As investment in the universities will effect the investment on human resources, and human capital usually effect on economic growth, So investigating the higher education expenditures and estimating cost functions helps development planners for analyzing the average of quantity growth and human capital improvement and also it can help optimal distribution of " Expenditure and Investment Credit " in the universities.The main goal in this research is investigating and analyzing the different kind of expenditures and estimating the cost function of higher education in Iran. Hence we use expenditure credit and the number of students in non-medical universities (year: 1388) using statistical and econometrics methods and cross section data for estimating cub-douglus and teranslog cost functions.The results show return on scale in these universities. It means that increasing the number of students decrease unit production cost. The second result is about the shape of cost function. It clearly shows cost function of higher education in non-medical universities has a common shape as a quadratic function. Also we have estimated different unit cost for different universities in different level (e.q B.sc M.sc and phD. Students). this is because of oldness, structional factors, the combination of human force or physical condition.

Regarding the fact that getting a suitable combination of the human resources and service stations is one of the important issues in the most service and manufacturing environments, In this paper, we have studied the two models of planning queuing systems and its effect on the cost of the each system by using two fuzzy queuing models of M/M/1 and M/E2/1. In the first section, we have compared two different fuzzy queuing models based on the costs of each model and fuzzy ranking methods are used to select optimal model due to the resulted complexity. This paper results in a new approach for comparing different queuing models in the fuzzy environment (regarding the obtained data from the real conditions) that it can be more effective than deterministic queuing models. Also a sensitivity analysis is carried out to help the decision maker in selecting the optimal model.

This paper aims to explore effect of supply chain members’ costs change on participants of the network. On one perspective, it explores when there is a cost change to a firm, how other firms are affected and who bear(s) the most effect. On the other perspective, it investigates how an individual firm’ s performance is affected by the other members in its network and whose cost change would impose a most significant effect on its profit.

In this study, a comprehensive meta-analysis was conducted using a random-effects model to examine the relationship between money supply and inflation and to address inconsistencies in previous research. The overall effect of money supply on inflation was estimated at 0/578, providing a broad measure of its impact. However, an assessment using a funnel plot and Egger's test revealed publication bias. To correct for this bias, the "trim and fill" method was applied, reducing the adjusted overall effect to 0/475. Additionally, meta-regression and subgroup analyses were performed to investigate moderating variables. The results showed that the effect of money supply on inflation differs across fixed and floating exchange rate regimes, time periods before and after 2000, and between static and dynamic models. These findings contribute to a clearer understanding of the impact of monetary and economic policies on inflation and provide a foundation for future research.