جواد نیک نفس

The present study aims to design and explain a university autonomy-oriented organization model using a mixed approach. In the qualitative section of the research, the statistical population consisted of scientific and organizational experts from Payam Noor University. So, 16 experts were selected for interviews using targeted snowball sampling. Moreover, in the quantitative section of the study, 245 people were selected out of 675 professors and staff, who formed the statistical population based on the sample size determined by Krejcie and Morgan table using random sampling. This study made use of semi-structured interviews and a researcher-made questionnaire as instruments of data collection in qualitative and quantitative sections, respectively. The qualitative data were analyzed through the thematic analysis technique using Maxqda10 software, while the quantitative data were analyzed using PLS3. Content and face validity were assessed, as well as the intercoder reliability. The results identified a total of 4 dimensions and 8 components for a university autonomy-oriented organization. The identified dimensions include organizational autonomy, personnel autonomy, financial autonomy, and academic autonomy. Also, the components consisting of supportive policy, clear policy perspective, organizational values, success trend analysis, financing, financial management, organizational communications, and sustainable thinking were approved by the software.

Purpose: The main purpose of this research was to identify the challenges of implementing participatory governance in the Ministry of Health, Treatment and Medical Education of the country. Methodology: This study was a mixed research. The statistical population in the qualitative section included the faculty members and experts in the field of public administration, professors familiar with the subject of the research and managers with experience in the Ministry of Health, Treatment and Medical Education of the country, who were selected as 12 subjects using the snowball method. The statistical population in the quantitative section also included managers, deputies and experts of the Ministry of Health, Treatment and Medical Sciences of the country. The research tool in the qualitative part was a semi-structured interview, and in the quantitative part, it was a researcher made questionnaire. Theme analysis was used to analyze the information in the qualitative part and the AHP method was used to prioritize the factors. Findings: The results indicated that; infrastructures, bureaucratic factors, environmental obstacles, weakness in policy making, public accountability, communication, joint commitment, trust building, obstacles related to executives and common destiny are the main challenges in the implementation of participatory governance in the Ministry of Health, Treatment and Medical Education of the country. Conclusion: A total of 10 main themes and 59 sub-themes were identified.

Network data envelopment analysis models assess efficiency of decision-making unit and its sections using historical data but fail to measure efficiency of its units and their internal stages in the future. In this paper we aim to measure efficiency of stages of bank branches and obtain efficiency trend of stages during the time, then to estimate their efficiency in the future therefore we can be aware of stages inefficiency before occurrence and prevent them. First, a two-stage structure including deposit collection and loan giving was designed for bank branches using literature review and comments of experts. Human forces and fixed assets were considered as input variables of the first stage, deposit as mediator variable, delayed claims as interim variable, and loan amount as output variable of the second stage. Then, a dynamic network data envelopment analysis model was formulated and stages efficiency were obtained for 16 consecutive periods. Therefore, efficiency trend of stages was obtained during the time. In the following, efficiency of various stages of branches were estimated using artificial neural network and some recommendations are provided according to obtained amounts in order to prevent inefficiency before occurrence.