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Mostafa Mardani Najafabadi, Yasamin Zebari, Nasrin Ohadi,
Volume 11, Issue 41 (12-2022)
Volume 11, Issue 41 (12-2022)
Abstract
Introduction
Population growth, the need to provide food security, and pressure on natural resources in developing countries are facing a fundamental challenge for the sustainable production of food products. The need to pay attention to sustainability in agriculture has been confirmed at local, regional, national, and global levels. Sustainable agriculture is a system that uses resources efficiently, produces healthy food resources, preserves the quality of the environment and resources for future generations, and is economically dynamic. Sustainability is a qualitative concept that cannot be measured directly, so appropriate indicators should be selected to determine the amount and durability of an agricultural system. Efficiency is a significant factor in the productivity growth of production resources, especially in developing countries. Increasing efficiency can be considered a suitable and sustainable complement to a set of policies that encourage and protect domestic production and promote the optimal use of resources. The exact definition of efficiency can be found in Pareto's definition. According to the definition of efficiency, a system has Pareto efficiency so that it is impossible to improve the economic status of an individual from society without worsening the economic status of another individual. In other words, the reallocation of resources should not worsen the situation of some people in society. Therefore, improving the efficiency and optimal consumption of production factors in improving the sustainability of agricultural operations in the direction of sustainable development is inevitable. Based on this, the main goal of the present study is to determine the efficiency and optimal use of production resources by rice farmers in rural areas of Gotvand in the direction of sustainable development under conditions of uncertainty (the application of robust Data Envelopment Analysis (DEA)).
Methodology
Efficiency measurement methods are classified into two parametric and non-parametric methods according to their characteristics. The most apparent model proposed in the non-parametric framework is the DEA model. In DEA, the efficiency of a group of investigated units is determined by using a multiple set of input and output variables. One of the major limitations of the mentioned method is the high sensitivity of this method to the change in the value of input and output data, or in other words, the presence of uncertainty in these data. Because agriculture is always faced with uncertainty, when the input and output values have uncertainty, the mentioned model faces problems. In this regard, it is necessary to use another method that can protect optimal solutions against uncertainty. Recently, various methods have been proposed to overcome the problem of uncertain data in DEA, such as Interval DEA (IDEA), Fuzzy DEA (FDEA) and Stochastic DEA (SDEA). Another method of dealing with uncertain data that was introduced in mathematical programming models in the late 1990s is Robust DEA (RDEA). This method does not have some shortcomings in other methods for applying uncertainty conditions in the DEA model. The RDEA is one of the robust and valuable models in conditions of uncertainty, and in this study, this method was used to analyze the efficiency of rice farmers. The required data in the study area was obtained through the distribution and completion of the questionnaire in 2018 by 121 rice farmers considering the statistical population and using simple random sampling.
Discussion and conclusion
The average technical efficiency in the state of constant return to scale efficiency and at the level of 0.5 deviation probability and 20% uncertainty level is equal to 0.79, which means that rice farmers can use a fixed technology without reducing production, reduce their input consumption by 21% and reach the production efficiency bound. As a result, the producers of the studied area need to use production inputs optimally to produce a given level of production. However, the actual values of input consumption by rice farmers in rural areas are far from the estimated optimal values. In other words, there is excess consumption for all inputs. The most inefficient inputs in the present study are the area under cultivation and herbicide. Therefore, achieving the optimal level of consumption of these inputs without reducing production by reducing 48% and 45% in the consumption of the cultivated area and herbicide, respectively. Considering the low technical efficiency and unfavorable input consumption among the rice farmers in the researched rural areas, it is suggested to identify efficient units and serve as a reference for inefficient units and develop a regular annual plan for optimal input consumption by farmers and as a result of improving efficiency, to improve the sustainability of agricultural operations in line with the goals of sustainable development. Also, educational planning is recommended to use suitable and advanced technologies to increase the productivity of production factors.
Population growth, the need to provide food security, and pressure on natural resources in developing countries are facing a fundamental challenge for the sustainable production of food products. The need to pay attention to sustainability in agriculture has been confirmed at local, regional, national, and global levels. Sustainable agriculture is a system that uses resources efficiently, produces healthy food resources, preserves the quality of the environment and resources for future generations, and is economically dynamic. Sustainability is a qualitative concept that cannot be measured directly, so appropriate indicators should be selected to determine the amount and durability of an agricultural system. Efficiency is a significant factor in the productivity growth of production resources, especially in developing countries. Increasing efficiency can be considered a suitable and sustainable complement to a set of policies that encourage and protect domestic production and promote the optimal use of resources. The exact definition of efficiency can be found in Pareto's definition. According to the definition of efficiency, a system has Pareto efficiency so that it is impossible to improve the economic status of an individual from society without worsening the economic status of another individual. In other words, the reallocation of resources should not worsen the situation of some people in society. Therefore, improving the efficiency and optimal consumption of production factors in improving the sustainability of agricultural operations in the direction of sustainable development is inevitable. Based on this, the main goal of the present study is to determine the efficiency and optimal use of production resources by rice farmers in rural areas of Gotvand in the direction of sustainable development under conditions of uncertainty (the application of robust Data Envelopment Analysis (DEA)).
Methodology
Efficiency measurement methods are classified into two parametric and non-parametric methods according to their characteristics. The most apparent model proposed in the non-parametric framework is the DEA model. In DEA, the efficiency of a group of investigated units is determined by using a multiple set of input and output variables. One of the major limitations of the mentioned method is the high sensitivity of this method to the change in the value of input and output data, or in other words, the presence of uncertainty in these data. Because agriculture is always faced with uncertainty, when the input and output values have uncertainty, the mentioned model faces problems. In this regard, it is necessary to use another method that can protect optimal solutions against uncertainty. Recently, various methods have been proposed to overcome the problem of uncertain data in DEA, such as Interval DEA (IDEA), Fuzzy DEA (FDEA) and Stochastic DEA (SDEA). Another method of dealing with uncertain data that was introduced in mathematical programming models in the late 1990s is Robust DEA (RDEA). This method does not have some shortcomings in other methods for applying uncertainty conditions in the DEA model. The RDEA is one of the robust and valuable models in conditions of uncertainty, and in this study, this method was used to analyze the efficiency of rice farmers. The required data in the study area was obtained through the distribution and completion of the questionnaire in 2018 by 121 rice farmers considering the statistical population and using simple random sampling.
Discussion and conclusion
The average technical efficiency in the state of constant return to scale efficiency and at the level of 0.5 deviation probability and 20% uncertainty level is equal to 0.79, which means that rice farmers can use a fixed technology without reducing production, reduce their input consumption by 21% and reach the production efficiency bound. As a result, the producers of the studied area need to use production inputs optimally to produce a given level of production. However, the actual values of input consumption by rice farmers in rural areas are far from the estimated optimal values. In other words, there is excess consumption for all inputs. The most inefficient inputs in the present study are the area under cultivation and herbicide. Therefore, achieving the optimal level of consumption of these inputs without reducing production by reducing 48% and 45% in the consumption of the cultivated area and herbicide, respectively. Considering the low technical efficiency and unfavorable input consumption among the rice farmers in the researched rural areas, it is suggested to identify efficient units and serve as a reference for inefficient units and develop a regular annual plan for optimal input consumption by farmers and as a result of improving efficiency, to improve the sustainability of agricultural operations in line with the goals of sustainable development. Also, educational planning is recommended to use suitable and advanced technologies to increase the productivity of production factors.
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