Recent Trends In Decision Science And Management

This book discusses an emerging field of decision science that focuses on business processes and systems used to extract knowledge from large volumes of data to provide significant insights for crucial decisions in critical situations. It presents studies employing computing techniques like machine learning, which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets, leadership, and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the 2nd International Conference on Decision Science and Management (ICDSM 2019), held at Hunan International Economics University, China, on 20–21 September 2019.

This volume analyses the rising inclusion of new and emerging technologies in business. It measures the effectiveness and challenges of these tools in various aspects of strategy and decision making within small and big businesses. Businesses in the competitive market must be agile and innovative to drive growth and the inclusion of technology and reliance on data science for decision-making is fraught with its own set of challenges. Through various case studies and analysis of trends, the book explores diverse dimensions of decision science from a micro as well as macro perspective. It examines the function, management and implementation of new technologies, like big data and AI in business operations and infrastructure highlighting their practical applications as well as the barriers to their adoption. This book will be useful to scholars and researchers of management studies, business management, financial management, business economics, international business, finance and marketing, development studies and economics. It will also interest policymakers and practitioners in the field.

This book presents the proceedings of the 3rd International Conference of Reliable Information and Communication Technology 2018 (IRICT 2018), which was held in Kuala Lumpur, Malaysia, on July 23–24, 2018. The main theme of the conference was “Data Science, AI and IoT Trends for the Fourth Industrial Revolution.” A total of 158 papers were submitted to the conference, of which 103 were accepted and considered for publication in this book. Several hot research topics are covered, including Advances in Data Science and Big Data Analytics, Artificial Intelligence and Soft Computing, Business Intelligence, Internet of Things (IoT) Technologies and Applications, Intelligent Communication Systems, Advances in Computer Vision, Health Informatics, Reliable Cloud Computing Environments, Recent Trends in Knowledge Management, Security Issues in the Cyber World, and Advances in Information Systems Research, Theories and Methods.

Decision science offers powerful insights and techniques that help people make better decisions to improve business and society. This new volume brings together the peer-reviewed papers that have been chosen as the "best of the best" by the field's leading organization, the Decision Sciences Institute. These papers, authored by respected decision science researchers and academics from around the world, will be presented at DSI's 45th Annual Meeting in Tampa, Florida in November 2014. The first book of papers ever assembled by DSI, this volume describes recent methods and approaches in the decision sciences, with a special focus on how accelerating technological innovation is driving change in the ways organizations and individuals make decisions. These papers offer actionable insights for decision-makers of all kinds, in business, public policy, non-profit organizations, and beyond. They also point to new research directions for academic researchers in decision science worldwide.

This book covers research trends of data science and management involving cutting edge technologies and novel research directions from diverse fields of industries, business and government sectors. It involves usage of various advanced tools and techniques for understanding different data collected at the grassroot level to generate actionable insights for making crucial decisions. This book aims to serve as a reference book for researchers in the area of decision science for management. It covers alternative solutions with innovative ideas and issues from different fields of business management.

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science. Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes: An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.

This book discusses an emerging area in computer science, IT, and management, i.e., decision sciences and management. It includes studies that employ various computing techniques like machine learning to generate insights from huge amounts of available data; and which explore decision making for cross-platforms that contain heterogeneous data associated with complex assets; leadership; and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the Third International Conference on Decision Science and Management 2021 (ICDSM 2021), held at Hang Seng University of Hong Kong in China.