Zugl.: Duisburg, Essen, Universiẗat, Diss., 2007.

Failure to identify major target market and lack of cost management have shown to be negative for enterprise operations. To remedy these two problems information technologies have promised to support effective and efficent decision-making processing by providing accurate and real-time information, so as to assist front-line sales, to lower down costs, to create more profits and to further diversified the risks. In steel industry, the repeated purchasing frequency (associated with customer loyalty) has been identified as one of the major determinants due to the narrow target market and capital-intensive features existed in steel business. Steel businesses often involve international transactions, which have much higher uncertainties than domestic transactions. Therefore, the major risk control task is on the collection and analysis customers¡¦ creditability. More customer information leads to fewer risks. As such, we believe that by applying the methodology of collecting and analyzing information through information technologies, the decision makers will be more confident in making correct decisions, which in turn help to generate profits. In this thesis, we develop a data warehouse system in support of order procurement. We begin by identifying the types of information that is crucial in making order procurement decision by consulting with the experienced international and domestic front-line sales managers. The different types of information are prioritized by applying Analytic Hierarchy Process (AHP) approach. We then construct a datawarehouse model that encompasses these information. A system prototype is finally developed to demonstrate the feasiblity of our approach.

<p>Organisations have spent billions of dollars (USD) on investments in data warehouses. Many have succeeded, but many have also failed. These failures are considered mostly to be of an organisational nature and not of a technological, as one might have expected. Due to the failures, organisations have problems to derive business value from their data warehouse investments. Obtaining business value from data warehouses is necessary, since the investment is of such a magnitude that it is clearly visible in the balance sheet. In order to investigate how the business value may be increased, we have conducted an extensive literature study, aimed at identifying opportunities and future directions, which may alleviate the problem of low return on investment. To balance the work, we have also identified pitfalls, which may hinder organisations to derive business value from their data warehouses.</p><p>Based on the literature survey, we have identified and motivated possible research areas, which we consider relevant if organisations are to derive real business value from their data warehouses. These areas are:</p><p>* Integrating data warehouses in knowledge management.</p><p>* Data warehouses as a foundation for information data super stores.</p><p>* Using data warehouses to predict the need for business change.</p><p>* Aligning data warehouses and business processes.</p><p>As the areas are rather broad, we have also included examples of more specific research problems, within each possible research area. Furthermore, we have given initial ideas regarding how to investigate those specific research problems.</p>

Thesis (doctoral)--Universität St. Gallen, 2002.

Thesis (doctoral)--Technische Universität, Braunschweig, 1999.

This research investigates the practical issues surrounding the development and implementation of Decision Support Systems (DSS). The research describes the traditional development approaches analyzing their drawbacks and introduces a new DSS development methodology. The proposed DSS methodology is based upon four modules; needs' analysis, data warehouse (DW), knowledge discovery in database (KDD), and a DSS module. The proposed DSS methodology is applied to and evaluated using the admission and registration functions in Egyptian Universities. The research investigates the organizational requirements that are required to underpin these functions in Egyptian Universities. These requirements have been identified following an in-depth survey of the recruitment process in the Egyptian Universities. This survey employed a multi-part admission and registration DSS questionnaire (ARDSSQ) to identify the required data sources together with the likely users and their information needs. The questionnaire was sent to senior managers within the Egyptian Universities (both private and government) with responsibility for student recruitment, in particular admission and registration. Further, access to a large database has allowed the evaluation of the practical suitability of using a data warehouse structure and knowledge management tools within the decision making framework. 1600 students' records have been analyzed to explore the KDD process, and another 2000 records have been used to build and test the data mining techniques within the KDD process. Moreover, the research has analyzed the key characteristics of data warehouses and explored the advantages and disadvantages of such data structures. This evaluation has been used to build a data warehouse for the Egyptian Universities that handle their admission and registration related archival data. The decision makers' potential benefits of the data warehouse within the student recruitment process will be explored. The design of the proposed admission and registration DSS (ARDSS) will be developed and tested using Cool: Gen (5.0) CASE tools by Computer Associates (CA), connected to a MSSQL Server (6.5), in a Windows NT (4.0) environment. Crystal Reports (4.6) by Seagate will be used as a report generation tool. CLUST AN Graphics (5.0) by CLUST AN software will also be used as a clustering package. Finally, the contribution of this research is found in the following areas: A new DSS development methodology; The development and validation of a new research questionnaire (i.e. ARDSSQ); The development of the admission and registration data warehouse; The evaluation and use of cluster analysis proximities and techniques in the KDD process to find knowledge in the students' records; And the development of the ARDSS software that encompasses the advantages of the KDD and DW and submitting these advantages to the senior admission and registration managers in the Egyptian Universities. The ARDSS software could be adjusted for usage in different countries for the same purpose, it is also scalable to handle new decision situations and can be integrated with other systems.

Zugl.: Hamburg, Univ., Diss., 2007

Universiẗat, Diss.--St. Gallen, 2006.

Techn. Univ., Diss.--Braunschweig, 1999. / Literaturverz. S. [251] - 282.

Zugl.: Duisburg, Essen, Univ., Diss., 2007