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Intelligent Decision-Making Support Systems (i-DMSS) are specialized IT-based systems that support some or several phases of the individual, team, organizational or inter-organizational decision making process by deploying some or several intelligent mechanisms.
This book pursues the following academic aims: (i) generate a compendium of quality theoretical and applied contributions in Intelligent Decision-Making Support Systems (i-DMSS) for engineering and management IT-based service systems (ITSS); (ii) diffuse scarce knowledge about foundations, architectures and effective and efficient methods and strategies for successfully planning, designing, building, operating, and evaluating i-DMSS for ITSS, and (iii) create an awareness of, and a bridge between ITSS and i-DMSS academicians and practitioners in the current complex and dynamic engineering and management ITSS organizational.
The book presents a collection of 11 chapters referring to relevant topics for both IT service systems and i-DMSS including: problems of selection of IT service providers, optimization of supply chain systems, IT governance decisions, clinical decision support, dynamic user-interface adaptation, re-engineering of processes, and generic decision problems. Advanced IT technologies used in some chapters are: fuzzy multi-criteria mechanisms, semantic processing, data mining processing, and rough sets. Other chapters report traditional DSS mechanisms but used or suggested to be used in innovative mode for IT service engineering and management tasks.
Inhaltsverzeichnis
Knowledge Management in ITSM: Applying the DIKW Model.- IT Governance Practice in a Malaysian Public Institute of Higher Learning and Intelligent Decision Making Support System Solution.- DSS based IT Service Support Process Reengineering using ITIL: A Case Study.- Managing Cloud Services with IT Service Management practices.- Towards semantic support for business process integration Roberto.- Integrating ERP with Negotiation tools in Supply Chain.- Adaptive Applications: Definition and Usability in IT-based Service Systems Management.- Attitude-based Consensus Model for Heterogeneous Multi-criteria Large-Scale Group Decision Making: Application to IT-based Services Management.- Improving Decision-Making for Clinical Research and Health Administration.- Improving IT Service Management with Decision-Making Support Systems.
Über den Autor / die Autorin
Prof. Dr. Jorge Marx Gomez ist Professor für Wirtschaftsinformatik an der Carl von Ossietzky Universität Oldenburg.
