This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.

This title was first published in 2000. This text is part of the "International Library of Management", which aims to present a comprehensive core reference series comprised of significant and influencial articles by the authorities in the management studies field. The collection of essays is both international and interdisciplinary in scope and aims to provide an entry point for investigating the myriad of study within the discipline.

The advancements in decision sciences theory and applications can be regarded as a continuously emerging field in all areas of interest including technology, industry, energy, healthcare, education, agriculture, social sciences, and more. Managers in all disciplines face an endless list of complex issues every day. One of the essential managerial skills is the ability to allocate and utilize limited resources appropriately in the efforts of achieving optimal performance efficiently. This is no less important for those who work in the transportation sector. The Handbook of Research on Decision Sciences and Applications in the Transportation Sector explores the importance of decision sciences and the ways in which they apply to the transportation sector. This book covers technologies and tools including machine learning, mathematical modeling, and simulation and their applications in such tasks as reducing fuel costs, improving passenger flow, and ensuring vehicle safety. It is an essential reference source for managers, professionals in the transport industry, supply chain specialists, safety officers, IT consultants, executives, practitioners, scientists, students, researchers, and academicians.

It is not uncommon to find books and other publications in the literature dealing individually with the subjects of 'decision sciences', 'technology' and ' globalisation' However, there are very few instances of books which integrate these three dimensions in an umbrella framework. This publication is one such attempt. This book comprises of 58 papers contributed by leading academia from universities and management institutes in India and abroad. Many of the contributions have come from USA, Canada, UK, Japan, Australia, New Zealand, UAE, Bahrain, Taiwan, Brazil and Mexico, adding to the rich diversity of the thought processes explored in the papers. Some of these papers are country-specific, while some others provide a transnational perspective. Also, while some papers provide enriched conceptual frameworks in specific disciplines, building upon existing frameworks, several other papers provide application-oriented coverage, focused at select organizations or industries, further adding unique value to this book. There are eight sections in the book, namely: Supply Chain Management Operations Management Information Systems & ICT IT & E-Business Strategies Business Modeling Global Business: Issues & Challenges Marketing and Globalisation New Paradigms in Education and Globalisation The issues touched upon by various papers within each section are diverse and yet highly relevant and contemporary. We believe this book would be useful not only to academia, research scholars and students of various disciplines of management, but also to those in the industry in India and abroad, who are seeking conceptual inputs and experience sharing in their respective positions.

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 provides an overview of Data and Decision Sciences (DDS) and recent advances and applications in space-based systems and business, medical, and agriculture processes, decision optimization modeling, and cognitive decision-making. Written by experts, this volume is organized into four sections and seven chapters. It is a valuable resource for educators, engineers, scientists, and researchers in the field of DDS.

This book provides a detailed description of machine learning algorithms in data analytics, data science life cycle, Python for machine learning, linear regression, logistic regression, and so forth. It addresses the concepts of machine learning in a practical sense providing complete code and implementation for real-world examples in electrical, oil and gas, e-commerce, and hi-tech industries. The focus is on Python programming for machine learning and patterns involved in decision science for handling data. Features: Explains the basic concepts of Python and its role in machine learning. Provides comprehensive coverage of feature engineering including real-time case studies. Perceives the structural patterns with reference to data science and statistics and analytics. Includes machine learning-based structured exercises. Appreciates different algorithmic concepts of machine learning including unsupervised, supervised, and reinforcement learning. This book is aimed at researchers, professionals, and graduate students in data science, machine learning, computer science, and electrical and computer engineering.

This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises’ productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem. The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.

Widely acknowledged, this popular and detailed text is a comprehensive treatise on Managerial Economics – both micro and macro-economic aspects. This text ensures a thorough understanding of core concepts before advancing to provide an expanded treatment of topics. It explains the economic environment and the impact on managerial decisions regarding price & output determination in different market structures followed by an account of the behaviour of individuals under conditions of uncertainty.

This open access book provides a theoretical framework and case studies on decision science for regional sustainability by integrating the natural and social sciences. The cases discussed include solution-oriented transdisciplinary studies on the environment, disasters, health, governance and human cooperation. Based on these case studies and comprehensive reviews of relevant works, including lessons learned from past failures for predictable surprises and successes in adaptive co-management, the book provides the reader with new perspectives on how we can co-design collaborative projects with various conflicts of interest and how we can transform our society for a sustainable future. The book makes a valuable contribution to the global research initiative Future Earth, promoting transdisciplinary studies to bridge the gap between science and society in knowledge generation processes and supporting efforts to achieve the UN’s Sustainable Development Goals (SDGs). Compared to other publications on transdisciplinary studies, this book is unique in that evolutionary biology is used as an integrator for various areas related to human decision-making, and approaches social changes as processes of adaptive learning and evolution. Given its scope, the book is highly recommended to all readers seeking an integrated overview of human decision-making in the context of social transformation.