Intelligent Decision-making Support Systems: Foundations, Applications and Challenges / Edition 1

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Decision-making Support Systems (DMSS) are computer-based systems that support individual or organisational decision-making processes. Recent advances in information technology and artificial intelligence are enhancing these systems and giving rise to intelligent-DMSS.

Intelligent Decision-making Support Systems: Foundations, Applications and Challenges is the first book to provide integrated coverage of the technical aspects of intelligent Decision-Making Support Systems together with discussion of their application and evaluation in organisational structures.

The book brings together up-to-date information on the theory and application of i-DMSS. Readers will learn about the foundations, architectures, methods and strategies for successfully designing, developing, implementing, and evaluating intelligent Decision-making Support Systems.

Intelligent Decision-making Support Systems: Foundations, Applications and Challenges will be of value to researchers in AI and management studies interested in the latest thinking in decision-making, as well practising managers and consultants who are involved with putting advanced information technologies into practice in organisations.

The Decision Engineering series focuses on the foundations and applications of tools and techniques related to decision engineering, and identifies their relevance in ‘engineering’ decisions. The series provides an aid to practising professionals and applied researchers in the development of tools for informed operational and business decision making, within industry, by utilising distributed organisational knowledge.

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Product Details

  • ISBN-13: 9781849965620
  • Publisher: Springer London
  • Publication date: 12/10/2010
  • Series: Decision Engineering Series
  • Edition description: Softcover reprint of hardcover 1st ed. 2006
  • Edition number: 1
  • Pages: 503
  • Product dimensions: 9.21 (w) x 6.14 (h) x 1.06 (d)

Meet the Author

Professor Jatinder N. D. Gupta is currently Eminent Scholar of Management of Technology, Professor of Management Information Systems, Industrial and Systems Engineering and Engineering Management, and Chairperson of the Department of Accounting and Information Systems at the University of Alabama in Huntsville, Huntsville, Alabama. He holds a PhD in Industrial Engineering (with specialization in Production Management and Information Systems) from Texas Tech University. Dr. Gupta serves on the editorial boards of several national and international journals. Recipient of the Outstanding Faculty and Outstanding Researcher awards from Ball State University, he has published numerous papers many journals. He was also editor of the book Decision Making Support Systems: Achievements and Challenges for the New Decade (Idea Group Publishing, 2002). His current research interests include e-commerce, supply chain management, information and decision technologies, scheduling, planning and control, organizational learning and effectiveness, systems education, knowledge management, and enterprise integration.

Guisseppi A. Forgionne is Professor of Information Systems at the University of Maryland Baltimore County (UMBC). Professor Forgionne holds a B.S. in Commerce and Finance, an M. A. in Econometrics, an M. B. A., and a Ph. D. in Management Science and Econometrics. He has published 25 books and approximately 150 research articles and consulted for a variety of public and private organizations on decision support systems theory and applications. Professor. Forgionne also has served as department chair at UMBC, Mount Vernon College, and Cal Poly Pomona. He has received several national and international awards for his work.

Manuel Mora is an associate professor of the Information System Department at the Autonomous University of Aguascalientes (UAA). He holds a Dr. in Engineering degree from the Engineering School in UNAM, Mexico (largest research university in Mexico). He also received his BSc and MSc degrees in Computer Systems and Artificial Intelligence from the Monterrey Tech (ITESM). His main research interest is the design and implementation of traditional and intelligent Decision Making Support Systems (DSS, EIS and ES/KBS) from a systemic and cybernetic perspective.

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Table of Contents

Part I Foundations of i-DMSS
A Multi-criteria Model for the Evaluation of Intelligent Decision-Making Support Systems (i-DMSS)
On the Legacy of Herbert Simon and his contribution to Decision Making Support Systems and Artificial Intelligence
Synergizing the Artificial Intelligence and Decision Support Research Streams: Over a Decade of Progress with New Challenges on the Horizon
From Knowledge Discovery to Computational Intelligence: A Framework for Intelligent Decision Support Systems
Taking Decisions into the Wild: An AI Perspective in the Design of i-DMSS
Development Processes of Intelligent Decision Making Support Systems: Review and Perspective
Explanatory Power of Intelligent Systems: Review and Perspective Part II Applications of i-DMSS
A New Paradigm for Developing intelligent Decision-Making Support Systems (i-DMSS): A Case Study on the Development of Comparison-Shopping Agents
A Causal Knowledge-Driven Negotiation Mechanism for B2B Electronic Commerce
A Simulation Study of Just-In-Time Knowledge Management (JITKM)
An IDSS for Regional Aquaculture Planning
An i-DMSS Based on Bipartite Matching and Heuristics for Rental Bus Allocation
MicroDEMON: A Decision-Making Intelligent Assistant for Mobile Business
Using System Dynamics and Case Based Reasoning (CBR) to build an Intelligent Decision-Making Support System (i-DMSS) that improves Strategic Public Decisions e-Negotiation Systems and Software Agents: Methods, Models, and Applications
Knowledge-Intensive Collaborative Decision Support for Design Process
The Application of Semantic Web Technologies for Railway Decision Support Part III Trends of i-DMSS
The Challenge of Supporting Emerging Inference-Based Decision Making
A Role for Information Portals as Intelligent Decision Support Systems: Breast Cancer Knowledge On-Line Experience
An Overview of Future Challenges of Decision Support Technologies
A challenging future for i-DMSS
A Software Laboratory for Advancing Decision Support Simulation
A Strategic Descriptive Review of Intelligent Decision-Making Support Systems Research: the 1980-2004 Period
The Optimization of What?

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