Development and Evaluation of a Decision Model for DBMS Selection to Support Enterprise Information Portal (EIP)

• 第一著者: Ahmad Fadli, Saad
• フォーマット: 学位論文
• 言語: English; English
• 出版事項: 2006
• 主題: QA71-90 Instruments and machines
• オンライン･アクセス: http://etd.uum.edu.my/1796/1/Ahmad_Fadli_bin_Saad-_Development_and_evaluation_of_a_decision_model_for_DBMS_selection_to_support_Enterprise_Information_Portal_%28EIP%29.pdf; http://etd.uum.edu.my/1796/2/Ahmad_Fadli_bin_Saad-_Development_and_evaluation_of_a_decision_model_for_DBMS_selection_to_support_Enterprise_Information_Portal_%28EIP%29-1-1.pdf; http://etd.uum.edu.my/1796/

The past decade has seen an extraordinary increase in the availability and use of DBMS in organizations. Today, DBMS also plays an important role to support Enterprise Information Portal (EIP) applications. However, a task for evaluation and selection from several candidates of DBMS tend to be very complex and difficult since both qualitative and quantitative issues need to be considered. Furthermore, the selection of DBMS must be based on expert perception of the organization. Wrong choice or improper selection of DBMS will negatively affect the implementation of EIP in the organization. This thesis presents the combination of Delphi technique and the Analytical Hierarchy Process (AHP), for selecting appropriate DBMS to support EIP application. The Delphi method has been applied to determine the selection criteria and sub criteria of DBMS for ElP from experts' perceptions. The AHP is proposed to develop and to evaluate the decision model of DBMS selection. It is seen as an effective approach in dealing with DBMS selection decision problems. This method adopts a multi-criteria approach that can be used for analysis and comparison of several aspects within DBMS. Two DBMS products namely ORACLE and SYBASE are examined for the study. The results of this research will be useful to organizations because it provides information and guideline regarding the importance of criteria and the sub-criteria and thus may help organizations to choose appropriate DBMS to match their needs.