درخت حوزه‌های تخصصی

This paper focuses on the role of influencers as an element of modern governance. As the fields of media, entertainment industry, and politics become increasingly interconnected, the phenomenon of influencer potentially affects many aspects of political life, such as campaigning and voting, policymaking, and international affairs. Using the network analysis method and applying a triple typification of influencers consists of media influencers, influencer politicians in power, and influencer opposition politicians out of power, and selecting 245 nodes on Instagram accounts, the article focuses on how do influencers interact within communication networks? Based on the triple typification, the article tries to find the pattern of networked political communications between influencers in the social network. The results prove that all three types of influencers are more interested in intra-group communication. However, both influencer politicians in power and influencer opposition politicians out of power have relatively similar tendencies to associate with media influencers.

Purpose: Considering the role of leadership in achieving the education missions, present research done with the aim of designing a suitable leadership model to achieve new missions of higher education. Methodology: This study in terms of purpose was applied and in terms of implementation was exploratory combined (qualitative and quantitative). The research population in the qualitative part was the higher education experts and in the quantitative part were the personnel of Islamic Azad University of Tehran province in 2018-19 academic years. The research sample in the qualitative part according to the theoretical saturation principle were estimated 13 people who were selected by purposive sampling method and in the quantitative part according to Cochran’s formula were estimated 385 people who were selected by cluster random sampling method with respect to classes (number of staff in universal branches). To collected data in the qualitative part used from interview and in the quantitative part used from researcher-made questionnaire (51 items) which the its content validity was confirmed by experts and its convergent validity by average variance extracted indicator was confirmed and its reliability was obtained by Cronbach’s alpha method 0.84. To analyze data were used from methods of open, axial and selective coding and exploratory factor analysis in SPSS-22 software. Findings: The findings of the qualitative part showed that suitable leadership had 79 concepts, 63 categories and 7 dimensions and new missions of higher education dad 20 concepts, 15 categories and 3 dimensions. The findings of the quantitative part showed that the suitable leadership model to achieve new missions of higher education had 51 indicators or items and 15 components. Also, a suitable leadership model to achieve new missions of higher education was designed and approved by experts. Conclusion: Based on the findings of the present study, higher education specialists and planners can design and implement programs to realization the new missions of higher education.

Purpose: The purpose of this study was to present a comprehensive model of empowerment in the Social Security Organization. Methodology: This research was based on the applied purpose and in terms of quantitative and qualitative research method (mixed) and in terms of data collection was descriptive-survey. The statistical population of the study consisted of two groups of experts and thinkers. The first group consisted of university professors whose field of study and field of study was related to the field of research and the second group included organizational experts with a master's degree or higher with managerial and experimental backgrounds related to human resources in the qualitative section after counting the criteria and indicators extracted. From the theoretical foundations, a researcher-made questionnaire based on the Looshe and Likert spectrum was prepared and after passing the Delphi survey, a conceptual model was extracted. Then, in the quantitative part, exploratory factor analysis method was used to identify the model factors and confirmatory factor analysis method was used to fit the model. In order to check the validity of the questions, purposive sampling method was used among organizational and academic experts, of which 15 people were included as a statistical sample. In the second and third stages of validity of the questions, to strengthen the screening process, the snowball method was used to compile the sample, which after saturating the data of 32 final experts for the exploration section and building a conceptual model participated. Statistical analysis was performed using SPSS software to cluster the indicators and create research components and Smart PLS software to confirm the research model. Findings: The results of this study identified 11 components and 37 indicators as the most important factors of comprehensive empowerment and showed that individuals will be empowered individually when intra-individual intelligence, creativity-oriented education, psychological self-knowledge, internal performance, knowledge-based decision making and individual self-efficacy. Together, they will be empowered in the collective, team, and organizational spheres when the culture of bureaucracy, internal reward, fundamental self-efficacy, and interactive policy come together. Conclusion: After exploratory factor analysis and component classification, the fit of the model obtained from the previous step was investigated and confirmed with a good fit.

This study explores the perceptions of Iranian MBA graduates regarding the integration of AI into business education. Drawing on survey data from 379 alumni across a range of Iranian universities, the research assesses five core dimensions: perceived usefulness of AI, ethical concerns, faculty preparedness, job market implications, and interest in AI-focused coursework. The study also investigates whether demographic factors such as age, gender, income level, and marital status significantly influence these perceptions. Results indicate a generally favorable view of AI integration, with particularly strong support for incorporating AI coursework into MBA programs. Despite broad enthusiasm, respondents expressed concerns about data privacy, algorithmic bias, and the limited readiness of faculty to teach AI-related content. Inferential tests and path analysis reveal that demographic variables had little predictive power over AI perceptions or preferences, suggesting widespread acceptance across social strata. The findings underscore both the readiness of Iranian MBA graduates for AI-related curricular reform and the need for targeted institutional responses, including faculty development and ethical frameworks.