Presenting a hybrid model for evaluation of the quality impacts of IT services and organizational innovation on the satisfaction of users based on the analytic network process method

The main purpose of this article is to determine the best plan for improving the current situation of the University of Applied Sciences. The type of goal is applied in this research and combined or qualitative-quantitative methods have been used to achieve this goal. For this purpose, a hybrid model has been designed in which the impact of the quality of information technology services and innovation of the organizational staff of the University of Applied Sciences is examined and evaluated based on user satisfaction. The target population in this study is all staff and students of the University of Applied Sciences and Klein theory and Cochran's formula have been used to determine the appropriate statistical sample in this study. In this study, questionnaires based on field research, expert opinion, and SERVQUAL model were designed to assess the quality of services according to the dimensions of organizational culture, the belief of senior managers, organizational structure, tangible service quality, service reliability, and accountability of officials. The validity of the questionnaires was assessed by the Lavache method and their reliability was assessed based on Cronbach's alpha (0.964). These questionnaires were collected based on the statistical sample and the collected answers were evaluated using SPSS software. Then, using the Pearson hypothesis test, the correlation of research variables was examined and it was found that the most important hypothesis in the quality of IT services is related to the beliefs of senior managers and in the innovation of organizational staff is related to service reliability. Then, the priority of the proposed projects to improve the quality of university services based on the opinions of experts, using the analytic network process (ANP) and the criteria mentioned in the Super Decisions software was examined. Finally, the design evaluation supermatrix was calculated and the best plan was determined.