Academic stress has become a concern among secondary students and higher education students in today’s educational environment. Various study habits and patterns like study session length, break frequency, structured study techniques, multitasking behaviours and mainly social media usage during studying time affects the overall well-being as there is massive usage of social media among students. This study investigates the relationship between the study habits and student stress among secondary school and higher education students in India and USA. Study is descriptive in nature, primary data is collected using a structured questionnaire, data were collected from respondents aged 14–25 years from India and USA. Findings reveal significant cross-country differences in study duration, structured scheduling, and stress levels. Multitasking and poor break management significantly increase stress and burnout risk. The moderating role of country highlights cultural variations in stress pathways.

This qualitative study explores mutual perceptions of German and Indian business leaders on cross-border foreign direct investment (FDI). Bilateral trade in goods reached USD 29.52 billion in FY 2024-25, with calendar 2024 at USD 33.40 billion and services at USD 17.03 billion, exceeding USD 50 billion combined. Cumulative German FDI in India totaled USD 15.11 billion from April 2000 to March 2025, with FY 2024-25 inflows at USD 469 million. German executives often view India as high-growth but bureaucratic, while Indian leaders see Germany as stable yet rigid. Semi-structured interviews identify opportunities (market scale, innovation synergies), risks (regulatory, cultural mismatches), and stereotypes rooted in Hofstede’s cultural dimensions. The India-EU FTA concluded on January 27, 2026—eliminating tariffs on 96.6% of EU exports—projects 41–65% trade surge and 0.12–0.13% GDP gains. Bridging strategies like cross-cultural training enhance FDI. The study offers bidirectional insights for cross-cultural management in emerging-developed partnerships.

The career awareness and resume development abilities of incoming undergraduate students are the main subjects of the study "A Study on Career Guidance and Resume Building among First Year Undergraduate Students." It draws attention to the fact that many students' academic and professional decisions are impacted by their lack of understanding regarding job options and the importance of professional resumes. 88 first-year students participated in career counseling and resume-building sessions as part of the community-engaged project. A structured questionnaire was used to gather primary data on institutional support and career awareness, and descriptive statistics were used for analysis. The study assesses how well students comprehend career planning, how often they use career counseling services, and how educational institutions support career development initiatives. The majority of pupils have a mediocre awareness of careers, which emphasizes the necessity of planned supervision. 41– 54% think workshops are helpful, and 50–55% acknowledge institutional support. 38–50% of respondents recognize the significance of resume skills, and 47–58% believe that workshops are beneficial for enhancing preparation and expertise. The findings of the ANOVA revealed no significant differences in views of institutional support (p = 0.715) or career awareness (p= 0.901). Participation in guidance programs was positively correlated with enhanced resume skills, according to correlation analysis (0.26–0.74). The results indicate that in order to ensure that students are better equipped for internships, placements, and long-term professional success, universities should implement regular career advising programs and resume workshops.

This study examines sustainability governance in the Mumbai Metropolitan Region (MMR), where institutional fragmentation and sectorial silos constrain integrated climate planning and cross-sector coordination. Using a convergent parallel mixed-methods design, thematic analysis of twelve academic and policy documents was combined with survey data from 120 stakeholders to assess climate planning integration, governance effectiveness, and collaborative capacity. The finding shows that there is uneven sustainability implementation, limited collaboration and resource misalignment. Statistical analysis indicates significant interrelationships among governance indicators, highlighting the importance of institutional coordination. The study proposes the FISA Framework to strengthen collaborative governance and metropolitan resilience.

In the digital era, social media marketing has emerged as a powerful promotional tool for start-ups seeking rapid growth and customer engagement. Indian start-ups increasingly rely on platforms such as Instagram, Facebook, and LinkedIn to build brand awareness and influence consumer behaviour. But in this oversaturated environment it is difficult to recognize what works and what is of utmost importance when starting with a new start-up’s marketing. Through this study we try to navigate the best practices for the social media marketing of Indian start-ups. The data analysed using methods and parameters like ANOVA, correlation and Chi square. At the conclusion of the study suggestions include a standard basic model for assessment of the effectiveness of a social media campaign.

This study examines how emotional patterns and cognitive processes influence learning efficiency among Generation Z students and teachers within modern educational institutions. It proposes a Structured Equation framework integrating core emotional-cognitive learning constructs to understand their collective impact on academic outcomes. A descriptive and applied research design with a mixed-method approach was adopted using purposive sampling techniques. Data were collected from 130 management students and 20 teachers in the KDMC region through structured questionnaires and interviews. Statistical tools including correlation, paired t-test and Single ANOVA were applied for analysis. The study further introduces the conceptual ECF-WR model and proposes an AI-based application to enhance emotional regulation, engagement and overall academic performance.

As the global financial landscape is transitioning from a traditional ecosystem to digitally based transactions rapidly, AI models for scam detection have turned into an indispensable pillar for proactive defence. The opaqueness of automated decision-making has however caused the Human Trust conundrum that cannot be addressed by algorithmic models alone. To find out the levels of trust among the users, this paper involves comparison of consumer trust in human-in-the-loop systems versus that of completely independent systems. The mean trust score of AI systems of the survey was calculated using inferential statistics and a 5-point Likert scale, the measure of trust, and provided a mean of 3.04 and a standard deviation of 0.30, compared to the average score of a human-led systems at 2.97 and a standard deviation of 0.32. The t-test of paired samples gave a value of 0.5984, that is, there is no considerable difference between the levels of trust between the two interventions. Moreover, ANOVA tests confirmed that trust level do not differ based on age group. Chi-square provided a p-value of 0.0529, that is, there is a strong marginal tendency preferring age- based preference, although 53.45% of the participants chose instantaneous AI blocking as opposed to human verification (46.55%). The result of these findings is a situation where trust is balanced, where users perceive that the respective systems are equally reliable, despite the possibility that functional preferences for speed may be directed towards a gradual shift to automated solutions.

Road traffic accidents are a major global concern. Driver drowsiness and alcohol impairment are among the leading causes of fatal crashes. Traditional detection systems rely on hardware- based tool like breath alcohol sensors and steering pattern analysis. The systems increase complexity and cost. This research introduces a camera-based Driver Monitoring AI system designed to detect drowsiness, distraction, and alcohol-induced impairment using computer vision techniques. The system analyzes facial landmarks in real-time to calculate Eye Aspect Ratio(EAR), Mouth Aspect Ratio(MAR), Blink frequency, PERCLOS(Percentage Eyes Closure), head pose estimation, and gaze deviation. Instead of chemically detecting alcohol, the system recognizes behavioral symptoms linked to intoxication. Built with python, Open-CV, and Media Pipe Face Mesh, it processes live video inputs to classify the driver’s state and generate alerts when necessary. Experimental results show that behavioral analysis through vision-based monitoring can effectively identify unsafe driving conditions. This system provides a scalable, cost-effective, and smart solution for road safety that fits with modern AI-driven automotive technologies.

This paper examines the impacts of personalized recommendation systems on user trust and user behaviour on online platforms. Platforms today have artificial intelligence and suggest content and products based on what users are searching, watching or purchasing. Although this simplifies and makes platforms interesting to use, it also influences the level of trust users have on this platform. To understand this, a survey with active users of digital platforms was carried out. Statistical analysis was performed to identify a relationship between the measures of personalization, trust, and behaviour. The findings indicate that users have a higher trust in the platform when they believe that the recommendations suit them. Increased trust also results in increased engagement, including increased time on the platform or engagement in content. This research finds that personalization is most effective when it is ethical and transparent. Thoughtfully, it can foster long-term credibility and can contribute to sustainable online development.

This study examines the financial feasibility of establishing a small-scale herbal mosquito repellent startup using natural ingredients such as neem, nirgundi, camphor, and cow dung powder. A descriptive research design was adopted, and primary data were collected from 248 respondents through structured questionnaires. Statistical analysis, including chi-square testing using Jamovi (Version 2.3), was conducted to examine the relationship between awareness and purchase intention. The results indicate significant association between awareness of herbal repellents and future purchase intention (χ²(4, N = 248) = 74.3, p < .001). Financial analysis shows an initial investment of ₹3,47,000, an estimated annual profit of ₹2,28,384, a break-even point of 8,908 boxes annually, a payback period of approximately 1.52 years, and a return on investment of 65.8%. The findings suggest that the proposed herbal mosquito repellent startup is financially viable and has strong market potential, supported by increasing consumer preference for safe and natural products

This study examines the marketing potential of plantable stationery as a sustainable alternative to conventional stationery products. With rising environmental concerns and increasing demand for eco- friendly solutions, plantable stationery offers an innovative product that combines functionality with environmental regeneration. A descriptive research design was adopted, and primary data were collected from 252 respondents using a structured questionnaire. Reliability was confirmed through Cronbach’s alpha, and hypotheses were tested using Pearson correlation and Welch’s ANOVA. The findings reveal a significant positive relationship between consumer awareness and purchase intention, as well as between environmental concern and consumer preference. Marketing strategies were also found to significantly influence buying behaviour. The study concludes that strategic green marketing and awareness initiatives can enhance market acceptance and promote sustainable consumption. However, the study is limited by its relatively small sample size and restricted geographic coverage, which may affect the generalizability of the findings.

Digital banking has rapidly evolved, enabling online money management while increasing vulnerability to fraud. Banks employ AI tools for real-time transaction monitoring to detect suspicious activities. A study assessed customer perceptions of AI fraud protection and its impact on satisfaction and trust. Survey results indicated that users found AI-based fraud detection to be quick and reliable, which alleviated concerns and fostered trust in digital banking. The findings suggest that effective fraud detection not only enhances security but also boosts customer satisfaction and retention in digital banking services. Thus, AI-driven fraud protection plays a crucial role in customer loyalty beyond mere security.

The incidence of lifestyle diseases is increasing at an alarming rate, and yoga has been found to be an effective, evidence-based, non-pharmacological solution for many of these diseases. In this study, an “AI-Driven Yoga Recommendation System” is presented, which consists of three main components: a rule-based system that maps 24 different healthcare conditions to yoga practices, a VGG16 Transfer Learning CNN for four- class pose classification with a 52-image custom dataset, and a MediaPipe BlazePose module that detects 33 real-time skeletal keypoints and offers live feedback. On a validation set of nine samples, the system showed 88.9% accuracy, a macro F1-score of 90.0%, and an AUC score of 1.00 for all four classes. The entire application can be run using a standard webcam and Flask web interface, with no additional hardware requirements. This demonstrates the effectiveness of the Transfer Learning approach with small datasets for real-world yoga coaching systems.

This study examines the level of Customer Relationship Management (CRM) awareness among small retailers. CRM is an important strategy that helps businesses maintain strong customer relationships and improve overall performance. Small retailers mainly depend on repeat customers and personal interaction, but many still use traditional methods for managing customer information. The objective of this study is to analyse CRM awareness, existing customer relationship practices, and the challenges faced by small retailers. The research follows a descriptive research design, and primary data was collected through questionnaires from selected shop owners. A total of 15 shops were surveyed from the Ramnagar and Dattanagar areas. The sample included different types of retail businesses such as medical stores, grocery shops, mobile shops, garment stores, and stationery shops, with three shops selected from each category. According to the results, the majority of respondents had a favorable opinion of CRM practices including keeping track of customers, interacting frequently, and offering quality service. Many merchants think that being courteous, keeping in mind the preferences of their customers, and promptly addressing concerns all contribute to the development of long-term relationships, customer loyalty, and trust. While the F-test (p > 0.05) reveals no significant variance within business experience groups, statistical results suggest a significant difference in CRM procedures and complaint management across business types (ANOVA, p < 0.05). The findings indicate that most retailers understand the importance of maintaining good customer relationships, proper communication, and basic record management. However, awareness about advanced digital CRM tools remains limited due to lack of technical knowledge, financial constraints, and limited exposure to modern technology.

Startups have an important role in promoting innovations, employment and economic development. However, they have to overcome various challenges during their early growth stage. Thus, this study aims to explore the major key challenges faced by startups during their initial phase. The major challenges may include funding issues, competition in the market, managerial inexperience, regulatory hurdles and technological hurdles. This research is based on descriptive research and uses primary and secondary data. In this paper the findings of the study show that funding issues, lack of awareness among customers and operational inefficiency are the major hurdles for the growth of startups. Thus, this paper concludes that with good financial planning, guidance, support of the government and effective business planning, startups can overcome their challenges during their early growth phase.

The rapid advancement of quantum computing poses a fundamental challenge to existing consensus protocols in distributed systems, particularly those underpinning blockchain technologies. Classical Byzantine fault-tolerant mechanisms rely on computational hardness assumptions, which are vulnerable to quantum algorithms such as Shor’s and Grover’s. This study proposes a Quantum Entanglement Swapping Consensus (QESC) framework. This novel model uses entanglement swapping and Bell state measurements to enable secure, tamper-evident agree- ments among distributed quantum nodes. Building on quantum key distribution protocols (BB84 and E91) and experimental demonstrations of long-distance entanglement over 103 km of optical fibre [11], we present a theoretical model in which consensus arises from verifiable entangled correlations rather than computational puzzles. We compared QESC with Practical Byzantine Fault Tolerance (PBFT) and evaluated it across latency, fault tolerance, and eavesdropping resistance. The results show that QESC can achieve consensus finality with unconditional security guarantees. The study concludes with a discussion of the hardware limitations and a roadmap for experimental validation.

Artificial Intelligence is transforming startup ecosystems, yet accountability in AI-driven startups remains fragmented and weakly institutionalized. Innovation frequently outpaces responsibility and oversight, creating risks related to bias, opacity, and declining trust. This paper addresses this challenge by proposing a Responsible and Sustainable Innovation Framework (RSIF) to reconceptualize accountability within AI-driven startup environments. Drawing on interdisciplinary research in algorithmic governance, ethical AI, and startup management, the study examines how accountability gaps emerge across key stages of the AI lifecycle, including design, deployment, monitoring, and scaling. Although existing ethical AI guidelines, governance frameworks, and regulatory initiatives have made important contributions toward responsible AI adoption, they often presume mature organizational structures and dedicated compliance capacities. Such assumptions limit their practical applicability within fast-paced, resource-constrained startup contexts. Findings from a lightweight prototype implementation indicate improved accountability traceability, earlier risk identification, and clearer responsibility distribution, while also revealing persistent challenges related to governance capacity and operational constraints. By integrating transparency, traceability, stakeholder participation, risk auditing, and adaptive governance into a lifecycle-based model, the proposed framework offers a practical pathway for embedding accountability into startup operations. While limitations remain, this research establishes a structured foundation for aligning AI-driven innovation with ethical responsibility, societal trust, and long-term sustainability.

Educational institutions frequently replace opera- tional assets due to technological upgrades and administrative restructuring, leading to accumulation of reusable yet discarded materials. Conventional waste handling practices emphasize disposal instead of structured reuse, resulting in financial in- efficiency and environmental strain. This study proposes the EcoBid Smart System, a technology-driven digital platform inte- grating intelligent asset classification, transparent redistribution mechanisms, and sustainability evaluation metrics. A survey of 300 institutional stakeholders was analyzed using the Chi- square test of independence. Results reveal statistically significant associations between sustainability awareness, perceived eco- nomic benefit, digital transparency, and platform acceptance. The proposed framework aligns with circular economy principles and smart campus sustainability initiatives. Findings indicate strong stakeholder readiness and scalability potential, demonstrating that structured digital reuse systems can enhance institutional resource optimization while supporting environmental and eco- nomic sustainability goals.

This study examines the personalisation–privacy paradox in the daily digital habits of college students, focusing on the relationship between privacy concern, perceived benefits of personalisation, digital literacy, and actual privacy protection behaviour. Using a mixed-method approach, primary data from 75 respondents were analysed through correlation, regression, t-test, and Friedman tests, supported by qualitative case review. The findings reveal no significant relationship between privacy concern and protection behaviour, but confirm a significant gap between expressed concern and actual actions. Digital literacy plays a key role in how well students understand informed consent. The study shows that, even as urban college students become more aware of privacy issues, they often stick to convenient habits online.

The rapid advancement of digital technologies has transformed entrepreneurial ecosystems, providing university students with access to digital platforms, artificial intelligence, and online business tools. However, limited research integrates humanitarian values and sustainability awareness within student-led digital entrepreneurship frameworks. To address this gap, this study proposes and empirically validates the HADES Model (Humanity-Driven Agile Digital Entrepreneurship for Sustainability), a student-centric framework explaining Sustainable Startup Intention. A quantitative cross-sectional design was employed, collecting primary data from 300 university students using a structured questionnaire measured on a five-point Likert scale. Reliability was confirmed through Cronbach’s Alpha, and hypotheses were tested using multiple regression and mediation analysis in Jamovi. Bootstrapping with 5000 samples was applied to validate the mediation effect. The findings reveal that Digital Competence and Humanitarian Orientation significantly influence Sustainable Startup Intention, while Sustainability Consciousness does not show a direct significant effect. Digital Entrepreneurial Agility partially mediates the relationship between Digital Competence and Sustainable Startup Intention. The model explains 58% of the variance, indicating strong explanatory power. The study validates the HADES Model as a comprehensive framework aligning digital capability, ethical responsibility, and adaptive agility to foster sustainable digital entrepreneurship among university students.

Currently, smartphones have become a vital component of our daily lives, and the situation of running out of power, especially during an emergency, can be stressful and frustrating. To solve this problem, this research proposes an innovative smartphone cover that can produce power using the natural motion of the smartphone during daily operations. The concept revolves around electromagnetic induction, whereby a small magnet with a spring oscillates within copper wires to produce electric power whenever the smartphone is in motion. Unlike conventional electric power systems that utilize only one motion direction, this system utilizes both vertical (up and down) and horizontal (side to side) motions. This increases the amount of electric power produced from simple operations such as walking or using the smartphone, the produced power is regulated by a boost converter to ensure it is safe for use during emergency charging. Although it is not meant to replace conventional charging systems, this smart phone cover is a feasible, portable, and environmentally friendly alternative with immense potential for future self-charging devices.

This study examines how artificial intelligence is transubstantiating fiscal requests and provides perceptivity for investors, fiscal institutions, controllers. It analyzes both the practical & structural goods of AI on request dynamics, contributing to the literature & supporting the development of nonsupervisory fabrics that encourage invention while icing investor protection & request security. The findings show that AI significantly improves decision- making speed, soothsaying delicacy, & functional effectiveness. AI plays a critical part in fraud discovery, threat identification, non-supervisory compliance, maintaining overall fiscal stability. still, the study highlights that algorithmic, high-frequency trading, while enhancing request liquidity, can increase short- term volatility during ages of request stress. It concludes that sustainable AI relinquishment requires strong governance, translucency, effective regulation to align invention with long- term fiscal stability

In years startups have become a popular career choice for students. However, many students are still hesitant to start their businesses. One of the reasons for this is the fear of failure and the perceived risk of starting a business. Student’s views on startup failure are influenced by factors, including financial risk, lack of knowledge and experience social and family pressure and concerns about future career stability. These views play a role in shaping their entrepreneurial intentions and decision-making. This study aims to examine the students’ perceptions of startup failure and risk factors and how these perceptions affect their attitudes towards entrepreneurship. By identifying whether fear of failure and perceived risk act as barriers or motivators the research seeks to understand the mindset among students. The findings are expected to provide insights for academic institutions and policymakers in developing effective entrepreneurship education and support systems.

India's consumer marketplaces have changed due to the rapid growth of forward-thinking digital businesses. The efficiency, accessibility, and relief of consumer life have all been improved by fintech applications, educational services, health care technology solutions, e-commerce platforms, and platform-based digital intermediaries. However, this technological advancement has also led to complex consumer protection challenges, including deceptive advertising, unfair trade practices, algorithmic discrimination, data manipulation, and privacy infringement. an ineffective grievance redressal procedure and a lack of openness. With the passage of the Consumer Protection Act, 2019, which also addresses new issues with the digital marketplace, India's consumer protection laws were modified. This study employs a mixed technique approach and a descriptive research design. Secondary data was simultaneously presented in journals and legal provisions.

The escalating complexity of modern computing workloads exposes the fundamental limitations of traditional, centrally governed data center architectures. This paper intro- duces the Agentic Data Center (ADC): a decentralized manage- ment framework in which autonomous software agents, coordi- nated through a permissioned Web3 ledger and immutable smart contracts, collectively govern infrastructure operations without human intervention. By incorporating Decentralized Physical Infrastructure Network (DePIN) principles, the ADC aligns economic incentives among distributed operators and transforms the data center into a self-healing, adaptive environment. Sim- ulation results confirm statistically significant improvements in fault tolerance, scheduling responsiveness, and SLA compliance relative to centralized baselines.

The challenge of urban solid waste management is an enduring problem in many cities in the developing world because of the inefficiencies in the monitoring and collection processes and the administrative accountability of the municipalities. The present research aims at proposing a conceptual framework called SwachhSurakshit, which is an AI-based governance framework for the enhancement of the waste monitoring processes in the municipalities. The framework would use multiple data sources such as CCTV surveillance, satellite imaging, and geo-tagging from the citizen community through deep learning-based object detection models. The research assesses the conceptual feasibility of integrating AI in the governance of waste in urban cities. The results show the positive social, environmental, and operational implications of integrating AI in the governance of waste in urban cities, and the strong potential of the SwachhSurakshit framework in addressing the civic technology needs of tier-2 and tier-3 cities.

Entrepreneurial education has become an essential tool for encouraging innovation, creativity, and self-employment among students. This study looks at how entrepreneurial education affects students’ views on startups. It focuses on how structured learning influences their attitudes, awareness, and intentions toward starting a business. The study investigates whether participating in courses, workshops, and hands-on activities improves their understanding of startup culture, willingness to take risks, and career choices. The research uses a descriptive design and relies on primary data collected through a structured questionnaire given to undergraduate and postgraduate students from various fields. It is also supported by secondary data from journals, reports, and academic articles. The researchers use statistical methods, including percentage analysis and mean score ranking, to interpret the data. The findings reveal that entrepreneurial education positively influences perceptions by building confidence, improving problem-solving skills, and raising awareness of business opportunities. As a result, students who experience this education are more likely to consider startups a viable career path. This emphasises the importance of including entrepreneurship in academic programs to develop an entrepreneurial mindset and support startup culture.

This paper presents a case study of bovine–human relationality in the desert ecologies of western India, focusing on Kachchh, located at the edge of the Thar desert. Based on The Kachchh Cattle Study 2024, a field investigation conducted across nine talukas and forty villages, the research examines the ecological, economic, and cultural dimensions of cattle rearing in arid regions. The study documents how cattle continue to play a central role in household livelihoods, ecological adaptation, and cultural practices despite persistent challenges such as fodder scarcity, inflation, and modernization. The paper is framed within Third World Environmentalism, emphasizing the interconnection between poverty, ecological degradation, and resource distribution, and engaging with the concept of the environmentalism of the poor. Drawing on perspectives from Ecocriticism, Eco-Marxism, Eco-Feminism, Deep Ecology, and critiques of Anthropocentrism, the study situates pastoral practices and panjrapole within broader debates on multispecies ethics, sustainability, and social justice. The research further identifies a gap in existing digital cattle-management technologies, which remain largely text-based, linguistically exclusive, and inaccessible to illiterate pastoral and tribal communities. The paper outlines the need for accessible, multilingual, voice-based digital tools as a potential intervention to support cattle care, ecological sustainability, and rural livelihoods, while maintaining the ethical and cultural dimensions of human–animal relationships in arid landscapes.

Digital journalism in India is rapidly transforming due to technological innovation, artificial intelligence (AI), platform dependency, and changing audience behaviour. This study examines emerging trends among national digital news start-ups using qualitative and quantitative content analysis. It analyses their content strategies, revenue models, distribution patterns, AI integration, audience engagement, and editorial positioning. Findings show increasing use of AI tools for content production, summaries, translations, and data analysis to improve efficiency and reduce costs. However, this has led to content homogenisation and reduced differentiation among platforms. With declining advertisement revenue and lower search traffic, many start-ups are shifting toward subscription and membership-based models. The study also highlights fragmented distribution across social media, newsletters, and messaging apps, along with growing information inequality as premium journalism moves behind paywalls. While AI offers innovation opportunities, sustainable growth depends on credibility, niche focus, and audience trust.

This study examines cryptocurrency market behaviour during crash conditions and evaluates the extent to which structured risk management techniques and behavioural biases affected financial losses. The study employs a quantitative design that is bolstered by qualitative observations. A structured questionnaire was used to gather primary data from (111) retail cryptocurrency traders. In order to obtain a deeper understanding of behaviour, (12) active cryptocurrency market traders were interviewed for qualitative analysis. The relationships between behavioural biases, social media influence, risk management techniques, and financial losses were examined using one-way ANOVA and Pearson correlation analysis. The results show that emotional biases like panic selling, overconfidence, FOMO, and frequent short-term trading greatly increase financial losses. A majority of respondent groups’ trading decisions were found to be influenced by social media sentiment. Most significantly, correlation analysis confirms that disciplined strategies significantly lower the magnitude of losses during times of high volatility by showing a strong negative relationship between structured risk management practices and financial losses.