The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.
Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students.
The business ecosystem within Asia is undergoing a transformation post COVID-19. Green issues, inclusion, and strategic disruptors in companies and economies have become rising topics in Asian businesses, causing such a change. This has the potential to be an evolution for Asian businesses, creating new business models for economic growth in Asia. The Handbook of Research on Big Data, Green Growth, and Technology Disruption in Asian Companies and Societies presents a rich collection of chapters exploring and discussing the emerging topics, challenges, and success factors in business, big data, innovation, and technology in Asia. This book will explore the changes made in the transition towards greener and sustainable societies and economies. Covering topics including information technologies, open innovation, and green issues, this book is essential for researchers, academicians, students, politicians, policymakers, corporate heads of firms, senior general managers, managing directors, information technology directors and managers, and libraries.
The emergence of new technologies within the industrial revolution has transformed businesses to a new socio-digital era. In this new era, businesses are concerned with collecting data on customer needs, behaviors, and preferences for driving effective customer engagement and product development, as well as for crucial decision making. However, the ever-shifting behaviors of consumers provide many challenges for businesses to pinpoint the wants and needs of their audience. The Handbook of Research on Consumer Behavior Change and Data Analytics in the Socio-Digital Era focuses on the concepts, theories, and analytical techniques to track consumer behavior change. It provides multidisciplinary research and practice focusing on social and behavioral analytics to track consumer behavior shifts and improve decision making among businesses. Covering topics such as consumer sentiment analysis, emotional intelligence, and online purchase decision making, this premier reference source is a timely resource for business executives, entrepreneurs, data analysts, marketers, advertisers, government officials, social media professionals, libraries, students and educators of higher education, researchers, and academicians.
Building on Handbook of Machine Learning - Volume 1: Foundation of Artificial Intelligence, this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.
Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors
Competitive advantage is a key factor to the success of any business in modern society. To achieve this goal, effective strategies for process improvement must be researched and implemented into an organization. The Handbook of Research on Managerial Strategies for Achieving Optimal Performance in Industrial Processes examines optimization techniques for improved business operations and procedures in the industrial sector. Highlighting management techniques, innovative approaches, and technological tools, this publication is an essential reference source for professionals, researchers, consultants, upper-level students, and academicians interested in the advancement of knowledge in industrial communities.
From traditional brick and mortar to new start-ups, businesses are harnessing the power of digital enterprise as a cost-effective model to deliver goods and services online. Digital enterprise strategy is adopted for transforming business, streamlining processes, and making the best use of online technologies to enhance interaction with customers and employees and deliver excellent customer experience in real time. Digital enterprises increasingly need digital workers to establish greater digital skills to bear on every activity and to drive management, strategy, and innovation, which are key for digital enterprise transformation. The Handbook of Research on Management and Strategies for Digital Enterprise Transformation is a crucial reference source that discusses leveraging technology for the customers’, employees’, and suppliers’ benefit, as well as integrating complex processes to management, marketing, production, manufacturing, and financial systems. Combining management, strategy, technology, and digital enterprise topics into one book provides the reader with a holistic understanding of the new developments in these emerging fields. This study will also include key topics of interest on how to address structural changes underway in the local and global business environment for digital enterprise transformation. Featuring research on topics such as e-commerce, organizational learning, and agile management, this book is ideally designed for business professionals, policymakers, researchers, students, and managers.
The Handbook of Applied Expert Systems is a landmark work dedicated solely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia. The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.