Research On University Finance Online Reimbursement System Using Willingness Based On SOM Neural Network Clustering And UTAUT Model

With the continuous development of China’s higher education,the scale of state investment in higher education is also expanding.As the main administrative department of funds,the financial department of universities has increased its business affairs year by year.The problem of the inefficiency of the traditional queuing reimbursement model has become growing problems.The phenomenon of "often queuing and lining up" for college faculty and staff who handle financial reimbursement has gradually become Normally,this not only wastes a lot of time and energy of universities’ teachers who undertake teaching and research tasks,but also creates various contradictions due to chaotic queues and overcrowding,which reduces the level of financial services.In recent years,the financial online reimbursement system innovatively adopts the O2O(online and offline)model of "inputting information online and submitting reimbursement offline." It completely solves the problems caused by the traditional queued reimbursement model.This article first sorts out the theory and models in the field of technology acceptance,selects the UTAUT model with high explanatory power as the theoretical basis,and uses the SOM neural network clustering method to perform cluster analysis on the data of the financial online reimbursement system.It is found that users can be divided into 4 types,the characteristics of these 4 types of users are extracted as the control variables of the research model for further research.Then according to the actual situation of the research object and the actual characteristics of the universities’ teachers group,delete the "social impact" variable,add the "perceived cost" variable,"perceived security" variable,"system reliability" variable and build a model of the influence factors of college teachers and staff’s willingness to use the online financial reimbursement system.Based on this model,11 research hypotheses are proposed.Next,based on the relevant maturity scales used in the UTAUT model at home and abroad,a questionnaire for this study was designed and distributed and recovered through network.Finally,an empirical analysis is performed on the collected data to verify whether the proposed hypothesis is valid and analyze the results of the data analysis,and to propose the influencing factors and countermeasures for the promotion of the online reimbursement system in universities.