An Integrated Decision-Making Model For Analyzing Key Performance Indicators In University Performance Management

University performance has an important effect on the social influence of universities. With increasing emphasis placed on higher education, it is important to improve and optimize university performance management. However, the performance of university management is affected by numerous indicators in practice, and it is difficult for administrators to optimize all of them because of resource restriction. To address this concern, in this paper, we design a novel integrated model by combining linguistic hesitant fuzzy sets (LHFSs) with the decision-making trial and evaluation laboratory (DEMATEL) method to identify key performance indicators (KPIs) for improving the level of university performance management. Specifically, the LHFSs are utilized to express the hesitant and vague interrelationship assessment of performance indicators provided by experts. A modified DEMATEL is adopted to visualize the causal relationship between performance indicators and determine critical ones. Moreover, we introduce a gray relation analysis (GRA)-based method to derive experts' weights when their weight information is unknown. Finally, a comprehensive university in Shanghai, China, is employed as an example to illustrate the practicability and availability of the proposed linguistic hesitant fuzzy DEMATEL model.