javad khalili

Since each person has unique characteristics, his learning needs are also different. The first and most essential step in education is examining educational needs. This study aimed to determine the educational needs of operating room technologists in selected hospitals in Isfahan and related factors in the year 2021.

The data collection tool in this descriptive and analytical study was a questionnaire that included four areas of general and specialized knowledge, management of the surgical field, job motivation, and the need to hold comprehensive training courses for operating room technologists. These questionnaires were given to 50 operating room technologists, who were included in the study through convenient sampling, in the operating room where they worked. The collected data were analyzed using descriptive(mean and frequency) and analytical (Spearman and Chi-square) statistical tests using SPSS software version 16.

40 people completed the entire questionnaire. The average scores of needs assessment in the fields of general and specialized knowledge, management of the surgical field, and the need and interest in improving the level of knowledge, as well as the necessity of holding comprehensive specialized training and consulting courses for operating room technologists, respectively, are equivalent to 44.37±6.75(upper average need), 28.50±6.76(average need) and 9.72±1.93(upper average need). The average score of job motivation was also 17.60±2.55 (average upward motivation).

The average score of operating room technologists' need for training and elevation was higher in the field of general and specialized knowledge, and in this field, the need for training in ergonomics and anatomy is more than in other topics, and it is suggested to implement helpful training courses in these topics and following the field of operating room technology. Also, the results of examining their job motivation showed their relatively favorable motivation to perform assigned tasks, and they considered low salaries and long working times as factors that reduce their job motivation.

Improving efficiency is one of the most important indicators to evaluate the Organization performance and the most basic and the first step to improve efficiency is measure and evaluate it. So far, little researches has been conducted on the hospitals performance evaluation using the combined of balanced scorecard (BSC) and data envelopment analysis (DEA). But in the researches has found by the researcher; 1. Simple performance of units has calculated using DEA classic models, which have two limitations: a) self-evaluation; and b) a lack of recognition between efficient DMUs; The new VFB-DEA cross efficiency model used in this research eliminates these limitations and makes the evaluation results more reasonable. 2. Conditions of uncertainty are not considered if some performance indicators require human judgment, to overcome this problem, the development of the VFB-DEA cross efficiency   model in fuzzy environment is done by the researchers. This research attempts by using fuzzy data envelopment analysis (FDEA) and BSC to evaluate the public hospitals performance in Mashhad during 2014. In this regard, the indicators used to evaluate the performance of health care in situations in past studies and with health experts, three indicators of Staff satisfaction, capita Education and the cost of medicine and supplies, and three indicators of patient satisfaction and the average length of stay and percentage of bed occupancy, in four perspectives of the balanced scorecards elected as input indicators and output indicators. Then, using a new model VFB-DEA in fuzzy environment, mentioned units were evaluated. The results show in the VFB-DEA model thehospital2is ranked first and the hospital 1 and 6 are the most inefficient hospitals. Given the uncertainty and determination of input and output indicators based on a balanced scorecard, the proposed model is more accurate than the past models and enables managers to make better and more accurate decisions to improve the efficiency of organizations.

The main purpose of this study is performance evaluationof the distribution of petroleum products in a green supply multi-criteria supply chain in the Grey environment. This is a case study of Fars National Iranian Oil Product Distribution Company. Under uncertainty conditions and with green evaluation perspectives, the Grey DEMATEL method is first used to study the causal relationships among the perspectives of the improved balanced scorecards and their effectiveness and weight. Then, by using the analytic network process method, the importance of the sub-criteria is determined. Also, the Grey VIKOR is used to evaluate and rank the products of Fars National Iranian Oil Product Distribution Company. With regard to the purpose of the study and the corresponding perspectives, petrol is ranked in the first place and kerosene stands in last place. The results of the study can help the managers of FNIOPDC and other organizations to improve their ability, reduce their weaknesses, and enhance their performance.

Efficiency is regarded as an important factor for both managers in different companies and organizations and customers who are interested in using the services related to these companies and organizations. However, the biggest challenges managers are coping with include an increase in the competition between companies and manufacturing centers, an increase in the efficiency of production, and finding suitable suppliers. The present study aimed to investigate the efficiency of green supply chain (GSC) by using Malmquist productivity index (MPI) based on the input and output indicators of the BSC model and accordingly providing some rules using the decision tree. To this aim, the efficiency of 15 automotive parts manufacturer firms in Iran was evaluated in the state of constant returns to scale during 2013-2016. Then, the obtained results were used as the class label of Decision Making Units (DMUs) which are regarded as the inputs of decision tree method. Finally, the implicit rules in the data were extracted by using the decision tree. The results indicated that the proposed model had a high degree of accuracy and interpretation in evaluating performance compared to previous models and helps managers to make better decisions to increase the efficiency.