مجله تحقیقات اقتصاد کشاورزی
سال دوازدهم شماره 3 (پاییز 1399)

The purpose of this study was to investigate the role of efficiency in the transmission of climate and price shocks on farmers' behavior. The hypothesis of this study is that efficient farmers in the agricultural sector are more resilient and less vulnerable to climate and price shocks. In order to test this hypothesis, data envelopment analysis approach and positive math planning model were used. Data needed for this purpose were collected from the Agricultural Jihad questionnaires in Razan township, north of Hamedan province. The findings indicate that, due to the effects of climate change, farmers' groups are less effective than inefficient farmers and have more resistance. Also, farmers are less effective than price changes, which reflect the stable situation of this group of farmers in relation to these shocks. Therefore, it can be inferred that moving towards a productive boundary can be a means to reduce the impact of climatic hazards, markets and fluctuations in agricultural production in the studied area.

The dairy industry has a special place in the global food industry. The theme of byproducts is to reduce waste, create high added value and reduce the corresponding environmental effects as part of the components of the dairy supply chain. Because of the nutritional value and also the cost of producing these products, measures to reduce waste and provide more food are economical. Among the byproducts in the process of processing dairy products, whey is considered to be the most important and nutritious ingredient. The present paper tries to develop a model in the supply chain of dairy products and add the variable of the decision of byproducts to it, a step towards achieving these goals. By analyzing and analyzing the new model using data from the dairy industry in Kurdistan province, the profitability of this chain increases significantly after affecting the effect of whey production.

In this study, physical and economic water productivities of agronomic and horticulture crops of Dezful city were calculated, and the priority cultivation of these crops was determined in the 2016. A regression model was used to investigate factors affecting water productivity. Necessary data were collected using stratified random sampling by completing a quetionaire of 221 farmers. The results indicated that maximum physical productivity is related to lettuce (22.8 kgh-1), carrot (15.03 kgh-1) and onion (9.19 kgh-1) and minimum physicsl productivity is related to orange (0.67 kgh-1) and grapefruit (0.84 kgh-1) respectively. The results also indicated that variables such as type of crop, age, experience and education level of farmers, planting area, nonagricultural job, kind of water source and irrigation method affect physical water productivity and variables such as age and experience of farmers, nonagricultural job, soil texture and type of water source affect economic water productivity.

The current study with the purpose of identifying and categorizing the driving factors influencing on consumers’ acceptance of SMS advertising was accomplished in a society include 259 customer of Agriculture Bank in Tehran. The results of using structural equation model show that Financial Rewards, Credibility, Perceived Social Utility, Control, Perceived Utility and Context Utility affect significantly on SMS advertising acceptance which creditability, finance rewards and control were the most important ones. Continuously by applying fuzzy Topsis technique, 22 sub criteria were categorized that “permission to sending SMS”, “delivering SMS match private needs” and “encourage to more usage of mobile phone and pay attention to SMS” with approximate weights 0.624, 0.471 and 0.448 were selected as the most important sub criteria. Finally, by using AHP technique, 3 criteria of advertising acceptance were ranked which “positive attitude about advertising” (0.37) was the most and “tending to accepting advertising by SMS” (0.31) was the least important ones. Attending to the results, managers are advised to send related SMS in terms of customers’ needs and desires.

This study aimed to design a new product performance model based on market orientation and innovation speed in the leather industry has been done. While this study is essentially an applied research and it is descriptive survey. Field data was collected using questionnaires in 2017 by referring to 200 managers and directors of leather manufacturing and sell units in Tabriz Township, that were selected randomly. Data analysis, testing hypotheses, and also fitting the conceptual model of research was performed using structural equation modeling and LISREL software. Findings indicate, market orientation in form of intelligence generation, intelligence dissemination and responsiveness influences new products performance positively and meaningfully, both directly and indirectly through innovation speed, and also have positive and meaningful effect on innovation speed. The results were obtained by surveying relationship between independent variables show, intelligence generation and intelligence dissemination have a significant effect on responsiveness to market intelligence. Finally, intelligence generation has a positive and meaningful effect on intelligence dissemination.

The purpose of this study was to investigate the effect of real exchange rate uncertainty on Iran's agricultural imports for the period of 1977-1389 and predict the level of Iranian agricultural imports by 1404 using GARCH, VAR, VECM and ANN methods. For this purpose, a generalized autoregressive conditional heterogeneity variance model was used to index the real exchange rate uncertainty, using autoregressive patterns and vector error correction for estimating co-integration and short-term and long-term coherent relationships and finally for prediction of artificial neural network method. The results showed that there is an indirect relationship between the real exchange rate fluctuations and consumption pattern of the society on agricultural imports and the direct relation between oil revenue variable and the absorption variable on agricultural imports. Then, comparing the efficiency of self-regression models and Vector Error Correction Model and artificial neural network, a neural network designed to predict the import of Iranian agricultural sector for the period 1396 to 1404 was used under a scenario and exogenous predictions were .....

In this study, the technical, allocative, cost and profitability efficiencies of potato cultivation were studied, using the Published data of the Ministry of Jihad-e-Agriculture for the 2014-2015 crop year. Based on the findings of input orientated and fixed return to scale approach, the average technical efficiency of potato production was 0.917 and in the output orientated with variable returns to scale, it was 0.970. According to the results, it was possible to increase the technical efficiency. The lowest and highest input efficiencies were 0.88 and 0.91 for labor and seed inputs, respectively. According to the results, average allocative efficiency was 0.708 and the lowest score belonged to Yazd province (0.247). In terms of cost efficiency, the lowest and most scores were related to Kermanshah and Yazd provinces with 1 and 0.247, respectively.

That is why literature marketing of agricultural products, marketing is more important than production is emphasized. The aim of this study was to investigate marketing melon Taybad County and the factors affecting it. In order to achieve the objectives of the study, the melon market margins; factors affecting it, and the producers, wholesalers and retailers in the market was paying. Results have shown an average of 12% of the price the consumer pays, the cost of marketing. The average cost of total marketing margin melon 4715 (IRR) is. The marketing margin for the wholesale marketing margin was estimated. Also the results show that the producer's share of the total margin of 61.26 percent, respectively. Stake in retail sales of 9.8 percent and 87/28 percent.

Analysis financial distress is an important phenomenon for investors, creditors and other users of financial information. Determining the probability of a company’s distress before occurrence of distress and bankruptcy is considered a very interesting and attractive subject and can be useful for both managers, and investors and creditors. In this study, using the information of 6 financial years during the period 2011 to 2016 in industry agriculture and food materials industry, the factors affecting financial distress and predicting it through methods based on machine learning (NBC and AdaBoost) have been studied. The results of the study indicate direct impack and inflationon, indirect impact of the ratio of non-executive directors, Stock returns, the ratio of operating cash flow financial distress. The results also show that AdaBoost method, using financial and economic data, has higher capability in predicting financial distress compared to NBC method.

The purpose of this study was determination of technical efficiency for Sirjan dairy farms using fuzzy data envelopment analysis approach. The underlying assumption of this method unlike conventional data envelopment analysis approach is that input and output data have imprecise. Since activities of agricultural and animal husbandry is done under environmental uncertainty conditions there is uncertainty about inputs and outputs. Therefore employing fuzzy data envelopment analysis is preferred into conventional data envelopment analysis. Necessary information for this study was collected through filling questionnaires for the years 2017 from 32 units of dairy farms in Sirjan. The result showed that the average technical for dairy farms was 81 percent. It has undulate from at least 36% up most 100%. In the other words, can increase amount of efficiency without changing the level of technology and better use of current technology. Also the gap between the best and the worst producer was 64% that can be improved by increasing technical and managerial knowledge, more promotion and new sciences and techniques among the dairy farms of the region.

Good governance consists a set of norms and values. In this research, we first use the Meta-synthesis method to find the important factors of agricultural governance worldwide. We have Iranian experts for ranking the variables by using the Shanon Entropy method. These experts weigh the variables by a pairwise comparison matrix of Fuzzy method. The results of the Meta-synthesis model show that international policy, group participation, and observance standards have the highest importance and rank. However, the Type-2 Fuzzy analysis the factors of agricultural sustainability, group participation have the highest weight in the political, social and environmental areas and the factors of increase production, and marketing have the highest weight in the economic area.

According to government`s policies role on production and utilization of all production factors in agriculture section, it is performed compared study of good governance indexes effect in this research by panel algorithm and 3SLS which are rule of law, corruption control, Government Effectiveness, quality law, responsibility and policy stability on production and utilization of all production factors in chosen developing and OECD countries agriculture section in 2000-2013 period time. Effects show that governance index have negative effect on agriculture section productions value and utilization of all developing countries factors and this effect is positive for section countries. In among of good governance six-indexes, corruption control with limit of -0.079 in group of developing countries and rule of law with limit of 0.075 OECD countries have been highest effect on agriculture section production. Effects show that if no utilizing appropriate policies and programing happen to reduce production value by government.