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Financial Socialisation, Decision-Making Power and Risk-Taking Behaviour of Rural Households: Moderating Mediation Analysis
Financial socialisation (FS) plays a vital role in determining the financial decision-making power and risk-taking behaviour of rural households. The present study investigates the interplay between financial socialisation, gender, and marital status in shaping decision-making power and investment risk-taking behaviour. A quantitative approach was employed, with 312 survey responses collected via a cross-sectional survey method from rural investors in Karnataka and Tamil Nadu, India. Financial socialisation was assessed using adapted and validated items from prior studies, while trading frequency was a proxy for risk-taking behaviour. The moderated mediation framework (PROCESS Macro Model 8) was employed to investigate the interplay between the variables. Results show that FS significantly increases womens risk-taking behaviour, but this effect is partly reduced due to their lower decision-making power in rural patriarchal households. For men, the direct effect of financial socialisation on risk-taking behaviour is positive but weaker, with no mediation through decision-making power. Married individuals exhibit more conservative risk-taking behaviour than unmarried individuals due to familial responsibilities. The study also found that education and income do not significantly impact decision-making power, possibly reflecting deeper socio-cultural influences in rural settings. These findings imply that policymakers should design targeted financial literacy programmes to address gender disparities and cultural barriers to financial participation. By promoting inclusive financial socialisation, households can achieve more equitable decision-making processes and risk management, which will improve the financial well-being of rural communities. This study contributes to understanding financial socialisation within patriarchal contexts and offers insights into targeted financial empowerment initiatives. The Author(s) 2026. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). -
Financial stress, financial literacy, and financial insecurity in India's informal sector during COVID-19
The lockdowns and restrictions imposed to control COVID-19 have made life miserable for people, especially those involved in informal economic activities. The pandemic induced financial hardships, caused financial anxiety and financial stress among informal sector participants. This study aimed to measure and analyze the financial stress and financial insecurity of one of the important informal sector elements (street vendors) in India. Street vendors in Bangalore were interviewed in this descriptive research through personal interaction and telephonic interviews. The collected primary data were processed using SPSS statistical package. The results have indicated that the pandemic inflicted financial stress on street vendors irrespective of their gender, marital status, age, education, monthly income, and type of product dealt. Financial stress levels varied depending on the number of dependents of street vendors and their business nature. Financial literacy differed according to street vendors' marital status. A person becomes extremely sensitive and cautious in personal finance matters on getting married. Financial stress and financial literacy correlated negatively. 89.5% of street vendors perceived that they had financial insecurity in the future due to this pandemic. The results indicated that financial stress and financial literacy did not affect financial insecurity perceptions of street vendors. The predictors of financial insecurity have been marital status and the number of dependents of the street vendors (r2: 16.6%). However, marital status alone impacted the 6% variance in financial insecurity. This study concluded that the pandemic caused financial stress and financial insecurity among street vendors, but not financial stress and financial literacy. Thangaraj Ravikumar, Mali Sriram, S Girish, R Anuradha, M Gnanendra, 2022. -
Financial Vulnerability in Households: Dissecting the Roots of Financial Instability
The phenomenon of household financial vulnerability, defined by unexpected shocksin income and expenditures, carries major implications for both individual households and the overall economy of a nation. For a considerable time, household debt has been widely acknowledged as the primary determinant of household financial vulnerability. This study aims to extend the analysis beyond the scope of household debt. Middle-income households may experience financial difficulties when faced with unexpected changes in income and expenses. These challenges can arise from several circumstances, including the inability to engage in discretionary activities such as dining out or vacations. For a very long time, it has been posited that low-income households exclusively experience financial vulnerability. Hence, it is imperative to thoroughly examine the concept of household financial vulnerability and its underlying factors to enhance households' ability to withstand adversities and better clarify the matter. In light of the prevailing economic recession triggered by the global pandemic and the ongoing confrontation between Russia and Ukraine, the significance of the matter is further underscored. This study aims to comprehensively define household financial vulnerability and examine its relationship with financial capability, digitalized payments, financial stress, and financial socialization. The current study anticipates establishing a foundational framework for future research endeavors in this specific field. Moreover, this paper also explores potential avenues for future research. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Financial Vulnerability in Households: Dissecting the Roots of Financial Instability
The phenomenon of household financial vulnerability, defined by unexpected shocksin income and expenditures, carries major implications for both individual households and the overall economy of a nation. For a considerable time, household debt has been widely acknowledged as the primary determinant of household financial vulnerability. This study aims to extend the analysis beyond the scope of household debt. Middle-income households may experience financial difficulties when faced with unexpected changes in income and expenses. These challenges can arise from several circumstances, including the inability to engage in discretionary activities such as dining out or vacations. For a very long time, it has been posited that low-income households exclusively experience financial vulnerability. Hence, it is imperative to thoroughly examine the concept of household financial vulnerability and its underlying factors to enhance households' ability to withstand adversities and better clarify the matter. In light of the prevailing economic recession triggered by the global pandemic and the ongoing confrontation between Russia and Ukraine, the significance of the matter is further underscored. This study aims to comprehensively define household financial vulnerability and examine its relationship with financial capability, digitalized payments, financial stress, and financial socialization. The current study anticipates establishing a foundational framework for future research endeavors in this specific field. Moreover, this paper also explores potential avenues for future research. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Financial well-being A Generation Z perspective using a Structural Equation Modeling approach
The current pandemic situation in the global economy has urged the need to revolutionize the financial services industry with a keen eye on consumers financial needs for sound financial decisions, which is necessary for financial well-being. The purpose of the study is to assess the financial well-being of Indian Gen Z students in relation to financial literacy, financial fragility, financial behavior, and financial technology. In addition, the study also tries to determine how Gen Z students financial well-being is influenced by other factors such as gender, age, parental education, employment status, and monthly income in India. The study uses the scientific data analysis approach, Partial Least Squares-SEM model to estimate, predict, and assess the hypotheses. A sample of 271 University students from India was surveyed using a self-administered structured questionnaire. Questions were incorporated to understand the effect of financial literacy, technology, fragility, behavior, demographic and parental characteristics on financial well-being. The results indicate that financial behavior is positively related to financial well-being, while financial fragility is negatively associated. However, financial literacy and financial technology do not significantly affect financial well-being. The results also show that financial well-being is significantly influenced by gender, parental education, employment status, and monthly income change. Understanding Indian Gen Z student financial well-being will expand the students understanding of the importance of financial literacy for well-planned financial behavior and informed decisions, hence high levels of financial well-being. Government and financial institutions can more effectively identify gaps and deficiencies in student financial well-being. 2022 LLC CPC Business Perspectives. All rights reserved. -
Financing for SDGs in India in Post Pandemic era - Challenges & Way forward
In 2015, a resolution known as Agenda 2030 was passed by United Nations General Assembly in which seventeen goals for Sustainable Development were laid down for global dignity, peace and prosperity. The post- pandemic era became full of uncertainties in pursuing those Sustainable Development Goals (SDGs) and its implementation became a challenge especially for the developing economies like India. The country is facing a tremendous gap in arranging for resources to meet the climatic changes and attaining the SDGs. India requires 170 billion dollars per year from 2015-2030 to fulfill the Sustainable Development Goals as per the estimation done by National Determined Contribution, a body setup after Paris agreement 2015 to monitor the efforts of the country towards reducing national emissions and adapting to climate change. There is a huge concern amongst the various agencies on exploring the ways to fill this financing gap especially after the economic slowdown seen in the post pandemic era. This research paper analyses the challenges imposed by the COVID 19 pandemic on financing for SDGs and also explores the options to mitigate them. The articles and research papers related to SDG financing are reviewed by the researchers to arrive at the above mentioned statements. This paper is an attempt to draw the attention of worldwide authorities towards this grim situation as sustainable finance is far from reality in India and requires immediate up scaling. The Electrochemical Society -
Financing Green Startups: A Blockchain-Powered Approach
Green startups routinely encounter difficulty in obtaining financing owing to the high funding needs to launch their business, and the imprecise market acceptance and future returns of those businesses, rendering them unacceptable to traditional latter-day funding methods. The funding modality available today fails to provide the needed transparency, flexibility and accessibility to encourage ventures based on green projects. This paper develops a funding model based in blockchain for green startups, that employs tokenization, decentralised finance (DeFi) and smart contracts with automaticity, as an efficient way of funding to provide secure, traceable funding structures that make funds available related to the performance of the venture. We present a conceptual model showing the responsibilities of startups, funders and smart contracts within a de-centralised funding ecosystem. Various case studies such as Power Ledger and WePower are investigated in order to validate the practical relevance of the model. Our research indicates how blockchain mechanisms can heighten trust, enhance liquidity, and automate funding that is linked to impact. This paper contributes to future work on scalable platforms that are both regulation compliant and also provide a fit between Blockchain infrastructure and the unique requirements of sustainable innovation. 2025 IEEE. -
Finding a New Life Through Adaptive Reuse for the Old Railway Terminus Complex, Kochi, Kerala
The research article, titled Finding a New Life through adaptive reuse for the Old Railway Terminus Complex, Kochi, Kerala, examines the historical and cultural importance of the original and still existing railway station complex in Ernakulam. This station, which symbolized the arrival of the initial train to Cochin, was constructed during the zenith of the Kochi kingdom in partnership with the British, making a substantial contribution to the regions progress. Over time, the stations original role steadily diminished, leading to its abandonment and subsequent deterioration. The aim of the study is to assess the effectiveness of adaptive reuse as a strategy for conserving this valuable urban asset. The objective of the research is to reuse these neglected structures with the goal of reintegrating them into the vibrant urban landscape of Kochi, thus ensuring a sustainable and environmentally conscious future for the city. The approach involves a thorough analysis of the historical context, current condition, and potential utilization of the precinct. The main findings emphasize that adaptive reuse is an effective method for optimizing space to meet modern requirements while maintaining the historical essence of the built environment. The study highlights the significance of preserving cultural assets by creatively repurposing decommissioned railway historical structures, demonstrating their potential to contribute to sustainable urban development. The research highlights the importance of finding a balance between preserving historical elements and incorporating modern practicality. It provides a framework that can be used by other communities dealing with similar challenges. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Finding balance in a digital world: Equanimity as a predictor of nomophobia
The present study examined the relationship between equanimity and nomophobia. The study also examined the differences in experience of nomophobia considering gender, education and employment status. The sample included 216 emerging adults (M = 64, F = 152) from across India. The Equanimity Scale 16 and the Nomophobia Questionnaire were used to measure equanimity and nomophobia, respectively. Mann-Whitney-U test and Rank-Biserial coefficient indicated that gender differences significantly affected the losing connectedness factor of nomophobia. Correlation analysis showed that equanimity had a significant negative relationship with nomophobia and its factors- not being able to access information, giving up convenience and losing connectedness. Regression analysis showed equanimity as a significant predictor of nomophobia. The studys findings hold potential implications for equanimity-based interventions for nomophobia and individual well-being, technological design improvements in the digital age and unfolds areas for future research. 2024 Taylor & Francis Group, LLC. -
Finding balance in a digital world: Equanimity as a predictor of nomophobia
The present study examined the relationship between equanimity and nomophobia. The study also examined the differences in experience of nomophobia considering gender, education and employment status. The sample included 216 emerging adults (M = 64, F = 152) from across India. The Equanimity Scale 16 and the Nomophobia Questionnaire were used to measure equanimity and nomophobia, respectively. Mann-Whitney-U test and Rank-Biserial coefficient indicated that gender differences significantly affected the losing connectedness factor of nomophobia. Correlation analysis showed that equanimity had a significant negative relationship with nomophobia and its factors- not being able to access information, giving up convenience and losing connectedness. Regression analysis showed equanimity as a significant predictor of nomophobia. The studys findings hold potential implications for equanimity-based interventions for nomophobia and individual well-being, technological design improvements in the digital age and unfolds areas for future research. 2024 Taylor & Francis Group, LLC. -
Finding Real-Time Crime Detections during Video Surveillance by Live CCTV Streaming Using the Deep Learning Models
Nowadays, securing people in public places is an emerging social issue in the research of real-Time crime detection (RCD) by video surveillance, in which initial automatic recognition of suspicious objects is considered a prime problem in RCD. Dynamic live CCTV monitoring and finding real-Time crime activities by detecting suspicious objects is required to prevent unusual activities in public places. Continuous live CCTV video surveillance of objects and classification of suspicious activities are essential for real-Time crime detection. Deep training models have greatly succeeded in image and video classifications. Thus, this paper focuses on the use of trustworthy deep learning models to intelligently classify suspicious objects to detect real-Time crimes during live video surveillance by CCTV. In the experimental study, various convolutional neural network (CNN) models are trained using real-Time crime and non-crime videos. Three performance parameters, accuracy, loss, and computational time, are estimated for three variants of CNN models for the real-Time crime classifications. Three categories of videos, i.e., crime video (CV), non-crime video (NCV), and weapon-crime video (WCV), are used in the training of three deep models, CNN, 3D CNN, and Convolutional Long short-Term memory (ConvLSTM). The ConvLSTM scored higher accuracy, lower loss values, and runtime efficiency than CNN and 3D CNN when detecting real-Time crimes. 2024 ACM. -
Fine-Tuned Deep Contextual BERT for Enhanced Aspect-based Sentiment Analysis: A Comparative Study on Laptop Reviews
Sentiment analysis entails the care full analysis, conduction of interpretation and conclusion of subjective texts even as an evaluation. In the business context, the companies' strategies towards growth makes use of both level of experience of consumers, market reach, social media, opinion and reputation of the brand. The different levels of performing the analysis includes the analysis at the document, phrase, and aspect levels. The sentiment which targets the polarity on some components of texts is often recognized by various Natural language processing (NLP) tasks for example aspect level sentiment analysis. This study presents the fine-tuned deep contextual BERT (FTDC BERT) aiming at improving the accuracy of sentiment polarization prediction. We look at different types of models including the LSTM based and the attention based and the BERT based models and where they performed on the laptop dataset. The fine-tuned and pre-trained BERT model exceeded all benchmarks and gave the most accurate work at 84.48%. This remarkable achievement testifies to the capability of the model in adapting its structure to varying degrees of sentiment contained in laptop reviews. Based on the comparative analysis, different models have different degree of success which indicates that sentiment has to be modelled separately for every set of data. This paper describes interesting areas of the future inline sentiment analysis for researchers and practitioners. 2025 IEEE. -
Fine-tuning Language Models for Predicting the Impact of Events Associated to Financial News Articles
Investors and other stakeholders like consumers and employees, increasingly consider ESG factors when making decisions about investments or engaging with companies. Taking into account the importance of ESG today, FinNLP-KDF introduced the ML-ESG-3 shared task, which seeks to determine the duration of the impact of financial news articles in four languages - English, French, Korean, and Japanese. This paper describes our team, LIPIs approach towards solving the above-mentioned task. Our final systems consist of translation, paraphrasing and fine-tuning language models like BERT, Fin-BERT and RoBERTa for classification. We ranked first in the impact duration prediction subtask for French language. 2024 ELRA Language Resource Association. -
Fine-Tuning Large Language Models for Personality Development
Large Language Models (LLMs) are state-of-the-art in Natural Language Processing (NLP) tasks but are extremely challenging to fine-tune with their size and computational needs. The current research targets the fine-tuning of the OpenLLaMA-3B model for personality development tasks with parameter-efficient fine-tuning (PEFT) via LoRA and QLoRA. To deal with hardware limitations, 4-bit quantization through BitsAndBytes was used, lowering memory without affecting accuracy. A FAISS-based Retrieval-Augmented Generation (RAG) pipeline was also used to improve contextual reliability. Semantic similarity (cosine similarity), BLEURT, ROUGE, and human evaluation were used to evaluate the model. The results of this experiment show that semantic similarity greatly increasing from 0% before fine-tuning to 80% after fine-tuning, demonstrating the benefit of PEFT and quantization in domain adaptation. The work illustrates that by leveraging effective fine-tuning, quantization, and retrieval augmentation, LLMs can be deployed at scale under limited resources while providing high contextual accuracy for personality development purposes. This approach not only enhances knowledge of the job, but it also has practical scalability for educational and self-improvement purposes. The findings highlight a viable path forward for applying small, yet strong, LLMs to personalized learning and adaptive human-AI interaction. 2025 IEEE. -
Finite Element Analysis of Hybrid Skin Sandwich Composite
Sandwich structured composite is a particular classification in composite materials. This type of structure has been mainly used in recent studies because of its high specific strength, low density, and stiffness. It is increasingly more commonly employed in structural designs due to its features and performance. The sandwich composites used in this investigation are made of aluminium alloys and areca fibre. The sandwich composites face sheet comes in a variety of thicknesses. The adhesive skin layer is also varied to investigate the effect of using natural fibre. The sandwich composite is subjected to 3 point bend test. The modal analysis is investigated using the finite element method. The 3D model of sandwich composites is modelled using solid works 2020. Using Altair Hyper Works, the boundary conditions and meshing is carried out. ANSYS Mechanical APDL is used to analyse the sandwich composites. This investigation analyses the behaviour of composite sandwich beams. 2022, Books and Journals Private Ltd.. All rights reserved. -
FINNET: A Hierarchical Graph Learning Framework for Adaptive Cross-Market Financial Risk Prediction
Systemic financial risk emerges from complex multi-scale interactions among entities, sectors, and markets. We introduce FINNET, a hierarchical graph neural network framework that models these vertical dependencies through volatility-aware adaptive pooling. Our approach features: (1) a tri-scale graph structure capturing entity, sector, and market dynamics; (2) dynamic embeddings combining static features with time-varying signals; (3) transfer learning for emerging markets; and (4) transparent risk decomposition for regulatory compliance. Validated on 58,432 financial entities across three continents, FINNET achieves 0.891 AUC with only 3.8% performance degradation during crises, while providing early warnings 15 days before failures. 2026 IEEE. -
FinTech and Financial Capability, What Do We Know and What We Do Not Know: A Scoping Review
Purpose: The scoping review of this study was to investigate the existing literature on FinTech's impact on financial competence and draw conclusions from it. We applied Danielle Levac's recommendations and used the scoping review framework developed by Arksey and O'Malley. Design/Methodology/Approach: The study involved identifying and analyzing 246 papers from major databases, followed by a rigorous screening process to select 54 relevant studies. Data coding, inclusion, and exclusion screening were conducted by us independently. Findings: According to the findings, studies on FinTech and financial capacity started in 2012, and since 2020, the number of studies has sharply increased. The analysis showed that financial inclusion was the primary focus of the major FinTech studies, suggesting possible research gaps in other aspects of financial competence. We suggested recommendations and prospective directions for further research in this developing subject based on these findings. Managerial Implications: This knowledge will help managers find opportunities for collaboration, offer fresh perspectives, and make wise choices, which will improve the sector. Theoretical Implications: Important concepts and relationships were found, new trends were highlighted, and theoretical advancements were suggested as a result of the inquiry. Through the filling of knowledge gaps, the study would guide future theoretical development, facilitate diverse perspectives, and support the construction of robust frameworks in the FinTech and financial capabilities sector. Originality/Value: This study offered a comprehensive review of the body of literature, pointing out areas in need of more research and knowledge gaps. The review's unique perspective for future study and innovation in understanding the relationship between FinTech and financial capacity is derived from its thorough synthesis of many studies. 2023, Associated Management Consultants Pvt. Ltd. All rights reserved. -
FinTech for Sustainable Financial Market Innovation: The FinTech Transformation of Traditional Finance
Fintech is transforming the traditional banking industry, resulting in creative solutions that enhance financial market sustainability. This section examines how financial technologies like blockchain, AI, mobile banking, and digital payment systems are changing banking operations to make them more transparent, efficient, and accessible. It also examines how Fintech may drive long-term financial innovation by increasing financial inclusion, lowering operating costs, and encouraging green banking activities. This chapter uses case studies and practical examples to investigate the influence of Fintech on the banking system, emphasizing green lending, digital currencies, and sustainable investing platforms. Adopting new technology presents operational and regulatory problems for banks. The global financial system is becoming increasingly dependent on sustainability, as seen by how banks use Fintech to meet the growing demands of ESG standards. This section examines how digital banking platforms, AI risk assessment algorithms, and blockchain green bonds might help banks allocate resources more responsibly. By adopting these technologies, banks can reduce their environmental impact while meeting the rising demand for ethical and accountable financial services. 2026 Nova Science Publishers, Inc. -
Fintech implications on ESG practices: Evidence from the Indian banking industry
This chapter aims to provide evidence-based insights into how Fintech is influencing ESG practices of Indian banks. The discussions focus on key areas such as Green fintech, Governance and risk management approach, financing Agri business, promoting carbon net zero mission, and also the fintech intervention towards financial inclusion. The chapter also exhibits the role played by public sector banks and private sector banks in promoting ESG practices. Methodology used is secondary data based on case studies, industry reports and empirical data sources. Insights from higher officials of the banking sector are also included to examine the challenges faced by the banking sector in this regard. Based on findings, the chapter provides a suggestive model on the potentialities of fintech to support ESG agenda which can be an insight for policy makers, financial institutions and other stakeholders. 2025, IGI Global Scientific Publishing. All rights reserved. -
FinTech in India: A systematic literature review
India is the second-most populous country in the world, with a rapidly growing economy. Its population is highly tech-savvy and has a high level of adoption of digital technologies. The Indian government has taken several initiatives to promote digital transactions and financial inclusion. These initiatives have been instrumental in the growth of fintech in India. Fintech, or financial technology, is transforming the financial sector worldwide. Fintech solutions have led to the creation of new business models, streamlined operations, and enhanced customer experience. India is no exception to this trend, as it has witnessed a significant growth in fintech in recent years. The fintech ecosystem in India is highly diverse, consisting of startups, technology companies, banks, and non-banking financial companies (NBFCs). There are various challenges faced by fintech companies in India, such as lack of access to capital, regulatory hurdles, and competition from established players. This chapter proposal aims to provide a basic literature review on the development of fintech in India. 2023, IGI Global. All rights reserved.