درخت حوزه‌های تخصصی

Purpose: The purpose of this study was to identify early growth indices of general managers in order to present the growth pattern of general managers of Iranian provinces in the academic year of 2017-2018. Methodology: To this end, the qualitative research approach and data arising theory (systematic design) have been the criterion for action in this study. The statistical population consisted of all heads of education provinces of Iran. Purposive sampling continued until the researcher saturated theoretically using a semi-structured interview with 14 sample members. Findings: The results showed 16 main categories that were modeled as a paradigm model including: causal conditions (organizational factors; extra-organizational factors; individual traits), focal categories (leadership and management traits; individual traits), growth strategies (extras organizational factors, organizational factors; Individual factors), contextual factors (social factors, economic issues, cultural issues), intervening factors (organizational factors; individual factors) and outcomes (community; organizational factors; individual factors), using the results of theoretical and background studies Research and analysis of the content of interviews conducted, early indicators of modality development The whole thigh has been identified and included in three stages of open coding, axial coding, and selective coding of general manager maturity model in five main categories of causal conditions, pivotal phenomenon (general manager maturity model), general manager maturity strategies, intermediary conditions, and managerial maturity outcomes. Conclusion: The professional development of principals leads to the implications that at the community level in the form of education and training of students, the formation of interaction with education and personal growth, growth, performance, communication, thinking and management and decision making, decision making. Finds and manages.

Purpose: The main purpose of this study was to identify the components of SMEs' knowledge rewards, and based on other components, learning and development strategies were developed based on the obtained components. Methodology: The present study was a descriptive survey in terms of purpose and method of data gathering and was mixed in terms of research method. Therefore, in the qualitative part, using semi-structured interviewing tool with 15 human resources experts and stakeholders Interviews were conducted and the data were analyzed using qualitative content analysis and a model was designed by combining them. Then, the model was tested by a researcher-made questionnaire and sample of 162 SMEs in Tehran, using quantitative structural equation research method with LISREL software and then to formulate strategies and strategies related to learning and learning. The paired t-test and SPSS software were used for development. Reliability of qualitative part of Holstein method was 0.83% and Cronbach's alpha coefficient was 0.81. Findings: The findings showed that 22 sub-components of comprehensive reward factors were identified, all of which had appropriate factor loadings and the model was confirmed. Among the non-material dimensions of learning and development, it was the most important factor and in explaining learning and development strategies, the highest gap was observed in education, which was the first and foremost strategies in this field. Conclusion: The findings of the study confirm the relationship of each of the material and non-material components to the concept of comprehensive reward, but the most important is the importance of the material components to the comprehensive reward. In the payment component, cash awards and in benefits, the benefits of flexibility had the highest impact, but among the non-material components that were secondary to the overall reward, the highest impact was on the learning and development component, which included performance evaluation. It matters the most. Non-material factors were expected to be of high priority for knowledge workers, but this was not favorable to the statistical population.