A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry

Khalili‐Damghani, Kaveh; Tavana, Madjid; Santos‐Arteaga, Francisco J.; Mohtasham, Sima

doi:10.1016/j.eneco.2015.06.020

Cited by 30 publications

(6 citation statements)

References 42 publications

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“…In this study, those homogenous organizations are farms producing wheat, and a farm is a decisionmaking unit (DMU). The criterion for deciding an efficient DMUS is that if any DMU produces a level of output that cannot be produced by another DMU using the same or a lesser amount of inputs, then it can be considered an efficient DMU [45]. There are two types of DEA applications: output-oriented DEA or input-oriented DE.…”

Section: Efficiency Estimationmentioning

confidence: 99%

Optimization of energy consumption and its effect on the energy use efficiency and greenhouse gas emissions of wheat production in Turkey

Imran

Özçatalbaş

2021

Discov Sustain

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This study aimed to model energy use, energy efficiency, and greenhouse gas emissions in rain-fed wheat production by using a nonparametric data envelopment analysis (DEA) method. Data were collected through face-to-face interviews with 140 wheat farmers in 4 districts of Antalya Province. The energy inputs (independent variables) were human labor, seeds, chemical fertilizers, herbicides, and diesel fuel, and the energy output was the dependent variable. The results showed that the average energy consumption and the output energy for the studied wheat production system were 21. 07GJ ha−1 and 50. 99 GJ ha−1, respectively, and the total GHG emissions were calculated to be 592.12 kg CO2eq ha−1. Chemical fertilizer has the highest share of energy consumption and total GHG emissions. Based on the results from DEA, the technical efficiency of the farmers was found to be 0.81, while pure technical and scale efficiencies were 0.65 and 0.76, respectively. The results also highlighted that there is a potential opportunity to save approximately 14% (2.93 GJ ha−1) of the total energy consumption and consequently a 17% reduction in GHG emissions by following the optimal amounts of energy consumption while keeping the wheat yield constant. Efficient use of energy and reduction in GHG emissions will lead to resource efficiency and sustainable production, which is the main aim of the green economy.

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Section: Efficiency Estimationmentioning

confidence: 99%

Optimization of energy consumption and its effect on the energy use efficiency and greenhouse gas emissions of wheat production in Turkey

Imran

Özçatalbaş

2021

Discov Sustain

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“…DEA involves the evaluation of technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE). Furthermore, DEA used to evaluate Decision-making Units (DMUs) and efficient DMU can produce more output than other DMUs with the same amount of inputs [50]. DEA is applied in two ways; an input oriented model tries to enhance the relative reduction in input variables, while an output-oriented model directly increases the output variables remaining within the envelopment space.…”

Section: Data Envelopment Analysismentioning

confidence: 99%

Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis

Ilahi

Raza

et al. 2019

Sustainability

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Energy is a major component in enhancing agricultural productivity for the rapidly growing world population. From that fact, a comprehensive analysis of energy inputs and outputs is required to conserve energy for future generations without threatening the food supply. Therefore, this study was performed in wheat production across important cropping zones of Punjab, Pakistan. In this study, the energy use pattern of wheat production was analyzed, and the degrees of technical efficiency of Decision Making Units (DMUs) were examined using Data Envelopment Analysis (DEA). Based on the results of the DEA analysis, the inefficient energy inputs were identified and further explored with the core objective of a significant reduction of excess valuable resources. Data were collected from conducting a face-to-face questionnaire of 200 farmers. The farms for sample were chosen randomly by a stratified normal approach. The results disclosed that the input energy of 34,430.98 MJ ha−1 was used up for wheat production with an output energy of 48,267.05 MJ ha−1. Energy use efficiency, specific energy, energy productivity, and net energy gain in wheat production were calculated as 1.4 MJ kg−1, 9.27 MJ kg−1, 0.10 MJ kg−1 and 13,836.07 MJ kg−1, respectively. The average technical, pure technical, and scale efficiency of DMUs were 0.668, 0.776, and 0.828, respectively, and 0.74% of consulted DMUs were functioning at decreasing returns to scale. Additionally, the significant energy consumption belongs to fertilizer, and diesel fuel, which contribute 65% of the total energy input. If these inputs are applied and managed in line with ours optimize value (29,388.5 MJ ha−1) could save 14.65% resources, which will eventually add the equal quantity in wheat-yield. The total Greenhouse Gas (GHG) emissions were calculated to be 866.43 kg CO2-eq ha−1. In conclusion, the results of the present study suggest that there is sensible capacity for enhancing the energy efficiency of wheat production in Pakistan by accompanying the recommendations for economical energy management, sustainable and efficient use of energy is extremely encouraged.

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“…Some assumptions were considered for developing the above Eqs. (4)(5)(6)(7)(8) and running the optimization model. First, physical habitat loss is the main effective factor in the ecological assessment of the river ecosystem.…”

Section: Optimization Systemmentioning

confidence: 99%

“…Data envelopment analysis (DEA) has been applied to optimize agricultural energy use which is a linear programming approach for evaluating the efficiency of decision-making units (DMUs). Minimizing energy use could be the purpose in the objective function of agricultural optimization models [6,7]. Rice is a strategic crop in many countries.…”

Section: Introductionmentioning

confidence: 99%

Balancing environmental impacts and economic benefits of agriculture under the climate change through an integrated optimization system

Sedighkia

Abdoli²

2022

Int J Energy Environ Eng

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The present study proposes a framework to mitigate impact of climate change on the rice production by maximizing the yield while the energy use and ecological impacts on the river ecosystem as the irrigation source are mitigated. Coupled general circulation model- soil and water assessment tool (SWAT) was utilized to project the impact of climate change on the stream flow. Fuzzy physical habitat simulation was applied to develop the ecological impact function of the river. Moreover, a data-driven model was developed to predict the rice yield through changing water and energy consumption. Finally, all the simulations were utilized in the structure of the optimization model in which minimizing loss of the production, greenhouse gas emission by reducing energy use and physical habitat loss were considered as the objectives. Based on the results, the Nash–Sutcliffe model efficiency coefficient of the SWAT is 0.7 that demonstrates its reliability for simulating the impact of climate change on river flow. The optimization model is able to reduce the impact of climate change on yield of production by balancing water and energy use. In the most pessimistic scenario, water use should approximately be reduced 25% for protecting river ecosystem. However, the optimization model approximately increased energy use 16% for preserving the yield of the rice. Conversely, model decreased the energy use 40% compared with the current condition due to increasing water supply. Moreover, physical habitat loss is less than 50% that means the combined optimization model is able to protect river habitats properly.

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A dynamic multi-stage data envelopment analysis model with application to energy consumption in the cotton industry

Cited by 30 publications

References 42 publications

Optimization of energy consumption and its effect on the energy use efficiency and greenhouse gas emissions of wheat production in Turkey

Optimization of energy consumption and its effect on the energy use efficiency and greenhouse gas emissions of wheat production in Turkey

Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis

Balancing environmental impacts and economic benefits of agriculture under the climate change through an integrated optimization system

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