Advancement In Business Analytics Tools For Higher Financial Performance

The relentless growth of data in financial markets has boosted the demand for more advanced analytical tools to facilitate and improve financial planning. The ability to constructively use this data is limited for managers and investors without the proper theoretical support. Within this context, there is an unmet demand for combining analytical finance methods with business analytics topics to inform better investment decisions. Advancement in Business Analytics Tools for Higher Financial Performance explores the financial applications of business analytics tools that can help financial managers and investors to better understand financial theory and improve institutional investment practices. This book explores the value extraction process using more accurate financial data via business analytical tools to help investors and portfolio managers develop more modern financial planning processes. Covering topics such as financial markets, investment analysis, and statistical tools, this book is ideal for accountants, data analysts, researchers, students, business professionals, academicians, and more.

Academic scholars find themselves confronted with a formidable challenge: staying abreast of the ever-evolving landscape of Artificial Intelligence(AI). The intricate interplay between AI and its profound impact on various facets of society, including customer engagement, remains an enigma for many. This knowledge gap not only hampers their ability to contribute meaningfully to their fields but also leaves them trailing behind the dynamic developments taking place in industries worldwide. As AI continues to reshape the business environment, it becomes imperative for academia to bridge this chasm between theory and practice. Leveraging ChatGPT and Artificial Intelligence for Effective Customer Engagement is an effective solution to the pressing problem at hand. With meticulous clarity, it unravels the complexities of ChatGPT, an innovative AI technology, and its revolutionary potential in the realm of customer engagement. It offers a lifeline to academic scholars seeking to navigate the uncharted territory of AI, providing them with an in-depth understanding of how ChatGPT can reshape customer interactions.

As the interplay of environmental, social, and governance factors becomes increasingly crucial, the global business landscape faces a monumental challenge. Climate change, social inequities, and economic uncertainties loom large, demanding immediate attention. The integration of Environmental Social Governance (ESG) principles and Artificial Intelligence (AI) technologies emerges as a powerful solution to these challenges. However, navigating the complexities of this integration, understanding its implications, and harnessing its full potential is a formidable task. Academic scholars, policymakers, and practitioners are grappling with a critical question: How can we leverage the convergence of ESG and AI to drive sustainable practices and address pressing global issues? The answer lies in comprehending the multifaceted dimensions of this integration, its ethical considerations, and its transformative potential. To gain these insights, a comprehensive resource is needed, one that offers a deep dive into ESG-AI integration, delving into empirical research, practical applications, and ethical concerns.Intersecting Environmental Social Governance and AI for Business Sustainability is a book that answers the call to action for this pressing challenge with an in-depth exploration of the evolving field of ESG and AI integration.

The advent of Industry Revolution 5.0 has brought unprecedented challenges to supply chain management, compromising the effectiveness, transparency, and security of operations. Traditional methods of transaction management and data sharing prove inadequate in this complex landscape, necessitating a comprehensive solution. Editors Mustafa Khan, Naveed R. Khan, and Arsalan Ghouri present Achieving Secure and Transparent Supply Chains With Blockchain Technology, an edited collection that offers a groundbreaking solution. This book provides a thorough overview of blockchain technology and its potential to enhance supply chain efficiency, security, and resilience. By leveraging its decentralized and secure platform, blockchain emerges as a transformative technology capable of revolutionizing supply chain management. With a focus on contemporary theoretical frameworks and the latest empirical findings, this book equips academics, practitioners, policymakers, researchers, professionals, and students with the knowledge needed to harness the power of blockchain technology in supply chain management. Covering diverse topics such as traceability, resilience, sustainability, and ethical sourcing, it explores the wide-ranging applications of blockchain in achieving secure and transparent supply chains. Achieving Secure and Transparent Supply Chains With Blockchain Technology serves as an indispensable resource for individuals involved in the field, offering a comprehensive guide to unlock the potential of secure and transparent supply chains in the digital age. With its forward-thinking approach and diverse perspectives, this book paves the way for a future where blockchain technology revolutionizes the management of supply chains.

Rapid digital transformation is forcing the manufacturing industry to drastically alter its current trajectory for future success. The remarkable convergence of digitalization and manufacturing is reshaping industries, ushering in an era known as Industry 5.0. This revolutionary transition has given birth to digital manufacturing and smart factories, heralding a new dawn in the way we produce goods. The amalgamation of artificial intelligence (AI), robotics, the internet of things (IoT), augmented reality (AR), virtual reality (VR), big data analytics, cloud computing, and additive manufacturing stands poised to unlock unprecedented avenues in the realm of production. Practitioners, researchers, dreamers, and pioneers all are beckoned to explore the uncharted territories of digital innovation in manufacturing. Human-Centered Approaches in Industry 5.0: Human-Machine Interaction, Virtual Reality Training, and Customer Sentiment Analysis spans domains from mechanical and electrical engineering to computer science, from industrial economics to business strategy, and this book addresses this diverse audience. The book embarks on a comprehensive voyage, unveiling the latest evolutions and nascent trends within digital manufacturing and smart factories. From inception to execution, from design optimization to predictive maintenance, every phase of the manufacturing lifecycle is scrutinized through the lens of cutting-edge technologies. Rather than relying exclusively on the theoretical realm, this book also ventures into the crucible of real-world application, offering practical insights drawn from varied industries, including automotive, aerospace, and pharmaceuticals.

In today's highly competitive and rapidly evolving global landscape, the quest for efficiency has become a crucial factor in determining the success of organizations across various industries. Data Envelopment Analysis (DEA) Methods for Maximizing Efficiency is a comprehensive guide that delves into the powerful mathematical tool of DEA, is designed to assess the relative efficiency of decision-making units (DMUs), and provides valuable insights for performance improvement. This book presents a systematic overview of DEA models and techniques, from fundamental concepts to advanced methods, showcasing their practical applications through real-world examples and case studies. Catering to a broad audience, this book is designed for students, researchers, consultants, decision-makers, and enthusiasts in the field of efficiency analysis and performance measurement. Consultants and practitioners will gain practical insights for applying DEA in various contexts, and decision-makers will be equipped to make informed decisions for maximizing efficiency. Additionally, individuals with a general interest in data analysis and performance measurement will find this book accessible and informative. This book covers a wide range of topics, including mathematical foundations of DEA, DEA models and variations, DEA efficiency and productivity measures, DEA applications in various industries such as healthcare, finance, supply chain management, environmental management, education management, and public sector management.

Data-driven decision making is crucial for ensuring the long-term sustainability of businesses and economic growth. While rapid technological advancements have enabled the collection and analysis of data on an unprecedented scale, businesses face challenges in adopting evidence-based decision making. Data-Driven Intelligent Business Sustainability is a comprehensive guide that examines the challenges and opportunities presented by data-driven decision making. It covers new technologies like blockchain, IoT, and AI, explores their potential for sustainable business success, and provides guidance on managing cybersecurity threats. The book also includes case studies and examples of successful implementations of data-driven decision making, making it a practical resource for those seeking to upskill or reskill in this field. Targeted at computer science and engineering professionals, researchers, and students, the book provides valuable insights into the role of data-driven decision making in business sustainability, helping businesses achieve long-term success.

In today's academic environment, the challenge of ensuring lasting commercial and economic success for organizations has become more daunting than ever before. The relentless surge in data-driven decision-making, based on innovative technologies such as blockchain, IoT, and AI, has created a digital frontier filled with complexity. Maintaining a healthy firm that can continually provide innovative products and services to the public while fueling economic growth has become a formidable puzzle. Moreover, this digital transformation has ushered in new risks, from pervasive cybersecurity threats to the ethical challenges surrounding artificial intelligence. In this evolving landscape, academic scholars face the pressing challenge of deciphering the path to long-term organizational prosperity in an era dominated by data. Data-Driven Decision Making for Long-Term Business Success serves as guidance and insights amidst this academic challenge. It is the definitive solution for scholars seeking to uncover the complexities of data-driven decision-making and its profound impact on organizational success. Each meticulously curated chapter delves into a specific facet of this transformative journey, from the implications of modern technologies and pricing optimization to the ethics underpinning data-driven strategies and the metaverse's influence on decision-making.