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The impact of agricultural cooperatives on apple farmers’ technical efficiency (TE) in China was examined. The cooperatives were divided into two groups: a collective marketing group for farmers and an equivalent non-marketing group that did not provide a marketing service, although other functions remained the same. Using the propensity score matching (PSM) procedure and stochastic production frontier (SPF) modelling, cooperatives’ key functions that potentially increase farmers’ TE can be identified. The results indicate that membership of either group is positively related to yield. However, cooperatives that were not engaged in marketing achieved higher TE than non-members. This suggests that policy makers should encourage cooperatives to focus on activities that do not include direct marketing to increase TE in apple production in China.
Ruopin Qu; Yongchang Wu; Jing Chen; Glyn Jones; Wenjing Li; Shan Jin; Qian Chang; Yiying Cao; Guijun Yang; Zhenhong Li; Lynn Frewer. Effects of Agricultural Cooperative Society on Farmers’ Technical Efficiency: Evidence from Stochastic Frontier Analysis. Sustainability 2020, 12, 8194 .
AMA StyleRuopin Qu, Yongchang Wu, Jing Chen, Glyn Jones, Wenjing Li, Shan Jin, Qian Chang, Yiying Cao, Guijun Yang, Zhenhong Li, Lynn Frewer. Effects of Agricultural Cooperative Society on Farmers’ Technical Efficiency: Evidence from Stochastic Frontier Analysis. Sustainability. 2020; 12 (19):8194.
Chicago/Turabian StyleRuopin Qu; Yongchang Wu; Jing Chen; Glyn Jones; Wenjing Li; Shan Jin; Qian Chang; Yiying Cao; Guijun Yang; Zhenhong Li; Lynn Frewer. 2020. "Effects of Agricultural Cooperative Society on Farmers’ Technical Efficiency: Evidence from Stochastic Frontier Analysis." Sustainability 12, no. 19: 8194.
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.
Sara Ilahi; Yongchang Wu; Muhammad Ahsan Ali Raza; Wenshan Wei; Muhammad Imran; Lyankhua Bayasgalankhuu. Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis. Sustainability 2019, 11, 3409 .
AMA StyleSara Ilahi, Yongchang Wu, Muhammad Ahsan Ali Raza, Wenshan Wei, Muhammad Imran, Lyankhua Bayasgalankhuu. Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis. Sustainability. 2019; 11 (12):3409.
Chicago/Turabian StyleSara Ilahi; Yongchang Wu; Muhammad Ahsan Ali Raza; Wenshan Wei; Muhammad Imran; Lyankhua Bayasgalankhuu. 2019. "Optimization Approach for Improving Energy Efficiency and Evaluation of Greenhouse Gas Emission of Wheat Crop using Data Envelopment Analysis." Sustainability 11, no. 12: 3409.