Doukidis: Knowledge Based Management ?support? Systems
Knowledge–Based Decision Support Systems With Applications in Business
This book examines an ontology-based knowledge management approach to enable the interoperation of heterogeneous knowledge management systems in the domain of reusing inter-organizational knowledge. This book also investigates a theoretical ontology mediation framework to develop an integrated ontology by reusing inter-organizational ontologies. This book makes research contributions in the area of applying ontology and its mediation methods to develop and manage inter-organizational knowledge management process.
IT-Governance has a major impact not only on IT management but also and foremost in the Enterprises performance and control. Business uses IT agility, flexibility and innovation to pursue its objectives and to sustain its strategy. However being it more critical to the business, compliance forces IT on the opposite way of predictability, stability and regulations. Adding the current economical environment and the fact that most of the times IT departments are considered cost centres, IT-Governance decisions become more important and critical. This research intends to provide an answer to IT-Governance requirements using Data Driven Decision Support Systems based on dimensional models. To address this research opportunity we have considered IT-Governance research (Peter Weill), best practises (ITIL), Body of Knowledge (PMBOK) and frameworks (COBIT). Key IT-Governance processes (Change Management, Incident Management, Project Development and Service Desk Management) were studied and key process stakeholders were interviewed. Based on the facts gathered, dimensional models (data marts) were modelled and developed to answer to key improvement requirements on each IT-Governance process.
This book presents a methodology for the design and development of Knowledge Management systems to support New Product Development based on Enterprise Architecture Frameworks (EAFs). The project focuses on information system specifications driven by business and knowledge users’ requirements in the automotive industry. The aim of this research is to extend the capabilities of the latest EAFs so that not only data and information, but also enterprise knowledge can be managed. A formal methodology has been developed based on the extended EAF, and implemented as easy-to-use folders for the management of product development knowledge. A guideline in the form of a flowchart has been developed using a process modelling tool called Design Roadmap. A case study in an automotive product development company proved that the developed methodology can be used to produce the functional specifications of their IT systems to include knowledge management capability. The system specification can then be used, either to assess a company’s existing information systems for future system improvement; or as a guide to developing and implementing complete new information/Knowledge Management systems.
During the last 20 years ITIL (IT Infrastructure Library) has been evolving with the latest version published in 2007. Incident Management and Problem Management are two main activities of ITIL service operation framework which handles incidents and their root causes respectively. Service Desk systems are software tools that help IT organizations in handling incidents and problems. On the other hand since Knowledge Management emerged, many corporates adopted Knowledge Management. By adding a Knowledge Management structure to the ITIL framework in 2007 the path of utilization Knowledge Management in Service Desk system is smoothed, however, the number of Service Desk systems that have adopted a Knowledge Management structure is few and the adoption is not practical in many cases. In this paper we try to address this issue and focus on Knowledge Management structure utilization in Service Desk systems by integrating Case-based Reasoning and Service Desk structure.
Knowledge Management and Information Systems Strategy for Growing Organizations examines the role that information systems play in helping SMEs use knowledge to achieve strategic organizational goals. Adopting a business perspective, it is ideal for students studying strategic information systems and knowledge management.
Duffin: ?knowledge? Based Systems – Applications I N Government
Inventory Model has been one of the important issues specially in recent years that need to be addressed to improve the complexity of the companies and business competitiveness. On the other hand, Decision Support Systems (DSS) that are a specific class of computerized information systems that supports business and organizational decision-making activities, can help decision makers especially inventory managers to compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make better decisions. In this Book, we focus more on the mathematical model and artificial intelligence for inventory by considering the concepts of Decision support systems in supply chain management. The proposed system in this book can help managers in forecasting item demand in future, and also it can assist managers in order to choose an appropriate model which capable of determining the optimal order quantity and frequency of ordering based on the demand.
Hickman: ?analysis? For Knowledge–based Systems: A Practical Guide To The Kads Methodolo
Nowadays companies have taken the task of develop better management information systems in order to help the decision makers to exploit data and models, with the final objective of discussing and improving decision-making. Decision support systems must be improved in order to deal with the large amount of available data and the heterogeneity of existing modeling approaches along the enterprise structure. This book proposes the application of ontologies as a decision support tool, since they are increasingly seen as a key semantic technology for addressing heterogeneities and for enabling data mining by semantics-driven knowledge processing. As a decision support tool, it must be capable of standing as a robust model which interacts among the different decision hierarchical levels, providing a unified framework for data and information. The work presented represents a step forward toward integration among the enterprise hierarchical levels, standardization in processes and enterprises, as well as improved procedures for decision-making. The aforementioned achievements are boosted by the application of semantic models, which are currently increasingly used.