A Rough Hybrid Multicriteria Decision-Making Model for Improving the Quality of a Research Information System

Abstract

Improving the quality of research information systems is an important goal in the process of improving the performance of research management in Chinese universities. Since the evaluation of information system (IS) quality is a multicriteria decision problem, it is critical to identify the interrelationships among the dimensions and criteria, and decide on the important criteria for proposed improvement strategies. This paper suggests a hybrid multicriteria decision-making (MCDM) model for improving the quality of a research information system. First, a rough method combined with the decision-making trial and evaluation laboratory and analytical network process (rough DANP) model is used to improve the objectivity of expert judgements. Additionally, the rough DANP can be used to construct an influential network relationship map (INRM) between research information system components to derive the criterion weights. The complex proportional assessment of alternatives with rough numbers (COPRAS-R) is applied to evaluate the performance of the research information system. A Chinese university research information system is chosen to illustrate the usefulness of the proposed model. The results show that efficiency, effectiveness, and user frequency have the highest priorities for improvement. Selected management implications based on the actual case study are supplied.