Studies in Economics and Business Relations
https://sabapub.com/index.php/sebr
<p>Studies in Economics and Business Relations (SEBR) is a peer reviewed international journal published by Saba Publishing. The aim of the journal is to provide a venue for researchers and practitioners to share theories, views, research and results in areas of Economics, Management, Accounting, Auditing and Finance. Articles are published in English.</p> <p><strong>Editor in Chief: <a href="https://www.scopus.com/authid/detail.uri?authorId=57218587272" target="_blank" rel="noopener">Mohammed A. Al-Bukhrani</a></strong><br /><strong>ISSN (online)</strong>: <a href="https://portal.issn.org/resource/ISSN/2709-670X">2709-670X</a><br /><strong>Frequency:</strong> Biennial</p>SABA Publishingen-USStudies in Economics and Business Relations2709-670XAcceptance of artificial intelligence technologies in business management, finance, and e-commerce: factors, challenges, and strategies
https://sabapub.com/index.php/sebr/article/view/1333
<p class="abstract"><span lang="EN-US">This research investigates the comprehensive acceptance of artificial intelligence (AI) in business management, finance, and e-commerce, focusing on the factors driving its adoption, the obstacles encountered, and strategies for enhancing integration. AI technologies have transformed these sectors, delivering exceptional efficiencies, predictive analytics, and personalized customer experiences. However, their acceptance is influenced by various factors, including technological readiness, organizational culture, and perceived benefits. In business management, AI improves decision-making processes, optimizes operations, and fosters innovation. Financial institutions utilize AI for risk management, fraud detection, and personalized banking services, while the e-commerce sector gains from AI through enhanced customer service, dynamic pricing, and inventory management. Despite these benefits, challenges such as data privacy concerns, high implementation costs, and resistance to change impede widespread adoption. Additionally, ethical considerations and the need for regulatory compliance add layers of complexity. This paper identifies key strategies to address these challenges, such as promoting a culture of innovation, investing in AI education and training, and developing robust data governance frameworks. Strategic partnerships and collaborations with AI experts and tech firms are also essential for navigating the AI landscape. By comprehensively addressing these factors and challenges, businesses can unlock AI's full potential, driving sustainable growth and competitive advantage. This study contributes to understanding AI acceptance in critical sectors, providing a roadmap for successful AI implementation and emphasizing the importance of strategic planning and stakeholder engagement.</span></p>Nitin RaneSaurabh P. ChoudharyJayesh Rane
Copyright (c) 2024 Studies in Economics and Business Relations
https://creativecommons.org/licenses/by/4.0
2024-09-072024-09-0752234410.48185/sebr.v5i2.1333Artificial Intelligence-driven corporate finance: enhancing efficiency and decision-making through machine learning, natural language processing, and robotic process automation in corporate governance and sustainability
https://sabapub.com/index.php/sebr/article/view/1050
<p>This research paper delves into the transformative possibilities of Artificial Intelligence (AI) within corporate finance, specifically focusing on its role in improving efficiency and decision-making processes. Through the utilization of machine learning, natural language processing (NLP), and robotic process automation (RPA), AI introduces innovative methods for enhancing corporate governance and sustainability practices. In the contemporary business landscape, corporations encounter mounting pressure to streamline operations while simultaneously addressing concerns regarding environmental, social, and governance (ESG) issues. Conventional finance methodologies often struggle to efficiently handle large volumes of data and extract actionable insights promptly. However, AI presents a shift in paradigm by enabling automated data analysis, recognizing patterns, and conducting predictive modeling, thus enabling finance professionals to make data-informed decisions swiftly and accurately. Machine learning algorithms play a pivotal role in detecting patterns and correlations within financial data, facilitating proactive risk management and strategic planning. Additionally, NLP technologies facilitate the extraction of valuable insights from unstructured data sources like regulatory filings, news articles, and social media, thereby enabling informed decision-making in corporate governance and sustainability endeavors. Moreover, RPA simplifies repetitive tasks and workflows, thereby reducing operational expenses and freeing up human resources for more strategic pursuits. Through the automation of routine processes such as data entry, reconciliation, and reporting, RPA enhances operational efficiency and ensures adherence to regulatory standards. Through the adoption of AI technologies, corporations can unlock novel avenues for innovation, optimize resource allocation, and promote sustainable growth within today's dynamic business milieu.</p>Nitin Liladhar RaneSaurabh P. Choudhary Jayesh Rane
Copyright (c) 2024 Studies in Economics and Business Relations
https://creativecommons.org/licenses/by/4.0
2024-06-012024-06-015212210.48185/sebr.v5i2.1050