Application Of Decision Science In Business And Management
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Application of Decision Science in Business and Management by Fausto Pedro García Márquez Pdf
Application of Decision Science in Business and Management is a book where each chapter has been contributed by a different author(s). The chapters introduce and demonstrate a decision-making theory to practice case studies. It demonstrates key results for each sector with diverse real-world case studies. Theory is accompanied by relevant analysis techniques, with a progressive approach building from simple theory to complex and dynamic decisions with multiple data points, including big data, lot of data, etc. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support analysis of multi-criteria decision-making problems with defined constraints and requirements. The book provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of decision making. It is complementary to other sub-disciplines such as economics, finance, marketing, decision and risk analysis, etc.
Strategic Management, Decision Theory, and Decision Science by Bikas Kumar Sinha,Srijib Bhusan Bagchi Pdf
This book contains international perspectives that unifies the themes of strategic management, decision theory, and data science. It contains thought-provoking presentations of case studies backed by adequate analysis adding significance to the discussions. Most of the decision-making models in use do take due advantage of collection and processing of relevant data using appropriate analytics oriented to provide inputs into effective decision-making. The book showcases applications in diverse fields including banking and insurance, portfolio management, inventory analysis, performance assessment of comparable economic agents, managing utilities in a health-care facility, reducing traffic snarls on highways, monitoring achievement of some of the sustainable development goals in a country or state, and similar other areas that showcase policy implications. It holds immense value for researchers as well as professionals responsible for organizational decisions.
Data Science for Business and Decision Making by Luiz Paulo Fávero,Patrícia Belfiore Pdf
Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. Combines statistics and operations research modeling to teach the principles of business analytics Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs
The Best Thinking in Business Analytics from the Decision Sciences Institute by Decision Sciences Institute,Merrill Warkentin Pdf
Today, business success depends on making great decisions – and making them fast. Leading organizations apply sophisticated business analytics tools and technologies to evaluate vast amounts of data, glean new insights, and increase both the speed and quality of decision making. In The Best Thinking and Practices in Business Analytics from the Decision Sciences Institute, DSI has compiled award-winning and award-nominated contributions from its most recent conferences: papers that illuminate exceptionally high-value applications and research on analytics for decision-making. These papers have appeared in no other DSI collection. Explore them here, and you’ll discover powerful new opportunities for competitive advantage through analytics. For all business, academic, and organizational professionals concerned with the science of more effective decision-making; and for undergraduate students, graduate students, and certification candidates in all related fields.
Data Science and Multiple Criteria Decision Making Approaches in Finance by Gökhan Silahtaroğlu,Hasan Dinçer,Serhat Yüksel Pdf
This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.
"A very rich book sprinkled with real-life examples as well as battle-tested advice.” —Pierre Haren, VP ILOG, IBM "James does a thorough job of explaining Decision Management Systems as enablers of a formidable business transformation.” —Deepak Advani, Vice President, Business Analytics Products and SPSS, IBM Build Systems That Work Actively to Help You Maximize Growth and Profits Most companies rely on operational systems that are largely passive. But what if you could make your systems active participants in optimizing your business? What if your systems could act intelligently on their own? Learn, not just report? Empower users to take action instead of simply escalating their problems? Evolve without massive IT investments? Decision Management Systems can do all that and more. In this book, the field’s leading expert demonstrates how to use them to drive unprecedented levels of business value. James Taylor shows how to integrate operational and analytic technologies to create systems that are more agile, more analytic, and more adaptive. Through actual case studies, you’ll learn how to combine technologies such as predictive analytics, optimization, and business rules—improving customer service, reducing fraud, managing risk, increasing agility, and driving growth. Both a practical how-to guide and a framework for planning, Decision Management Systems focuses on mainstream business challenges. Coverage includes Understanding how Decision Management Systems can transform your business Planning your systems “with the decision in mind” Identifying, modeling, and prioritizing the decisions you need to optimize Designing and implementing robust decision services Monitoring your ongoing decision-making and learning how to improve it Proven enablers of effective Decision Management Systems: people, process, and technology Identifying and overcoming obstacles that can derail your Decision Management Systems initiative
This book examines various decision-making processes, influences and its role in business management. The chapters describe the original decision-making approach based on joint use of the multi-criteria method and the method of group preferences in business management; a discussion on the internationalization decision-making process of small-medium enterprises (SMEs); and an examination on the efficiency of computer decision support systems by developing a set of universal analytic models for increasing the efficiency of fuzzy input information processing.
Management Decision-Making, Big Data and Analytics by Simone Gressel,David J. Pauleen,Nazim Taskin Pdf
Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers. The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management. The book features chapters on cutting-edge topics, including: • Big data • Analytics • Managing emerging technologies and decision-making • Managing the ethics, security, privacy and legal aspects of data-driven decision-making The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles. Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels.
Applications of Decision Science in Management by Taosheng Wang,Srikanta Patnaik,Wu Chun Ho Jack,Maria Leonilde Rocha Varela Pdf
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.
Decision Sciences and Applications in the Transportation Sector by Said Ali Hassan,Ali Wagdy Mohamed Pdf
"This book will provide relevant theoretical and practical frameworks and the latest research findings in the area of decision sciences and applications in the transportation sector for researchers, executives and practitioners who want to enrich their scientific knowledge and improve their understanding of the decision-making process in facing real-world problems in the transportation sector"--
Decision Intelligence Analytics and the Implementation of Strategic Business Management by P. Mary Jeyanthi,Tanupriya Choudhury,Dieu Hack-Polay,T P Singh,Sheikh Abujar Pdf
This book presents a framework for developing an analytics strategy that includes a range of activities, from problem definition and data collection to data warehousing, analysis, and decision making. The authors examine best practices in team analytics strategies such as player evaluation, game strategy, and training and performance. They also explore the way in which organizations can use analytics to drive additional revenue and operate more efficiently. The authors provide keys to building and organizing a decision intelligence analytics that delivers insights into all parts of an organization. The book examines the criteria and tools for evaluating and selecting decision intelligence analytics technologies and the applicability of strategies for fostering a culture that prioritizes data-driven decision making. Each chapter is carefully segmented to enable the reader to gain knowledge in business intelligence, decision making and artificial intelligence in a strategic management context.
Decision Sciences for COVID-19 by Said Ali Hassan,Ali Wagdy Mohamed,Khalid Abdulaziz Alnowibet Pdf
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.
Models and Applications in the Decision Sciences by Decision Sciences Institute,Merrill Warkentin Pdf
NEW ADVANCES IN THE SCIENCE OF DECISION MAKING: Practical and relevant research from DSI, the field’s leading organization 14 OUTSTANDING PAPERS APPLYING RIGOROUS RESEARCH METHODS TO IMPORTANT SOCIETAL AND BUSINESS DECISION ENVIRONMENTS NEW OPPORTUNITIES TO IMPROVE PERFORMANCE IN STRATEGY, TACTICS, AND OPERATIONS FOR ALL DECISION MAKERS, AND ALL DECISION SCIENCE RESEARCHERS AND STUDENTS More than 1,000 papers were submitted to the Decision Science Institute’s 2015 annual conference. This book presents the 14 papers chosen as most insightful and useful. This peer-reviewed research addresses a richly diverse set of business topics, illuminating opportunities to improve decision making at strategic, tactical, and operational levels. Spanning analytics, information systems and technology, supply chain operations management, and other disciplines, these papers identify multiple opportunities for immediate and long-term performance improvement. The authors address challenges ranging from talent management to lean transformation, mobile app marketing to corporate ethics, driving change to predicting stock prices. Their work reflects both the intellectual vibrancy of the discipline of decision science and its immense practical value. Decision sciences research leads to improved decision outcomes. This volume brings together peer-reviewed papers chosen as “best of the best” by the field’s leading organization, the Decision Sciences Institute. Authored by respected researchers worldwide, these papers were presented at DSI’s 46th Annual Meeting in Seattle. They describe new methods and approaches in the decision sciences, with a special focus on translating theoretical impact into practical relevance to improve decision making within business, public policy, non-profit organizations, and beyond. Assess willingness to learn ERP systems based on knowledge update and other factors Exploit application integration to improve ERP’s value after implementation Discover how mobile users decide whether to search for and adopt a new app Quantify links between absenteeism and hostile environment/sexual harassment Assess correlations between employee development and worker outcomes Explore perceptions of change, intentions to leave, and the role of cynicism Promote lean transformation by evolving HR performance management systems Understand how links between corporate ethical values and firm performance are mediated Bring a global sourcing perspective to issues of ethical consumption Improve quality by choosing practices with the best cultural fit Use Multilayer Perceptron (MLP) and Bayesian Networks (BN) to predict diabetes Apply a comprehensive empirical framework for assessing patient care quality Promote sharing of clinical knowledge among a practice group’s physicians Forecast variable impacts in S&P 500 equity prices
Management Theories and Strategic Practices for Decision Making by Tavana, Madjid Pdf
There is an immense amount of information to be considered when attempting to solve complex strategic problems. To recognize the complexity of this process, the creation of tools and techniques are essential to aid decision makers in developing a rational model for strategy evaluation. Management Theories and Strategic Practices for Decision Making brings together a collection of research aiming to provide communication for the management of new methodologies to solve strategic problems and applying decision making approaches. This reference is useful for government agencies, practicing managers, academic and research institutions interested in bringing together strategic decision-making and decision sciences.
Data Science for Business by Foster Provost,Tom Fawcett Pdf
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates
