrates that stronger governance mechanisms significantly improve financial disclosure quality, organizational accountability, and stakeholder confidence. The findings confirm that effective governance frameworks play a vital role in strengthening financial transparency within digital financial ecosystems. The study contributes to the growing literature on fintech governance and financial reporting, offering valuable insights for regulators, investors, and policymakers seeking to enhance governance standards in technology-driven financial institutions.

The rapid advancement of artificial intelligence (AI), big data analytics, automation, and digital platforms is fundamentally transforming higher educational institutions (HEIs) across the globe. Digital leadership has emerged as a strategic imperative to navigate AI-driven disruptions while ensuring resilience, ethical governance, sustainability, and inclusive development. This theoretical paper examines the conceptual foundations of digital leadership in HEIs, synthesizes extant literature on AI-based disruptions, and proposes an integrated ethical-sustainability roadmap for institutional leaders. Drawing upon leadership theories, digital transformation frameworks, technology acceptance models, institutional theory, stakeholder theory, sustainability paradigms, and ethical AI governance frameworks, this paper reviews more than thirty scholarly contributions to position digital leadership as a multidimensional construct encompassing technological competence, ethical foresight, governance agility, and sustainable value creation. The study contributes to interdisciplinary discourse by aligning AI governance with academic values, digital resilience, and policy frameworks, thereby offering a comprehensive roadmap for HEIs to evolve into ethically responsible, digitally resilient institutions.

The rapid growth of financial technology (FinTech) has significantly transformed traditional financial services by introducing digital platforms, algorithm-based financial solutions, and technology-driven service delivery models. In such a dynamic and highly competitive environment, Innovation Management Practices have become a critical strategic capability for FinTech startups seeking to maintain technological competitiveness, operational efficiency, and sustainable market growth. However, despite the growing importance of innovation within FinTech ecosystems, many startups encounter challenges in establishing structured innovation frameworks due to resource constraints, regulatory uncertainty, and rapid technological change. This study examines the role of innovation management practices in influencing the performance and adaptability of FinTech startups. The research adopts a quantitative research approach using secondary data obtained from industry reports, startup databases, and financial disclosures of selected Indian FinTech firms such as CRED, Moneyview, Fibe, and LenDenClub. Statistical techniques including correlation and regression analysis were applied to evaluate the relationship between research and development investment, technological collaboration, product innovation, and revenue growth. The data analysis reveals a strong positive relationship between innovation management activities and startup performance, indicating that firms emphasizing R&D investment, digital innovation, and technology partnerships achieve improved product development efficiency, market responsiveness, and financial growth. The study concludes that effective innovation management significantly strengthens the competitiveness and sustainability of FinTech startups and provides valuable implications for entrepreneurs, investors, and policymakers aiming to promote innovation-driven financial ecosystems.

Public-Private Collaborations have emerged as a key strategy for improving higher education in India by leveraging private-sector investment, efficiency and innovation. This paper explores the conceptual framework, examines notable success stories, and analyses lessons learned from these initiatives. Despite noteworthy success stories, the study also identifies major challenges, including regulatory challenges, affordability issues and limited capacity. Through a review of literature, policy analysis and case studies, the paper provides a comprehensive understanding of the effectiveness of collaboration in higher education. The study concludes with policy suggestions to make the collaboration more inclusive, sustainable and accountable. These insights offer key suggestions for educational leaders, policymakers and private stakeholders seeking to reform and expand higher education system in India through collaborative models.

The rapid expansion of Financial Technology (FinTech) has fundamentally transformed the global financial services landscape by integrating digital platforms, artificial intelligence, and data-driven technologies into traditional financial operations. In such knowledge-intensive environments, effective Knowledge Management (KM) practices are essential for enabling organizations to innovate, enhance operational efficiency, and sustain long-term competitive advantage. Despite the increasing growth of FinTech firms, limited empirical research has examined how structured knowledge management processes influence organizational performance and innovation capability in this emerging sector. The present study investigates the role of knowledge acquisition, knowledge sharing, and knowledge application in shaping the performance of FinTech companies. The research adopts a quantitative research design using secondary data collected from industry reports, corporate disclosures, and financial technology databases covering selected FinTech firms during the period 2018–2024. Statistical techniques including correlation analysis and multiple regression analysis are applied to examine the relationships between knowledge management practices and organizational outcomes. The empirical analysis reveals a strong positive relationship between knowledge management practices and innovation capability, with regression results indicating that KM variables explain a substantial proportion of variation in organizational performance. Firms demonstrating stronger knowledge sharing cultures and technology-enabled knowledge systems exhibit higher levels of innovation, strategic decision-making efficiency, and operational effectiveness. The study concludes that systematic implementation of knowledge-driven management frameworks significantly enhances innovation-led growth in FinTech companies. The findings provide valuable insights for FinTech managers, policymakers, and researchers seeking to strengthen knowledge-based capabilities within rapidly evolving digital financial ecosystems