Requirements analysis of an intelligent decision support system using an improved iterative non-linear process model to help performance evaluation of the research institutes

Performance evaluation is a semi-structured issue; therefore, an intelligent decision support system can help decision makers in the Ministry of Science, Research and Technology, as well as, managers of the research institutes to better evaluate the performance, by providing the required knowledge and appropriate evaluation models. Conducting a requirements analysis process in the early stages of the development of a decision support system can guarantee the better performance of this system. The existing information system for evaluating the performance of research institutes affiliated to the Ministry of Science, Research and Technology does not allow for a proper decision on the evaluation and prediction of the performance of these institutes. Although iterative non-linear process model is suitable for analysing the requirements of an information system, it does not consider any risk assessment. In this research, an adjusted iterative non-linear process model was proposed for requirements analysis and risk assessment. To validate this process model, it was implemented through consensus methods such as Delphi and Brainstorming for requirements analysis and risk assessment of an intelligent decision support system suitable for performance evaluation. The calculation of means and standard deviations of successive rounds of Delphi showed that different stakeholders reached a consensus on the main functional and non-functional requirements of the intelligent decision support system. In addition, the risks of the new system were identified.