No description available.

Documents are records of activities and related knowledge generated from organizational operations. With the trend of more and more documents being stored in the digital form, how to manage this knowledge has become an important issue. The first step is to manage knowledge is to activate the content of knowledge. These documents stored in an organization can not only be retrieved for future reference but also be analyzed to assist managers in making the right decision. Therefore, it is important for a organization to develop document-driven DSS that can discover useful knowledge from a large amount of documents in an organization. Most previous research on document management are focused on the indexing, retrieval and mining of documents, few applications have investigate how this technology can be used to construct knowledge for decision support. The purpose of this research is to propose an approach for developing document-driven DSS. In particular, the research proposes a methodology that combines ontology, indexing, and information retrieval technology to develop event scheme that can be used as a basis for the document-driven DSS. A prototype system has been designed to analyze documents collected from a journal ranking exercise to demonstrate the feasibility of the proposed approach.

<p>Introduction</p><p>Organizations are exposed to a rapidly changing business environment with never ending challenges. Investments in information technology (IT) have been one common approach to support organizations. Business Intelligence (BI), an off-spring from IT, is a system that assists many organizations in taking more accurate and timely decisions, improving process monitoring and providing better support for decision making. Recently organizations have started to realize the value of investing in BI, by discovering its analytical methods and capabilities to create business value.</p><p>Problem</p><p>Investments in BI have increased substantially over the past years and one reason for this might be due to vendors praise about BI’s ability to deliver business value. Significantly increased business value, better decision making, and high returns on investments are only a few benefits that have been claimed for. When considering the fact that it is very difficult to measure any direct benefits from IT investments in general, and BI as a consequence, an interest for analyzing the arguments used for selling BI emerged.</p><p>Purpose</p><p>The purpose of this thesis is to identify what arguments vendors and suppliers use when selling BI solutions, and explore their value by analyzing them through the use of existing theories from literature.</p><p>Method</p><p>A qualitative approach has been adopted, where unstructured interviews with BI vendors and suppliers were conducted. An inductive approach has been applied to gather arguments and then shifted to a deductive, in order to finalize the study and analyze arguments with appropriate theory. The research has been performed from without the Swedish market with well-known organizations.</p><p>Conclusions</p><p>A single version of the truth, control, and time savings are credible arguments for investing in BI. Furthermore, cost savings and improved analytical capabilities are fairly credible, whereas increased efficiency has least credibility when analyzed against theories. In general, we believe that the ability to gain from these positive effects from BI, organizations have to take an active role in realizing these.</p>

Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (leaves 261-272).

Thesis (M.A.)--University of Wyoming, 2007. / Title from PDF title page (viewed on June 11, 2009). Includes bibliographical references (p. 82-89).

Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 2004. / Thesis advisor(s): Man-Tak Shing, Richard Riehle. Includes bibliographical references (p. 89). Also available online.

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, March 2004. / Thesis advisor(s): Alex Bordetsky. Includes bibliographical references (p. 83-85). Also available online.

Thesis (M.S. in Mechanical Engineering and M.S. in Information Technology Management)--Naval Postgraduate School, September 2003. / Thesis advisor(s): Joshua Gordis, Dan Boger. Includes bibliographical references (p. 85-86). Also available online.

Thesis (M.S.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains ix, 161 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 49).

Thesis (Ph. D.)--University of Missouri--Columbia, 2002. / "May 2002." Typescript. Vita. Includes bibliographical references (leaves 104-114).