Volume 13 | Issue 2 |

 Abstract

In India's Shifting Organized Retail Sector, This Study Seeks To Understand Consumers' Clothes Buying Habits. The Study Seeks To Link Respondents' Assessments Of Shop Qualities To Customers' Reasons For Buying From And Frequenting Organized Retail Outlets. It Reveals The Factors Influencing Indian Consumers' Purchase Decisions. This Paradigm Evaluates How Many Factors Influence Behavior And Retail Industry Profitability. India's Dynamic Organized Retail Landscape Was Shaped By Rising Literacy Rates, More Working Women, High Disposable Income, Easy Access To Low-Interest Credit, High Media Penetration, And The Guarantee Of Comparable Quality Products With Wide Price Differences. Only Consumers' Desires That Their Purchasing Patterns Be Analyzed Are Driving The Organized Retail Market's Growth And A Business's Success. The Study's Primary Data Came From 178 Retail Customers Of Apparel Retailers In Top Hyderabad And Secunderabad Who Were Interviewed Using A Mall Intercept Questionnaire. The Results Reveal That Customers Value The Criterion Differently, So They May Be Highlighted Without Guessing. The Data Also Show That Style > Value > Diversity > Demand > Credibility > Concern > Referral Groups Influence Clothing Purchasers' Purchases. For Theoretical And Practical Grounds, This Study Informs Academic And Retail Management.

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 Keywords

Retail Industry Profitability, Influence, Behavior, Credibility

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The Tourism Industry, As One Of The Fastest-Growing Sectors Globally, Offers Vast Entrepreneurial Opportunities. Entrepreneurs With Strong Financial Knowledge Can Significantly Determine The Enduring Performance Of Tourism Businesses. This Research Investigates The Effect Financial Literacy Has On Tourism Entrepreneurship Together With Its Influence On Tourism Business Performance Outcomes. This Research Examines Financial Knowledge Together With Decision- Making Processes Among Tourism Entrepreneurs To Demonstrate The Direct Connection Between Business Accomplishment And Financial Literacy Within This Industry. The Researchers Plan To Obtain Comprehensive Data By Conducting Quantitative Surveys Alongside Qualitative Interviews With Tourism Entrepreneurs Who Work As Hotel Operators And Tour Operators As Well As Travel Agency Managers. Through This Research We Will Evaluate Whether Entrepreneurs' Financial Literacy Affects Major Business Choices Including How They Develop Budgets And Manage Investments As Well As How They Implement Cost Controls And Predict Financial Results. The Research Will Examine How Financial Expertise Helps Tourism Enterprises To Combat Usual Business Obstacles Including Seasonal Changes And Market Instability With Economic Backward Thrusts. Researchers Expect Their Results To Show That Entrepreneurs Who Understand Finance Better Tend To Produce More Strategic Marketing Decisions Which Boost Financial Outcomes And Enable Sustained Success. This Investigation Will Reveal Financial Education Shortages In Tourism Along With Suggesting Ways To Strengthen Entrepreneurial Financial Knowledge Training. It Strengthens Our Knowledge About Financial Literacy Functioning As An Essential Factor That Contributes To Both Development And Robustness Within Tourism Business Enterprises.

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 Keywords

Financial Literacy, Tourism Entrepreneurship, Business Performance, Tourism Industry, Sustainability, Entrepreneurial Success, Financial Decision-Making, Tourism Sector Challenges, Business Resilience.

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Swami Vivekananda, A Perceptive Intellectual And Revered Spiritual Guide, Made A Lasting Impact On The Field Of Education. His Concepts Regarding Education And Individual Development Still Have A Strong Impact In The Current Dynamic And Evolving Society. Vivekananda's Educational Theory Prioritised The Cultivation Of Self-Assurance, Focus, And Ethical Principles, Surpassing Simple Intellectual Understanding To Foster The Holistic Growth Of Individuals. The Article Examines Vivekananda's Versatile Approach To Education And Its Significance In Contemporary Times. The Book Explores His Ideas On Authentic Education, Societal Progress, Empowerment Of Women, And Practical Expertise. The Conversation Also Encompasses His Perspectives On Ethical And Spiritual Development, Physical Well-Being, And Worldwide Civic Responsibility. Lastly, It Explores The Implementation Of Vivekananda's Educational Ideal In Modern Contexts.

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Knowledge; Holistic; Philosophy; Spiritual; Teaching

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In This Research, Generative AI Models Are Evaluated For Their Efficiency In Stock Market Predictions Compared To Traditional Models Such As Stock-GPT, Gans And LSTMS. Research Would Suggest Generative AI Models Can Boast Of Good Prediction Precision: Stockgpt Provides An Average Annual Return Of 119% With A Sharpe Ratio Of 6.5 During Back Testing Which Is Better Than Simple Econometric Models. These Models Can Follow The Floor Movements And Capture And Respond To Complex Interactions, Nonlinearities, Uncertainties, And Fluctuations Useful During Volatile Conditions Resulting In Better Risk-Adjusted returns And Investor decision-Making. However, Obstacles Persist And Are Fully Formed And Live In Detail. It Demonstrates That Model Biases Inherent In Dependence On Past Data Reduce Predictiveness In New Market Contexts. Furthermore, High Computational Demands Hinder The Availability Of Information For Smaller Firms And Individual Investors. Privacy And Data Ownership Issues And Truth And Regulations Also Pose More General Problems For The Broader Adoption Of Ethical Standards. Therefore, The Study Supports The Idea Of Generative AI As A Promising Prospect For The Stock Prediction Context And Views It As A Perspective For The Further Advancement Of Financial Analysis. Nevertheless, Several Challenges Need To Be Resolved To Work With Such Models More Responsibly: Computational Cost, Data Quality, And Ethics. It Is Suggested That Empirical Studies Be Proceeded With To Examine Immediate Use And To Set Up Moral Guidelines For AI Operations In Finance.

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Generative AI, Stock Market Prediction, Predictive Accuracy, Risk Management, Stockgpt, Gans, Lstms, Finance, Investor Decision-Making

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Technology Has Become An Integral And Inseparable Element Of Our Daily Life. Social Media (SM), Which Is A Technology, Provides Educational Institutions With A Greater Variety Of Opportunities To Promote Themselves And Attracts More Students As Compared To Traditional Marketing. The Term "Traditional Marketing" Refers To All Types Of Marketing That Are Not Conducted Online. This Includes Print, Broadcast, Direct Mail, Telemarketing, And Outdoor Marketing Such As Billboards. People Are Able To Interact With One Another, Search, Share, And Connect To Their Desired Contents Regardless Of Their Physical Location, Undoubtedly The Credit Of Such Ease To Be Given To Social Media. It Is Now Generally Accepted That One Of The Most Promising Ways For Educational Institutions To Achieve A Competitive Edge By Enticing Prospective Students Is To Take Use Of Social Networking Platforms. (Perrault & Hildenbr And, 2019 The Number Of Internet Users In India Has Increased Significantly In Recent Years. As Can Be Seen From The Drastic Increase Of 142.23 Million Users In 2015 To 755.47 Million Users In 2022.Although Marketing Higher Education (Hren) Has Started Emerging As A Developing Area To Be Worked Upon And Gaining Its Due Importance Globally, Yet Not Much Attention Has Been Given To The Usage Of Social Media To Encourage Admission To A Higher Education School. Most Of The Marketing Approaches Being Used In Hren Are Under Developed And Lack Strategic Recognition. As Universities Compete For Students, Marketing Using SM Technology Has Become An Important Admissions Approach In The Digital Era. Many Professions And Programs Will Benefit From Social Networking, Including A More Efficient College/University Admissions Process.

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 Keywords

Social Media, SM Technology, Information Technology, Multimedia, Social Media Platform

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Inclusive Education Has Emerged As A Pivotal Approach To Addressing The Diverse Learning Needs Of Neurodiverse Students, Including Those With Autism Spectrum Disorder (ASD), Attention-Deficit/Hyperactivity Disorder (ADHD), And Dyslexia. In This Context, Teacher's Socio-Emotional Intelligence (SEI) Is Increasingly Recognized As A Critical Competency For Fostering Supportive And Adaptive Learning Environments. SEI Encompasses Self-Awareness, Emotional Regulation, Empathy, And Interpersonal Skills, Which Enable Educators To Effectively Manage Challenges And Create Inclusive Classrooms. This Paper Systematically Reviews Existing Literature To Explore The Relationship Between Teacher's SEI And Their Ability To Implement Neurodiverse-Inclusive Teaching Practices. The Findings Underscore The Significance Of SEI In Enhancing Teacher-Student Relationships, Mitigating Behavioral Challenges, And Promoting Equitable Learning Opportunities. Despite Its Importance, Limited Research Specifically Examines The Intersection Of SEI And Neurodiverse Pedagogy, Particularly In The Indian Context, Where The National Education Policy (NEP) 2020 Emphasizes Inclusive Education. The Implications For Future Research Are Discussed, Emphasizing The Alignment With NEP 2020's Vision Of Holistic Education.

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Socio-Emotional Intelligence, Inclusive Education, Neurodiverse Learners, Teacher Training, NEP 2020.

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Digital Marketing, Regarded As A Modern Approach To Promotion, Has Provided Organizations With The Ability To Operate Continuously In Today's Competitive Global Economy. Personal Interactions Can Be Advantageous. Currently, Internet Usage Is Surging Across Various Sectors. This Era Is Dominated By Digitalization, Prompting Marketers To Embrace Digital Marketing Strategies That Leverage Digital Technology To Promote Products And Services, Gather Feedback, And Convert Potential Buyers Into Loyal Customers. The Levels Of Customer Satisfaction Among Retained Clients Are Examined To Assess The Extent Of Digitalization. The Research Aimed To Identify The Factors Influencing Digital Marketing And The Level Of Customer Satisfaction It Achieves. One-Way Anova Was Utilized To Analyze The Study, And The Findings Indicated Significant Results.

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Digital Marketing, Digitalization, Internet, Customer Satisfaction,Digital Technology

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This paper examines the attitude of B.Ed. trainees towards the skill-based teaching approach in the context of teacher-education colleges in Chikkamagaluru district, Karnataka. The study is descriptive in nature and follows the normative survey method. A total of 120 B.Ed. trainees (60 males and 60 female) were administered a self-constructed 20-item Likert-type Attitude towards Skill-Based Teaching Scale (Cronbach's alpha=.57). Since the male sub-group's scores departed from normality (Shapiro-Wilk p=.005) while the female sub-group's scores were normally distributed (p=.408), data were analyzed using the non-parametric Mann-Whitney U test with respect to gender. The results indicate that attitude towards skill-based teaching differed significantly by Gender (U=1357.50, p=.020), with female trainees reporting a significantly more favorable attitude than male trainees. Implications for skill-based curriculum implementation in teacher-education colleges are discussed.

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Skill-Based Teaching, B.Ed. Trainees, Attitude, Teacher Education.

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Because digital content is growing so quickly, sentiment analysis (SA) is now an important tool for figuring out how people feel and sorting through text data. Natural language processing (NLP) has come a long way, but low-resource languages, especially Sindhi, still haven't been studied enough because there aren't enough computational tools and annotated datasets. This study fills this gap by presenting the Sindhi News Headlines Dataset (SNHD), a new collection of data that has been labelled for both SA and category classification in eight areas: Crime, Economy, Entertainment, Health, Politics, Science & Technology, Social, and Sports. We compare different machine learning (ML), deep learning (DL), and transformer-based methods on SA and category classification tasks to see how well they work. We also use Explainable Artificial Intelligence (XAI) methods like Local Interpretable Model-Agnostic Explanations (LIME) to learn more about how models make decisions. The SNHD dataset shows that traditional ML models work better than DL and transformer-based models in experiments. Support Vector Machines with Radial Basis Function (SVM-RBF) is the best for SA (0.74 accuracy and weighted F-score), and the Ridge Classifier (RC) is the best for category classification (0.84 accuracy and weighted F-score). XLM-RoBERTa is one of the best transformer models for category classification, with an accuracy of 0.82 and a weighted F-score. These results set a standard for future research in Sindhi NLP and show how hybrid methods could help with problems that come up with low-resource languages. This work is a basic resource for NLP researchers who want to improve computational methods for Sindhi and other lesser-known languages.

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 Keywords

Sentiment Analysis, Sindhi News Headlines Dataset (SNHD), Category-Based Classification, Machine Learning, Transformer Models, Explainable Artificial Intelligence, Low-Resource Language Processing

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 Keywords

Web Text Classification, BERT (Bidirectional Encoder Representations from Transformers), BiGRU (Bidirectional Gated Recurrent Unit), Convolutional Neural Network (CNN), Attention Mechanism, Natural Language Processing,

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