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
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.