جستجوی مقالات مرتبط با کلیدواژه « مراکز آموزش عالی » در نشریات گروه « مدیریت »

The purpose of this research is to identify, validate and rank the drivers of education to gain competitive advantage of higher education centers.

the combined research method is based on mixed exploratory research (text review - qualitative - validation - prioritization). In the qualitative section, the statistical population was faculty members and heads of higher education centers and experts in the field of educational management, in the accreditation section, faculty members and heads of higher education centers in Tehran, and in the prioritization section of higher and middle managers of higher education centers in Tehran. In the qualitative section, using the snowball sampling method until reaching theoretical saturation, an in-depth interview was conducted with 12 experts, in the validation section, with a targeted non-probability method, 20 experts were interviewed using a semi-structured and structured checklist in three rounds, a face survey. and in the prioritization section, 35 people were selected and answered the matrix questionnaire with the purposeful sampling method. In order to determine the validity and reliability in the qualitative stage, necessary checks including acceptability (expert review) and confirmability (re-review by experts), in the validation stage, review and review of the survey were used, and in the prioritization section, the content of the matrix questionnaire was The opinion of comprehensibility and expressiveness was confirmed by five academic and organizational experts and the rate of inconsistency of the criteria was calculated between 0.03 and 0.07. Qualitative data were analyzed with ground theory technique in Atlas software, validation data with Delphi technique in SPSS software, and prioritization data with Analytic Hierarchy Process (AHP) technique in Expert Choice software.

The results of the qualitative and validation section indicated that the paradigmatic model had 26 drivers, and the results of the prioritization section also indicated the greater importance of "outcome" and the "smart management and leadership" component.

Conclucion: 

Considering the important role that higher education centers play in society and are trying to solve part of the country's problems; it is very important to pay attention to the factors affecting the acquisition of competitive advantage. The results showed that the explanatory factors of competitiveness are among the current needs of higher education centers to gain competitive advantage and successful performance in scientific fields.

The aim of the study was to model the components of strategic intelligence with an emphasis on the role of job-creating skills in higher education centers (HEC). For this purpose, a mixed-method based on qualitative-quantitative studies was used. The statistical population in the qualitative part for conducting semi-structured interviews related to data theory including professors of Golestan universities, and in the quantitative part using a researcher-made questionnaire consisting of professors of Gorgan universities. Data analysis in the qualitative part used the grounded theory method based on Strauss-Corbin theory and in the quantitative part structural equation modeling and LISREL software was used. Based on qualitative findings, the most important organizational skills that create employment in the HEC of the province are communication, teamwork, information technology, management, problem-solving, planning, and learning. The results of the analysis using the structural equation model method showed that organizational skills and strategic intelligence have a positive-significant effect on employment in Gorgan HEC. Strategic intelligence can be divided into three main components: strategic management, intelligence related to other universities, and environmental intelligence. The validity of the questionnaire was confirmed by calculating the CVR index and Cronbach's alpha of all dimensions was above 0.7.

Higher education centers are the axis of the sustainable social, economic, political, cultural, and scientific development of human societies; as a result, their efficiency evaluation has attracted a lot of attention at the international level. Data envelopment analysis models (DEA) are one of the most successful, efficient and practical efficiency measurement techniques due to their special features and advantages. DEA models, in addition to measuring relative efficiency, are also able to provide the necessary planning to improve efficiency. Hence, so far, a lot of research has used DEA models to measure the efficiency of higher education centers. In this study, in order to measure the quality of performance of higher education centers, one of the DEA models called Input efficiency profiling model (IEP) has been used, as well. The proposed model is a new evaluation model called Improved input efficiency profiling – Super efficiency model (IIEP – SE), which has improved the performance of IEP model by addressing some of its shortcomings. It has been shown by a numerical example and comparing the proposed model with other DEA models that the proposed model has necessary reliability and desirable performance. In order to plan for achieving the efficiency of the inefficient units, pattern and reference units and the amount of necessary change in the input and output criteria for each of the inefficient units have also been determined.

This study aims to provide a learning organization SEM and the application of done at Tehran University. The research method is descriptive-correlational and analytical method was SEM. The population was University of Tehran staffs on the number of 2730 people. Sample size by using Cochran sampling formula and simple random sampling, were selected 243 people. To collect data, a questionnaire based on the model of Peter Senge (1990) designed by reliability (94/0 = α). Also evaluated and approved content and construct validity. For data analysis, Kolmogorov-Smirnov structural equation modeling, and one-sample t-test, was used. The results showed that the learning organization model has been fitted to the data. Accordingly, the individual features of the paradigm (γ =0/24) and systematic approach (γ =0/52) been effective. Systematic approach to the common cause (β=0/51) and collective learning (β=0/44) and shared vision have also had an impact on collective learning (β=0/17) has had impact. Finally, mental models based on shared vision and collective learning as well as individual features common cause whatsoever. The results showed that the application of learning organization and all aspects of its application in the target population, below the average and only mental patterns was middle.

This study aimed to test the conceptual model for predicting the for human resource productivity of higher education based on the variables of effective leadership and strategic planning. The research community samples were universities of western Azerbaijan faculty members consisted of 310 people randomly stratified (112 from state universities, 114 from Islamic Azad Medical, 84 from medical sciences univrsities). The research method was descriptive and multivariate with three effective leadership tools Saatchi and colleagues, strategic planning based on University of New Jersey model and Shah & Schaniz models (2008), and Human Resources Productivity Questionnaire based on the Acheive Model by Hers And Goldsmith that the content validity (construction) and content reliability (Cronbach's alpha) were reported suitable. Analysis was done using AMOS software and structural equation model. Results have shown meaningful positive relationship between effective leadership and strategic planning with the scientific Human Resources Productivity.Additionally, effective leadership has the most direct positive impact on strategic planning and improving the Human Resources Productivity of scientific research and strategic planning is less effective on improving the Productivity.

Cloud computing is a new technology that considerably helps Higher Education Institutions (HEIs) to develop and create competitive advantage with inherent characteristics such as flexibility, scalability, accessibility, reliability, fault tolerant and economic efficiency. Due to the numerous advantages of cloud computing, and in order to take advantage of cloud computing infrastructure, services of universities and HEIs need to migrate to the cloud. However, this transition involves many challenges, one of which is lack or shortage of appropriate architecture for migration to the technology. Using a reliable architecture for migration ensures managers to mitigate risks in the cloud computing technology. Therefore, organizations always search for suitable cloud computing architecture. In previous studies, these important features have received less attention and have not been achieved in a comprehensive way. The aim of this study is to use a meta-synthesis method for the first time to analyze the previously published studies and to suggest appropriate hybrid cloud migration architecture (IUHEC). We reviewed many papers from relevant journals and conference proceedings. The concepts extracted from these papers are classified to related categories and sub-categories. Then, we developed our proposed hybrid architecture based on these concepts and categories. The proposed architecture was validated by a panel of experts and Lawshe’s model was used to determine the content validity. Due to its innovative yet user-friendly nature, comprehensiveness, and high security, this architecture can help HEIs have an effective migration to cloud computing environment.

The earthquake and its hazards and vulnerability are the main concerns addressed by the discussions on crisis management. The higher education institutes are considered the important organizations which provide essential human resources, scientific and historical equipment. This study offers a model of risk analysis, using PSHA method in combination with FMEA. The results show that the faculty of Civil engineering enjoys an acceptable risk structure in earthquake on 9 Richter scale but has an unacceptable risk but bearable structure in 8 Richter scale. It is unbearable in earthquake on 7 Richter scale. Given the structure of the building, which is resistant against the earthquake, one needs to reconsider the application and use of the building?