AbstractAgricultural activities are inherently riskier than other types of production and are often accompanied by inefficiencies. Therefore, studying risk and inefficiency simultaneously can help enhance productivity. The statistical population in this study consisted of rice farmers in Rasht County. Based on data from the Agricultural Jihad Organization of Guilan province (2016), the total number of farmers at the time of the study was 38,763. Using Cochran’s formula, the required sample size was calculated to be 226, representing approximately 58 percent of the population. The questionnaire consisted of two parts: one focusing on the inputs used in the rice production process, and the other on the socio-economic characteristics of farmers and their farms. To simultaneously evaluate the technical efficiency and production risk of rice farmers in Rasht County in 2018, a generalized Stochastic Frontier Production (SFP) model with flexible risk properties was employed. The results of estimating production risk function showed that (i) rice production was significantly affected by land, seed and labour inputs; (ii) land, water, age, and gender variables were risk-increasing factors; (iii) seed, herbicides, machinery, farmer’s education, family size, and farming experience were risk-reducing inputs; (iv) seed, labour, membership in the agricultural cooperatives and insurance increased technical inefficiency; and (v) nitrogen fertilizer, water, gender, experience, and participation in educational and promotional programs reduce technical inefficiency in the studied area. The results of estimating technical efficiency showed that the average technical efficiency of the rice paddy field was 93.47 percent and 96.27 percent with and without a risk component, respectively. Therefore, it is clear that estimating the model without a risk component leads to biased results of technical efficiency. In conclusion, it is recommended that the risk component be considered when measuring the technical efficiency of paddy fields to achieve sound risk management and highly efficient production.
Introduction The economy of countries are always exposed to shocks, including the Covid-19 pandemic, which causes many problems. The Covid-19 pandemic had various effects and consequences in different sectors, including the agricultural sector. The decline in income and production, coupled with the loss of customers due to health quarantines and border closures, severely impacted farmers businesses and created many problems for activists of various sectors of the agriculture. One of the most important effects of the Covid-19 pandemic is the decline in global economic growth. This has led to increased unemployment, decreased purchasing power among the population, and consequently, a decrease in demand. According to the impact of the covid-19 pandemic on food demand resulting from disruptions in the supply chain and income shocks, this research aims to investigate the existence of a structural break in the preferences of Iranian consumers for livestock products (red meat, chicken, eggs, and milk) using the Quadratic Almost Ideal Demand System (QAIDS) and the switching regression framework developed by Ohtani & Katayama (1986) during the period from Spring 2015 to Winter 2022. Materials and Methods Nonparametric and parametric approaches are utilized to investigate structural break in consumer preferences. This research employs parametric approaches and the Quadratic Almost Ideal Demand System to assess the structural break. The switching regression framework proposed by Ohtani and Katayama (1986) is utilized to model structural changes in preferences. In fact, a time transition function is incorporated into the demand system. Based on the characteristics of demand in the literature of structural changes, the Bewley likelihood-ratio test is applied to select an appropriate model. To evaluate the structural break and calculate the price and income elasticities, the price and per capita consumption data of livestock products are required, and in this research, seasonal time series data for the period of spring 2015 to winter 2022 have been used. The information related to the price of livestock products was obtained from the Joint Stock Company of the Support of Livestock Affairs. To obtain the per capita consumption, first, the information on the amount of production of red meat, chicken, milk, and egg are received from the joint stock company for livestock affairs. Then, by summing the amount of production and the amount of import of red meat, chicken, milk and eggs and deducting the amount of export from the said amount and dividing it by the population of the country, the amount of consumption per capita are calculated. The amount of export and import of red meat, chicken, milk and eggs is taken from the export and import report of the Ministry of Agriculture (Jihad), which is published monthly. Results and Discussion To estimate the system equations, one equation was removed, and the remaining equations were solved and estimated based on the removed equation. Accordingly, the equation related to milk was removed and the QAIDS with 33 parameters and three equations including those related to red meat, chicken and egg were estimated using the maximum likelihood estimator non-linearly. The results show the Based on the statistics of log-likelihood and DW the existence of a sudden structural break as a result of the Covid-19 pandemic. Comparing the Bewley likelihood-ratio test statistics calculated for an Non-Restricted QAIDS (with structural break) and a Restricted QAIDS (without structural break) with a critical χ^2 value with degrees of freedom of nine at the probability level of 5% indicates that the Non-Restricted QAIDS is selected as the appropriate functional form. Also, the results show that after the Covid-19 epidemic, the own price elasticity of red meat and chicken has increased significantly. Considering the high elasticity of the price of red meat, chicken and eggs after the Covid-19 epidemic, it is suggested that the government utilize price tools such as electronic coupon system to support consumers. Conclusion Due to the high cross-elasticity coefficients of demand for red meat, chicken and eggs after the Covid-19 pandemic, it can be expected that a change in the price of one of the red meat, chicken and egg products will significantly change the demand for the other product. Therefore, in case of a price increase in one of the products, it is suggested to consider special discounts for other products to support the consumers.
AbstractOne of the essential goals of societies, primarily developing and underdeveloped countries, is to eradicate poverty and achieve sustainable development. As vulnerable individuals in many communities’ face growing economic, environmental, and political challenges, proactive crisis management by governments and policymakers—aimed at increasing the productivity of key economic sectors such as agriculture—has become essential. The efficiency of the farm sector is not only crucial for ensuring national food security, but it also significantly impacts the livelihoods, incomes, and resilience of rural smallholders. The purpose of this study is to investigate the impact of agricultural support policies on the resilience of rural farmers in the Fariman region. The study area is the Hossein Abad Rekhneh Gol village, Iran, and the data were collected through documentation and the use of questionnaires. The Resilience Index Measurement and Analysis (RIMA) introduced by the FAO has been used to determine the resilience of rural farmers. Additionally, the distribution of subsidized fertilizers to farmers as a common agricultural support policy in the country has been chosen. The impact of this agricultural support policy on the resilience of rural farmers has been estimated using the propensity score matching method in this study. The study results indicate that households eligible to receive subsidized fertilizers have higher resilience on average compared to households that are not eligible. Based on the research findings for the study area, it is recommended that rural smallholders be prioritized in the allocation of subsidized fertilizers, which is constrained by quantity and budget limitations imposed by the government, compared to large-scale farmers. Additionally, facilitating rural farmers’ access to the available agricultural wells owned by non-private institutions can potentially improve farmers’ resiliency.
Introduction The seed industry is a growing industry in the world, and the role of processed seeds in increasing the production performance is undeniable. Due to the population growth, the importance of achieving food security is increasing. Healthy seed is one of the important factors in the development of agricultural production. Although agricultural production systems have increased their production, it does not seem to be enough, though. The basic problems of the seed market and insufficient supply of seeds required by farmers have made it necessary to identify samples of seed quality development. The current research was the first research at the national level dealing with the design of a conceptual model for the development of control and certification of wheat seeds using the grounded theory method and prioritization of effective factors. Materials and MethodsThis research had a fundamental-applicative goal and was applied in at two stages. In At the first stage, after designing the interview questions, the grounded theory was carried out in three stages of open, central, and selective coding using a systematic approach in order to design a conceptual model. After designing the paradigm model and identifying the factors affecting the development of seed control and certification, the prioritization of the components was done including technical, social, economic and structural criteria using analytic network process. Results and DiscussionAfter analyzing the interviews, 140 initial codes were identified and the initial codes were reduced to 94 and then to 47 concepts. In the following parts, 11 core categories including processed seed production standards, laws and regulations, environmental factors, regulatory factors, equipment and technology, stability in the seed market, government support policies, human factors, wheat seed quality, attitude and awareness, and economic infrastructure were identified. The results of prioritization among the four effective criteria on the development of seed certification indicated that the technical criterion was more important than the other three criteria. In terms of the prioritization of the components, the quality of the seed kernel having a weight of 0.49, the performance of the responsible expert having a weight of 0.44, the cost of producing processed seeds having a weight of 0.39 were the first priority of technical, social, and economic criteria. Applying the ranking of production units with a weight of 0.57 and making the seed market competitive with a weight of 0.26 were more important than other components of structural criteria. ConclusionAccording to the results of this study, and the first priority of the technical criterion, it is suggested to monitor the quality of seed kernels and select appropriate farm inspectors. Moreover, in order to strengthen the human resources system, it is recommended to hold continuous courses in the field of seed quality. To implement the solutions of the paradigm model, it is recommended to prevent buying and selling unhealthy seeds and balance the costs of producing and selling processed seeds.
AbstractThe COVID-19 pandemic presented major global challenges, including a decline in per capita income growth across all income groups in 2020. The protein sector, particularly Animal-Source Foods (ASF) faced increased pressure on both supply and demand, resulting in price volatility. This study examines how income shocks affected food expenditure patterns and consumption behavior, with a focus on protein-rich ASF. Utilizing the QUAIDS model, budget data from Iranian households in rural and urban areas were analyzed for 2019 (pre-pandemic) and 2020 (during pandemic). The findings yield three key insights: (1) The average food expenditure share rose from 37% to 42%, with a sharper increase in rural areas; (2) Positive expenditure elasticities were observed across the six ASF groups including livestock meat, poultry, aquatic animal products, dairy, eggs, and fats, while own-price elasticities were relatively smaller; and (3) Welfare losses across ASF groups ranged from 2% to 24.2%, driven by policy imbalances, supply chain disruptions, and unequal utility distribution. Rural households experienced greater welfare losses in all ASF categories except fats. The study recommends targeted interventions: price-based support for urban areas and expanded social services for rural regions. To strengthen policy responses and enhance long-term food security, future research should assess the potential for substituting plant-based proteins as sustainable and cost-effective alternatives. These findings offer valuable guidance for policymakers aiming to improve nutritional resilience and economic stability in the post-pandemic era.
Introduction This research investigates the capacities and factors influencing entrepreneurship development in the rural areas of Hamun County. Given the importance of entrepreneurship in creating employment, reducing poverty, and improving the quality of life in rural regions, identifying and analyzing key factors in this context is essential. The significance of rural entrepreneurship lies not only in its potential to stimulate local economies but also in its ability to foster social cohesion and community development. As highlighted by Petrin (1992), entrepreneurship serves as a central force for economic growth in rural areas, and without it, other developmental efforts may prove ineffective. Thus, understanding the dynamics of rural entrepreneurship is crucial for policymakers and stakeholders aiming to enhance the livelihoods of rural communities. In light of the challenges and opportunities present in rural entrepreneurship, this article aims to identify effective factors influencing entrepreneurial development while reviewing existing literature. By categorizing these factors into human and individual, infrastructural, cultural, economic, and social dimensions, the study seeks to provide a comprehensive analysis that can inform future initiatives aimed at strengthening entrepreneurship in these areas. The findings are expected to offer practical recommendations for enhancing the entrepreneurial ecosystem in Hamun County. Materials and Methods The present study utilized a stratified random sampling method, involving 278 entrepreneurs and individuals active in rural business sectors. The research categorized influential factors into six primary groups: human and individual factors, infrastructural factors, cultural factors, economic factors, and social factors. Data analysis was conducted using Stata and Excel software to model relationships among these variables effectively. This structured approach allows for a nuanced understanding of how different factors contribute to or hinder entrepreneurial development in rural contexts. Results and Discussion The results indicate that "government support and subsidies for production," "income," and "diversification of rural products" play significant roles in explaining and influencing entrepreneurial behavior from an economic development perspective. In terms of cultural and social aspects, "experience," "consultation and support services," "awareness levels," and "interest in village improvement" were found to have substantial impacts on entrepreneurial behavior. From an infrastructural standpoint, "access to services and facilities" along with "access to a dynamic rural environment" emerged as critical determinants explaining the variance among extracted factors. Furthermore, regarding individual aspects of entrepreneurial development, findings revealed that "motivation," "education," "psychological resilience," and "management creativity" significantly contribute to explaining variations in behavior among entrepreneurs. The results indicated that among various influencing factors on entrepreneurship development, economic factors, cultural and social factors, institutional and educational factors, as well as infrastructural factors had positive and significant effects on the likelihood of individuals achieving high levels of entrepreneurial motivation. Conclusion Among the identified indicators, government support and subsidies for production had a more substantial impact on income levels while diversification of rural products significantly influenced entrepreneurial behavior from an economic development perspective. In terms of cultural and social dimensions, experience, consultation services, awareness levels, and interest in village improvement were crucial for explaining variations in entrepreneurial behavior. From an infrastructural perspective, access to services and facilities alongside access to a dynamic rural environment played a decisive role in explaining the variance among extracted factors. Finally, individual development aspects revealed that motivation, education, psychological resilience, and management creativity significantly contributed to variations in behavior among entrepreneurs. The findings suggest that within the studied villages—specifically Mohammadabad, Ali Akbar Town, Dek Dehmardeh Town, Sanjoli Town, Mir Town, Bandei Town, and Kermani—there are ideal conditions for entrepreneurship compared to other assessed villages. Furthermore, using an ordered logit model revealed that economic indicators along with cultural-social factors significantly influence individuals' motivations for entrepreneurship. This expanded introduction provides a comprehensive overview of your research topic while highlighting its significance within the broader context of rural entrepreneurship development.
Abstract The importance of understanding consumer engagement with digital marketing in agriculture is highlighted by the rapid evolution of digital platforms, which are transforming traditional marketing approaches. This study investigates the factors influencing consumer intentions to engage with digital marketing of agricultural products in Urmia, Iran. Data were collected from 385 respondents through a structured questionnaire and analyzed using a logistic regression model. Results indicate that perceived usefulness, perceived ease of use, trust, information quality, and social influence positively and significantly impact engagement intentions. Demographic factors such as age (negatively), education level, and income (both positively) also play significant roles. Notably, prior online purchase experience emerged as a strong predictor of engagement intention, while price sensitivity showed a marginally significant negative effect. The study contributes to the literature by providing empirical evidence from a developing country context and offering a comprehensive model for understanding consumer behavior in digital agricultural marketing. Implications for marketers include developing user-friendly platforms, prioritizing trust-building mechanisms, and tailoring strategies to different demographic segments.
Introduction The agricultural sector in Iran holds significant importance due to its substantial capabilities and capacities. This sector is full of risk and uncertainty. Risks and crises significantly influence producers’ behavior, shaping both the income derived from their products and their decisions regarding input use and product supply. Since individuals’ attitudes toward risk vary, effective risk management in the agricultural sector is a critical concern for farmers and stakeholders alike. Risk management encompasses the application of diverse methods, tools, and policies designed to mitigate the adverse impacts of different types of hazards. Risk and crises influence the behavior of producers, and the outcomes of these are reflected in their effect on the income generated from products and farmers' decisions regarding the use of inputs and product supply. People's attitudes toward these risks differ. Therefore, risk management in the agricultural sector is a critical issue for farmers and stakeholders in this field. Risk management refers to the use of various methods, tools, and policies to reduce the negative impacts of various types of hazards. Strategies such as crop diversification, contract farming, producing crops in exchange for guaranteed prices, and intercropping complementary crops can help mitigate their negative effects by spreading or distributing risks among individuals, organizations, products, and different options. Given the importance of this issue, the present study investigates the impact of risk aversion on crop diversification in the northern Rudpay region of Sari County. Materials and Methods In this study, the degree of risk aversion is calculated using the Multi-Attribute Utility Function (MAUF) method. This technique is based on calculating the weight of risk and, as a result, the risk aversion coefficient. This method is based on weighted goal programming. In this research, the two-stage cluster analysis method is used to classify the risk aversion coefficient. Finally, to examine the impact of risk aversion on crop diversification, the Tobit model will be used. The degree of crop diversification will be analyzed using the developed Herfindahl index. The data required for the research, such as water, land, fertilizer, and capital, were partly provided by centers affiliated with the Ministry of Jihad Agriculture in Mazandaran Province. The rest, such as the cropping patterns of each farmer, were collected through the completion of questionnaires and using simple random sampling in the northern Rudpay region. Results and Discussion Based on the classification, only one farmer is considered risk-neutral. This indicates that this individual among the farmers of the northern Rudpay region is indifferent to risk and chooses activities without considering their level of risk. In other words, the presence or absence of risk in performing activities is not a concern for them. The next category, which includes 24 individuals, indicates that 10% of the farmers have low risk aversion. The final category shows that 225 individuals (90%) of the sample fall into the high-risk aversion category. Therefore, as observed, the dominant tendency among the studied individuals is high risk aversion. This result suggests that farmers in the region are only willing to adopt new phenomena, such as modern programs and technologies, if they expect or anticipate a higher return compared to the current situation. The results of the Herfindahl index analysis show that the average crop diversification index is 0.57, which, according to various studies, is a reasonable and acceptable value. Nearly 70% of the farmers, with an index below the average Herfindahl value, have crop diversification and include different products in their cropping patterns. Furthermore, the results indicate that there is no significant relationship between crop diversification and the farmer's age, while variables such as the risk aversion coefficient, the farmer's education, farm size, and the share of agricultural income have a significant effect on crop diversification. Conclusion Considering that agricultural products are generally produced in a risky and uncertain environment, this study aimed to calculate the degree of risk aversion of farmers in the northern Rudpay region of Sari County using the Multi-Attribute Utility Function. The results from determining the risk aversion level of farmers in the northern Rudpay region in the first part of the study show that the majority of farmers in the region have a strong degree of risk aversion. The results of examining the impact of socio-economic variables on crop diversification show that there is no significant relationship between crop diversification and the farmer's age. However, variables such as the risk aversion coefficient, the farmer's education, farm size, and the share of agricultural income have a significant effect on crop diversification. The share of agricultural income had the most significant impact on the choice of management tools for crop diversification. Specifically, as the share of income from agriculture increases, the likelihood of using management tools increases by 0.06%. Given the positive impact of education and income on the use of risk management tools, it is recommended to enhance farmers' awareness through agricultural extension programs and increase farmers' income by improving their cropping patterns.
Introduction Rice is one of the oldest and most important cultivated crops and consumed food items in the world, and half of the world's population depends on rice as a staple food. This product is of great importance in the food basket of Iranian households, and as a basic and strategic commodity, its supply through domestic production and imports plays an important role in ensuring the country's food security. Over the past two decades, the Iranian rice market has undergone notable transformations. The increase in rice imports, coupled with a decline in domestic production, has gradually diminished the share of Iranian rice in household consumption baskets. Imported rice, particularly from neighboring countries like India and Pakistan, has gained popularity due to its competitive pricing, adequate quality, and effective marketing strategies, replacing domestic rice in many cases. These trends have raised significant concerns about whether such changes signal a fundamental shift in consumer preferences or merely reflect temporary market dynamics influenced by external factors. The objective of this study is to critically analyze the stability of consumer preferences for rice in Iran using advanced non-parametric methodologies, specifically the Weak Axiom of Revealed Preferences (WARP) and the Generalized Axiom of Revealed Preferences (GARP). By doing so, the study seeks to distinguish between structural changes in consumer loyalty and transient factors shaping consumption patterns. Materials and Methods This research investigates consumption preferences for domestic and imported rice over a twenty-year period, from 2003 to 2022. The analytical framework includes constructing normalized WARP matrices to evaluate the adherence to revealed preference principles, coupled with statistical tests like the Kruskal-Wallis test to assess the stability and coherence of consumer choices over time. Price and per capita consumption data for domestic and imported rice were meticulously sourced from national databases, normalized using grain-specific consumer price indices to account for inflationary effects, and analyzed computationally using MATLAB software. This methodology allows for a comprehensive exploration of preference dynamics while ensuring the robustness of statistical evaluations. In addition to quantitative analyses, the study considers qualitative aspects of consumer preferences, including cultural and economic factors that may influence purchasing decisions. Results and Discussion The results indicate a strong resilience in consumer loyalty towards domestic rice, despite temporary increases in the market share of imported alternatives. Four instances of violations in consumer preferences were observed during the study period; however, these violations were determined to be transient and attributable to non-systematic shocks, such as seasonal consumption trends, temporary price fluctuations, or short-term economic pressures. The Kruskal-Wallis test confirmed the stability of consumer preferences by indicating no statistically significant structural breaks. Similarly, GARP analysis validated the rationality and consistency of consumer behavior, as all violations remained within the acceptable margins of measurement error, suggesting no deviation from stable preference patterns. These findings align with previous studies examining consumer preferences, reinforcing the notion that Iranian consumers exhibit steadfast loyalty to locally produced rice. Moreover, the study highlights the temporary nature of market pressures favoring imported rice, emphasizing the opportunity to reestablish the competitive edge of domestic rice through targeted interventions. Conclusion The findings of this study highlight the persistent preference of Iranian consumers for domestic rice over the past two decades, despite competitive pressures from imported rice in terms of price and quality. To promote the sustainable growth and competitiveness of the domestic rice industry, this study proposes several strategic recommendations:
Introduction Medicinal plants, as a group of plants originating from natural resources and possessing therapeutic properties, play a remarkable role in health, employment, and economic development of the human being. The cultivation of medicinal plants has garnered significant attention in recent years in the Mazandaran Province, particularly in rain-fed farmlands. These cultivations could generate considerable added value within the sustainable agriculture framework, increase farmers' income, and, as a result, mitigate rural-to-urban migration. Nevertheless, despite efforts to develop these cultivations, various challenges still exist in their sustainable development pathway. Materials and Methods This study aimed to identify the development pattern of medicinal plant' cultivation in the rain-fed farmlands of Mazandaran Province. To do so, the grounded theory was employed for data analysis. The study population comprised 16 experts, specialists, and pioneering farmers who were actively working in the medicinal plants' field of Mazandaran province and were selected through a purposive sampling method. Data were collected through in-depth semi-structured interviews and analyzed using MAXQDAV24.4.1 software. A three-stage conventional content analysis process, including open, axial, and selective coding, was utilized to recognize the relationships between components and factors that influenced the development of these cultivations. According to the findings, five main components influencing the development of medicinal plant cultivation were detected in the rain-fed farmlands of Mazandaran Province. Results and Discussion The first and most important detected component was "the causal conditions' component", which included the following subcategories: the role of medicinal plants’ cultivation in employment, added value, the improvement of agricultural economics in the rain-fed farmlands, production management and expansion of processing companies active in the medicinal plants’ value chain, and finally focusing on cultivation of sustainable, industrial, and high-demand medicinal species. Farmers require accurate information and technical support for the successful cultivation of medicinal plants, which should be provided by governmental and private institutions. The second obtained component was named the contextual conditions' component", which was primarily attributed to the following subcategories: market challenges, ecological and environmental capacities of the rain-fed farmlands used for medicinal plants' cultivation, climatic capacities, suitable lands of the province, and weaknesses in processing and supplementary industries. Mazandaran Province has extraordinary potential for cultivating various medicinal plants because of its climatic diversity and suitable soils. Furthermore, noticeable market opportunities for medicinal plants, especially in the pharmaceutical and food industries, would motivate farmers to grow larger amounts of them on their farms. The third component was called "intervening conditions, which was predominantly attributed to the following subcategories: selecting compatible plant species with the region's ecosystem, the necessity of farmers' financial and institutional support, difficulties in trading medicinal plants, and eventually structural and planning challenges. The lack of advanced processing industries and weaknesses in the marketing of medicinal plants are among the distinguished bottlenecks preventing farmers from exploiting these plants. The fourth component was determined as the strategies' component", which included the following subcategories: empowering farmers, education and extension of sustainable cultivation, utilizing mechanization in agriculture, providing financial facilities, supporting farmers through guaranteed purchases, and modelling and showcasing medicinal plant cultivation in the model sites and pilot projects. The use of modern agricultural techniques and continuous training of farmers can reinforce the cultivation of medicinal plants. Furthermore, financial support and improved access to financial resources, particularly for small- and medium-sized farmers, are indispensable. The fifth component was identified as "the consequences' component", which referred to the following subcategories: improving sustainable employment, utilizing specialized human resources, and developing the economic situation of rural communities. Developing medicinal plant cultivation could lead to employment generation in various sectors, including the production, processing, and marketing of medicinal plants, and could improve farmers' livelihoods and reduce their migration rates. Conclusion Based on these findings, a comprehensive and multifaceted approach is necessary for the sustainable development of medicinal plant cultivation in the rain-fed farmlands of Mazandaran Province. In addition, strengthening infrastructure and processing industries, financial support, and required facilities should be considered by both the government and private sectors. Developing stable markets through guaranteed purchases and establishing strong supply chains can effectively reduce production risks. Education and extension of sustainable agriculture, and adoption of modern technologies are also crucial factors that are compulsory for the success of these cultivations. Ultimately, considering the favorable ecological conditions and existing potential of Mazandaran Province, the development of medicinal plant cultivation can be regarded as a suitable solution for the economic and social development of this province.
Investigating food consumption patterns in rural areas of Iran is necessary to understand the state of food security and social health in the country. Identifying provinces with standard and homogeneous consumption patterns not only helps improve planning to meet food needs, but also can lead to the formulation of appropriate and effective policies to address issues related to nutrition and public health. This study examined: (i) the current food consumption patterns in rural areas of Iran in 2023, compared to the standard dietary pattern; (ii) the ranking of provinces based on the similarity of their dietary patterns to the standard; (iii) the identification of similar food consumption patterns across rural regions in different provinces; and (iv) the relationship between food consumption patterns and the infrastructural, economic, and social indicators of the provinces. The methodology of this study includes statistical analysis tools, such as TOPSIS method and k-means clustering technique. The results showed that the current dietary pattern of households in rural areas of Iran mainly consists of various types of cereals, providing more than 60% of an adult's daily calorie intake. Comparing, global scale, cereals provide 50% of daily calories intake, averagely, varying from 30% to 55% and 70% in high, middle, and low-income societies, respectively. We found that food consumption in rural areas of Iran does not necessarily align with the standard pattern, meaning 28.4% lower food items than required in the standard basket, and 16% less than standard energy requirements. For instance, the consumption of bread was more than recommended level while the share of dairy products, fruits, and red meat, was 64.4%, 52.1%, and 50% lower than the recommended amount, respectively. While the dietary patterns in rural areas of six provinces - Chaharmahal and Bakhtiari, Markazi, Isfahan, Hamedan, Zanjan, and Mazandaran - satisfied the standard dietary. The converse evidence was observed for Hormozgan, Semnan, Kerman, North Khorasan, Ilam, and Sistan-Baluchestan. Between comparison of provinces confirmed (i) a heterogenous consumption pattern, mostly, dominated by five types of behavioral patterns; (ii) non-significant effect between consumption pattern and geographical distribution; (iii) a more desirable consumption pattern depending on more suitable infrastructure, economic, and social indicators. To deal with the undesirable consequences of calorie shortage and non-standard consumption pattern, this study suggests a comprehensive plan regulating supportive policies, public awareness, sustainable agriculture, and educational programs about nutrition and market access. Nutrition in rural regions is influenced by economic, regional, social, cultural, and individual factors, and improving dietary health necessitates addressing these interconnected elements.
Abstract Risk is an undeniable factor in agricultural activities, and its neglect can lead to inefficient resource allocation in the sector. Various theories and mathematical programming models have been developed to assist decision-making in cropping pattern management under risk conditions. This study aimed to determine the optimal cropping pattern for Dehgolan Plain, Iran, using data from 2014 to 2023. A linear programming model was employed to maximize farmers' gross income, and the results were compared with those from a Quadratic Programming Model and the Minimization of Total Absolute Deviation (MOTAD) model, both incorporating risk minimization. The findings revealed that risk factors can significantly influence cropping patterns. Under the highest level of risk, the profit-maximizing cropping pattern included only cucumber, alfalfa, and canola, indicating a preference for higher gross-income crops despite their greater water requirements. However, when risk was incorporated into the model, the cultivated area of wheat and barley increased compared to the risk-neutral scenario. This shift reflects a tendency toward lower water-requirement crops, even at the cost of reduced gross income. These results highlight the necessity of balancing income maximization and risk management for more sustainable cropping pattern.
Introduction Effective measures in grape production and processing are essential for understanding market needs. By leveraging acquired knowledge, products should be aligned with market demand, which requires a thorough understanding and application of the value chain. The value chain is a network of actors who are involved in the supply, production, processing, marketing, and consumption of a product or service, and its actors seek to realize added value in each of the links of the chain and add value as a whole. It is for the activities that take place along the chain. An efficient value chain plays a key role in reducing poverty and food security in the country and has inherent potential for the development of job opportunities. The benefits of the value chain include reducing production costs, increasing productivity, providing valuable services to farmers, a variety of new services with added value, innovation at a faster speed, creating new circles, creating more jobs, reducing rural poverty, transparency in the price of agricultural products, balance of supply and demand, improvement of quality and health of agricultural products, reduction of product waste, increase of product health quality, increase of real profit, consumer satisfaction, reduction of mediation and brokerage, increase of flexibility power and sustainability in production and export. Materials and Methods In this research, data was collected from each agent (link in the chain) using a questionnaire. Various methods exist for analyzing the value chain, with the SWOT analysis (identifying strengths, weaknesses, opportunities, and threats, as well as determining strategic positioning) being the most significant. This method was utilized in the study and will be briefly explained in relation to the SWOT matrix analysis process. However, since the SWOT analytical matrix generates multiple strategies without prioritizing them, the QSPM matrix was employed to establish priorities. This matrix is used in the last stage of strategy development and for selecting and prioritizing strategies. This matrix prioritizes different strategy options according to their attractiveness score. Results and Discussion In the present study; 74 components in the template (15 strengths, 23 weaknesses, 19 threats and 17 opportunities) were extracted and categorized. To evaluate the internal factors of the grape value chain with an emphasis on its yield, the internal factors evaluation matrix (IFE) was used. In this matrix, the strengths and weaknesses were listed and scored using special coefficients and ranks to determine the final score of the evaluation of internal factors. The analysis of internal factors revealed a total score of 61.2, indicating that the grape value chain in Hamedan Province is in a strong position. In other words, its internal strengths outweigh its weaknesses. Similarly, the analysis of external factors showed a weighted score of 2.87. Therefore, the grape value chain in Hamedan has an external opportunity. In other words, the opportunities of the grape value chain are more than its threats. Conclusion and Suggestions To improve this situation, the raisin value chain model was designed based on observations and research findings. This model is an executive model that has five main actors including 1- Input supply link (without timely supply of inputs and without creating a basis for the development of a competitive environment in this link, one cannot hope for sustainable production and export), 2- The link of grape growers is 3- the circle of packaging and processing factories, 4- the circle of distribution and marketing, and 5- the circle of consumption and communication with customers. This model also has a support link (providing consulting, training, and support services to investors to help create and launch new businesses within the chain) that supports all the links in terms of structure, design, research, training, financial management, and resource management. Humanity supports. These measures attract investment, create employment, develop chain links and growth, and help to achieve the goals of economic and social development of the region. The most significant missing link in the grape value chain is the production and processing of the product under a specialized brand. Establishing these processes is essential for attracting foreign markets. Given the high quality of grapes in Hamedan Province and their potential to compete with international products, it is crucial to transform this potential into reality. This requires the development of high-quality processed products to gain a competitive edge and capture market share from competitors.
Introduction Food prices are an important indicator of societal well-being, and food inflation can deepen poverty in developing economies. Severe food price fluctuations not only affect food security in developing countries, but also affect economic growth and social stability. Any increase in food prices can push many people back below the poverty line. Rising food prices hit low-income households hard, as the household food basket accounts for nearly half of household living expenses. Therefore, food price stability is of particular importance to policymakers trying to lift households above the poverty line. Food prices in Iran have always been on the rise, and even in recent years, the rate of food price growth has accelerated. Today, inflation, especially food inflation, remains a major problem in Iran, and policymakers are always trying to reduce food inflation. In this regard, and with the aim of controlling food prices, different policies have been implemented in Iran, and the effectiveness of these policies has been discussed. Therefore, understanding the behavior of food prices in response to macroeconomic factors is essential for policymakers to implement appropriate policies at the right time and place to keep domestic prices stable. In this regard, in the present study, the asymmetric effect of macroeconomic variables (money supply, GDP per capita, exchange rate, and trade openness) affecting food inflation in Iran is examined using the nonlinear ARDL approach. Materials and Methods The main objective of this study is to examine the asymmetric effect of domestic macroeconomic factors on food prices in Iran using a Non-linear Autoregressive Distributed Lag (NARDL) model. According to the theoretical literature, in this study, it is assumed that food prices are a function of macroeconomic variables, including money supply (MS), GDP per capita (GDPER), exchange rate (RATE), trade openness (OPEN), and global economic policy uncertainty index (EPU). Therefore, in accordance with Shin et al. (2014), the NARDL model used in this study is developed to examine the asymmetric effect of domestic macroeconomic factors (for example, money supply) as follows: In the above relationship, each of the macroeconomic factors (including the money supply, GDP per capita, exchange rate, and trade openness) is separated into the sum of positive and negative components. In fact, two additional variables are created in each equation, one indicating an increase in the variable of interest with a positive sign and the other indicating a decrease with a negative sign. The variable of global economic policy uncertainty index also plays the role of a control variable. Due to the availability of data, the time period in this study is 1991 to 2022. Results and Discussion The results of the linear and nonlinear bounds test in the ARDL model showed that there is a long-term relationship between macroeconomic variables including money supply, GDP per capita, exchange rate, trade openness, global economic policy uncertainty and food prices in Iran. In addition, the results of short-term and long-term symmetry tests using the Wald test showed that the effect of the exchange rate variable on food inflation in Iran is asymmetric in the long and short run, while the effect of the money supply and GDP per capita variables is asymmetric only in the long run; the effect of the trade openness variable is also symmetric in the short and long run and has a linear behavior. The results of the ARDL linear model estimation showed that in the short and long run, the effect of the growth of the variables of money supply, GDP per capita, exchange rate and global economic policy uncertainty on food inflation in Iran is positive and significant, while the effect of trade openness is negative and significant. The results of the NARDL model estimation also showed that the response of food inflation to increases and decreases in money supply and GDP growth is positive and significant, and their increase on food inflation is greater than the effect of their decrease. The response of food inflation in the long and short term to increases in the exchange rate is positive and significant, while the effect of decreasing the exchange rate in the long and short term is negative, but not statistically significant, and the effect of increasing the exchange rate on food inflation in the long term is greater than its effect in the short term. The effect of trade openness on food inflation is symmetric, with an increase in trade openness leading to a reduction in food inflation in both the short and long term. Conclusion Linking the prices of agricultural products to market conditions and liberalizing the market for these products is an appropriate method for coordinating the effects of macro policies and specific agricultural policies that should be considered by policymakers. Given the importance of the agricultural sector, the government's economic policies in relation to food prices will be of high importance and sensitivity. Considering the results of implementing contractionary monetary policies in coordination with other Central Bank policies, increasing investment and efforts to increase productivity in the agricultural sector, appropriate foreign exchange policies are recommended to prevent unreasonable increases in the exchange rate, and reducing tariffs and trade restrictions to increase trade openness.
Introduction The growing virtual water trade globally reflects economic principles associated with international trade, particularly the Heckscher-Ohlin theory. Each nation tends to export products that utilize relatively abundant and inexpensive production factors while importing those that necessitate scarce and costly resources. The strategic use of virtual water in the management of water resources is a critical issue, mainly, considering that a significant portion of Iran experiences arid and semi-arid conditions, leading to severe and increasing water shortages. Among the agricultural products that Iran requires are oilseeds, such as soybean and sunflower, which the country produces and imports in substantial quantities annually. Materials and Methods The present study aims to assess the trend of importing virtual water from oilseeds through trade partners and determine the effects of economic and environmental factors influencing their import during 2005-2020, utilizing the generalized gravity model. Economic and trade variables such as the ratio of Iran's GDP to other countries, import tariff ratio, real exchange rate growth, country risk index, distance between countries, and sanctions are considered. Environmental variables such as area under cultivation, access to water, and lack of access to water per capita are also included. The variables related to access and lack of access to water consist of four environmental factors: total water withdrawal, total renewable water, agricultural water withdrawal, and total freshwater volume. Results and Discussion The virtual water trading model is considered a scientific model and a practical solution to address the water shortage crisis in countries, especially Iran. In this research, through gravity models, the determinants affecting the volume of oilseed imports to Iran were identified. The variables of the ratio of Iran's GDP to the trading partner country and the access to water of the trading partner country were effective in both estimations, while the variable of the import tariff ratio was not effective in any of them. The risk variables of the countries have also been effective in importing virtual water. The variables of access to water and lack of access to water are environmental variables that influence the model, similar to economic variables. Therefore, the import of oilseeds is affected by economic variables; however, since the importation of oilseeds is supported to meet the country's needs and government currency has been utilized during the studied period, the variable of real exchange rate growth has less effect on imports. On the other hand, the variables of access and lack of access to water, which consist of four environmental factors (total water withdrawal, total renewable water, agricultural water withdrawal, and total freshwater volume), play an important role in the import of virtual water through oilseeds to Iran. The following suggestions can be made: Considering the significance of the variable distance between countries in the estimation, instead of meeting the demand for oilseeds from producers located at a large geographical distance, it is suggested to exchange these products with neighboring countries and regional markets if they are capable of producing these products. In other words, the Iranian government should accept the risk of importing oilseeds from neighboring and regional markets that are closer, rather than necessarily from the production hub. This may reduce the cost of importing this product by choosing these countries. Additionally, based on the role of the risk index, it is expected that countries with lower risk will be chosen as trading partners. Although the area under cultivation may be associated with a reduction in virtual water imports, considering the state of Iran's water resources and the need to import these two types of oilseeds, increasing the area under cultivation may not be feasible. Importing virtual water can play an important role in the sustainability of water resources while simultaneously meeting domestic needs. Based on the significance of access to and lack of access to water in the estimated relationships for soybean and sunflower production, certain countries have a relative advantage in cultivating these crops. Therefore, to enhance the management and sustainability of water resources, it is recommended to import from countries with greater water availability and higher production capacity. As a result, importing more virtual water supports the conservation of local water resources while ensuring the cultivation of these crops.
Introduction According to United Nations reports, the world population will increase from 7.2 billion people to 9.9 billion people during the years (2016-2050) with 38% growth. With population growth, amount of demand for food consumption (in order to eliminate malnutrition and demand caused by population growth) will increase by 150 to 170 percent by 2050. Today, one of the problems and threats facing the realization of food security in human societies is existence of an unusual amount of agricultural product waste. Every year, about one third and approximately 1.3 billion tons of total food production consumed by humans with a monetary value of 936 billion dollars, it is lost or wasted, which means that 0.9 million hectares and 306 square kilometers of water required for the production of agricultural products are wasted every year. The presence of this amount of waste in Iran's agricultural products indicates a significant waste of resources in country, and management of the country's resources (especially water) according to Iran's climatic situation and forecasting and drawing the future. It is telling that (resources used in agricultural sector) will soon become an important challenge. Considering that in country, 93.5% of water resources are used in agriculture, other issues such as pollution of water reserves, transfer of agricultural water to other sectors and low efficiency of water consumption in agriculture, increasing demand for water, increasing periods drought, phenomenon of fine dust, human impact on natural resources, etc. affect the amount of agricultural production. Subgroups of fruits and vegetables have the largest share in the consumption basket of households, but there are no specific statistics for recent years about share of consumption per capita of households (separated by products used) in Iran. It is important to note that the amount of waste generated by consumers varies between 1 kg per household per week and 4.5 kg per person per week, depending on consumer behavior. Given the significance of agricultural inputs, particularly water, in the production of these agricultural products and their substantial share in household consumption, this research focuses on the fruit and vegetable subgroups. Materials and Methods The case study of this research acknowledges that, in addition to consumers in Mashhad, there is heterogeneity among retail and wholesale shops, as well as the city's main market squares, each contributing to varying percentages of agricultural product waste. These differences can fluctuate based on urban areas, necessitating a model that accounts for the heterogeneity within the studied population. Therefore, the multilevel Bayesian model was selected as the most appropriate tool, as discussed in the following section on the modeling methodology. Results and Discussion Based on the results in Table (7), the gender variable, with a mean value of 0.8285 for its parameter distribution, falls within the estimated confidence interval. It is identified as one of the factors influencing the reduction of waste in fruit and vegetable products. Specifically, being a woman and having women manage household affairs (compared to men) leads to a reduction in waste. Regarding the education level of consumers, waste from fruit and vegetable products is significant only in the group with a diploma to bachelor's degree (compared to the group with education levels below a diploma). The negative sign of the average distribution of its parameter (-1.4599) indicates that this group produces more waste than those with lower education levels. The variable of household size also affects the amount of waste from fruit and vegetable products, with a mean parameter distribution of 0.3151. An increase in household size is associated with a reduction in waste. Additionally, the number of people working in the family (mean parameter distribution = 0.3733) also reduces waste, likely because a higher number of working family members can lead to increased income, allowing for the purchase of higher-quality products. The relative price parameter of agricultural products, with a mean parameter distribution of 0.1475, reduces the waste generated by consumers. As the relative price of agricultural products (e.g., fruits and vegetables) increases—when consumers compare the value of these products to other goods—they realize that consuming these products will result in less waste. Similarly, the parameter related to the distribution location of agricultural products, with a mean parameter distribution of 0.1744, also reduces the waste generated by consumers. This suggests that the more efficiently agricultural products are distributed, the less waste is produced. Suitable places for product distribution can give better access and power of choice to consumer, and based on this, consumer can avoid bulk purchases or worry about running out of products in nearby stores; He avoids and the amount of waste formed by him decreases. Product parameter (goods or services offered to customer) for agricultural products (parameter distribution mean = -0.1902) causes an increase in the waste formed in agricultural products by consumers. In other words, with increase in the supply of products (fruits and vegetables), consumers become more willing to buy and consume (like consuming a specific product during the supply season), and this causes increase in number of purchases to affect the amount of waste generated. Parameter of promoting agricultural products (parameter distribution mean = 0.0683) reduces the waste formed in agricultural products by consumers. With better introduction of product and advertisements related to the production process until its consumption; consumer understands the value of the product and tries to reduce its waste. Conclusion The research demonstrates that individual and marketing mix factors can effectively reduce waste. Beyond the importance of each link in the food supply chain, consumer-level interventions using the marketing mix (price, product, promotion, and location) can contribute to reducing agricultural product waste. Therefore, studying consumer behavior, considering individual and social characteristics and the influence of the marketing mix, represents a potentially low-cost solution for minimizing agricultural product waste.
Introduction Many governments provide subsidies to members of the agricultural supply chain to ensure food security, maintain economic stability, and uphold the social benefits associated with the agriculture sector. The conflicting goals of food security and environmental protection have become a major problem, especially in developing countries. On the one hand, the government aims to boost food production by offering agricultural subsidies. On the other hand, the excessive use of chemical inputs due to these subsidies has raised concerns about environmental pollution. Therefore, one of the most significant global challenges is to balance agricultural production to meet the increasing demand of the growing population while maintaining the quality of the environment. Any changes in government support policies for the agricultural sector can lead to fluctuations in input and product prices, directly impacting farmers' profits. As a result, these changes can influence cultivation patterns and the use of agricultural inputs, ultimately affecting the environment. Therefore, before implementing any policy changes, it is crucial to assess both the economic and environmental impacts and make informed decisions based on these considerations. Materials and Methods This study uses positive mathematical programming (PMP) on the environmental impact of chemical fertilizers’ subsidies change and transfer subsidies to crops in Zarandieh city of Markazi province. The necessary information was collected through the statistical sources of the Ministry of Agricultural Jihad for the crop year 2023 for the three crops including irrigated wheat, irrigated barley, and silage corn, which occupies more than 85 percent of the cultivated area of this region. At the first stage, the amount of greenhouse gas (GHG) emissions by each product was calculated, and then the environmental impact of different subsidy policies was investigated. To calculate the greenhouse gas emissions, the emission coefficient of each of the inputs that have been cited in various studies was used. To model and analyze the data, positive mathematical programming with the cost function approach was used. Excel and GAMS software has been used to run the models. Results and Discussion The results of the study showed that the highest amount of greenhouse gas emissions is related to corn silage, and electricity, diesel, and chemical fertilizers have the largest share of the greenhouse gas emissions. The simulation results for the region’s cultivation patterns, considering scenarios where only chemical fertilizers—N-fertilizer, P-fertilizer, and K-fertilizer—were used separately and together with increases of 25%, 50%, 75%, and 100%, indicate that as input prices rise, both the cultivated area and farmers' income decrease. Additionally, increasing the price of P-fertilizer has a greater potential to reduce environmental impact compared to raising the price of other chemical fertilizers.To assess the environmental impact of reallocating subsidies from chemical inputs to agricultural products, a scenario was simulated in which the price of chemical inputs increased by 100%, while product prices rose by 5% and 10%, respectively. The model results revealed that the lowest environmental impact per hectare of crop production occurs when chemical fertilizer prices increase by 100% and product prices rise by 5%.Based on these findings, reallocating subsidies to agricultural products rather than production inputs appears to yield more favorable environmental outcomes. In other words, when the subsidy is allocated to the product instead of chemical inputs, the environmental impact of crop production in this area would be reduced and the amount of emissions per hectare of farm or million Tomans of gross profit would be less compared to other situations. Conclusion It is necessary to support the agricultural sector to boost food production but these supports should be done with the least environmental impact. According to the findings of this study, if subsidies are given to agricultural products instead of inputs, greenhouse gas emissions will be reduced while maintaining the area of crops and the amount of gross profit of farmers. The policy of setting a guaranteed price for basic agricultural products in Iran can be a suitable tool to realize this. In other words, transferring the credits allocated for purchasing chemical fertilizers to the guaranteed purchase of agricultural products will be an effective step in reducing the emission of greenhouse gases and their impact, as well as maintaining the country's food security.
Introduction In the continuity of human life, agriculture as a strategic activity plays a key role in providing food. In addition, the agricultural sector plays an important role in economic development, social welfare and environmental sustainability of all countries. However, this sector is facing many challenges in recent years. Some of its most important challenges include the increasing growth of the world's population, a 40% reduction in water and soil resources, the destruction of a quarter of agricultural land, climate change, a lack of specialized labor, poor access to financial resources, strict laws, and a decrease in the number of farmers due to a decrease in motivation. Therefore, in order to meet the growing demand for food and overcome its challenges, the agricultural sector is forced to look for new solutions such as adopting digital transformation enhanced by artificial intelligence technology. The use of artificial intelligence (AI) technology has recently become increasingly prominent in the agricultural sector. AI-based solutions assist farmers in achieving higher productivity with fewer resources, ensuring the production of high-quality and healthy products, and accelerating the marketing process. Given the significance of AI technology in enhancing the overall efficiency of the agricultural sector, this research aims to identify the key predictors that influence the behavioral intention and adoption of AI technology in agricultural companies. Materials and Methods The main objective of this research is to determine the key predictors of behavioral intention and behavior of using artificial intelligence technology in agricultural companies through the combination of the developed UTAUT2 model and TOE factors. The statistical population of this research is the total employees of nine cultivation and industry of Razavi Agricultural Company, which are about 465 people. Data were collected by completing multidimensional questionnaires along with semi-structured interviews from households in 2023. In total, 250 questionnaires were completed. Data of 39 respondents were excluded due to missing values. The questionnaire is designed based on the seven-point Likert scale (strongly disagree = 1, strongly agree = 7). The questionnaire used in this research includes 14 constructs in the form of 60 items. Excel 2019 software was used to analyze the raw data of the questionnaire and SmartPLS software was used to test the research hypotheses. In order to guarantee the stability of the data, a complete bootstrap method with 5000 sub-samples was performed. Results and Discussion The results revealed that the values of Cronbach's alpha and CR for all constructs were higher than 0.7, which shows acceptable internal consistency of the model and adequate reliability of the research constructs. AVE scores and factor loading values for all constructs are above 0.5, which indicates the correct definition of constructs and high convergence between constructs and its items. The values of rho_A as an important reliability measure for PLS-SEM for all constructs are greater than the acceptable value of 0.7. The results of the Fornell-Larcker criteria and the Heterotrait-Monotrait ratio (HTMT) indicate that the model is confirmed in terms of the constructs' discriminative validity. In addition, the research model was able to explain 89.4 and 51.7 percent of the variance of the variables of behavioral intention and the behavior of people to use artificial intelligence technology in the agricultural sector. According to the results, all research hypotheses are confirmed and the behavioral intention to adopt artificial intelligence technology is positively and significantly influenced by expected performance, social effects, hope for effort, facilitating conditions, pleasure-seeking motivation, price-value, habit, trust in technology, technological aspects, organizational aspects, and environmental aspects. However, the fear of technology variable has a negative and significant impact on people's behavioral intention. Conclusion This study highlights the determining the role of expected performance constructs, social influences, fear of technology, and organizational and environmental aspects compared to other constructs in predicting people's behavioral intention to adopt artificial intelligence technology in the agricultural sector and provides important information for different stakeholders. According to the results, it is suggested that the government should invest in the development of the necessary infrastructure for this technology and provide a platform for its development by establishing efficient laws and paying low-interest facilities. In addition, Designers should create user-friendly tools tailored to the agricultural conditions of the country.
Iran Mercantile Exchange is striving to become a regional hub for price discovery of essential commodities and raw materials, providing producers with financial instruments and risk management tools. This study investigates the optimal hedge ratio in future and commodity deposit receipts (spot) contracts for Round Fandoghi pistachios. Using the BEKK-VAR-TARCH model, the impact of seasonal and daily volatility on returns and hedge ratios was assessed over the period from 19 October 2018 to 18 January 2022. The results showed that volatility on specific days of the week and during different seasons affect speculative and investment decisions in the commodity exchange. Particularly, sharp volatility during certain periods can lead to significant changes in returns and hedge ratios. These findings suggest that investors should update their investment strategies based on seasonal and daily volatilities. Additionally, the importance of utilizing financial instruments suited to market conditions for managing existing risks was confirmed. Ultimately, investors, speculators, and policymakers in the commodity exchange are advised to pay special attention to temporal changes and existing volatilities when composing their investment portfolios and adjusting hedge strategies. Furthermore, the use of futures contracts and derivative instruments is recommended as risk management approaches. This study contributes to a better understanding of volatility behavior and offers strategies for improved risk management in the Round Fandoghi pistachio market.
IntroductionGiven the rapid process of industrialization, expansion of agriculture, increased reliance on fossil fuels, and the intensification of climatic conditions, air quality has rapidly deteriorated in recent years. One of the most important issues and challenges facing the world today is air pollution, particularly PM2.5 pollution. This problem has evolved into one of the most complex and serious dilemmas affecting the lives of people worldwide. Exposure to high levels of air pollution has negative health implications. The present study aims to measure the willingness to pay of Mashhad city residents for the improvement of PM2.5 pollution and identify the factors influencing this willingness to pay. Materials and MethodsThis study used contingent valuation and the multiple-bound discrete choice model to calculate individuals' willingness to pay. The research focused on the certainty level of "definitely yes" and generated 13 different proposals ranging from 10,000 Toman to 200,000 Toman. The ordered logit regression model was employed to analyze the factors influencing the willingness of Mashhad citizens to pay for air quality improvement. The study collected 343 questionnaires from Mashhad city residents, considering variables such as education level, age, gender, marital status, family size, presence of children, chronic respiratory diseases and individuals' income. The dependent variable was the public's willingness to pay for improving air quality regarding PM2.5. Results and DiscussionThe study found that a significant portion of respondents were willing to pay for air quality improvement. About 22.45% were willing to pay less than 10,000 Toman, 60.06% were willing to pay between 45,000 and 58,000 Toman, 5.83% were willing to pay between 95,000 and 120,000 Toman, and 11.66% were willing to pay between 155,000 and 200,000 Toman. The average willingness to pay for PM2.5 pollutant improvement in Mashhad was estimated to be 55,488 Toman. Education, age, respiratory diseases, income, and family size were found to affect willingness to pay. Conclusion Improving air quality and reducing pollution requires costly efforts and collaboration from society. This research examines individuals' willingness to financially contribute to air quality enhancement. Factors influencing their willingness to pay are also studied. Based on the findings, it is recommended that the government and municipal authorities impose taxes and levies on polluting sectors, considering the calculated value of air pollution and its sources. Educational programs tailored to diverse educational backgrounds, along with technology and social media, can raise environmental awareness among youth. Developing cost-effective public transportation systems and providing discounts for low-income individuals can also help reduce pollution. Financial programs and incentives for cleaner resources are another solution for improving air quality.
