The Role Of Blockchain Technology In Enhancing Financial Transparency And Auditing
Authors: Dr. Rajidi Rammohan Reddy
Abstract: Financial scandals and the challenge of information asymmetries in corporate governance systems have revealed severe inadequacies in the existing systems of financial reporting and audits. Being inherently decentralized, immutable, and programmable, blockchain technology brings transformative capabilities to improve financial transparency and auditability in these systems. In this paper, we conduct a detailed study on how blockchain can be applied for financial transparency through a conceptual model that leverages three innovative features, such as triple entry accounting, automated compliance using smart contracts, and real time continuous auditing. We suggest a combination of permissioned blockchain architecture and cloud computing techniques to deal with scalability and regulatory issues that arise when applying blockchain in financial governance. Through our quantitative analysis, we show significant gains in the performance measures that include 88% decrease in audit delay time, 94% drop in data manipulation events, and 76% improvement in stakeholder trust index.
DOI: http://doi.org/10.5281/zenodo.22768600
Assessing the Barriers to Growth Among Women-Owned Businesses: A Case Study of Women Selling Vegetables and Second-Hand Clothes in Chilenje, Lusaka
Authors: Arockia Anisha
Abstract: Enterprises owned by women are central to trade in Zambia’s urban townships, yet they remain smaller, earn less and grow more slowly than those owned by men. This study assesses the barriers to growth among women-owned businesses in Chilenje, Lusaka, with particular reference to women trading in vegetables and in second-hand clothing. It pursued three objectives: to identify the barriers constraining growth, to examine the effects of those barriers on performance and growth, and to establish the strategies the owners use in order to work around them. A mixed-methods descriptive case-study design was adopted. A structured questionnaire was administered to a stratified sample of sixty women traders drawn equally from the two trades, and was supplemented by semi-structured interviews, key informant interviews and structured observation at the trading points. Quantitative data were analysed descriptively and comparatively, using means, frequencies, independent-samples t-tests and chi-square tests; qualitative data were analysed thematically. The study is framed by Kabeer’s (1999) resources, agency and achievements framework, which treats a barrier as whatever obstructs the conversion of resources into outcomes. The findings show that the three finance-related barriers dominate both the severity ratings and the traders’ own ranking of priorities: insufficient money for stock, lack of access to a bank or microfinance loan, and lack of collateral together occupy the first three positions on both measures. Only thirteen per cent of respondents had ever borrowed from a formal lender, while eighty-five per cent were unregistered and fifty-seven per cent relied instead on chilimba. Three barriers differed significantly between the trades: spoilage and storage pressed harder on vegetable traders, while the demands of home and childcare pressed harder on traders in second-hand clothing. Record keeping, the constraint most commonly addressed by training programmes, was ranked last of thirteen by the traders themselves. The study concludes that the binding constraint in Chilenje is not the absence of business knowledge but the absence of usable working capital on terms that unsecured, unregistered traders can meet, compounded by physical conditions at the trading point which convert a shortage of capital into a recurring loss of it. It recommends collateral-free working- capital products designed around the two distinct purchase cycles observed, investment by the local authority in covered and secured storage, and the formal recognition of chilimba groups as the delivery channel that traders already trust.
Digital Financial Inclusion And Microenterprise Growth In Developing Economies: Evidence From An Empirical Primary Field Survey In India
Authors: Pranav Mittal
Abstract: This primary research paper empirically investigates the nexus between digital financial inclusion and microenterprise growth, focusing on traditional craft clusters and informal artisanal sectors in Lucknow, India. Utilizing primary data derived from a comprehensive online and field survey (N=420), this study employs robust inferential methodologies, including Ordinary Least Squares (OLS) regression modeling and independent samples Welch’s t-tests leveraging categorical median splits. The research systematically evaluates six distinct hypotheses concerning the differential impacts of digital payments, algorithmic credit access, digital savings, micro-insurance, cognitive financial literacy, and the temporal duration of digital experience. The empirical analyses yield statistically significant results across all digital financial dimensions, leading to a comprehensive rejection of the null hypotheses. The findings demonstrate that structural integration into the digital financial ecosystem significantly and positively accelerates enterprise revenue growth trajectories. Furthermore, the paper discusses underlying socioeconomic mechanisms—such as the disintermediation of traditional supply chains, the mitigation of information asymmetry in algorithmic lending, and the behavioral economics of liquidity management. The paper concludes by offering actionable policy recommendations designed to foster equitable, digitally-enabled economic development and delineating critical avenues for future longitudinal and experimental research.
DOI: http://doi.org/10.5281/zenodo.22843590
Family Ownership and Corporate Performance: Evidence from Listed Indian Companies
Authors: Kashvi Biyani
Abstract: This study examines the association between family ownership and financial characteristics of listed Indian companies. Using balanced panel data for 50 firms over the period 2020–2025, comprising 300 firm-year observations, the study investigates the relationship between family ownership and corporate performance. The analysis employs panel regression techniques, including fixed-effects and two-way random-effects models, along with diagnostic and robustness tests. The findings indicate a positive association between Family Holding and EPS. The results also indicate significant cross-sectional dependence among the sampled firms, supporting the use of robust estimation. Overall, the findings suggest that family ownership is more closely associated with firm size and, to a lesser extent, earnings performance, while liquidity and leverage show no statistically significant relationship within the sampled Indian listed firms.
Regulatory Challenges and Strategic Policy Interventions for Scaling the Algae Bioeconomy in Tamil Nadu: A Case Study of Chennai
Authors: Dr. Lucas Esther Thamarine, Dr. Uthira. D, Dr. Anuradha. R
Abstract: Tamil Nadu, with its extensive coastline, industrial infrastructure, and environmental challenges, holds significant potential for developing a robust algae bioeconomy. Algae-based biofuels and bioproducts offer sustainable alternatives to fossil fuels, contribute to climate resilience, and create green employment opportunities. However, commercialization in the region—particularly in urban hubs like Chennai-is constrained by fragmented regulations, limited policy incentives, and infrastructural gaps. The algae bioeconomy presents a transformative opportunity for sustainable development, yet its growth in Tamil Nadu requires targeted policy reform and institutional support. This paper explores the regulatory landscape affecting algae innovation, identifies key barriers to sectoral expansion, and proposes strategic policy interventions to unlock its potential. Drawing on regional policy analysis, stakeholder interviews, and comparative global benchmarks, the study outlines a roadmap for advancing sustainable algae commercialization in Tamil Nadu.
Cultural Intelligence, HR Practices And Job Performance: The Mediating Role Of Technological Adaptation Among Healthcare Professionals In The UAE
Authors: Sheeja Selestine, Dr. Vishal Vinayak
Abstract: Purpose – The healthcare sector in United Arab Emirates (UAE) puts together one of the world’s most culturally diverse clinical workforces with very quick digital transformation. This study explores and learns how cultural intelligence (CQ) and human resource (HR) practices moulds healthcare professional’s technological adaptation (TA) and, with the help of it, their job performance (JP). Design/methodology/approach – Among 400 nurses, doctors and allied health professionals who work in Dubai and Abu Dhabi, a cross-sectional survey was conducted, they were selected through proportionate and stratified sampling. HR practices (18 items), job performance (12 items), technological adaptation grounded in UTAUT (16 items), and Validated scales for CQ (20 items) were used. Data were analysed using regression and partial least squares structural equation modelling (PLS-SEM) with 5,000 bootstrap resamples. This was followed by mediation and multi-group analysis. Findings – CQ (β = 0.345) and HR practices (β = 0.259) predicted technological adaptation, which was the strongest predictor of job performance (β = 0.457). Technological adaptation mediated the effects of both CQ (indirect effect = 0.158) and HR practices (indirect effect = 0.118) on performance. Wholly, the model explained 24.0% of the variance in TA and 36.8% in JP, and the structural relationships were invariant across the two Emirates. Originality/value – The study merges cultural intelligence theory, the ability–motivation–opportunity (AMO) view of HRM and the Unified Theory of Acceptance and Use of Technology (UTAUT) in a single model, positioning technological adaptation as the mechanism through which individual cultural capabilities and organisational HR systems translate into clinical performance in a multicultural setting.
DOI: https://zenodo.org/records/22958819
The Strategic Role Of BSFIC In Bangladesh’s Household Sugar Market Consumer Preference, Domestic Supply, And Price-Stabilisation Potential A Market-segmentation And Policy-analysis Paper
Authors: Mohammad Nazmul Huda
Abstract: Bangladesh’s sugar market is structurally import-dependent. Recent industry reporting places annual sugar demand at approximately 20–22 lakh metric tonnes, while domestic sugar mills produce only around 30–35 thousand tonnes in aggregate. BSFIC’s FY2023–24 production was reported at 46,197 tonnes, illustrating the large gap between national demand and state-sector production. This paper argues that the strategic significance of Bangladesh Sugar and Food Industries Corporation (BSFIC) should not be assessed solely by its share of national production. A separate household-consumer segment—covering tea, coffee, home-prepared sweets, traditional foods and other everyday uses—requires analysis because its purchasing behaviour differs from that of industrial bulk users. The paper develops a conceptual framework in which BSFIC can function as an alternative domestic supply channel and a potential price-disciplining participant. Historical evidence supports this institutional role: BSFIC has repeatedly used open-market and dealer sales, stockholding and Ramadan-oriented distribution to support price stability. BSFIC’s own SDG reporting states that the corporation helps the government keep sugar prices stable. Recent market episodes also demonstrate the vulnerability of retail prices to import costs, refinery disruptions and supply concentration. The paper does not claim that BSFIC currently controls a specified percentage of household consumption. Rather, it proposes that household market presence, consumer preference for naturally processed/local sugar, strategic stocks and accessible retail distribution should be treated as measurable variables in future empirical research. The article concludes with a market-segmentation strategy built around household retail, institutional supply, industrial B2B sales and strategic reserve functions.
DOI: http://doi.org/10.5281/zenodo.23007645
Evaluating Machine Learning Alternatives To Black-Scholes-Merton For Option Pricing: A Focus On Deep Out-of-the-Money Regimes
Authors: Anmol Bajpai
Abstract: The Black-Scholes-Merton (bsm) model has been the cornerstone of options pricing theory since Black and Scholes (1973) and Merton (1973), yet its assumption of con-stant volatility under Geometric Brownian Motion produces systematic mispricing in the distributional tails — most acutely for deep out-of-the-money (dotm) con-tracts where fat tails and jump risk concentrate. This paper delivers an empirical, quantitative investigation into whether non-parametric machine learning architec-tures can correct this structural deficiency. We construct a synthetic options dataset of 20,000 contracts on a liquid S&P 500–like index, deliberately engineered to replicate the empirically documented volatil-ity smile surface incorporating negative skew, curvature, and term-structure effects. Against this ground truth, we benchmark three models: the standard bsm formula (applied using a flat at-the-money volatility), an XGBoost gradient-boosted tree en-semble, and a two-layer Long Short-Term Memory (LSTM) recurrent neural network. Model selection and hyperparameter optimisation are performed on a time-based split to preclude data leakage. Our central empirical finding is stark: XGBoost reduces dotm Root Mean Squared Error (RmsE) from $99.56 to $17.22 — an 82.7% improvement over bsm — and reduces dotm Mean Absolute Percentage Error (mapE) from 126.27% to 46.82%. The LSTM, conversely, underperforms even the bsm baseline across all moneyness bands, exposing a critical architectural mismatch: sequential models require panel data (repeated observations of the same contract over time), not the cross-sectional option chains typically available in practice. SHAP value decompo-sition of the XGBoost model reveals that BSM price residuals, log-moneyness, and the VIX regime collectively account for the dominant share of pricing decisions in the dotm region, corroborating the practitioner intuition that tail risk is priced through vol-regime conditioning rather than structural parameter updates. We dis-cuss arbitrage constraint violations, computational trade-offs, and the regulatory implications of deploying black-box pricers in risk-management contexts.
DOI: https://zenodo.org/records/23008520
Designed to Trade? Product Design, Choice Architecture and Retail Trading Frequency on Indian Discount-Broking Platforms
Authors: Palash Jauhari
Abstract: Discount-broking applications have transformed retail access to Indian capital markets. Zero brokerage on equity delivery, paperless onboarding and one-tap order execution have removed long-standing financial and operational barriers. At the same time, regulatory studies show that more than nine in ten individual traders in equity futures and options (F&O) lose money. This paper asks whether, and through which channels, the design of a trading application shapes how often and how speculatively its users trade. We make three contributions. First, we develop a conceptual framework that links six product-design levers (visual salience of profit-and-loss and top movers, gamification, order friction, push notifications, derivatives prominence and voluntary friction tools such as a kill switch) to behavioural mediators (attention, fear of missing out, overconfidence, myopic loss aversion and loss-chasing) and to measurable investor outcomes. Second, we set out a mixed-methods empirical design (a platform design audit, a survey, a randomised interface experiment and interviews) together with its econometric specification. Third, we build and run an agent-based model of 5,000 heterogeneous investors, simulated over 30 Monte Carlo replications, and use it to test the internal logic of the framework and the identification strategy. Under our stated assumptions, an engagement-first design generates about 4.1 times as many orders per month as a utility-first design (6.6 vs. 1.6), a higher F&O share of orders (32.0% vs. 12.1%), shorter holding periods (26.8 vs. 43.6 days) and far higher derivatives adoption among novices (50.4% vs. 13.6%). A voluntary kill switch reduces F&O orders by only 5.6%, whereas a mandatory cooling-off step reduces them by 40.7%. Because these results come from a calibrated simulation rather than observed trading data, we present them as quantified hypotheses and as a validated research design, not as empirical estimates. We close with implications for ethical product management in fintech and for the Securities and Exchange Board of India (SEBI).
DOI: https://zenodo.org/records/23013075
A Study on Customer Satisfaction Towards Quick Commerce Delivery Services to Zepto
Authors: Neelakantam Akshitha
Abstract: Quick commerce has become an important part of online shopping by providing customers with fast delivery and convenient access to groceries and daily-use products. This study titled “A Study on Customer Satisfaction Towards Quick Commerce Delivery Services with Special Reference to Zepto” was conducted to understand customer satisfaction towards Zepto’s quick-commerce delivery services and to examine the relationship between customer perception, expectation–experience gap, delivery speed, product availability, service quality, and customer satisfaction. The study is based on primary data collected directly from Zepto users through a structured questionnaire prepared using Google Forms. The study adopted a descriptive research design and used convenience sampling for collecting responses. A total of 150 responses were considered for the study. The collected data were organized and analyzed using Microsoft Excel and Microsoft Power BI, with percentage analysis, average scores, graphical representation, and correlation analysis used for interpretation. The findings of the study show that the average customer satisfaction score was 4.51 out of 5, indicating a high level of satisfaction among the respondents. The average customer perception score was 4.48 out of 5, showing a positive perception towards Zepto. The study also found that 58.7% of respondents belonged to the 21–30 years age group, while 51.3% were students. The correlation analysis showed positive relationships between the selected study variables and customer satisfaction. The findings indicate that delivery speed, product availability, service quality, and the gap between customer expectations and actual experience are important aspects of the customer experience. The study suggests that Zepto should focus on maintaining timely delivery, meeting customer expectations, ensuring product availability, improving customer service, enhancing application usability, and maintaining order accuracy and product quality. Overall, the study provides insights into customer satisfaction and the areas that can be considered for improving Zepto’s quick-commerce delivery services.
A Comparative Study of Zomato & Swiggy of Customer Switching Behaviour in Online Food Delivery Platform
Authors: Avula Harshitha Yadav
Abstract: The online food delivery industry has grown rapidly in recent years due to increased internet usage, smartphone adoption, and changing consumer lifestyles. Among the leading platforms in India, Zomato and Swiggy have become the preferred choices for customers by offering convenience, a wide variety of restaurants, attractive promotional offers, and fast delivery services. However, the intense competition between these platforms has increased customer switching behaviour, making it important to understand the factors that influence customers to switch from one platform to another. This study aims to conduct a comparative analysis of Zomato and Swiggy by examining the factors that affect customer switching behaviour. The research focuses on three key variables: service quality, perceived value, and customer satisfaction. It seeks to study the impact of service quality, examine the effect of perceived value, and analyze the influence of customer satisfaction on customers' decisions to continue using or switch between the two online food delivery platforms. The study is based on primary data collected through a structured questionnaire from customers who have experience using both Zomato and Swiggy. The collected data will be analyzed using appropriate statistical tools to identify the relationship between the selected variables and customer switching behaviour. The findings of this study are expected to help online food delivery companies understand customer expectations and improve their services by enhancing service quality, providing better value, and increasing customer satisfaction. The study will also assist companies in developing effective customer retention strategies to reduce switching behaviour and strengthen customer loyalty. Furthermore, the research contributes to a better understanding of consumer behaviour in the highly competitive online food delivery market.
Impact of Crude Oil Price Fluctuations on the Indian Rupee–Us Dollar Exchange Rate
Authors: N. Rishika
Abstract: Crude oil is an important commodity that significantly influences the economic and financial conditions of oil-importing countries such as India. Since India depends substantially on imported crude oil and international crude oil transactions are mainly denominated in U.S. dollars, fluctuations in crude oil prices can affect the demand for foreign currency and create pressure on the Indian Rupee–U.S. Dollar exchange rate. This study examines the impact of crude oil price fluctuations on the Indian Rupee–US Dollar exchange rate during the period from July 2024 to June 2026. The study focuses on Brent crude oil prices and the USD/INR exchange rate using 24 monthly observations of secondary data. Microsoft Excel and Power BI are used for data organization, analysis and visualization, while trend analysis and Pearson correlation are used to examine the movement and relationship between the variables. The study also considers selected major geopolitical events in West Asia and their associated movements in crude oil prices and the exchange rate. The correlation analysis resulted in a coefficient of 0.2007, indicating a weak positive relationship between Brent crude oil prices and the USD/INR exchange rate during the study period. The findings also show that crude oil prices experienced greater fluctuations during major geopolitical developments, while exchange rate movements were comparatively moderate. The study highlights the interconnected nature of global crude oil markets and India's foreign exchange market and provides useful insights into the relationship between energy prices and currency movements in the Indian economy.
A Study on Impact of Green HRM Practices on Organizational Sustainability – south IT Sector
Authors: M. Haripriya
Abstract: Green Human Resource Management (Green HRM) has emerged as an important approach for integrating environmental sustainability into human resource practices. In the Information Technology (IT) sector, increasing energy consumption, electronic waste, and resource usage have created a need for organizations to adopt environmentally responsible workplace practices. Green HRM enables organizations to incorporate environmental considerations into activities such as recruitment, training, employee involvement, rewards, and paperless processes. The present study focuses on Green HRM Practices and Organizational Sustainability in the South Indian IT sector. The study aims to analyze the Green HR initiatives followed by organizations, examine the impact of Green HRM on organizational sustainability, and understand employees’ awareness and participation in Green HR practices. The study addresses the research gap related to the limited sector-specific research on Green HRM and sustainability in South Indian IT organizations. A descriptive research design was adopted for the study. Primary data were collected from employees working in IT organizations through a structured questionnaire distributed using Google Forms. Convenience sampling was used to select respondents. Secondary information was collected from research journals, books, company reports, published articles, official websites, and conference papers to provide theoretical and contextual support. Microsoft Excel and Power BI were used for data organization, calculations, and visualization. The study provides a structured understanding of how Green HRM can be incorporated into HR practices and how employee awareness and participation can support organizational sustainability. It is intended to provide useful insights for HR managers and organizational leaders in strengthening environmentally responsible HR practices and developing a sustainable workplace culture. The study also contributes to the growing academic literature on Green HRM and organizational sustainability in the IT sector.
The Role of Storytelling in Advertising and Enhancing Brand Awareness: A Study on Canva
Authors: Gundu keerthi
Abstract: Storytelling has emerged as a powerful communication strategy in contemporary advertising, enabling brands to move beyond product-centered promotion and establish meaningful emotional connections with consumers. This study examines the role of storytelling in advertising and its contribution to enhancing brand awareness, with particular reference to Canva, a widely used visual communication and design platform. The study explores how Canva uses narratives, relatable experiences, visual content, user-generated stories, and emotionally engaging campaigns to communicate its brand identity and values. It focuses on the relationship between storytelling elements and consumers’ ability to recognize, recall, and associate themselves with the brand. The study also considers how digital and social media platforms amplify storytelling by encouraging audience interaction and content sharing. A descriptive and analytical approach is proposed to examine the effectiveness of storytelling in creating brand visibility and strengthening consumer engagement. The study suggests that consistent, authentic, and visually compelling narratives can enhance brand recognition and recall while contributing to stronger consumer-brand relationships. The findings are expected to provide useful insights for marketers seeking to integrate storytelling into advertising strategies and strengthen brand awareness in an increasingly competitive digital environment.
A Study on the Factors Influencing Workplace Adaptability Among Early-Career Employees
Authors: Krishna Priya Panakanti
Abstract: Workplace adaptability is important for employees, especially during the early stage of their careers. Early-career employees may face difficulties in communication, learning new tasks, managing workload, understanding job roles, and adjusting to a new work environment. This study focuses on the factors influencing workplace adaptability among early-career employees. It examines individual factors, job performance, workplace challenges, and organizational support and their relationship with workplace adaptability. The study uses a descriptive research design and a quantitative approach. Primary data were collected from 150 early-career employees through a structured questionnaire using a five-point Likert scale. The collected data were organized and analyzed using Microsoft Excel and Microsoft Power BI. Average analysis and correlation analysis were used to understand the responses and relationships between the study variables. The study aims to analyze factors influencing employee performance, identify workplace challenges, and evaluate the role of organizational support in workplace adaptability. The findings show that respondents have a high level of workplace adaptability. Individual Factors show the strongest positive relationship with Workplace Adaptability (r = 0.888). Organizational Support (r = 0.612) and Job Performance (r = 0.563) also show positive relationships with Workplace Adaptability. Workplace Challenges show a lower positive relationship (r = 0.348). The findings indicate that communication skills, confidence, learning ability, training, manager support, colleague support, and learning opportunities are important factors associated with workplace adaptability. Overall, the study highlights the importance of both personal abilities and organizational support in helping early-career employees adjust to their workplace.
The Influence of Workplace Conflict and Quiet Quitting Behavior among IT Employees
Authors: S. Akash
Abstract: This study examines the influence of workplace conflict on quiet quitting behavior among employees in the Information Technology (IT) sector. Workplace conflict, arising from differences in opinions, communication gaps, workload, interpersonal relationships, role ambiguity, and organizational practices, can significantly affect employees’ attitudes and work engagement. Quiet quitting refers to a pattern in which employees perform the duties formally required by their jobs while reducing discretionary effort, participation, and involvement beyond those basic expectations. The study explores how various forms of workplace conflict may contribute to reduced motivation, emotional disengagement, lower organizational commitment, and the development of quiet quitting tendencies among IT employees. It also considers the potential role of factors such as job satisfaction, work-life balance, managerial support, organizational culture, and communication in shaping this relationship. The study highlights the importance of creating a supportive and collaborative work environment, addressing conflicts constructively, and strengthening employee engagement to reduce disengagement behaviors. The findings are expected to provide useful insights for IT organizations and human resource professionals seeking to improve workplace relationships, employee well-being, productivity, and organizational effectiveness.
Generative Engine Optimisation & Brand Visibility In AI Search
Authors: Ansh Yadav
Abstract: Consumers increasingly meet brands not in a list of ranked links but inside a single synthesised answer written by a large language model (LLM). This paper develops a conceptual framework for Generative Engine Optimisation (GEO), the practice of shaping the probability that a brand is retrieved, cited, named, and recommended by generative search engines, and synthesises the empirical evidence available as of September 2026. We formalise brand presence as a four-stage retrieval–citation–recommendation funnel with a parallel parametric-memory route, define a family of measurable outcomes (citation share, share of model voice, ghost-citation rate, recommendation rank) and combine them into a Brand Visibility Index (BVI). We then synthesise eight primary and secondary studies, graded by evidential tier, spanning the original GEO benchmark of Aggarwal et al. (2024), the earned-media audit of Chen et al. (2025), the verifiability audit of Liu et al. (2023), and industry and institutional studies of click behaviour and brand mentions. Four regularities emerge. First, the click economy around AI summaries is contracting: two independent designs report roughly 40–47% fewer organic clicks when a summary is shown. Second, content-level interventions that raise evidence density (quotations, statistics, source citations) improve inclusion in generated answers by up to about 40% in controlled tests, while keyword stuffing does not. Third, engines exhibit a systematic preference for third-party, earned-media sources over brand-owned content, and branded web mentions correlate with AI Overview brand mentions at 0.664 against 0.218 for backlinks. Fourth, being cited and being named are distinct events: in one industry audit, 61.7% of domain appearances were citation-only. We derive eight testable propositions, specify a pre-registrable audit and field-experiment protocol, and discuss ethical limits, including the boundary between legitimate optimisation and adversarial manipulation. No new primary data are reported; the contribution is conceptual and integrative.
DOI: http://doi.org/10.5281/zenodo.23077972
The Solid Protocol and the Decentralized Web: Transforming Data Ownership, Interoperability, and Control
Authors: Dr. K. Chitra
Abstract: The contemporary Web is decentralized at the level of protocols but highly centralized at the level of data custody, identity, application ecosystems, and economic power. Solid (Social Linked Data), initiated by Tim Berners-Lee and developed through the Solid community, proposes a different application architecture: data is stored in independently hosted Personal Online Datastores (Pods), identified and linked through Web standards, while applications obtain permissioned access rather than becoming the permanent custodians of user data. This article provides a detailed analysis of Solid as both a technical protocol family and a data-governance model. It updates earlier descriptions of Solid by distinguishing WebID-based identification, Solid-OIDC authentication, and authorization through Web Access Control (WAC) and Access Control Policy (ACP). It examines RDF and Linked Data, data portability, interoperability, security, privacy, user experience, decentralized discovery, performance, governance, and regulatory alignment. Recent evidence is incorporated from the Flemish data-vault ecosystem, which targets approximately 6.5 million citizens; 2024-2026 studies of Solid usability and decentralized search; and developments in European data regulation, including the European Health Data Space (EHDS), which entered into force in March 2025. The analysis finds that Solid offers a technically credible mechanism for separating data from applications and enabling reusable, permissioned data, but that decentralizing storage does not by itself solve semantic interoperability, usability, trust, cybersecurity, discovery, governance, or platform-network effects. Solid is therefore best understood not as a replacement for the Web or as a blockchain system, but as an evolving standards-based layer for user-centric data spaces. Its long-term significance will depend on interoperable implementations, understandable permission models, institutional governance, viable business incentives, and evidence that decentralized data control can operate reliably at population scale.
Consumer Buying Behavior Towards Packaged Food Products
Authors: Venu Gopal Kodumagulla
Abstract: The packaged food industry has experienced significant growth in recent years due to rapid urbanization, changing lifestyles, increasing disposable incomes, and the growing demand for convenient food options. Consumers today have access to a wide variety of packaged food products, making their purchasing decisions more complex and influenced by multiple factors. Understanding consumer buying behaviour has therefore become essential for food manufacturers and marketers to develop effective business and marketing strategies. This study, titled "Consumer Buying Behaviour Towards Packaged Food Products," aims to examine the factors that influence consumers' purchasing decisions. The research focuses on key determinants such as product quality, price, brand image, packaging, nutritional value, taste, convenience, promotional activities, and product availability. It also seeks to understand consumer preferences, purchasing frequency, and satisfaction levels with packaged food products. The study adopts a descriptive research design and uses both primary and secondary data. Primary data are collected through a structured questionnaire administered to consumers, while secondary data are gathered from books, research journals, company reports, websites, and published articles. The collected data are analysed using appropriate statistical and analytical tools to identify patterns and relationships in consumer buying behaviour. The findings of this study are expected to provide valuable insights into consumer preferences and the factors that drive purchasing decisions. The results will help packaged food companies improve their product offerings, pricing strategies, packaging designs, promotional activities, and customer engagement practices. The study will also contribute to the existing body of knowledge on consumer behaviour and serve as a useful reference for researchers, students, marketers, and business professionals interested in the packaged food industry.
The Role Of Artificial Intelligence In Transforming Financial Accounting And Tax Compliance
Authors: Dr. Lakshmipathi K N, Prof A.Seshachalam
Abstract: The role of artificial intelligence (AI) in transforming financial accounting and tax compliance is one of those areas that have become very intricate in terms of regulation. Based on the systematic review and synthesis of recent empirical research and industry surveys (2021–2026), the study evaluates how AI, including machine learning, natural language processing, and generative AI, transforms essential accounting and tax processes. As follows, the implementation of AI technologies leads to efficiency gains, including 81% productivity increases and the enhancement of accuracy up to 98%. Companies using AI-powered compliance solutions attain the accuracy rate in fraud detection of more than 98%, while the processing time is reduced to less than a second. However, despite numerous benefits, there are still some challenges identified, including the lack of appropriate internal skills among 44% of respondents and low data readiness among 80% of respondents. Thus, the paper concludes that effective application of AI technologies is possible only through effective collaboration between humans and AI and appropriate governance, which requires significant investments into data infrastructure.
DOI: http://doi.org/10.5281/zenodo.23095556
Evaluating the Impact of Monetary Policy on Mortgage Lending Patterns: A Longitudinal Study of the Indian Housing Finance Sector
Authors: Dr Ranjith Kumar Billa, Dr Dulari
Abstract: Monetary policy has a pronounced impact on India’s mortgage lending patterns: tightening central bank rates curb housing loan growth while easing measures stimulate credit (outstanding mortgage loans rose from about 8.0% of GDP in 2014–15 to 11.2% by 2024–25; total housing credit jumped from ₹9.97 lakh crore to ₹37.14 lakh crore over 2000–2025). This study examines how RBI policy tools (repo rate, CRR, SLR) affect mortgage volumes, loan pricing and access across borrower segments and regions. Objectives include quantifying transmission channels, institutional differences (public/private banks vs. HFCs), and the dynamic effects of policy changes. The analysis employs a longitudinal approach (2000–2025, quarterly data) using secondary sources: RBI databases (policy rates, banking credit, liquidity ratios), NHB reports (housing loan disbursements, outstanding loans, RESIDEX prices), CMIE and macroeconomic indicators. Key variables include the policy rate, repo, CRR/SLR, housing loan volumes and interest spreads, lender type (HFC vs bank) credit flows, and NPA ratios. Empirical methods combine time-series and panel econometrics: vector autoregressions, VECMs with impulse-response and variance-decomposition analysis, panel regressions and difference-in-differences with fixed effects, supplemented by robustness checks (alternative lags, sub-samples, threshold models). Results indicate that contractionary policy significantly dampens mortgage growth and loan approvals, raising lending rates and spreads. For example, a 1% repo rate hike lowers credit growth by roughly 0.8% in the short run (with error-correction adjustment). Banks’ lending is generally more interest-sensitive than HFCs, reflecting HFCs’ diversified funding. HFCs continue to supply ~45–50% of formal housing credit, but both lenders slow lending under tight policy. Borrowers in lower-income segments and tier-II/III regions face disproportionately higher credit constraints. These effects work with lags, and interact with housing price cycles and macroprudential measures. Policy implications: Regulators should calibrate monetary and macroprudential tools jointly to support housing demand (e.g. adjust LTV or provisioning norms when rates rise) and safeguard affordable housing credit. Lenders should adapt loan pricing and origination to minimize exclusion of vulnerable borrowers. The findings underscore the need for better data and coordination between monetary and housing policy.
Digital Tax Compliance And E-Invoicing: Challenges And Opportunities For Business Sustainability
Authors: Chethan Kumar G M, Dr. Allah Bakash
Abstract: Global move towards mandatory electronic invoicing and real time digital tax filing is a paradigm shift in fiscal governance, with 40 countries currently adopting real time transaction controls. This paper explores the two aspects of the process: the burden of compliance requirements for firms including Small and Medium Enterprises (SMEs) and the business opportunities offered by adoption of e-invoicing systems. The paper draws from examples of implementation of digital tax requirements in Europe, Latin America and the Asia Pacific region to explore a methodology for sustainable adoption of electronic invoicing based on coherent tax technology architecture. The analysis shows that although the process brings considerable revenue benefits to governments, compliance costs for micro businesses are likely to be higher than the taxes they pay. From the findings, organizations adopting technology strategies are able to record major cuts in processing costs and ensure that their tax operations become strategic business facilitators. Business sustainability in the era of digital tax requirements calls for considering compliance as data management problem rather than a requirement.
DOI: http://doi.org/10.5281/zenodo.23099542
Digital Payment Adoption And Consumer Trust In Cashless Business Ecosystems
Authors: Dr. P. Srimathi
Abstract: The move towards cashless ecosystems is a paradigm shift in consumer behavior regarding financial transaction; however, the significance of consumer trust in this process and its ability to accelerate or hinder the shift is not well understood yet. This research paper studies the complex connection between digital payments adoption and consumer trust in the context of cashless ecosystems with the use of UTAUT and TAM theoretical models to develop an analytic framework. The study uses the mixed methods approach and analyzes both quantitative data obtained through survey of 479 participants of different demographics and adoption patterns. Results show that consumer perception of trust and security is the most powerful predictor of their intentions regarding cashless transactions; moreover, facilitating conditions and social influence were found to have a significant positive impact on intentions. Surprisingly, perceived ease of use was found to have no direct significant impact on adoption intentions, which indicates that modern interfaces are intuitively designed enough. The study makes contributions to theory in terms of adoption trust framework proposition and has practical implications for public policy makers, banks and service providers aiming to increase adoption rates of digital payments in developing countries.
DOI: http://doi.org/10.5281/zenodo.23099615
ESG Reporting Practices And Their Impact On Corporate Financial Sustainability
Authors: Dr. S Revathi, Dr. M. Mariammal
Abstract: This paper explores the link between ESG reporting and financial sustainability of corporations across different economies. Relying on the synthesis of empirical evidence gathered during 2021-2026, the study explores the impact of the quality of ESG reporting on cost of capital, firm valuation and financial sustainability of firms in the long run. The methodology suggested consists of meta-analytic literature review and panel analysis of firm-level data. The findings reveal a positive connection between high ESG scores and cost of debt and equity that is considerably lower than that of firms with lower ESG scores, especially those related to social and governance dimensions of ESG ratings. Based on meta-analytical evidence based on 60,247 firm-level observations, the results reveal that ESG disclosure lowers the weighted cost of capital and improves market-based performance measures. However, the relationship between disclosure and performance is conditional upon the institutional setting, assurance quality and the nature of ESG involvement.
DOI: http://doi.org/10.5281/zenodo.23099669
Financial Inclusion Through Digital Banking: Trends, Challenges And Future Directions
Authors: Vanishree G M, Hema Priyadharshini M
Abstract: Digital banking has proved to be a powerful transformational tool for achieving financial inclusion, especially in disadvantaged and distant communities. This research looks into the developments within the field of digital banking and its ability to solve the problem of financial exclusion among developing and emerging economies. The research uses an extensive review of the existing literature and empirical evidence to highlight current trends such as mobile money expansion, use of AI technologies and application of blockchain. However, there are several challenges that include lack of necessary digital infrastructure, financial illiteracy, cyber-security issues and gender inequality. This study proposes an innovative methodological approach that combines quantitative panel analysis and Digital Financial Inclusion Index to evaluate the adoption of digital banking technology in 25 emerging economies. The results show a significant and positive relationship between the rate of adoption of digital banking and financial inclusion measures, which is moderated by internet usage and education levels.
DOI: http://doi.org/10.5281/zenodo.23099875
Emerging Trends In AI, FinTech And Business Management: Innovations In Digital Payments, Blockchain, Banking And Accounting
Authors: Dr K Jecintha Sathiyavathi
Abstract: An interaction between Artificial Intelligence (AI), Financial Technology (FinTech), and management significantly changes the financial sector, digital payments, banking operations, and accounting. This paper provides an investigation into the current trends with the focus on automation through artificial intelligence, blockchains, and their effect on financial systems. Through the use of a methodology that includes a literature review and the application of a quantitative approach, we will consider some of the recent innovations such as generation artificial intelligence for fraud detection, automation of smart contracts, and agential artificial intelligence systems. The findings of the analysis demonstrate significant improvements in efficiency, accuracy of fraud detection, and financial inclusiveness. However, some challenges associated with regulatory compliance, algorithmic bias, and security still remain. A comparative analysis shows that the use of AI-FinTech enhances the efficiency of fraud detection by 35-45%, reduces the costs of transactions by 20-30%, and improves access to finance for underrepresented groups.
DOI: http://doi.org/10.5281/zenodo.23100131
A Study on Human Resource Management in Startups
Authors: Associate Professor Dr. Kanupriya Dubey, Assistant Professor Ms. Avantika Tripathi, Assistant Professor Mr. Rahul Sharma
Abstract: Human Resource Management (HRM) is the most delicate and sensitive part of an organisation, that plays a vital role in the success of a startup. Its function is not only to do administrative tasks but it also plays its part in the strategic functions to enhance the performance, be innovative and shape organizational culture. The aim of Human Resource Management (HRM) is to provide a cooperative work environment for employees coming from diverse cultural backgrounds, which helps them grow professionally. At the same time, it ensures that employees work in alignment with the company's vision and mission. Humans are the primary and active factor of a firm. Startups face many challenges in establishing their name in a competitive market. In such situations, not having a positive and enthusiastic workforce can lower their morale. They face many challenges in acquiring, retaining qualified employees, managing high employee turnover, motivating employees, getting experienced employees to work according to their way. HRM designed before works better in the companies who operate at a wide scale so they often fail to assist the new startups to align with their work and resources convenience. This is the reason why many HR strategies fail when it gets applied to new firms. In these startups founders work as HR who recruit and make them work as per their vision. As they lack the experience of the same, their HR strategies backfire at them big time. With the growth of the startups transitioning from informal working style to formal working style is essential, so the company can manage more employees efficiently and provide proper assistance to all the employees. This involves selection of the candidate, job profiling, job descriptions, analyzing the performance, compensation structures, payroll, managing legal aspects of the department. Startups don’t have time for a long term growth and adaptability of the employees to the firm norms, they focus more on short term necessities. Therefore this paper is going to focus on the challenges faced by the new startups in managing their human resource and how they tend to remove the same.
A Study on Consumer Buying Behaviour Towards Authentic Handloom Products With Special Reference to Erode City
Authors: Associate Professor Dr.K.R.Sakthidevi, Research Scholar Mrs.K.Sagunthala
Abstract: This article examines consumer buying behaviour towards authentic handloom products in Erode City. The paper follows a focused two-objective framework and studies the demographic and purchase profile of consumers along with the major factors influencing purchase decisions. A sample of 120 consumers is used for analytical presentation. Four analyses are presented: frequency analysis, awareness and purchase pattern analysis, ranking analysis and chi-square analysis. The results show that female consumers, young and middle-aged buyers, employees and middle-income consumers form important segments. Product quality and durability, authenticity, design variety and price fairness are the most important purchase factors. The chi-square analysis shows that purchase frequency does not significantly differ according to monthly income.
Perceived Benefits, Perceived Risk, And Trust As Determinants Of E-Shopping Behaviour: An Empirical Study Among Consumers In Chennai City
Authors: Dr. P. Porseziyan, Mr. M. Ramesh, Mr. S. Santhosh Kumar
Abstract: This empirical study examines the influence of perceived benefits, perceived risk, and trust on e-shopping behaviour, with particular reference to consumers in Chennai City. The study examines how these factors influence consumers’ online shopping decisions and whether demographic characteristics significantly influence their perceptions and e-shopping behavior. The study adopted a quantitative research design and collected data from 300 respondents in Chennai City. The data were analysed using appropriate statistical techniques, including the Chi-square test, Analysis of Variance (ANOVA), correlation analysis, and multiple regression analysis, to examine the relationships among the study variables. The findings indicate that perceived benefits and trust play significant roles in encouraging e-shopping behaviour, whereas perceived risk acts as a potential deterrent to consumers’ online purchasing decisions. The study provides useful insights for e-commerce businesses to strengthen consumer trust, enhance perceived benefits, reduce perceived risks, and improve customer engagement and satisfaction in the rapidly evolving digital marketplace.
DOI: http://doi.org/10.5281/zenodo.23117543
Decoding Consumer Purchase Decisions: Assessing the Influence of Sustainability, Brand Trust, and Brand Preference in Toyota Vehicles
Authors: Puli Vinay kumar
Abstract: This study examines the factors influencing consumer purchase decisions regarding Toyota vehicles, with particular emphasis on sustainability, brand trust, and brand preference. As consumers become increasingly aware of environmental concerns and corporate responsibility, sustainability has emerged as an important consideration in automobile purchasing. At the same time, brand trust influences perceptions of product quality, reliability, transparency, and long-term value, while brand preference reflects consumers’ personal attitudes and loyalty toward a particular automobile brand. The study explores how these three factors contribute to consumers’ purchase intentions and decision-making processes concerning Toyota vehicles. It considers consumers’ perceptions of Toyota’s environmentally responsible technologies, product performance, corporate reputation, safety, reliability, and overall brand image. The research adopts a consumer-oriented framework to assess the relationships between sustainability perceptions, brand trust, brand preference, and purchase decisions. The findings are expected to provide insights into the relative importance of environmental and brand-related factors in shaping automobile purchasing behaviour. The study may also assist automobile marketers and manufacturers in developing strategies that strengthen consumer trust, communicate sustainability initiatives effectively, and enhance long-term brand preference. Overall, the research contributes to a better understanding of contemporary consumer behaviour in the sustainable automobile market.
GST and Digital Tax Transformation in India: Compliance, Revenue Mobilization, and Economic Formalization
Authors: Assistant Professor Dr. Prathima V, Professor Dr. N Nagaraja
Abstract: One of the major milestones in the indirect tax system of India is the enactment of the Goods and Services Tax (GST) on July 1, 2017. It transformed the tax administration, compliance and economic governance landscape through digitalization. The present study discusses the possibilities of the technology-based governance systems to expedite digital taxation and drive economic transformation with GST. The study is descriptive and analytical research design and only secondary data from government documents from 2017 to 2025, peer-reviewed journals, reports of the GST Council, publications by the Ministry of Finance, bulletins by the RBI and Economic Surveys have been used. Analytical approaches (trend analysis, comparative analysis, percentage evaluation and interpretative assessment) were employed to examine the impact of GST on revenue mobilization, taxpayer expansion, the efficiency of compliance and economic formalization. The analysis revealed the significant impact of GST on enhancing accountability, transparency, and operational efficiency in India's taxation system by leveraging digital platforms such as online registration, electronic return filing, e-way bills, e-invoicing, automatic invoice matching, and centralized monitoring via the GST Network (GSTN). These measures decreased tax evasion, enhanced compliance, and promoted the adoption of digital accounting systems, online payments, and technology enabled financial processes by companies. The survey, however, also identifies some persistent challenges, particularly for Micro, Small and Medium-Sized Enterprises (MSMEs), which include cyber security risks, infrastructure limitations, technical portal disruptions, digital literacy and complexity in compliance.
A Study on Marketing Environment with Reference to Betting Apps in India
Authors: Y. Sanketh
Abstract: This study explores the burgeoning online betting app market in India, highlighting its rapid expansion fueled by increased smartphone usage, widespread internet access, and the integration of digital payment systems like UPI. The rise of fantasy sports and real-money gaming platforms has transformed the way Indian users engage with sports and mobile entertainment. The research delves into the intricate regulatory environment, marked by central and state-level legal complexities, evolving definitions of "games of skill" versus "games of chance," and advertising restrictions that pose significant challenges to market Players. The study emphasizes the growing need for localization strategies, including support for regional languages, cultural relevance, and sport-specific targeting—especially cricket, which remains the dominant sport influencing user engagement. Using strategic marketing frameworks such as PESTLE and 5Cs analysis, the research examines how betting and fantasy platforms deploy aggressive promotions, influencer marketing, and intuitive app design to attract and retain users in a highly competitive environment. Through secondary data analysis, the project identifies key trends in user behavior, regulatory shifts, and market dynamics. It concludes that while the Indian betting app market holds substantial growth potential, long-term success depends on how well platforms navigate legal uncertainties, build consumer trust, and adopt responsible marketing practices tailored to the Indian audience. The findings offer valuable insights for marketers, app developers, and policy-makers interested in the evolving landscape of digital gaming and betting in India.
The Empathy Gap in HR: How AI Speeds up Recruitment, But Creates Psychological and Operational Friction Among Staff
Authors: Aditi Kar
Abstract: I am currently studying contemporary trends in enterprise HR. I have noticed that companies are increasingly relying on automated software and data-driven systems. In addition to processing thousands of job applications and monitoring daily employee productivity, AI-based tools help companies speed up recruitment processes and reduce operational costs. However, I also found that these tools create significant psychological and operational friction among employees. Behavioral decision models show that employees do not judge their workplaces solely based on quantitative performance metrics. Employee motivation and commitment to their organization depend heavily on whether they feel that they are treated fairly and with genuine empathy. This article provides an empirical assessment of automated system decisions compared to qualitative human management. By combining primary observational data with corporate case evaluations, I evaluated the "empathy gap" inherent in metric-centric management and developed a balanced "Human-in-the-Loop" model for modern enterprise operations.
Value Before Satisfaction: Serial Mediation of Tourist Experience and Perceived Value in the Smart Tourism–Satisfaction Relationship in a Heritage Tourism District of Tamil Nadu, India
Authors: Dr. K. Suganthi, Assistant Professor Mrs. P. Nisha, K. Gayathria, M. Priya Dharshinia, P. Mahalakshmia, R. Rashithaa
Abstract: Destinations are investing in QR codes, mobile applications and other smart tourism features, yet little is known about the psychological route by which such features translate into tourist satisfaction. This study tests whether tourist experience and perceived value transmit the effect of smart tourism destination attributes on satisfaction. Data were collected from 94 tourists who had visited Mayiladuthurai District, Tamil Nadu, through an online questionnaire (27–30 September 2026; convenience sampling), and six attributes – destination branding, tourism infrastructure, QR-based smart tourism, mobile application quality, accessibility and service quality – were averaged into a composite. Reliability analysis, correlation, multiple regression and a bootstrap-based serial mediation model (5,000 resamples) were applied. The six attributes explained 54.7% of the variance in tourist experience, and only mobile application quality (β = 0.40) and service quality (β = 0.38) were significant individual predictors. The total effect on satisfaction (0.909) comprised a significant direct effect (0.528) and a significant total indirect effect (0.381, 95% CI [0.139, 0.623]). Indirect effects ran through perceived value alone (0.242) and through experience and value in sequence (0.242), whereas the path through experience alone was not significant (−0.103); the pattern held after removing 12 straight-lining respondents. A good experience therefore raises satisfaction chiefly by first creating perceived value, evidence from a district-level heritage destination that is rarely studied in smart tourism research. Destination managers should pair digital services with visible value cues and fix basic services (cleanliness, safety, transport) first, because value, not experience alone, converts into satisfaction.
Digital Marketing in the Age of AI-Driven Personalization and Privacy-First Regulation: A Conceptual Review and Framework
Authors: Abhishek Kumar, Mariyam Ahmed, Jitendra Singh
Abstract: Digital marketing has evolved from a supplementary channel of promotion into the dominant mode through which brands identify, reach, and build relationships with consumers. Since early reviews of the field characterized digital marketing primarily as the use of electronic channels – search, email, and display advertising – to connect with customers, the discipline has been reshaped by two largely unanticipated forces: the mainstreaming of artificial intelligence in campaign personalization and targeting, and a parallel, intensifying shift toward privacy-first data practices driven by regulation, platform policy, and consumer expectation. This paper synthesizes the conceptual foundations of digital marketing with current evidence on these two forces to develop an integrated conceptual framework linking digital marketing channels, AI-enabled personalization, consumer engagement and trust, and business outcomes, with privacy regulation and consumer data trust positioned as a critical moderating condition rather than a peripheral compliance concern. Drawing on recent industry and academic evidence, the paper finds that while AI-driven personalization now touches nearly every stage of the marketing funnel and delivers measurable performance gains, its effectiveness is increasingly conditional on brand’s ability to earn and retain consumer trust in an environment of tightening data-privacy constraints. The paper discusses illustrative applications of the framework, outlines managerial implications for structuring digital marketing strategy in this environment, and identifies directions for future empirical research.
A Comparative Analysis Of Machine Learning Techniques For Power, Performance, And Area Optimization In Low-Power VLSI Design
Authors: Maneesh Pawar
Abstract: The continuous scaling of semiconductor technology has significantly increased the complexity of Very Large-Scale Integration (VLSI) design. Modern integrated circuits are required to deliver high computational performance while operating within strict power and area constraints. Traditional optimization approaches based on exhaustive design-space exploration, manually tuned heuristics, and iterative Electronic Design Automation (EDA) tool execution can become computationally expensive as the number of design parameters increases. Machine Learning (ML) provides an alternative data-driven approach for predicting design quality, reducing expensive evaluations, and guiding the search toward promising design configurations. This paper presents a comparative analysis of major machine learning techniques applicable to Power, Performance, and Area (PPA) optimization in low-power VLSI design. Supervised learning methods, ensemble learning, artificial neural networks, deep learning, reinforcement learning, and graph-based learning are analyzed with respect to their suitability for PPA prediction and optimization. The study considers power consumption, timing performance, silicon area, computational cost, interpretability, scalability, training-data requirements, and generalization capability as major evaluation dimensions. A unified ML-assisted VLSI optimization framework is proposed in which circuit and synthesis features are extracted from RTL and EDA-generated reports, machine-learning models estimate PPA metrics, and an optimization engine searches for configurations satisfying multi-objective constraints. The comparative analysis indicates that no single ML technique is universally optimal for all VLSI optimization tasks. Tree-based ensemble models are attractive for structured tabular design data because of their relatively low training cost and interpretability, whereas neural and graph-based models are better suited to highly nonlinear and structural circuit relationships. Reinforcement learning is particularly promising for sequential design-space exploration and physical-design optimization, although its computational cost and dependence on reward formulation remain important limitations. The paper therefore recommends a task-oriented hybrid strategy rather than the indiscriminate use of a single ML algorithm. The proposed framework provides a reproducible foundation for future experimental validation using open VLSI benchmarks and publicly available ML-for-EDA datasets.
DOI: https://doi.org/10.5281/zenodo.23235674
Predictive Workforce Analytics for Employee Attrition and Retention Management
Authors: Assistant Professor Dr.J.Srilekha
Abstract: Attrition among employees is one of the greatest concerns in the modern organization due to high expenses caused by recruiting new personnel, productivity losses, and reduction of corporate knowledge. In the research under consideration, there is a developed predictive modeling system intended to predict employee attrition and develop appropriate retention strategies. The proposed methodology uses complex machine learning techniques such as Random Forest, Gradient Boosting, and ensembles along with mechanisms of explainable artificial intelligence that provide transparency of the model and facilitate its application. By applying the IBM HR Analytics Employee Attrition dataset containing information about employees' features, the framework uses advanced techniques of preprocessing, class balancing, and feature engineering to take into account complex aspects of attrition. As a result of experiments, it is revealed that the ensemble model demonstrates better forecasting results compared to baseline models. The interpretation of results based on the SHAP technique shows that overtime, monthly income, length of service, and job satisfaction are the most important factors affecting attrition. Thus, the research provides an innovative approach that will help turn human resource management into proactive workforce planning.
Generative AI Based Personalized Content Creation for Digital Marketing Campaign
Authors: Associate Professor Dr.P.Jayalakshmi
Abstract: The use of generative AI within the sphere of digital marketing has completely revolutionized the way in which firms generate and personalize their content. In this paper, I am going to introduce a comprehensive framework for personalized content creation based on the use of large language models and multimodal generative systems. The methodology includes several stages such as audience profiling, prompt engineering, multimodal content generation, and feedback collection. The discussed framework is going to deal with such issues as semantic consistency, personalization level, and content quality evaluation with the help of embedding-based assessment methods. The results of my experimental analysis show that personalized content generation helps to achieve better engagement rates in comparison with non-personalized baselines, with multimodal strategies performing better than single-modality systems.
Youth Unemployment And Its Socio-Economic Implications In Afghanistan: A Reflection Analysis
Authors: Ahmad Nawid Noori
Abstract: This paper examines the socio-economic implications of youth unemployment in Afghanistan as well as its causes. Youth are very important stakeholders in any society. They are not only the future of Afghanistan, but also major stakeholders and a useful resource in nation building. However, available data show that youth unemployment is very prevalent in Afghanistan with far-reaching implications for the stability of the economy. Unemployment has a negative multiplier effect not only on the individuals involved but on the society as a whole. This paper identifies the main causes of youth unemployment in Afghanistan, which are: adoption of untimely economic policy measures, wrong impressions about technical and vocational studies, the neglect of the agricultural sector, poor educational planning, and a poor enabling environment, anchoring the explanation of the causes of this youth unemployment on neo-liberalism that created economic and social dislocations. The paper argues that many anti-social activities such as political thuggery, militancy, restiveness, and other social vices evident among the unemployed and jobless youth are real dangers to the stability of the country. Youth unemployment has been identified as one of the core causes of the rising level of social disorder and insecurity permeating the entire country of Afghanistan. The paper concludes that addressing the problem of youth unemployment must involve all stakeholders. Suggested from the analysis, therefore, are that effective policy measures such as re-prioritization of the agricultural sector, reformation of the educational system, and provision of an enabling environment that will drastically reduce unemployment and poverty should be adopted to eradicate the menace of youth unemployment.
DOI: https://doi.org/10.5281/zenodo.23338766
CONSUMER DISPUTE RESOLUTION IN DIGITAL COMMERCE: AN EMPIRICAL STUDY
Authors: Dr. K. Rukmani, Dr. B. Vasuki, Dr. S. Ruby Grace
Abstract: The rapid growth of digital commerce in India has been accompanied by a rising volume of consumer disputes relating to refunds, delivery failures, defective products, and billing errors. How these disputes are resolved shapes consumer confidence in online markets. This study examines the effect of six dimensions of dispute resolution — Accessibility of Grievance Channels, Timeliness of Resolution, Procedural Fairness, Outcome Fairness, Interactional Fairness, and Awareness of Legal Remedies — on Consumer Satisfaction with Dispute Resolution, and compares satisfaction across the resolution channels consumers use. A descriptive research design was adopted, and primary data were collected from 400 online consumers in the Chennai Metropolitan Area who had experienced at least one dispute with a digital commerce platform in the previous twelve months, using a structured five-point Likert-scale questionnaire and stratified random sampling. Data were analysed using descriptive statistics, Pearson correlation, multiple regression, and one-way ANOVA. All six dimensions significantly and positively predicted satisfaction, with Outcome Fairness (β = 0.247) and Procedural Fairness (β = 0.189) emerging as the strongest predictors; the model explained 65.9% of the variance in satisfaction. Satisfaction differed significantly across resolution channels, with payment-provider chargebacks rated highest and consumer commission proceedings rated lowest. The findings offer implications for platform grievance design and consumer protection policy.
DOI: https://doi.org/10.5281/zenodo.23334639
Ethics-Aware Hybrid Graph–Neuro-Symbolic Framework for Adaptive Fraud Management in Large-Scale Financial Systems
Authors: Vijay Mohan
Abstract: Fraud management systems are becoming more and more based on data-driven artificial intelligence processes to identify anomalous and malicious behavior in massive digital ecosystems. Nevertheless, the current solutions are usually characterized by low flexibility, inability to be interpreted, and such ethical limitations like bias, biased decision-making, and low transparency. This paper aims to tackle these issues by introducing a hybrid ethics-aware framework of fraud management relying on Graph Neural Networks (GNNs), Neuro-Symbolic Reasoning, and Reinforcement Learning (RL) as one framework. The suggested model assumes transactional environments to be dynamic graphs, which allows GNNs to efficiently learn the relation pattern and identify coordinated fraudulent patterns that are challenging in conventional feature-based models. In order to increase transparency and ethical adherence, domain-specific rules, regulatory requirements and principles of fairness would be directly inserted into the decision maker with a neuro-symbolic reasoning layer. Moreover, the limited reinforcement learning subsystem is continuously refining the policies of fraud detection in response to changing fraud methods, and it optimizes the risk thresholds, being explicit about avoiding ethical risks such as discriminatory results and excessive false positives. Empirical studies of benchmark fraud data sets show that the hybrid framework proposed can much better detect fraud, be resistant to concept drift, and explain decisions compared to traditional machine learning and deep models. Moreover, it is stated that ethical performance indicators are more favorable, and the framework is appropriate to be applied in actual financial and digital security systems. The findings reveal the promise of ethics-based hybrid AI systems as a dependable and trustworthy solution to fraud management in the new generation.
The Currency Of Connections: Social Capital, Caste, And Institutional Bypass In India
Authors: Tia Nerurkarr
Abstract: This paper examines the socio-economic phenomenon of “connections” in India, analysing how kinship, caste, and professional networks operate as a form of unregulated informal currency that mediates access to employment, political influence, and business opportunity. Formal institu-tions govern much of India’s legal and financial architecture, yet a parallel system of social capital frequently determines who can convert ability into opportunity. Drawing on a systematic synthesis of peer-reviewed research, government statistics, and international governance indices, this study traces the dual character of these networks: a critical informal safety net in a labour market where the large majority of workers remain informally employed, and simultaneously a mechanism that entrenches nepotism and undermines meritocracy in the formal sector. Evidence from correspondence-based hiring audits, national employment surveys, and corruption indices indicates that reliance on relational networks produces measurable disparities in access, disadvantaging individuals without inherited or acquired social capital, particularly along caste lines. By conceptualising connections as a medium of exchange operating outside codified regulation, the paper argues that the institutional bypass and nepotism this creates warrant the same policy scrutiny typically reserved for unregulated financial instruments. The study concludes that strengthening institutional transparency, evidenced already by early digitisation efforts such as the Government e-Marketplace, is central to narrowing the exclusionary effects of this informal currency.
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Factors Influencing Consumer Purchase Behaviour Towards Herbal Cosmetics in Tamil Nadu: The Roles of Product Quality, Brand Trust, and Digital Marketing
Authors: Assistant Professor Dr.K.Umamaheswari, Assistant Professor Dr.M.Sathyapriya
Abstract: Herbal cosmetics have become an important area of consumer interest, creating opportunities for marketers to develop effective product positioning, branding, and promotional strategies. Understanding the factors influencing consumer purchase behaviour is important for herbal cosmetic businesses seeking to build consumer trust and long-term customer relationships. This study aims to examine the relationships between perceived product quality, brand trust, digital marketing exposure, price perception, and purchase intention towards herbal cosmetics among consumers in Tamil Nadu, India. The proposed study adopts a quantitative, cross-sectional research design using a structured questionnaire administered to consumers who have used herbal cosmetic products. Descriptive statistics, reliability analysis, correlation, and multiple regression are proposed for analysing the collected data. The study will examine the extent to which the selected marketing-related factors are associated with purchase intention and whether purchase intention is associated with actual purchasing behaviour.
Green Marketing And Consumer Purchase Intention In India: A Conceptual Review
Authors: Dr. Archana Awasthi
Abstract: Environmental concerns have encouraged businesses to promote products through claims about recyclability, energy efficiency, responsible sourcing and reduced packaging. This conceptual review examines how green marketing may shape consumer purchase intention in India and why positive environmental attitudes do not always translate into purchases. It considers perceived product quality, price, trust, availability, environmental knowledge and greenwashing. Drawing on consumer-behaviour theory and established marketing literature, the paper proposes that credible and specific claims are more likely to influence intention than vague environmental language. It recommends transparent evidence, consistent product performance, accessible pricing and stronger consumer education. The paper synthesises secondary literature and does not claim original survey results.
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Financial Literacy and Investment Decision-Making Among Young Adults in India: A Conceptual Review
Authors: Assistant Professor Dr. R.S.Gupta
Abstract: Financial literacy can help individuals understand financial products, assess risk, compare costs and make informed saving and investment choices. This conceptual review examines the relationship between financial knowledge and investment decision-making among young adults in India. It considers budgeting, inflation, compounding, diversification, risk tolerance, digital access and behavioural influences. Drawing on established financial-literacy research and public financial-education resources, the paper argues that knowledge is important but may not be sufficient: confidence, social influence, access to trustworthy advice and behavioural biases also shape decisions. The paper recommends practical financial education, transparent product disclosures and stronger evaluation of financial-literacy programmes. It uses secondary literature and does not report original survey findings.
Influencer Marketing in The Age of Artificial Intelligence: Exploring The Impact Of Ai-Generated Influencers on Brand Credibility and Purchase Intention
Authors: Ms. Devi.P, Ms. Pooja. P
Abstract: Brands are increasingly partnering with AI-generated influencers — computer-generated personas that post, endorse, and interact on social media. Whether such endorsers can build the credibility on which purchase decisions depend remains unclear. This study examines the effect of five attributes of AI-generated influencers — Perceived Realism, Perceived Authenticity, Perceived Expertise, Parasocial Interaction, and Perceived Transparency (AI disclosure) — on Brand Credibility, and tests the role of Brand Credibility in shaping Purchase Intention.A descriptive and analytical research design was adopted, and primary data were collected from 400 social media users in Tamil Nadu who had encountered branded content from AI-generated influencers, using a structured five-point Likert-scale questionnaire and stratified random sampling by age group. Data were analysed using descriptive statistics, Pearson correlation, multiple regression, and bootstrapped mediation analysis (PROCESS Model 4).All five attributes significantly predicted Brand Credibility, with Perceived Authenticity (β = 0.268) and Perceived Expertise (β = 0.206) strongest; the model explained 59.0% of its variance. Brand Credibility strongly predicted Purchase Intention (β = 0.424), and the full model explained 64.2% of the variance in intention. Brand Credibility significantly mediated all five relationships, fully for Perceived Realism and Perceived Transparency and partially for the others. The findings offer implications for brands, agencies, and regulators on the use and disclosure of AI-generated influencers.
DOI: https://doi.org/10.5281/zenodo.23415485
Sustainable Management and ESG: Integrating Environmental, Social, and Governance Practices into Corporate Strategy
Authors: Post-doctoral Research Scholar Dr. Geo Paul K, Professor P S Aithal
Abstract: The use of Environmental, Social and Governance (ESG) factors has shifted from being a niche topic in corporate responsibility to becoming a much more prominent role in strategic management, risk governance, investment analysis and organizational accountability. This paper explores the potential of applying ESG principles to the company's strategy to achieve sustainable management and long-term company resilience. The study adopts a conceptual and secondary-research method that draws on academic literature, sustainability frameworks, regulatory trends, management insights, and environmental performance, social responsibility, governance quality, stakeholder engagement, risk management and value creation. The paper suggests an integrated ESG–Corporate Strategy Framework, in which ESG aspects are integrated throughout the strategic process of diagnosis, materiality assessment, objective setting, resource allocation, operational implementation, performance measurement, disclosure and continuous improvement. The analysis suggests that the best NFT in the ESG integration process is an organization's transition from separate sustainability initiatives to embedding material ESG issues into fundamental business decisions and board oversight, investment planning, supply-chain management, innovation, human-capital practices, and performance indicators. The paper also addresses the key challenges to implementation, such as disparate ESG data, different metrics, short-term management pressure, greenwashing, lack of internal resources and challenges of reconciling various stakeholder demands. The need for credible and decision useful ESG information has further grown in importance in recent times with the developments in sustainability reporting. The paper argues that ESG should not be just a reporting tool, but a comprehensive management framework that is able to weave sustainability goals into a competitive positioning, organizational resilience, stakeholder legitimacy and long-term value creation.
Influence of Financial Literacy on Investment Decision of Working Women
Authors: Km. Neha, Dr.Manaka Biswal, Dr. Evgeniya Zharikova
Abstract: This study examines the impact of financial literacy on the investment decisions of working women in INDIA, revealing a positive correlation between higher literacy, improved investment divers, and increased confidence. While risk aversion often drives a preference for traditional, safe assets, increased financial knowledge empowers women to shift toward informed, strategic, and higher-yield instruments In today’s volatile and rapidly changing financial markets, financial literacy—the capacity to understand and apply skills like budgeting, investing, and risk management—has become a vital, global imperative. Financial literacy, now a top global priority, is defined as the ability to use knowledge and skills to make info, effective money management decisions. Financial Literacy is the amalgamation of skill, knowledge, attitude and behavior that transforms into relevant financial decisions and proper usage of financial services. Financial literacy improves the quality of life an individual can afford as it helps to equip persons with fundamental tools for budgeting, facilitates them to attain the discipline towards saving and thus, make sure that they can benefit and can plan a good life post retirement. The strength of this study is that it is the reflection of women’s voices, ideas and concerns. For women, emotion, money, and family are issues that are difficult to separate.
DOI: https://doi.org/10.5281/zenodo.23416459
Data Science Approaches for Misinformation Detection in Social Media
Authors: Nisha Salunkhe, Neha Lavand, Parth Nagarkar, Divija Kadam
Abstract: Misinformation on social media has become a major challenge due to the rapid spread of false and misleading information. This research explores data science approaches for detecting misinformation using machine learning, natural language processing, and deep learning techniques. The proposed approach includes data collection, preprocessing, feature extraction, model training, and evaluation. Techniques such as TF-IDF, Logistic Regression, Support Vector Machine, Random Forest, LSTM, and BERT can be used to classify social media content. The study also examines challenges such as class imbalance, multilingual content, changing misinformation patterns, and model explainability. The research highlights how data science can support automated misinformation detection and assist users and factcheckers in identifying potentially misleading content.
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Evaluating Gamified Recruitment For Skill Assessment And Employability
Authors: Minerva Das, Dr. Sujit Kumar Acharya
Abstract: Modern hiring practices increasingly incorporate interactive game-style mechanisms to evaluate talent and gauge candidate readiness for the workplace. Tools like scenario-based simulations, structured quizzes, and competitive scoring systems allow recruiters to measure practical capabilities directly rather than relying solely on traditional resume screenings. This empirical study investigates how job applicants perceive various gamified selection methods, focusing on their effectiveness in assessing essential workplace skills and supporting graduate employability. Data were gathered from 104 participants—including higher education students, active job seekers, and industry professionals—using a standardized survey instrument. Statistical analysis using percentage distributions, analysis of variance (ANOVA), and multiple linear regression reveals a strong candidate preference for simulations and task-oriented quizzes, which respondents associated with clearer skill demonstration and higher engagement. Conversely, technical barriers, unclear instructions, and fairness concerns emerged as primary impediments. The findings indicate that while gamified hiring offers a reliable avenue for evaluating candidate competencies, its success in closing the graduate employability gap hinges on deliberate tool design, transparent evaluation criteria, and alignment with academic training.
DOI: https://doi.org/10.5281/zenodo.23494082
ESG PERFORMANCE AND PROFITABILITY NEXUS: AN EMPIRICAL STUDY OF HDFC BANK, ICICI BANK AND AXIS BANK
Authors: Gorre Rakesh
Abstract: Sustainability plays a prominent role in the current world, the financial institutions of India also integrated Environmental, Social, and Governance (ESG) factors into their operations. Present study examines the ESG integration on the financial performance of strong ESG practicing banks in India, this study has taken sample as HDFC Bank Limited, ICICI Bank Limited, and Axis Bank Limited, which are having higher ESG score and also part of the NIFTY 100 ESG Index. This study collected secondary data from the past five years, this research assesses performance indicators such as Return on Assets (ROA), Return on Equity (ROE). First section contains the introduction of ESG, second section carries out review of literature. Third section shows the Research Gap and statement of the problem, fourth section shows the objectives of the study, fifth section contains the research methodology, sixth section contains the data analysis and its interpretation. Last section carries out conclusions of the research study. This research concludes that ESG integration on the financial performance of strong ESG practicing banks in India having positive growth. ICICI Bank emerges as the most improved performer over the five-year period, while HDFC Bank maintains strong but steady financials. Axis Bank shows signs of catching up, particularly in equity returns.
DOI: https://doi.org/10.5281/zenodo.23557672
Household Waste Segregation And Recycling Behaviour: A Study Of Urban Waste Disposal System
Authors: Sonam Dhama, Dr.Manaka Biswal, Dr. Evgeniya Zharikova
Abstract: In urban areas, rapid urbanization, population growth, changing consumption habits, and poor waste management have driven a major rise in household waste. While proper segregation and recycling are essential to protect the environment and conserve resources, success depends heavily on how responsibly households participate. This study investigates urban household waste segregation and recycling behaviors, highlighting key influencing factors and operational challenges."Household waste management has become a significant environmental concern in urban areas due to rapid urbaniZAtion, population growth, changing lifestyles, and increasing consumption of goods. The improper disposal of household waste contributes to environmental pollution, public health problems, blocked drainage systems, and the degradation of urban surroundings. Household waste segregation and recycling are essential practices for reducing the amount of waste sent to landfills, conserving natural resources, and promoting sustainable urban development. However, the effectiveness of waste management systems depends not only on municipal infrastructure but also on the awareness, attitudes, and active participation of households. The present study aims to examine household waste segregation and recycling behaviour within the urban waste disposal system. It focuses on understanding the waste management practices adopted by urban households, their level of awareness regarding waste segregation, and the factors influencing their participation in recycling activities. Furthermore, this study identifies the main obstacles households encounter when sorting biodegradable, non-biodegradable, and hazardous waste at the source. Factors like education, environmental awareness, bin availability, collection consistency, and facility access are evaluated to understand disposal habits. The study utilizes a descriptive research design, gathering primary data via structured household questionnaires alongside secondary data from relevant literature and government reports. Data analysis employs percentage analysis, frequency distributions, tables, and graphs to map key trends and patterns."The study is expected to highlight the importance of environmental education, community participation, efficient municipal waste collection, and accessible recycling facilities in improving urban waste disposal systems. It may further suggest measures such as awareness campaigns, source-level waste segregation, incentives for recycling, and stronger coordination between households and municipal authorities. The findings may help policymakers and urban local bodies develop effective strategies for improving household waste management and encouraging environmentally responsible behaviour. Overall, the study emphasiZEs that a sustainable urban waste disposal system requires the combined efforts of individuals, communities, municipal authorities, and recycling agencies. Promoting responsible waste segregation and recycling practices can contribute to cleaner urban environments, better public health, and the achievement of long-term environmental sustainability.
DOI: https://doi.org/10.5281/zenodo.23558947
Financial Services And Lower- And Middle-Income Groups: A Systematic Literature Review Of Awareness, Access And Utilisation
Authors: Dr.Sagar P.Suke, Dr.Suhas Pakhare, Dr.Pankaj Bhokare
Abstract: Health insurance is a cornerstone of financial risk protection, yet voluntary adoption among India’s organised-sector salaried workforce remains uneven despite the near-universal provision of employer-sponsored group cover. This study examines the behavioural determinants of health insurance adoption among salaried employees in Pune, one of India’s largest urban employment hubs, integrating the Health Belief Model, the Theory of Planned Behaviour and Andersen’s behavioural model into a single explanatory framework. A cross-sectional, questionnaire-based design was adopted, with respondents stratified across information technology, banking, education, healthcare, manufacturing and public-sector employment in the Pune Metropolitan Region. A calibrated dataset of 384 salaried respondents was analysed to test the hypothesised relationships. Reliability was assessed using Cronbach’s alpha, and the hypotheses were tested using chi-square tests of independence, Pearson correlation, binary logistic regression and multiple linear regression. Roughly one in four respondents (26.6%) held a personal policy over and above their employer-provided cover. Income (OR = 1.83, p < 0.001), awareness (OR = 1.77, p = 0.004) and age (OR = 1.29, p = 0.028) significantly predicted adoption, while literacy, perceived benefits and trust were significant at the margin. Purchase intention was driven principally by perceived benefits (β = 0.27), perceived barriers (β = − 0.20) and trust (β = 0.22), together explaining 15.2% of the variance. The findings suggest that employer cover creates a substitution effect rather than a gateway to comprehensive protection, and that insurer trust and literacy—not price alone—are the decisive levers. The study recommends employer-embedded awareness programmes, standardised pre-purchase disclosure, and portable top-up products to deepen voluntary adoption.
DOI: http://doi.org/
Understanding Health Insurance Adoption Behaviour Among Salaried Employees: Evidence From Pune’s Urban Workforce
Authors: Dr.Sagar P.Suke, Dr.Suhas Pakhare, Dr.Pankaj Bhokare
Abstract: Health insurance is a cornerstone of financial risk protection, yet voluntary adoption among India’s organised-sector salaried workforce remains uneven despite the near-universal provision of employer-sponsored group cover. This study examines the behavioural determinants of health insurance adoption among salaried employees in Pune, one of India’s largest urban employment hubs, integrating the Health Belief Model, the Theory of Planned Behaviour and Andersen’s behavioural model into a single explanatory framework. A cross-sectional, questionnaire-based design was adopted, with respondents stratified across information technology, banking, education, healthcare, manufacturing and public-sector employment in the Pune Metropolitan Region. A calibrated dataset of 384 salaried respondents was analysed to test the hypothesised relationships. Reliability was assessed using Cronbach’s alpha, and the hypotheses were tested using chi-square tests of independence, Pearson correlation, binary logistic regression and multiple linear regression. Roughly one in four respondents (26.6%) held a personal policy over and above their employer-provided cover. Income (OR = 1.83, p < 0.001), awareness (OR = 1.77, p = 0.004) and age (OR = 1.29, p = 0.028) significantly predicted adoption, while literacy, perceived benefits and trust were significant at the margin. Purchase intention was driven principally by perceived benefits (β = 0.27), perceived barriers (β = − 0.20) and trust (β = 0.22), together explaining 15.2% of the variance. The findings suggest that employer cover creates a substitution effect rather than a gateway to comprehensive protection, and that insurer trust and literacy—not price alone—are the decisive levers. The study recommends employer-embedded awareness programmes, standardised pre-purchase disclosure, and portable top-up products to deepen voluntary adoption.
DOI: https://doi.org/10.5281/zenodo.23587931
Evaluating The Determinants of Digital Marketing Channels on Consumer Buying Behavior in The Kathmandu Valley
Authors: Dr. Gopal Thapapurnima, Thaparupa Karki, Rupa Karki
Abstract: This empirical study evaluates the influence of five key digital marketing channels: Search Engine Marketing (SEM), Content Marketing (CM), Social Media Marketing (SMM), Affiliate Marketing (AM), and E-mail Marketing (EM) on consumer buying behavior in Kathmandu Valley, Nepal. A quantitative descriptive and explanatory research design was adopted to collect primary survey data from 300 active digital consumers across the Kathmandu Valley using a five-point Likert scale questionnaire. Descriptive, Cronbach's alpha reliability analysis (α = 0.871), Pearson correlation and Chi-square tests of independence were conducted to evaluate the impact of various digital marketing channels on consumer buying behavior. The study results revealed that Search Engine Marketing (χ 2 = 243.433, p < .001), Social Media Marketing (χ2 = 231.653, p < .001), and Affiliate Marketing (χ 2 = 381.387, p < .001) significantly contribute to consumer buying behavior in Kathmandu Valley, Nepal, while Content Marketing (p = .673) and E-mail Marketing (p = .453) have no notable direct influences on the behavior of consumers in the Chi-square analysis though they showed a positive Pearson correlation. This study offers implications for marketing managers and digital strategy experts in emerging economies.
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