https://www.adrjournalshouse.com/index.php/Journal-QualityControl-Mgt Journal of Advanced Research in Quality Control & Management Advanced Research Publications en-US Journal of Advanced Research in Quality Control & Management 2582-3280 https://www.adrjournalshouse.com/index.php/Journal-QualityControl-Mgt/article/view/2196 <p><strong>Purpose</strong><br>This study investigates the ethical dilemmas in financial reporting, focusing on the interplay between compliance, transparency, and strategic disclosure. It aims to identify trends in financial misrepresentation and their impact on investor trust.</p> <p><strong>Design/Methodology/Approach</strong><br>A mixed-methods approach was employed, combining case studies, regression analysis, and chi-square tests to examine the dynamics of financial reporting ethics. The study analyzed data from 2020 to 2024 to assess changes in financial misrepresentation and selective disclosure practices.</p> <p><strong>Findings</strong></p> <ul> <li><strong>Financial Misrepresentation</strong>: The study found a significant increase in financial misrepresentation from 30% in 2020 to 45% in 2024, while selective disclosure rose from 25% to 40%.</li> <li><strong>Transparency and Investor Trust</strong>: Regression analysis revealed a strong correlation (R² = 0.99) between financial transparency and investor trust, indicating that ethical reporting enhances corporate credibility.</li> <li><strong>Strategic Disclosure vs. Transparency</strong>: Statistical models showed that strategic disclosure, rather than full transparency, has a stronger impact on investor confidence, highlighting the complexity of balancing ethical reporting with strategic communication.</li> </ul> <p><strong>Originality/Value</strong><br>This research contributes to understanding the ethical challenges in financial reporting and the impact of transparency on investor trust. It provides empirical evidence supporting the need for enhanced regulatory frameworks and technological solutions to mitigate unethical reporting practices.</p> <p><strong>Practical Implications</strong></p> <ul> <li><strong>Regulatory Enhancements</strong>: Strengthen regulatory frameworks to prevent financial misrepresentation and ensure compliance.</li> <li><strong>AI-Driven Auditing</strong>: Implement AI-driven auditing systems to improve the accuracy and reliability of financial reports.</li> <li><strong>Corporate Governance</strong>: Enhance corporate governance structures to promote ethical financial communication and maintain investor trust.</li> </ul> <p><strong>Conclusion</strong><br>The study concludes that ethical financial reporting is crucial for maintaining corporate credibility and investor confidence. It recommends a balanced approach between compliance, transparency, and strategic disclosure, supported by robust regulatory and technological measures.</p> Mbonigaba Celestin Anjay Kumar Mishra Copyright (c) 2025 Journal of Advanced Research in Quality Control & Management https://creativecommons.org/licenses/by-nc/4.0 2025-04-29 2025-04-29 10 1 1 14 https://www.adrjournalshouse.com/index.php/Journal-QualityControl-Mgt/article/view/2197 <p><strong>Purpose</strong><br>This study investigates the impact of transitioning from traditional paper-based financial reporting to AI-generated financial statements, focusing on AI’s role in enhancing accuracy, efficiency, and compliance with global standards like IFRS and GAAP.</p> <p><strong>Design/Methodology/Approach</strong><br>A mixed-methods approach was employed, incorporating regression analysis, paired T-tests, and Chi-Square tests to assess the effects of AI-driven automation on financial reporting. The study analyzed the changes in financial statement accuracy, reporting time, and compliance rates following AI implementation.</p> <p><strong>Findings</strong></p> <ul> <li><strong>Accuracy and Efficiency</strong>: AI adoption resulted in a 19% improvement in financial statement accuracy and a 58% reduction in reporting time, significantly enhancing the reliability and speed of financial reporting.</li> <li><strong>Compliance</strong>: A 21% increase in compliance rates was observed, indicating better adherence to regulatory standards.</li> <li><strong>Correlation Analysis</strong>: Strong correlations were found between AI adoption and improvements in accuracy (0.984), efficiency (-0.998), and compliance (0.972), underscoring AI’s positive impact on financial reporting quality.</li> </ul> <p><strong>Originality/Value</strong><br>This research contributes to understanding how AI can transform financial reporting by reducing errors, optimizing processes, and ensuring regulatory compliance. It provides empirical evidence supporting the integration of AI in financial reporting systems.</p> <p><strong>Practical Implications</strong></p> <ul> <li><strong>Cybersecurity</strong>: Implement robust cybersecurity frameworks to protect sensitive financial data.</li> <li><strong>Regulatory Standardization</strong>: Establish standardized AI regulations to address algorithmic bias and ensure consistent compliance.</li> <li><strong>Hybrid Collaboration</strong>: Foster hybrid AI-human collaboration to leverage AI’s strengths while maintaining human oversight and judgment.</li> </ul> <p><strong>Conclusion</strong><br>The study concludes that AI-driven financial reporting enhances transparency, reduces risks, and strengthens investor confidence. Despite challenges such as data security and regulatory complexities, the benefits of AI adoption justify its integration into financial reporting systems.</p> Mbonigaba Celestin Anjay Kumar Mishra Copyright (c) 2025 Journal of Advanced Research in Quality Control & Management https://creativecommons.org/licenses/by-nc/4.0 2025-04-30 2025-04-30 10 1 15 27 https://www.adrjournalshouse.com/index.php/Journal-QualityControl-Mgt/article/view/2156 <p>A class of control charts based on quasi midranges for process location parameter is proposed. Performance of some of its members including middecile and midhinge control charts are studied using various evaluation measures under some symmetric distributions. The proposed control charts are compared with their competitors and are illustrated through examples.</p> Sharada V. Bhat Shradha Patil Copyright (c) 2025 Journal of Advanced Research in Quality Control & Management https://creativecommons.org/licenses/by-nc/4.0 2025-05-03 2025-05-03 10 1 28 45 https://www.adrjournalshouse.com/index.php/Journal-QualityControl-Mgt/article/view/2253 <p>In today’s competitive market, ensuring high-quality products and services is crucial for business success. This review article explores various methodologies, tools, and techniques used to enhance product and service quality across industries. It provides an in-depth analysis of quality management frameworks, statistical tools, and emerging technologies that drive improvements in quality assurance and customer satisfaction. The article further examines case studies demonstrating successful implementations of these strategies and offers recommendations for organizations seeking to optimize their quality management processes.</p> Dhruv Chechi Copyright (c) 2025 Journal of Advanced Research in Quality Control & Management https://creativecommons.org/licenses/by-nc/4.0 2025-05-03 2025-05-03 10 1 46 50 https://www.adrjournalshouse.com/index.php/Journal-QualityControl-Mgt/article/view/2247 <p style="text-align: justify;">The current position of robots in terms of automation and its adoption and barrier in the hospitality industry. Formerly, the robots were used extremely limited in the industry, but due to the covid pandemic, the demand has increased—this paper fills this niche. This paper focuses on the utilization, service, adoption, and automation of robots in the hospitality industry, including tour and travel agencies, museums, art galleries, and hotels.</p> Vijender Noonwal Copyright (c) 2025 Journal of Advanced Research in Quality Control & Management https://creativecommons.org/licenses/by-nc/4.0 2025-05-03 2025-05-03 10 1 51 55