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Iran's economy is founded on three main sectors: cooperative, private, and governmental. Various key documents outline objectives for each sector, highlighting certain industries with unique advantages and capacities. These industries not only have strong interconnections with other sectors but also drive demand and contribute to economic growth. This study aims to analyze and present various potential futures for Iran's economy, adopting a holistic and comprehensive perspective. It explores the key factors shaping the economy, including constructive economic drivers, significant uncertainties, and potential future scenarios, considering various influential dimensions. The research employs a qualitative scenario-based approach, structured in eight stages. Data is gathered through interviews, expert panels, and the Delphi survey method, with analysis supported by Mac and Scenario software and a wizard tool. The study identifies primary economic drivers for Iran, including economic growth, oil dependency, the impact of economic sanctions, fundamental challenges, and the level of economic openness. While other factors like high unemployment, a small capital market, rent-seeking, weak infrastructure, and corruption significantly influence the economic landscape, they are not classified as primary drivers in this study. However, these elements will be considered in developing future economic scenarios. Also, in order to prioritize solutions to deal with economic threats, it should be said that using short-term methods in the programs and executive plans of the country's institutions will be the first step to deal with threats. At the same time, planning and using solutions of higher levels, respectively, can move the country step by step in terms of structure and institutions in the direction of resilience, invulnerability and regeneration. [ABSTRACT FROM AUTHOR]

Downscaling and simulating various meteorological variables at different time scales are fundamental topics for making climate change studies in a geographic region. Here, a new approach for downscaling the mean daily temperature was implemented using a vine copula‐based approach and considering the best CanESM2 predictors. The accuracy of the copula‐based approach was compared with genetic programming (GP), optimized support vector regression (OSVR), support vector machine (SVM), adaptive neuro‐fuzzy inference system (ANFIS) and artificial neural network (ANN) models at Birjand synoptic station in Iran. In the proposed approach, after examining the different vine copulas, the D‐vine copula was selected as the best copula according to the evaluation statistics and tree sequences. According to the root‐mean‐square error (RMSE) and Nash–Sutcliff efficiency (NSE), the accuracy of the ANN model in downscaling the mean daily temperature data was not acceptable and the other considered models were slightly overestimated. The results indicated that the copula‐based approach outperformed the other models in downscaling the mean daily temperature with NSE = 0.61. However, given the 99% confidence interval of the simulations, a slightly overestimation at temperatures above 20°C was observed for the copula‐based approach, which has better performance than the other considered models. The copula‐based approach was able to reduce RMSE by about 82, 20, 24, 47 and 34% compared to ANN, OSVR, GP, SVM and ANFIS models, respectively. The results also showed that the performance of the support vector regression model optimized by the ant colony algorithm is also acceptable and is in the second rank after the copula‐based approach. The accuracy of the copula‐based approach was also confirmed according to Taylor diagram and violin plot. The proposed approach has a higher accuracy than data‐driven models due to use of the conditional density of vine copulas, and the joint distribution of the mean daily temperature and selected predictors. [ABSTRACT FROM AUTHOR]

In this study, the frequency analysis of river flow deficiency (FD) of the Siminehrood River in the south of Lake Urmia located in northwest Iran was investigated with regard to rainfall deficiency (RD) during the period of 1992–2013 using copula functions. The main purpose of this study is to provide a comprehensive method for bivariate simulation and forecasting based on marginal distribution and joint behavior of the studied series. For this purpose, the FD and RD values were extracted using the deficiency value method. By preparing deficiency values, 57 different distribution functions were fitted to the studied values, and the generalized extreme value (GEV) distribution was selected as the best marginal distribution function based on the evaluation criteria. Before fitting the copula function, the correlation between the RD and FD values was examined using Kendall's tau, and a correlation of 70% was obtained. After selecting the marginal distribution function and examining the correlation, the goodness of fit of seven different copula functions was examined for frequency analysis of RD and FD values in the Siminehrood River at the Dashband station. The results indicated that the Clayton copula had the best performance for creating a joint distribution of RD and FD values. It was also determined from the joint analysis of deficiency values that the FD values can be estimated with high accuracy for RD values of more than 0.68 mm. Also, the results indicated that if rainfall in the study area were less than long-term mean for 10-day and 60-day durations, with different return periods and probabilities, different conditions will occur for FD values, which can be used as typical curves for water resources management and allocation in the basin. Finally, the accuracy of the copula-based model and its conditional density in the two phases of simulation and forecasting were investigated. The accuracy of the copula-based model and its conditional density in the simulation phase was confirmed [ R2=0.87 , root mean square error (RMSE)=0.1 m3/s , and nash-sutcliffe efficiency (NSE)=0.86 ]. In the forecasting phase, the forecasting equation based on the proposed method had a RMSE of 0.14 m3/s and NSE of 0.89. By using the violin plot, the model certainty was also confirmed. According to the proposed equation, FD values can be forecasted affected by RD values for 10-day duration with high certainty and accuracy. In this paper, a method for forecasting and simulation of meteorological and hydrological parameters is presented that considers two parameters simultaneously. This study discusses meteorology and hydrology from a different perspective. Given the current climate change, this study uses deficiency values. The proposed forecasting method provides regional results that can be used in the water resources management in each basin specifically. By implementing this method, it is easy to forecast the desired values in the basin with different probabilities and return periods. In this study, river flow deficiency (FD) affected by rainfall deficiency (RD) can be forecasted. The difference between the proposed method and other methods and models of simulation and forecasting is in the connection of two variables with each other, which makes the results more certain and reliable. This method can be used in the field of basin management and water resources allocation and also water resources monitoring. [ABSTRACT FROM AUTHOR]

Intensified competitiveness in global markets has directed most organizations toward retaining their employees as their most important intangible assets, because losing such individuals can impose huge costs to them. Therefore, managers do their best to keep employee satisfaction. For this purpose, they need to understand the needs of their employees and the organization's conditions. In such a situation, employees' positive voice behavior is of utmost importance for managers as it helps enhance their awareness. Therefore, it is essential to identify the factors inducing this behavior. Given that workplace comfort might shape employee voice behavior (EVB) and managers with leadership psychological skills (LPSs) can create a state of calmness for these individuals, as highlighted in previous research, the present study reflected on the relationship between the effects of LPSs on EVB. As employee work engagement (EWE) can be also influenced by LPSs and consequently shape EVB, the mediating role of this variable in the relationship between LPSs and EVB was further discussed. To meet the research goals, a total number of 310 employees working in Iranian food industry companies were employed as the study sample. Structural equation modeling (SEM) and the LISREL software were used for data analysis purposes. The study results ultimately demonstrated that LPSs could affect EVB when mediated by EWE. [ABSTRACT FROM AUTHOR]

In the present study, a method based on the conditional density of vine copulas was used to drought monitoring and predicting the rainfall deficiency signature for a 60‐day duration in Dashband, sub‐basin of Lake Urmia basin. The annual rainfall and rainfall deficiency signatures at 10‐, 30‐ and 60‐day durations were considered as variables. D‐, C‐ and R‐vine copulas were used to represent the dependence among the variables, finding that D‐vine copula results to be more accurate for the case of interest. We found that, if the rainfall is less than the long‐term mean in the region, the rainfall deficiency signature for near future can be estimated by acceptable accuracy. Moreover, the results of the conditional probability analysis of rainfall deficiency signature for a 60‐day duration respect to the other variables showed that, on average, the probability of the occurrence of rainfall deficiency signature of 250 mm compared to the long‐term mean in the study area is more than 50% per year. The results showed that the proposed approach may facilitate the meteorological drought management in the considered sub‐basin. [ABSTRACT FROM AUTHOR]

Floods are among the most common natural disasters that if not controlled may cause severe damage and high costs. Flood control and management can be done using structural measures that should be designed based on the flood design studies. The simulation of outflow hydrograph using inflow hydrograph can provide useful information. In this study, a copula-based approach was applied to simulate the outflow hydrograph of various floods, including the Wilson River flood, the River Wye flood and the Karun River flood. In this regard, twodimensional copula functions and their conditional density were used. The results of evaluating the dependence structure of the studied variables (inflow and outflow hydrographs) using Kendall's tau confirmed the applicability of copula functions for bivariate modeling of inflow and outflow hydrographs. The simulation results were evaluated using the root-mean-square error, the sum of squared errors and the Nash-Sutcliffe efficiency coefficient (NSE). The results showed that the copula-based approach has high performance. In general, the copula-based approach has been able to simulate the peak flow and the rising and falling limbs of the outflow hydrographs well. Also, all simulated data are at the 95% confidence interval. The NSE values for the copula-based approach are 0.99 for all three case studies. According to NSE values and violin plots, it can be seen that the performance of the copula-based approach in simulating the outflow hydrograph in all three case studies is acceptable and shows a good performance. [ABSTRACT FROM AUTHOR]

Vine copula had a great impact on the study and analysis of dependence structures in various sciences. In multivariate analyses with dimensions of more than two variables, it is associated with computational complexities that solve vine copulas and these problems. In this study, in order to provide an approach to simulate potential evapotranspiration based on meteorological parameters in Birjand meteorological station from different family copulas including R-vine, independent R-vine, Gaussian, independent Gaussian, C-vine, C-vine independent, D-vine and D-vine independent were used. In this regard, vine copula simulation and conditional density were used. In pair correlation analysis of the studied variables using Kendall's tau statistic, dependence structure confirmed the studied parameters. The results showed a minimum correlation of −0.32 and a maximum of 0.77. The results of Akaike's information criteria (AIC), Bayesian information criteria (BIC) and LogLike statistics in evaluating the performance of vine copula dependency structure introduced the C-vine copula as the superior copula for analysing the pair dependence of the studied variables. By introducing the superior dependency structure and internal copulas, the tree sequence of the pair of values under study was obtained. Pair of simulated values was performed using vine copula. Comparison of Kendall's tau values in both simulation and observation modes showed that Kendall's tau values were close to each other in both modes and were approximately similar. The simulation results of vine copula potential evapotranspiration values and precipitation, temperature and relative humidity values showed 92% efficiency. The efficiency of C-vine copula in dependence analysis and simulation of potential evapotranspiration (PET) values is very high, which shows the ability of vine family copulas in multivariate analysis. [ABSTRACT FROM AUTHOR]

The complex hydrological events such as storm, flood and drought are often characterized by a number of correlated random variables. Copulas can model the dependence structure independently of the marginal distribution functions and provide multivariate distributions with different margins and the dependence structure. In this study, the conditional behavior of two signatures was investigated by analyzing the joint signatures of groundwater level deficiency and rainfall deficiency in Naqadeh sub-basin in Lake Urmia Basin using copula functions. The study results of joint changes in the two signatures showed that a 90-135 mm reduction in rainfall in the area increased groundwater level between 1.2 and 1.7 m. The study results of the conditional density of bivariate copulas in the estimation of groundwater level deficiency values by reducing rainfall showed that changes in values of rainfall deficiency signature in the sub-basin led to the generation of probability curves of groundwater level deficiency signature. Regarding the maximum groundwater level deficiency produced, the relationship between changes in rainfall deficiency and groundwater level deficiency was calculated in order to estimate the groundwater level deficiency signature values. The conditional density function presented will be an alternative method to the conditional return period. [ABSTRACT FROM AUTHOR]

The prediction of global climate change using the values recorded in a statistical period requires a precise method that can accurately identify the fluctuations of these changes. By patterning these changes, the parameter values for the years or future periods are predicted, or the statistical gap can be eliminated. In this research, meteorological data of six stations in different climates of Iran were used to model and estimate the values of the dew point temperature (DPT). The stations studied are Ahvaz, Urmia, Kerman, Gorgan, Rasht, and Babolsar. In order to estimate the DPT values, support vector regression was used, and to optimize the parameters of the support vector regression model, the ant colony algorithm was used. In this study, four different input patterns of meteorological data have been investigated as input of the support vector regression model. Pattern I with seven inputs (monthly minimum, maximum, and average air temperatures, monthly precipitation, saturation vapor pressure, actual vapor pressure and relative humidity), Pattern II with three inputs (monthly average air temperature, saturation vapor pressure, and actual vapor pressure), Pattern III with two inputs (monthly minimum and maximum air temperatures), and Pattern IV with an input (monthly average air temperature) were used. It is recommended that if the number of inputs in the model is small, the model will be more user-friendly. Based on the results of analyzing different patterns, it can be concluded, that Pattern III is the suitable pattern for estimating DPT values at the stations studied in different climates of Iran based on the three criteria of root mean square error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE), and coefficient of determination (R2). Overall, the results showed that the selected pattern increases the accuracy of the model by up to 24% compared to the conventional model. [ABSTRACT FROM AUTHOR]

Thousands of billions of cubic meters of fresh water collected at great expense are evaporated annually from dams, and salts of evaporating water reduces water quality. In this study, the efficiency of the vector autoregressive model called VAR model has been examined on an annual scale using pan evaporation data in the salt lake basin, Iran, during the statistical period of 1996-2015. Since hydrologic modeling is concerned with the accuracy and efficiency of the model, therefore, we must try to evolve and improve the results of the models. In this study, VAR multivariable time series and nonlinear GARCH models have been used. The results of linear and nonlinear hybrid models in modeling the annual and monthly pan evaporation values of studied stations at the basin area of the salt lake indicated, that the pan evaporation values in the annual scale have the best fit with hybrid models. The results of the study of the accuracy of these models in modeling the pan evaporation values indicated, that the VAR-GARCH hybrid models have a high accuracy relative to the vector models and have been able to model the pan evaporation values with good accuracy and with the lowest error rate. Of the two models that have both annual nature (VAR and VAR-GARCH), the best model can be selected based on the estimation of the error values. In this study, we first examine the accuracy of the relatively new vector autoregressive model. The results of the estimation of error and efficiency of the model indicated the acceptable accuracy of this model in estimating the pan evaporation values in the annual scale. The 95% confidence interval confirmed the simulation results of the calibration step. Overall, the results showed that both VAR and VAR-GARCH models have high accuracy and correlation, and the model's performance criterion also confirms this. The percentage of improvement in the results from the model of the pan evaporation values in the annual scale using the VAR-GARCH model is about 4% relative to the VAR model. However, due to modeling the random section and reducing the uncertainty of the model, the results of modeling the pan evaporation values using the VAR-GARCH model are better than the VAR model. But due to the complexity of calculating the GARCH model, the VAR model can also be used. [ABSTRACT FROM AUTHOR]

The present interdisciplinary research was enlightened by the contingency theory of human resource management (HRM) and aimed to explore Iranian EFL teachers' leadership and conflict management styles in the private sector. To this aim, Fiedler's leadership measurement instrument along with Thomas & Kilmann's conflict management instrument were used to collect data from 51 EFL teachers teaching in private language institutes of Khorasan Razavi, Iran. The aim was to find what proportion of teachers were task-oriented and what proportion were relation-oriented in leadership, and which conflict management styles were more prevalent among task-oriented and which were dominant among relation-oriented teachers. Furthermore, comparisons were made between male/female, younger (20-30 yrs.)/older (>30 yrs.) and experienced (>5 yrs.)/novice (<5 yrs.) teachers in terms of the leadership style as well as the conflict management style. Descriptive as well as inferential statistics were used to analyze the data in SPSS21. The results revealed that the majority of participants used task-oriented leadership style in class. Task-oriented teachers showed to use the accommodating conflict management style more while relation-oriented teachers prevalently used the collaborating style. Statistically significant differences were found between demographic groups in terms of the leadership and conflict management styles. Awareness of different leadership and conflict management styles can enrich teacher training courses and professional development programs in Applied Linguistics. [ABSTRACT FROM AUTHOR]

Investigations of the long-term observations of climate variables, as a practical approach to monitor climate changes, have attracted the interest of many researchers around the world. One of the important variables in this context is precipitation. The investigation of precipitation, one of the most important meteorological factors directly affecting accessibility to water resources, is of special importance. In every region, studies of precipitation on daily, monthly, or annual scales provide important information on the distribution, concentration, and dispersion of precipitation, as well as some conclusions about the associated hydrological problems. In this study, the precipitation concentration was calculated and zoned by means of the precipitation concentration index (PCI) in the basin of Lake Urmia, using monthly and annual rainfall data of 42 selected rain gauge stations, from which 24 stations located in the West Azerbaijan province (in the west of Lake Urmia) and 18 stations located in the East Azerbaijan province (in the east of Lake Urmia) during 1984-2013. The results of the studies of the precipitation concentration index over the basin of Lake Urmia showed that the dominant concentrations of spring, autumn, and winter precipitation were moderate, indicating a moderate distribution for the precipitation of the months in these seasons. In addition, in the period under study, uniform and regular precipitation concentrations (PCI<10) were observed only in winter and in the borders of the basin. In summer, almost the entire surface of the basin (excluding its northeastern part) faced a strongly irregular distribution of precipitation, indicating irregular rainfall in July, August, and September. Most of the basin of Lake Urmia is covered by an irregular distribution of precipitation on an annual scale. By investigating the precipitation distribution in the first and the last 10 years of the statistical period considered and by comparing them, it was revealed that the greatest increase in the precipitation concentration index was in autumn, it rose by approximately 20.55 percent. According to the results, on the basin scale, the concentration index showed that the daily rainfall of the Lake Urmia basin was neither in regular nor in strongly irregular conditions at any of the stations studied. All the stations studied were in fairly regular, moderate concentration and fairly irregular conditions of daily precipitation distribution. The results also showed that the moderate concentration includes most of the daily precipitation distributions throughout the basin. [ABSTRACT FROM AUTHOR]

Background and Objectives: Despite the dramatic growth of medical tourism in recent years, there is little information about the role of quality, satisfaction and trust in explaining the international patients' behavior after the purchase. The present study investigated these variables. Material and Methods: The purpose of this study was practical and it is a survey-analytic one. The statistical population of this study was all the patients outside the country (clients) of selected hospitals operating in the field of medical tourism in Mashhad and sampling was conducted as convenience. Data analysis was performed using bifurcated and multivariate regression and structural equation modeling in the SPSS and AMOS software. Based on the data gathered from 174 international patients, validity and reliability of the research were confirmed. Results: The results of the study showed that the quality of medical services and the quality of services, patient satisfaction, trust in staff and trust in the medical clinic had impact on the motivation for subsequent referrals of patients and the motivation for the next visit to the medical centers of medical care in Mashhad. Also, the logical price has a moderating role for thoese relationship. Conclusion: The role of tested variables, especially the reasonable price of health services, is important for the international referral of patients, and therefore requires the cooperation of all health care administrators, including nurses, doctors and managers to include these for the prosperity of the tourism industry and the development of the country. [ABSTRACT FROM AUTHOR]

As a long-term water deficit condition, drought is a challenging issue in the management of water resources and has been known as a costly and less known natural disaster. Monitoring and predicting droughts, especially accurate determination of their beginning and duration are crucial in management of water resources and planning for mitigating the damaging effects of drought. In this study, the droughts in the southwestern region of Asia (Iran, Afghanistan, Pakistan, and Turkmenistan) were evaluated using the joint deficit index (JDI). Data of monthly and annual precipitation of 1392 downscaled rain gauge stations (by using the Bias Correction Spatial Disaggregation (BCSD method) within the statistical period of 1971-2014 were employed to calculate JDI. The results indicated that in recent years, the number of dry months in the studied region (especially in humid regions of Iran) has significantly increased, such that across all regions in Iran, the percentage of dry months has reached over 50%. The results also showed that in addition to scientific description of the general drought condition, JDI is also able to specify the time of beginning of droughts as well as long-term droughts, allowing investigation of the drought condition on a monthly scale. The results of investigating the trend of changes in the JDI values in the studied region revealed that the variations in these values have decreased on annual scale in the studied region. The extent of reduction in JDI and the increase in the number of dry months within the statistical period of 1971-2014 have been significant (at level of 5%) in Iran, suggesting increased drought in Iran, especially during winter. The values of monthly and annual precipitation in the studied region have been descending, where among the studied countries, Iran has experienced the maximum extent of reduction in precipitation. [ABSTRACT FROM AUTHOR]