This book examines emerging developments in the decision support system (DSS) field as it enters its third decade. The book is based on the NATO Advanced Study Institute on Recent Developments in Decision Support Systems held in Italy in June 1991. The contributors are an international assortment of active DSS researchers who offer diverse perspectives on DSSs and examine recent advances in the field. There are four major parts to the book. Part 1 is concerned with DSS foundations, including concepts, theories, frameworks and models. Part 2 examines DSS development in terms of tools and methods for building DSSs. Part 3 is concerned with DSS usage and evaluation. Part 4 concludes with presentations of specific DSS applications. Researchers, graduate students and practitioners in the DSS field will find that the book provides a stimulating and current treatment of DSS topics, helping to usher in the next decade of DSS advances.

This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations, methods, methodologies, models, tools, and techniques for designing, developing, implementing and evaluating advanced DSSs in different fields, including finance, health, emergency management, industry and pollution control. Decision support systems employ artificial intelligence methods to heuristically address problems that are cannot be solved using formal techniques. In this context, technologies such as the Semantic Web, linked data, big data, and machine learning are being applied to provide integrated support for individuals and organizations to make more rational decisions. The book is organized into two parts. The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.

Foundations of Decision Support Systems focuses on the frameworks, strategies, and techniques involved in decision support systems (DSS). The publication first takes a look at information processing, decision making, and decision support; frameworks for organizational information processing and decision making; and representative decision support systems. Discussions focus on classification scheme for DSS, abilities required for decision making, division of information-processing labor within an organization, and decision support. The text then elaborates on ideas in decision support, formalizations of purposive systems, and conceptual and operational constructs for building a data base knowledge system. The book takes a look at building a data base knowledge system, language systems for data base knowledge systems, and problem-processing systems for data base knowledge systems. Topics include problem processors for computationally oriented DSS, major varieties of logical data structures, and indirect associations among concepts. The manuscript also examines operationalizing modeling knowledge in terms of predicate calculus; combining the data base and formal logic approaches; and the language and knowledge systems of a DSS based on formal logic. The publication is a valuable reference for researchers interested in decision support systems.

Over the past two decades, many advances have been made in the decision support system (DSS) field. They range from progress in fundamental concepts, to improved techniques and methods, to widespread use of commercial software for DSS development. Still, the depth and breadth of the DSS field continues to grow, fueled by the need to better support decision making in a world that is increasingly complex in terms of volume, diversity, and interconnectedness of the knowledge on which decisions can be based. This continuing growth is facilitated by increasing computer power and decreasing per-unit computing costs. But, it is spearheaded by the multifaceted efforts of DSS researchers. The collective work of these researchers runs from the speculative to the normative to the descriptive. It includes analysis of what the field needs, designs of means for meeting recognized needs, and implementations for study. It encompasses theoretical, empirical, and applied orientations. It is concerned with the invention of concepts, frameworks, models, and languages for giving varied, helpful perspectives. It involves the discovery of principles, methods, and techniques for expeditious construction of successful DSSs. It aims to create computer-based tools that facilitate DSS development. It assesses DSS efficacy by observing systems, their developers, and their users. This growing body of research continues to be fleshed out and take shape on a strong, but still-developing, skeletal foundation.

"The rapid commercialization of the Internet and success of online direct marketing led to the burgeoning field of business-to-business e-commerce, a growing industry analyzed with the most recent research developments and successful implementation strategies in this business volume. E-commerce environments, supply chain management issues, and value chain networks are explored with respect to process, research, and electronic tendering. More complex discussions of classification schemes, manufacturing connectedness, and structuration theory provide the academic dimension of the practical business challenges presented."

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.

For MIS specialists and non-specialists alike, this text is a comprehensive, readable, understandable guide to the concepts and applications of decision support systems.