Decision Support Systems: Issues and Challenges covers the proceedings of the International Institute for Applied Systems Analysis (IIASA) International Task Force Meeting. The book reviews papers that tackle issues about decision support systems (DSS). Comprised of 17 chapters, the book organizes the chapters according to the topic of discussion, including framework, resource discipline, application experience, and issues for the future in DSS. The opening chapter is an introduction to the main topic of the book. Chapter 2 discusses frameworks for research on decision support systems, and Cha ...
For MIS specialists and non-specialists alike, this text is a comprehensive, readable, understandable guide to the concepts and applications of decision support systems.
Decision Support Systems: Issues and Challenges covers the proceedings of the International Institute for Applied Systems Analysis (IIASA) International Task Force Meeting. The book reviews papers that tackle issues about decision support systems (DSS). Comprised of 17 chapters, the book organizes the chapters according to the topic of discussion, including framework, resource discipline, application experience, and issues for the future in DSS. The opening chapter is an introduction to the main topic of the book. Chapter 2 discusses frameworks for research on decision support systems, and Chapter 3 covers the decision support systems. The fourth chapter deals with organizational science contributions to the design of decision support systems, while the fifth chapter discusses using data bases for decision support. Chapter 6 tackles the overview of database technology in decision support systems, and Chapter 7 talks about doing and speaking in the office. The eighth chapter discusses a look back at an office of the future, while the ninth chapter covers the implications for research of installing a decision support system. Chapter 10 tackles the problems of design and implementation of computer-based decision support systems. Chapter 11 discusses an interactive modeling system for analysis of alternative decisions; Chapter 12 covers the structure of decision support systems. Chapters 13 to 15 review the group discussion during the conference about the issues for the future in DSS. This book will be of great interest to leaders, since it discusses the integration of technology in the interaction within an organization.
Three case studies of decision support systems; Connoisseur foods: the introduction of modeling and data retrieval capabilities; Great eastern bank: a portfolio management system; Gotaas-larsen shipping corporation: a corporate planning system; Choices for the user and implementer; A taxonomy of decision support systems; Using decision support systems to indrease the effectiveness of individuals; Patterns of system usage; Toward successful implementation; Difficulties in system usage; Implementation patterns; Implementation risk factors and implentation strategies; Trends for the future; Additional case studies; Equitable life: a computer-assisted underwriting system; Interactive market system: a media decision support system; The great northern bank: a system for budgeting, planning and control; The cost of living council: decision support in a regulatory setting; AAIMS: an analytic information management system.
Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries.
Annotation The book presents state-of-the-art knowledge about decision-making support systems (DMSS). Its main goals are to provide a compendium of quality chapters on decision-making support systems that help diffuse scarce knowledge about effective methods and strategies for successfully designing, developing, implementing, and evaluating decision-making support systems, and to create an awareness among readers about the relevance of decision-making support systems in the current complex and dynamic management environment.
Scientists from management and strategy, information systems, engineering and telecommunications have discussed a novel concept: Smart Business Networks. They see the future as a developing web of people and organizations, bound together in a dynamic and unpredictable way, creating smart outcomes from quickly (re-)configuring links between actors. The question is: What should be done to make the outcomes of such a network 'smart', that is, just a little better than that of your competitor? More agile, with less pain, with more return to all the members of the network, now and over time? The technical answer is to create a 'business operating system' that should run business processes on different organisational platforms. Business processes would become portable: The end-to-end management of processes running across many different organizations in many different forms would become possible. This book presents you the outcomes of an energizing and new direction in management science.
Praise for the First Edition "This is the most usable decision support systems text. [i]t is far better than any other text in the field" —Computing Reviews Computer-based systems known as decision support systems (DSS) play a vital role in helping professionals across various fields of practice understand what information is needed, when it is needed, and in what form in order to make smart and valuable business decisions. Providing a unique combination of theory, applications, and technology, Decision Support Systems for Business Intelligence, Second Edition supplies readers with the hands-on approach that is needed to understand the implications of theory to DSS design as well as the skills needed to construct a DSS. This new edition reflects numerous advances in the field as well as the latest related technological developments. By addressing all topics on three levels—general theory, implications for DSS design, and code development—the author presents an integrated analysis of what every DSS designer needs to know. This Second Edition features: Expanded coverage of data mining with new examples Newly added discussion of business intelligence and transnational corporations Discussion of the increased capabilities of databases and the significant growth of user interfaces and models Emphasis on analytics to encourage DSS builders to utilize sufficient modeling support in their systems A thoroughly updated section on data warehousing including architecture, data adjustment, and data scrubbing Explanations and implications of DSS differences across cultures and the challenges associated with transnational systems Each chapter discusses various aspects of DSS that exist in real-world applications, and one main example of a DSS to facilitate car purchases is used throughout the entire book. Screenshots from JavaScript® and Adobe® ColdFusion are presented to demonstrate the use of popular software packages that carry out the discussed techniques, and a related Web site houses all of the book's figures along with demo versions of decision support packages, additional examples, and links to developments in the field. Decision Support Systems for Business Intelligence, Second Edition is an excellent book for courses on information systems, decision support systems, and data mining at the advanced undergraduate and graduate levels. It also serves as a practical reference for professionals working in the fields of business, statistics, engineering, and computer technology.
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
