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.

Organizations are facing an array of complex challenges that demand innovative solutions. From managing a diverse workforce and harnessing the power of data analytics to adapting to remote work and the pressing need for emotionally intelligent leaders, the demands on modern businesses are constantly evolving and increasing. Staying ahead of these challenges is not only essential for survival but also for thriving in an ever-changing environment. Leveraging AI and Emotional Intelligence in Contemporary Business Organizations is a compass that guides academic scholars, students, and practitioners through the turbulent seas of modern business management. It dissects the problems and offers clear, well-researched solutions. With a team of respected researchers, academicians, and professionals at the helm, this book is a beacon of knowledge, illuminating the path to success in today's business landscape.

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.

Within information sciences and organizational management, a pressing challenge emerges; How can we harness the transformative power of artificial intelligence (AI) and data analytics? As industries grapple with a deluge of data and the imperative to make informed decisions swiftly, the gap between data collection and actionable insights widens. Professionals in various sectors are in a race to unlock AI's full potential to drive operational efficiency, enhance decision-making, and gain a competitive edge. However, navigating this intricate terrain, laden with ethical considerations and interdisciplinary complexity, has proven to be a formidable undertaking. AI and Data Analytics Applications in Organizational Management, combines rigorous scholarship with practicality. It traverses the spectrum from theoretical foundations to real-world applications, making it indispensable for those seeking to implement AI-driven data analytics in their organizations. Moreover, it delves into the ethical and societal dimensions of this revolution, ensuring that the journey toward innovation is paved with responsible considerations. For researchers, scholars, and practitioners yearning to unleash the potential of AI in organizational management, this book is the key to not only understanding the landscape but also charting a course toward transformative change.

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.

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 the digital transformation era, integrating business intelligence and data analytics has become critical for the growth and sustainability of industrial organizations. However, with this technological evolution comes the pressing need for robust cybersecurity measures to safeguard valuable business intelligence from security threats. Strengthening Industrial Cybersecurity to Protect Business Intelligence delves into the theoretical foundations and empirical studies surrounding the intersection of business intelligence and cybersecurity within various industrial domains. This book addresses the importance of cybersecurity controls in mitigating financial losses and reputational damage caused by cyber-attacks. The content spans a spectrum of topics, including advances in business intelligence, the role of artificial intelligence in various business applications, and the integration of intelligent systems across industry 5.0. Ideal for academics in information systems, cybersecurity, and organizational science, as well as government officials and organizations, this book serves as a vital resource for understanding the intricate relationship between business intelligence and cybersecurity. It is equally beneficial for students seeking insights into the security implications of digital transformation processes for achieving business continuity.

Information Logistics for Organizational Empowerment and Effective Supply Chain Management delves into the profound impact of information technology on modern businesses and supply chains. As the world becomes increasingly reliant on the virtuous triangle of the Internet of Things (IoT), big data, and artificial intelligence (AI), industries face both challenges and opportunities. This book explores the multifaceted effects of information logistics on supply chain performance, considering various dimensions and key indicators. With a focus on empowering supply chains, the book uncovers procedures and tools that can enhance the intelligence, security, flexibility, agility, and efficiency of logistics systems. By understanding the interplay between traditional logistics and the information space, readers gain valuable insights into building seamless, intelligent supply chains for the contemporary world. Ideal for students, researchers, and graduates in industrial engineering, industrial management, economics, mathematics, and related fields, this book offers a comprehensive resource for understanding and implementing smart supply chain practices. Professionals working in diverse industries such as food, arbitration, agriculture, electronics, and more will find practical applications and solutions for improving logistics processes. Additionally, individuals with an interest in smart supply chains and the evolving landscape of information logistics will find this book a valuable reference.

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.

The complexity of managing and modeling various systems, from social networks to educational institutions and technical systems, has reached unprecedented levels. Traditional approaches struggle to keep pace with the dynamic nature of these challenges, leaving scholars, educators, and professionals searching for innovative solutions. This growing problem calls for a comprehensive guide to harnessing the potential of digital technologies for effective modeling and management. Educational Perspectives on Digital Technologies in Modeling and Management is a groundbreaking book that addresses the pressing need for modern solutions to keep up with the evolving challenges of modeling systems. This research book emerges from the collaborative efforts of teaching staff from leading universities, and years of dedicated scientific research and experimentation. It focuses on modeling complex systems using digital technologies, presenting fresh insights and innovative methodologies for academics, scholars, and aspiring professionals who are delving into the world of digitalization of economic processes and their management. The text caters to the specific needs of educators, IT professionals, and business analysts. Covering a wide array of topics, from information security to speaker verification and turbulent gas flow, this book serves as a valuable resource for a diverse audience seeking to excel in their respective fields.