Purpose: This research has been designed to identify the effective components of the internationalization of the entrepreneurial university that contribute to the creation of knowledge-based Economics. Methodology: The research method was a blended method and the statistical population included experts and experts in the field of growth centers in Islamic Azad universities in Fars province. In the qualitative section of 11 people in the interview process and in the quantitative section with a population of 976 people, 277 people participated as an example in this study. The data gathering tool was an interview and a researcher-made questionnaire. After validation, its reliability was 0. 83. Descriptive statistics were used to analyze the data and exploratory and confirmatory factor analysis was used in the inferential part. Findings: The results of the research of findings showed that the continuous validation components of the university in order to achieve international standards, conduct innovations and international initiatives on campus, the relationship of faculty members with foreign graduates with the highest factor load (0. 88) And the component of the application of the system of international education in the university with the least factor load (0. 63) of the total variance explained, and other components were important in the following order respectively. Discussion: The coefficient of the effect of components in the internationalization of the entrepreneurial university in creating a knowledge-based economy alone is the highest coefficient of influence on the continuous validation component of the university in order to achieve international standards, carry out innovations and international initiatives on campus, the relationship of faculty members with Foreign graduates with 0. 88 and the least in the component of using the distance education system at university.

Purpose: The purpose of research is to observe the influence of public trust on accepting KBOs. The implementation method of the research is descriptive (non-experimental) and with correlation analysis model formed by structural equations used the least minor squares. Methodology: The participants of the survey were consumers of KBO services. According to Cochran formula for unspecified society, 384 individuals were chosen as statistical sample selected totally random. From 384 questionnaires distributed, 370 were answered and 14 others were discarded due to many unanswered questions. In due course 370 questionnaires were processed. To measure social trust, Safarinia and Sharif questionnaires were used. (1389). due to receptivity of KnowledgeBased organizations, researcher-made questionnaire were utilized. this questionnaire contains 5 elements which composed based on available questionnaire. We realized there is a meaningful and significant relation between KBO admission and all aspects of social trust. the influence of social trust on KBO’ S admission was positive and meaningful. The influence of social trust on KBO’ s admission is positive and meaningful. Findings: According to the results, 72% Variance model in KnowledgeBased organizations admission were indicated by Research model. Therefore, we realized strengthening social trust will bring acceptance to KBO’ s presence. Discussion: In this regard, managers and officials in KBOs must concentrate on gaining and obtaining social trust in case of adequate social acceptance.

Purpose: Considering the quantitative growth of university growth and technology centers in the country and the need for solutions to facilitate the success of these companies in global competition, this study identifies the indicators of innovation ecosystem of university growth and technology centers with the knowledge-based economy approach with data foundation approach. Methodology: This research was based on empirical philosophy and has been done with a deductive-inductive approach. From the perspective of the goal, it was a fundamental research that has been done with a mixed research method. The study population of this study includes entrepreneurship professors and managers who have work experience in knowledge-based companies. Sampling was done by non-probabilistic and purposeful sampling method. Data collection tools are interviews and questionnaires. In the analysis of the interviews, the data theory of the foundation (selective, open and pivotal) was used. Also, the identified indicators have been validated by fuzzy Delphi method. Finally, the final model of the research is presented. Research data analysis was performed in the qualitative phase with MAXQDA software and in the quantitative phase with Matlab software. Findings: To achieve the objectives of the research, by analyzing interviews with experts, a set of practical indicators of the innovation ecosystem were identified. In the open coding stage, 517 codes were identified, which with the observed observations, 9 main categories and 41 sub-categories were obtained. Conclusion: Based on the achievements of this study, issues such as organizational management, growth center rules and regulations, innovation ecosystem infrastructure, knowledge ecosystem, innovation ecosystem, ecosystem capital, economic ecosystem, innovation ecosystem challenges and key players are key elements in the success of these universities in KnowledgeBased economy was considered. These cases also interact with each other in 41 minor areas.