This proceedings volume aims to consolidate current knowledge of research into the many fields of DSS, and to identify key issues which should be incorporated into the future research agenda. The main themes of this volume include: DSS for distributed decision processes, Embedding knowledge in DSS, and DSS and organizational change.

During the past two decades, the consideration of mUltiple objectives in modeling and decision making has grown by leaps and bounds. The nineties in particular have seen the emphasis shift from the dominance of single-objective modeling and optimization toward an emphasis on multiple objectives. The proceedings of this Conference epitomize these evolutionary changes and contribute to the important role that the tield of multiple criteria decision making (MCDM) now plays in planning, design, operational, management, and policy decisions. Of special interest are the contributions of MCDM to manufacturing engineering. For example, it has recently been recognized that optimal, single-objective solutions have often been pursued at the expense of the much broader applicability of designs and solutions that satisfy multiple objectives. In particular, the theme (MCDM and Its Worldwide Role in Risk-Based Decision Making) of the XIVth International Conference on Multiple Criteria Decision Making (Charlottesville, Virginia, USA, June 8-12, 1998) represents the growing importance of risk-cost-benefit analysis in decision making and in engineering design and manufacturing. In such systems, minimizing the of rare and extreme events emerges as an essential objective that risk complements the minimization of the traditional expected value of risk, along with the objectives attached to cost and performance. These proceedings include forty-five papers that were presented at the Conference. A variety of techniques have been proposed for solving multiple criteria decision-making problems. The emphasis and style of the different techniques largely reflect the fields of expertise of their developers.

This book will be bought by researchers and graduates students in Artificial Intelligence and management as well as practising managers and consultants interested in the application of IT and information systems in real business environment.

Presents the advances in decision support theory and practice with a focus on bridging the socio-technical gap. This book covers a wide range of topics including: Understanding DM, Design of DSS, Web 2.0 Systems in Decision Support, Business Intelligence and Data Warehousing, Applications of Multi-Criteria Decision Analysis, and more.

In today's rapidly changing educational and business climate, organizational transformation has become a key area of development for many different and varied environments, both commercial and academic. This book addresses issues related to developing Decision Support Systems (DSS) which are sensitive and adaptable to different contexts and evolving technical and work environments. In addition to addressing the various cultural/social, organizational/individual, task/technology contexts of DSS, the book also anchors these discussions in a practical context, drawing on case studies to illustrate the theoretical dimensions stressed. This book includes the following issues: Frameworks for understanding the contexts and environments of decision support; Cases and issues in decision support and organizational transformation in context; An inter-disciplinary analysis of DSS, covering a wide variety of situations; and Real-world applications of DSS . It contains selected papers presented and discussed at the International Conference on Context-Sensitive Decision Support Systems, which was sponsored by the International Federation for Information Processing (IFIP) and held in Bled, Slovenia in July 1998. The book will prove invaluable to anyone working in information and decision support systems development, management, implementation and evaluation, as well as to researchers/practitioners in organizational analysis and development, management and business administration, sociology and psychology of organizations, human relations and human factors management.

The vast flow of information to be considered by policy and decision makers in national and local governments is continuing to expand during the 1990s, whilst budgets for staff to process the information are being tightened. This publication provides a forum for the examination of the problem. It aims to focus the efforts of researchers and practitioners more effectively in applying information technology to increase the performance of decision makers in public administration despite the limited resources. Topics explored include the following: design considerations and approaches for, and practical experiences with, communication and information processing infrastructure and applications at the workplace level; the design and implementation of support systems for individual or group decision making in governmental and municipal settings; modelling and model management techniques, based on case reports of successful and unsuccessful modelling efforts; concepts, approaches and models for re-designing tasks and processes in public administration; issues and challenges in integrating the information systems of several governmental bodies. The book is divided into two parts for the discussion of these themes - the first section deals primarily with theoretical and conceptual issues; the second part contains papers with a stronger emphasis on systems, their functionality and experiences in their development and application. The authors' affiliations (17 organizations from 8 different countries) indicates the international nature of the contributions. The ideas put forward in their papers show that research into supporting decision making in public administration is well on its way but that the research area is vast, with yet many hills to scale.

Intelligent Support Systems for Marketing Decisions examines new product development, market penetration strategies, and other marketing decisions utilizing a confluence of methods, including Decision Support Systems (DSS), Artificial Intelligence in Marketing and Multicriteria Analysis. The authors systematically examine the use and implementation of these methodologies in making strategic marketing decisions. Part I discusses the basic concepts of multicriteria analysis vis-à-vis marketing decisions and in new product development situations. Part II presents basic concepts from the fields of Information Systems, Decision Support Systems, and Intelligent Decision Support Methods. In addition, specialized categories of DSS (multicriteria DSS, web-based DSS, group DSS, spatial DSS) are discussed in terms of their key features and current use in marketing applications. Part III presents IDSS and a multicriteria methodology for new product development. Further chapters present a developmental strategy for analyzing, designing, and implementing an Intelligent Marketing Decision Support System. The implementation discussion is illustrated with a real-world example of the methods and system in use.

The main purpose of this paper is to contribute to the discussion about the design of computer and communication systems that can aid the management process. 1.1 Historical Overview We propose that Decision Support System can be considered as a design conception conceived within the computer industry to facilitate the use of computer technology in organisations (Keen, 1991). This framework, built during the late 1970s, offers computer and communication technology as support to the decision process which constitutes, in this view, the core of the management process. The DSS framework offers the following capabilities: • Access: ease of use, wide variety of data, analysis and modelling capacity. • Technological: software gel)eration tools. • Development modes: interactive and evolutionary. Within this perspective, computer and communication technologies are seen as an amplification of the human data processing capabilities which limit the decision process. Thus, the human being is understood metaphorically as a data processing machine. Mental processes are associated with the manipulation of symbols aOO human communication to signal transmission.

Advances in technology have resulted in new and advanced methods to support decision-making. For example, artificial intelligence has enabled people to make better decisions hrough the use of Intelligent Decision Support Systems (DSS). Emerging research in DSS demonstrates that decision makers can operate in a more timely manner using real-time data, more accurately due to data mining and 'big data' methods, more strategically by considering a greater number of factors, more precisely and inclusively due to the availability of social networking data, and with a wider media reach with video and audio technology._x000D_ _x000D_This book presents the proceedings of the IFIP TC8/Working Group 8.3 conference held at the Université Pierre et Marie Curie in Paris, France, in June 2014. Throughout its history the conference has aimed to present the latest innovations and achievements in Decision Support Systems. This year the conference looks to the next generation with the theme of new technologies to enable DSS2.0. The topics covered include theoretical, empirical and design science research; case-based approaches in decision support systems; decision models in the real-world; healthcare information technology; decision making theory; knowledge management; knowledge and resource discovery; business intelligence; group decision support systems; collaborative decision making; analytics and ‘big data’; rich language for decision support; multimedia tools for DSS; Web 2.0 systems in decision support; context-based technologies for decision making; intelligent systems and technologies in decision support; organizational decision support; research methods in DSS 2.0; mobile DSS; competing on analytics; and social media analytics._x000D_ _x000D_ The book will be of interest to all those who develop or use Decision Support Systems. The variety of methods and applications illustrated by this international group of carefully reviewed papers should provide ideas and directions for future researchers and practitioners alike.

This book reports on cutting-edge research carried out within the context of the EU-funded Dicode project, which aims at facilitating and augmenting collaboration and decision making in data-intensive and cognitively complex settings. Whenever appropriate, Dicode builds on prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze, and aggregate data from diverse, extremely large and rapidly evolving sources. The Dicode approach and services are fully explained and particular emphasis is placed on deepening insights regarding the exploitation of big data, as well as on collaboration and issues relating to sense-making support. Building on current advances, the solution developed in the Dicode project brings together the reasoning capabilities of both the machine and humans. It can be viewed as an innovative “workbench” incorporating and orchestrating a set of interoperable services that reduce the data intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and effective in their work practices.