Identification and Ranking of Factors Influencing Innovation in Universities in the View of Faculty Members; Case Study: Amir Kabir University

The purpose of this study is to identify and rank the factors influencing innovation in Amirkabir University. The research method for practical and data collection purposes has been descriptive-correlational and structural equation modeling. The statistical population is all faculty members of Amir Kabir University in 22 colleges with 983 people. Using the Cochran sampling formula, a sample size of 276 people was selected by simple random sampling. Thirteen factors affecting innovation in higher education were identified by going through the history of researches and theoretical foundations in educational organizations (universities) and non-educational ones, namely leadership, knowledge management, human capital empowerment, university structure, university culture , mission and strategy, learner's organization, motivation, university environment, ICT, curriculum, communication and interactions and academic entrepreneurship. The factors were then categorized based on research literature into organizational, human and supra- organizational. To collect data, a 78-item researcher-made questionnaire was used. The Cronbach's alpha coefficient for the infrastructural factors of the tool was 82.3. To verify the validity of the questionnaire, confirmatory factor analysis was used. The results of this study showed that: 1) The overall model of research using confirmatory factor analysis was processed with ten factors of culture, structure, leadership, information and communication technology, knowledge management, individual skills, group skills, international relations, communication with other universities and communication with industry 2) All markers are significantly related to their underlying factors and the model of measurement is desirable during the evaluation of partial indices.3) Friedman test was used to rank the factors influencing innovation in higher education. The Chi-square statistic shows that there is a significant difference between the mean averages at 0.05 level.