جستجوی مقالات مرتبط با کلیدواژه « risk management » در نشریات گروه « اقتصاد کشاورزی »

Today, the businesses of the poultry industry are facing many challenges, because this industry has to manage a number of unique processes, methods and risks at the same time. Therefore, identifying the business risks of poultry production units can play an effective role in reducing the level of vulnerability of these businesses. Considering the need to increase the productivity of the poultry industry, one of the basic solutions is to identify the risk and measure the existing risks of this industry. Risk identification and quantification can reduce costs for industry stakeholders, and risk reduction leads to better production planning. In this regard, this study identifies the business risks of poultry production units in Khorasan Razavi province.

This study is applied as purpose and descriptive survey in terms of nature and method. This research is based on mixed research, qualitatively and quantitatively. The statistical population is poultry industry experts, 18 of whom were investigated by snowball sampling method as the research sample. This study proposes a new Delphi technique that uses the features of traditional Delphi techniques and the Fuzzy Delphi method. The proposed new Delphi technique is based on the integration of pentagonal fuzzy sets and the Delphi technique.

The results of the modified pentagonal Fuzzy Delphi method showed that five main risks and 36 secondary risks out of 58 identified risks are part of the business risks of poultry production units. Identified business risks of poultry production units, in order of priority, include inputs price fluctuations, command pricing, exchange rate fluctuations, sanctions, chicken price fluctuations, delay in accessing inputs, fluctuations in the purchase price of day-old chickens, fluctuations in drug and vaccine prices, imported inputs, lack of government support in the matter of production, fluctuations in subsidies to inputs, lack of animal inputs, import of poultry products, Promulgation of various instructions, poultry diseases, lack of liquidity of poultry farmers, bankruptcy of poultry farmers, fluctuations in current costs, losses, lack of medicine and vaccines, lack of expansion of poultry business, lack of confidence of poultry farmers in the government, fluctuations in profitability, investment, seasonal fluctuations in egg demand, dependence of poultry farmers on Special suppliers, supply of day-old chicks, lack of energy, exclusivity of the livestock and poultry feed supply system, egg price fluctuations, seasonal fluctuations in chicken production, seasonal fluctuations in chicken demand, weakness in providing working capital facilities to poultry farmers, lack of skilled human resources in time Appropriate, lack of technical knowledge of advanced technologies and lack of variety of poultry food ingredients.

The business of poultry production units is facing various challenges and risks, and due to the many risks of this industry, production in this industry is facing problems and it is not possible to plan for it, and production will be disrupted in the future. Therefore, in this research, an effort was made to fully identify the business risks of poultry production units. In order to complete and finalize the business risks of poultry production units, the pentagonal Fuzzy Delphi method was used. In this regard, a questionnaire was prepared that included two parts. The first part is about the survey and information about the background of the respondents, and the second part includes the ranking of 54 identified risks. Fuzzy Delphi method in this study was done in two rounds and based on the opinion of experts, 4 more risks were added to the total of 54 risks, and finally 58 risks were analyzed using Fuzzy Delphi method. In Fuzzy Delphi, the selection of risk components among all the components that were identified in the research literature was based on the accepted threshold criterion. The results of the second round of modified pentagonal Fuzzy Delphi showed that there are 36 important sub-risks in the sector of production, market, financial, institutional and personal business risks of poultry production units. Considering the price fluctuations of livestock inputs and exchange rate fluctuations, it is suggested to allocate currency and control it by government policies in order to reduce mentioned fluctuations, or move towards diversifying poultry feed ingredients and formulating new poultry feed rations. Also, in order to avoid fluctuations in the price of chicken or eggs, it is suggested to make the distribution network smarter to prevent these fluctuations. In the poultry market, it is better to set a fair price for each kilogram of chicken according to the production costs of poultry farmers, or not to interfere with the government in the market and allow the government to set the price based on the supply and demand mechanism.

The use of multiple risk management tools at the same time is a common practice among the farming communities around the world. Therefore, this study is designed to investigate the Factor affecting of Simultaneous adoption of managing custom catastrophic risks tools such as diversification and precautionary savings in agriculture in Khorram Abad Area of Tonekabon. So bivariate probit model was used to cope the possible correlation between the risk management adoption decisions. The results highlighted that, age, education of the household head, family size, in farm income, land size and risk aversion coefficient has the significant effect on the decisions to adopt diversification and precautionary savings to manage farm risks. Risk aversion coefficient has the most effects on decisions to adopt managing catastrophic risks tools; Increasing in risk aversion coefficient, was increased the probability of simultaneously use of risks management tools by 0.22 percentage. Therefore, due to the positive impact of education and income on the use of risk management tools, increasing farmers 'awareness and increasing farmers' income through modifying their cropping pattern has been suggested.

One of the most important concerns of investors in the capital market is choosing a portfolio that is optimal in terms of profitability and risk. The purpose of this study is to compare the profitability and risk level of portfolios containing different percentages of shares of agricultural and food industry groups and other industries. For this purpose, the daily returns of 18 companies active in the Tehran Stock Exchange for the metals, agriculture, food industry, banking, petrochemical, and chemical groups during the period 2019-2020 were collected and classified into 11 portfolios. The returns of the portfolios were simulated and the best portfolios were determined based on stochastic dominance criteria. The results showed that if the degree of risk aversion of individuals is not known, portfolios 10 and 6, which have 30% and 25% of shares of the agriculture and food industry, respectively, are superior, and if the degree of risk aversion of individuals is clear, portfolio 11 with 30% of shares of agriculture and food industry group is the best portfolio among the risk portfolios. Also, for people with lower risk aversion, portfolio 6 with 25% of agricultural and food industry shares and 20% of petrochemical group shares, and portfolio 4 with 80% of petrochemical group without food and agriculture industry shares are superior portfolios, and for people with a higher degree of risk aversion, portfolios 10 and 2 with 30% and 10% of the shares of agriculture and food industry group, respectively, are superior to the other portfolios. The top portfolios have the highest percentage shares of in the agriculture and food industry and the highest percentage is related to the shares of the petrochemical group. Therefore, the shares of the agriculture and food industries group, along with other shares, can contribute to the superiority of the portfolio. Also, by increasing the percentage of petrochemical stocks in the portfolio, the utility can be maximized.

Due to the importance of the agricultural sector in the world's nutrition systems, and in order to continue productive activities, it is necessary to support farmers by using appropriate methods of risk management. One of the most common and efficient methods in risk management is the use of insurance coverage. Agricultural insurance can play an important role to improves famileis life quality. This study aims at prioritizing and ranking the factors that affecting farmers' satisfaction with agriculture insurance under fuzzy environment. 

AHP Fuzzy model of Hierarchy analyze is suggester.this descriplive research using specific method like observational method case study and survey method that indentify factors of golestan province farmers satistaction of agricultural insurance according to content of research.

The research shows that the factors of insurance fee, variables of Keshavarzi Bank and the quality of services received have the highest priority, while the factors of farmers' commitment to Keshavarzi Bank and the amount of compensation received have the lowest rank.

According to the results of this study, receiving insurance premiums from farmers in installments, timely payment of the true value of damages and improving the quality of insurance services by making reforms and diversification in order to satisfy farmers should be a priority. In addition, the participation of the insurer in the bank's programs and the consideration of new methods of accountability will play an important role in farmers' satisfaction with product insurance.

The scope and complexity of activities in food supply chains has exposed this networks to more negative risks, so that decision makers and business actors in this chains are forced to identify and evaluate the risks correctly and also adopting the necessary policies to reduce the likelihood of risks occurrence and severity consequences. The purpose of this study is to investigate and measure the supply chain performance in real conditions under different risks and to analyze it with using agent-based simulation. For this purpose, milk supply chain was studied in Zahedan city during 2018 and 2019 period. In this study, the theoretical sampling method of Strauss and Corbin was used. A regular series of purposefully in-depth and semi-structured interviews was conducted with a group of 24 experts and specialists related to the chain to extract qualitative data. Identified 61 risks in the chain in the field research were initially evaluated using the Failure Mode, Effects and Criticality Analysis, then, the active chains in the region was simulated with the agent-based modeling approach and using Net Logo software, and 27 risk reduction scenarios were examined to evaluate the changes in the performance indicators of the chain. Regarding the validation of the results of simulation tests, paired (t) test was performed and also the results of 30 independent replications of the model was compared with each other. Among the identified various risks in the chain, price fluctuations of agricultural inputs (seeds, fertilizers, labor, etc.), milk price fluctuations and lack of information had the most negative impact on chain performance and as a result of appropriate measures such as the use of marketing and futures contracts and other local tools that reduce the level of risk from high to medium level in the chain, some other performance indicators of the chain can be improved while increasing the overall revenue of the chain.

Agriculture is always been known for the high production, market and financial risks that farmers face. There are tools for crop risk management whose adoption depends on farmers' decisions and persuasions. The main purpose of this research was to study the determinants of wheat farmers' decision to adoption a crop risk management tools in Ilam Province. The study was an empirical research, which followed a quantitative paradigm based on a survey research method. The required data collected through interviewing 150 farmers and completing a researcher-made questionnaire. Two-stage random sampling was performed and the data were analyzed using Logit model in Shazam software environment. The results showed that variables such as area under cultivation, income level, level of education, agriculture as the main job, the previous records of loss, awareness about insurance and its benefits, amount of payment for crop loss had significantly a positive effect on the likelihood of adoption of a crop risk management tools by farmers. While the time to pay crop loss had a significant negative effect on the likelihood of adoption of a risk management tools. It is recommended that some policies be adopted to increase farmers' awareness about the crop insurance benefits and to reduce the time of crop loss payments by the authorities.

One of the crises in Iranian agriculture sector is drought and identfying the risk management solutions for this problem are a necessity. The purpose of this research is analyzing the agricultural drought risk management strategies by fuzzy Delphi method that a mix of quantitative and qualitative methods was performed. The statistical population of the research consisted of key experts including subject mater related administrators and specialists of state organizations in Lorestan province. 20 of them were selected as sample using chain purposfull sampling. This research uses the risk and crisis cycle model by whilhite which risk management solutions fall into three categories: "reduction", "planning" and "monitoring and forecasting". The results showed that the most important priority in the reduction step was watershed management and aquifer development; at the planning step, preparation and implementation of the Land use Planning and In the step of monitoring and forecasting, establishing warning systems.based on results land use planning,adjusting the Cropping patern,international and regional collaboration for reinforcement of warning systems and drought monitoring and training and continous training to related  practioners was recommended.

Introduction and

Agriculture is a risky occupation. The different natural, social, and economic hazards have created handicaps and problems for agricultural producers, which result in the instability of income for producers. In general, the nature and environment of agricultural activities are at high risk. The risks of agricultural activities are often associated with low performance, increased cost, and time lag. In order to from the perspective of risk management, studies can be categorized into three types including product hazards, price risks, and natural hazards. Major economies in the rural areas of south Khorasan province is based on the planting and selling three products of barberry, saffron and jujube, which are resistant to water deficit and drought, and at the same time all have the high economic value. This province in Iran accounts for about 96 to 98% of the barberry and jujube production. Therefore, this study aims to examine the factors affecting the barberry and jujube production in the South Khorasan province, Iran. .

Genetic function approximation (GFA) algorithm describes the basic problem of approximating the function. Many factors affect the response variable and primary input correlated with best response. The GFA algorithm works with a range of strings called population, developed for the purpose of searching.  The selection, crossover, and mutation operators also run appropriately. New members were given scores according to the estimator’s criteria. In the GFA, the criteria scoring is obtained for fitted regression models. The selection probabilities should add each new member to the population again. This method continued for a specified number of generations until the point of convergence. GFA algorithm can be used to produce a generation with respect to the evolution charts according to the achieved time. This graph shows the number of events for each variable about the population, which has evolved for each generation. GFA algorithm converges as no progress in population occurred. At this time, the model is significant which means the best choice for all models of population. Using GFA and MS modeling software, modeling is used to identify the factors affecting the knowledge of barberry and jujube producers in order to determine which one of 15 independent variables were effective on the risk management information of barberry and juvenile producers in South Khorasan province.

The results showed that frostbite risk had the lowest risk, affecting the risk index of barberry producers. Awareness of hail hazards exerted the greatest effect on the risk index of jujube producers in south Khorasan region. The least effective factor was the awareness of fire hazards in the jujube gardens.

The results suggest that most jujube and barberry producers use traditional knowledge and experience and do not acquire the necessary training that are needed for dealing with natural hazards due to poor knowledge and non-compliance with the principles of agricultural education in dealing with hazards. Therefore, it is recommended  that the system of agricultural extension and education and agricultural meteorology must have been improved the knowledge of the farmers' risk management and skills in the southern Khorasan region by presenting appropriate training programs to address these risks (drought, , storm, sudden precipitation, etc.). Accordingly, the information and promotion system, accompanied with appropriate training in relation to new innovations, will increase the awareness among the male and female producers and government support should be taken in this area.  So producers can use modern methods for better managing natural hazards in the Jujube and Barberry gardens of South Khorasan province.

Agriculture is one of the most important vulnerable sectors regarding drought phenomenon with significant impacts on the economy of countries. In many previous studies, drought risk management has been mentioned as one of the best scientific methods of drought management. In this regard, this study was conducted in Ferdows County, South Khorasan province of Iran, aiming at both identifying the drought risk indexes to assess agricultural drought risk factors of the region and providing a framework to plan an operational risk response. Precise determination of these indexes and their relative importance makes it possible to assess and analyze drought risk of that region; moreover, a definite framework for agricultural drought risk management can be developed. In this paper, a list of possible drought risk response actions was provided and then they were prioritized. Based on this initial prioritization, cost and difficulties of executing each drought risk response action, the final prioritization of drought risk response actions were determined. Since the risk assessment indexes and drought risk response actions were evaluated based on opinions of experts and linguistic variables, Fuzzy Analytical Hierarchal Process was used to determine the weight of each risk index, and Fuzzy TOPSIS was applied to determine the priority of risk response actions. The study results indicated the pivotal role of “reducing the groundwater and surface water use of agricultural activities” in addressing the agricultural drought and “subsurface irrigation” as the best reaction treatment

Moghan plain (Ardabil province) always has been considered as one of the important pillars of agriculture in Iran. However due to the new climatic changes, increasing occurrence of phenomena such as drought and reduction of water resources, and spread of pests and weeds, farmers facing with the phenomenon of risk as a major challenge in the region. Farmers will be obliged to make decisions about allocating resources to their agricultural productions which facing environmental conditions and different biotic and abiotic risks, as ambient conditions, the status of inputs and outputs prices and their agronomic performance, are not stable enough. Finally, these conditions influence farmers' agronomic decisions which under such circumstances the results of farmers' decision making are different from the results in safer conditions. There are also different values of inputs consumption in risky and safe agricultural conditions and these values also depend on other factors such as variance of the product price, the degree of risk aversion and the marginal share of inputs in production variance as well as outputs and inputs prices and production levels. In this regard, agricultural crop insurance is one of the major management strategies to overcome agricultural risks, weather and other unavoidable natural hazards. Risk management is an appropriate management of operational unit with awareness and understanding of the environment and risky factors. It is actually one of the ways to increase productivity of production factors and to improve the efficiency of farming operation systems through making suitable decisions about controlling risk factors and resources. Therefore, increasing range of production risk and the importance of agricultural crops insurance of maize production in Moghan plain led to investigate and determine the effects of agricultural crops insurance adoption on the components of production risk management among the maize farmers of Moghan plain. This study is an applied one based on descriptive-correlative method that was designed and implemented in 2016-2017. Study area was Moghan plain that it located in the northern part of Ardabil province. Sampling method was multi-stage and applying the Yamane (1967) formula. Data including sample size of 278 maize farmers in 9 villages were collected. The research instrument was a questionnaire including 69 items in three sections (personal and professional characteristics, determining risk aversion coefficient and risk management components). Items of questionnaire were composed of personal and professional characteristics of respondents (18 items), variables determining risk aversion coefficient (19 items) and risk management components (32 items). Risk management components were consisting of planting risk management (5 items), maintenance risk management (5 items), harvest risk management (4 items), Risk management of economics and marketing (5 items), risk management of farm and technical infrastructure (7 items) and the risk-sharing management (6 items). Items of risk management components with equal weights were collected in the five-part Likert scale (the range of 1 (very low) to 5 (very much)).
To calculate the risk aversion coefficient and the risk sentiments in maize farmers' decision-making, we used safety first rule (SFR). For the final analysis of the main purpose of the research was to use the binary logistic regression method in step-by-step approach. According to study results, maize farmers with different risk aversion coefficient, includes four groups as follow: 1: risk-taker (15.1% of respondents); 2: risk-neutral (19.8% of respondents); 3: low risk-averse (37.4% of respondents) and 4: high risk-averse (27.7% of respondents). There was also a significant difference between the adopter and non-adopter maize farmers of insurance based on the degree of risk aversion. In other words, non- adopter maize farmers of insurance had significantly higher risk aversion compared to adopter maize farmers of insurance. Based on the results of logistic regression, from among 17 studied factors in eight steps, only 8 components including education (B = 0.254), average annual agricultural income (B= 0.68), number of agricultural risks (B =0.361) and risk-sharing management (B=0.447) at 5% level, and risk management variables of economics and marketing (B= 0.492), planting risk management (B = 0.382) and risk management of farm and technical infrastructure (B = 0.617) at 1% level were positive and significant. But for the component of age (B= -0.142) a negative and significant relationship at the 5% level was found.
The results of calculating the risk aversion coefficient showed that majority of maize farmers were risk-averse (65.1%). Also, the adopter maize farmers of insurance were significantly less risk aversion than non-adopter maize farmers of insurance. Many number of maize farmers in the area are small-holder farmers (mean of farm lands size equals 5.0054 hectares). The smallholder farmers compared to other farmers are very vulnerable facing with the agricultural risks, so this leads to high risk eversion level of maize farmers in the study area compared to other farmers. Also, the adopter maize farmers of insurance were significantly less risk aversion than non-adopter maize farmers of insurance. The results of logistic regression showed that among various types of risk management components, planting risk management (Wald: 0.382), risk management of economics and marketing (Wald: 0.492), risk management of farm and technical infrastructure (Wald: 0.617) and risk-sharing management (Wald: 0.447) had the positive and significant effects on agricultural crops insurance adoption.

This study has considered the factors regarding the willingness to pay weather-based index insurance of apple gardeners of Damavand county in the proposed plan. For this purpose, Logit and Tobit models were used. Required information were collected through interviews and completing questionnaires of 307 gardeners of Damavand region by stratified random sampling with suitable assigning. Results of Logit model showed that factors such as education level, garden area, using current insurance, garden construction region, familiarity with weather-based index insurance and the type of gardener activity have a positive and significant effect, and gardeners' satisfaction of the current insurance has a negative effect on the acceptance probability of the proposed plan of weather-based index insurance. The average willingness to pay apple gardeners' premium in Damavand county has been calculated as 7900 thousand Rials per hectare. Also, the results of Tobit model indicated that the level of education, garden area, using the current insurance, the location of garden construction, the level of familiarity with weather-based index insurance, and the type of gardener activity have a positive effect on the level of willingness to pay insurance premium of apple gardeners. Since such factors as the gardener's education level and his knowledge about the weather-based index insurance has a positive and significant impact on acceptability probability of the weather-based index insurance and willingness to pay premium, Thus, to introduce the weather-based index insurance and offer the advantages and shortcomings of current insurance system and weather-based index insurance, it is suggested that agricultural insurance fund provides full information for gardeners to improve their consciousness level and provide a public knowledge before this proposed plan is implemented.

Uncertainty existence in farmers crop production pulsed on important and necessity of science of risk management in the agricultural sector. The new risk management selects the best tools and techniques to minimize risks and consequences of decisions. Furthermore, determining the nature of the risk of crops yield can provide useful information about how to manage the risk of the agricultural sector. One of the effects of climate change is caused damage in the agricultural sector. Dependence of crops to climate change is caused that climate factors have a determinative role in the occurrence of crops damaged. Performed studies on the economic effects of climate change have shown that climate change has a significant impact on agricultural yield and its production risk. Moreover, climate change influences crop yield and the risk of crop yield. Although several studies have been carried out about the impact of climate change on crops yield in Iran, the effect of climate change on crops yield risk is infrequently considered. Therefore, this article tries to offer a new way for calculating the risk of crops yield using of CVaR in the period 2017-2047 in the zayanderud agricultural system. The innovation of this study can be stated as follows:1) This study used of Value at Risk index, as one of the most important indicators of risk measuring, to measure the risk of crops yield, 2) For calculating of Value at Risk index, different studies are used from a famous probability distribution such as normal distribution, historical data or Monte-Carlo simulation, while in this study tried to calculate VaR index based on the forecasted scenarios of crops yield, and 3) In this study, in order to produce future scenarios of crops yield is used from ANN-PSO combined method for forecasting crops yield.
The method of this study includes the following steps:1) The production of possible scenarios of temperature and precipitation using of AOGCM models: Today, one of the best tools for the production of climate scenarios is Atmosphere-Ocean General Circulation Models (AOGCM).But the main problem in the use of the output of the AOGCM models is the large spatial scale of their computational cells toward the area under study. LARS-WG model is also one of the most famous models to small scale for outputs of AOGCM models. In this study uncertainty related to AOGCM models, is used of for scenarios of all AOGCM models(including A1B, B1 and A2).
2)The production of scenarios of selected crop yield and available water in the period 2017-2047: The production of scenarios of selected crops yield and available water is performed using of combinedmethod of ANN-PSO.To combine neural network with particles warm optimization algorithm, from particles warm optimization algorithm is instead of training the neural network using gradient-based algorithms.
3) Measuring risk of crops yield using of VaR and CVaR indexes: VaR index is one of the most important criteria to measure downside risk that it determines the maximum amount of expected losses of a variable for a certain time period and specific confidence level. In this study (according to the non-normal distribution of crops yield scenarios) is used on the historical simulation approach.
In the first phase of research methodology, for producing of climate scenarios from daily available stats related to weather stations of Isfahan, Kabuotarabad, Kuohrang, and Daranwere used. Validation results of LARS-WG model showed that this model is well able to simulate changes of climate parameters. Eventually, 44 scenarios of the maximum temperature, minimum temperature and rainfall wereproduced in each studied stations and for each year. The results of the network design using trial and error methods revealed the best forecast combination model obtained with 3 and6 neurons in the input layer and hidden layer of neural network and assuming the initial population of 200, in PSO algorithm. Results of this step showed that ANN-PSO model is well able to forecast crops yield (wheat, barley, maize and alfalfa) and available water. Furthermore, calculating VaR and CvaR criterain confidence level %95 and for future period of 2017-2047, showed that the values of these two criterions for wheat, barley, maize and alfalfa were equal to (4240, 4205), (4062, 4057), (49061,48480) and (10875,10743) kg/ha. The comparison of the values of these two criterions with the values of last period also showed that for all selected crops, VaR and CvaR criterions is bigger in future period toward last period.
The new offered method can calculate the risk of crops yield due to climate change. The more accurate measuring of risk using of new methods such as CVaR can be suitable guidance for policy man to better management of production risk of crops.

Agriculture sector has had a significant grow thing role in the Iran, but growth and development in this sector is not possible without a suitable risk management. This study has tried to predict and measure the risk from changing weather condition on agriculture products of Gorgan County using Mont Carlo Stimulation as one of the powerful tools on risk analysis. The results showed that the highest level of production risk is for the crop such as barley, soya and wheat and the least level of the risk is for the crops such as bean, clover and pea, respectively. To sum up, the research results indicated a significant effect of production risk in this area and therefore managers and policy makers need to notice it.

Agriculture relies on nature and farmers face environmental، social، financial and legal issues that makes farming to be consistently and strongly associated with risk. Agriculture can be considered to be the most risky economic venture. Ahmadi (1) listed several main sources of risk that farmers face. Economic risk includes price fluctuations for raw materials such as seed and fertilizer and for machinery at the pre-market delivery stage، difficulty obtaining bank credit and loans، price volatility for products in the post market delivery stage، inconsistent government policies for products and global fluctuations in the price of products. Social risk includes theft of crops، production and agricultural machinery and war. Nature-related risk includes natural disasters، climate change، agricultural pests and diseases. Market risk includes changes in the price of raw materials and products and increasing interest rates. Given that the range of agricultural activities having critical risk are diverse and the climate can vary widely، more sophisticated services are needed to meet the demands، cope with hazards and decrease risk. Understanding how women rice farmers deal with risk is essential for educators، and agriculture-related industries such as insurance، and policymakers. If the attitudes of these women towards risk are accurately recognized، risk management strategies، risk-related educational programs and risk strategies can be designed to meet their needs. The overallaim of this research isto investigate factors affecting risk management، and proposing and designing a model among rice cultivating women in Sari. The population of the study comprised 1677rice cultivating women in Sari of whom 248 were selected through stratified random sampling. A combination of quantitative، and descriptive-inferential statistics served as the methodology for the study and SPSS 16 and LISREL were applied for data analysis. To determine the validity of the questionnaire، copies were distributed to experts in the field and their comments were recorded and relevant corrections were made. Corrected content validity was determined by experts at the Agricultural Organization of Mazandaran province، then reliability of the questionnaire was assessed by random completion of 30 questionnaires by women rice farmers in Qaem Shahr by interview and survey. Cronbach’s alpha and ordinal theta were 0. 84 and 0. 89، respectively. The questionnaire contained questions about age، work experience، area of owned land، extent of financial difficulty related to rice farming، and educational level of the women rice farmers. The questionnaire contained questions about risk management approaches (17 questions)، sources of information for women rice farmers in Sari (12 questions) and sources for borrowing funds (7 questions). The Likert scale was: none (0)، very low (1)، low (2)، moderate (3)، high (4)، and very high (5). The average age range of women in the study was 46. 68 years and their relative work experience was 26. 17 years. The average financial difficulty for the women was high. The woman rice farmers were most likely to obtain loans from friends and neighbors and also to obtain financing from winning lottery. There was a significant positive relationship between information resources، borrowing resources، extent of financial difficulty، rice cultivation experience، and educational level with risk management methods. Tabatabaee et al. (30) stated that the extent of borrowing affected risk management. Tiraee (31) pointed to agricultural experience affecting risk management. Monfared (21)، Torkamani and Ezatabadi (33) and Garavandi and Alibige (10) believe that the level of education affects risk management،which is consistent with the results of this study. Structural equation modeling showed that information sources influenced the use of risk management methods. Structural equation modeling showed that information sources had an effect on risk management rate which is consistent with the results of Tabatabaeeet al. (30) and Stevenet al. (29). The results indicate that the average age of women was 46. 68 years and their average work experience was 26. 17 years، which represents a good work experience on paddy land. Women should be encouraged to pursue off-farm income sources and occupations as risk management methods. Collaborative rice farming and consulting agricultural experts are other forms of risk management. Recommended sources of information were the Internet، Jihad-e-Keshavarzi management and service center، participating in agricultural extension classes، educational publications and communicating with agricultural experts. Women farmers should be encouraged to increase their knowledge and awarenessabout the sources of risk and this can improve risk management. This should be regarded as a mission for agriculture extensions. Borrowing sources، the extent of farmer financial difficulties، work experience and educational level should be considered when risk management methods for women rice farmers are advocated.

Agricultural activities have been always faced with production, price and income fluctuations. At the time, attention to management procedures can be very useful in order to reducing these fluctuations. Income insurance with covering risks due to fluctuations in prices and production, able to covered the fluctuations of crop income. The purpose of this study is to design income insurance in order to reducing the income fluctuations of Darab cotton tillers. Required information were collected through questionnaire which was conducted in a sample 50 Darab cotton farmers by a multi stage sampling random method. Furthermore, due to forecasting futures values, time series data that collected from various recourse of cotton tillers cooperative union and agriculture organization was used. For computing the insurance premiums, a statistic simulation method called bootstrapping was used. The results relative to computed income insurance premiums, analyzed with two hypotheses such as direct and indirect relationships between yield and price. Ultimately, it became clear that applying direct relationship between yield and price due to negative correlations of these two variables can cause reduction of income insurance. Comparing the present value with computed income insurance premiums showed the superiority of income insurance scheme. The value of income insurance premiums for poor and rich farmers with assumptions "0.9 loading coefficient and 65% government subsides", computed 0.81789 and 25.60451 dollars respectively. At the end its presented suggestion to aim the appropriate risks management. The most important suggestion is creation a bilateral solidarity between farmer and insurer, Another one is election of income insurance scheme as final policy for poor group.

The purpose followed in this descriptive correlational research was to investigate factors influencing the adoption of risk management in industrial dairy farmers in Tehran Province. Population of the study included industrial dairy farmers in commercial animal husbandries in Tehran Province (N=320). A cluster sampling technique was employed to select the sample in the study (n=175). Data was gathered through questionnaire. Validity of the instrument was established by the help of a panel of experts. A reliability analysis was conducted in which Cronbach''s Alpha coefficient was recorded from 0. 78 to 0. 94. Findings of the study indicated that a majority (49%) of the industrial dairy farmers’ risk management was considered to be at a «moderate» level. The results showed the main methods for risk management among industrial dairy farmers to include: consultation with experts and specialists، as well as employment of veterinary help. There was a statistical significant positive relationship observed between distance from the help husbandry farm and the manager''s site of residence، the awareness of risk factors، size of capital، annual income، number of livestock، and the level of use of informational channels vs. the level of risk management among the farmers. The results of the multivariate regression revealed that 50. 90 percent of variability in risk management stems from: size of capital، annual income، and the degree of awareness regarding risk factors.