A two-stage DEA model to evaluate sustainability and energy efficiency of tomato production

Raheli, Hossein; Rezaei, Rassul Mohammad; Jadidi, Majid; Mobtaker, Hassan Ghasemi

doi:10.1016/j.inpa.2017.02.004

Cited by 64 publications

(46 citation statements)

References 26 publications

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“…As expected, education was also shown to exert positive influence on EE levels of edible canna farms, i.e., with more years of schooling or more human capital, farmers are likely to be more productive and efficient because of better skills in planning farming activities, transferring technology, and accessing market information. This result is in agreement with Nargis and Lee [47], Linh [48], and Raheli et al [49]. Therefore, a means to improve the efficiency level of edible canna farms in Backan province could focus on short-term training courses for farmers.…”

Section: Factors Influencing On Environmental Efficiency Of Edible Casupporting

confidence: 90%

Evaluation of Environmental Efficiency of Edible Canna Production in Vietnam

Peng

Chung

2019

Agriculture

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Increasing yield while minimizing environmental pollution in agricultural production is nowadays the primary concern in agriculture-based countries, including Vietnam. This study aims to assess the environmental efficiency and technical efficiency, as well as to determine the factors influencing efficiency of edible canna farms in Backan province, by using the stochastic frontier analysis and truncated regression, respectively. Data were collected from a face-to-face interview of 346 farmers in 2017/2018 production year. The findings revealed that the average environmental efficiency score was low, of 0.57 and 0.58 for Nari and Babe districts, respectively; while the technical efficiency was found to be higher than the environmental efficiency with 0.74 for Nari district and 0.72 for Babe district. In addition, the results of the inefficient effects and truncated regression model indicated that education, extension contact, and experience individually had a significant and positive effect on efficiency scores. Hence, the government should designate policies focused on the extension system to provide training and facilitate technology transfer for farmers.

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Section: Factors Influencing On Environmental Efficiency Of Edible Casupporting

confidence: 90%

Evaluation of Environmental Efficiency of Edible Canna Production in Vietnam

Peng

Chung

2019

Agriculture

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“…Even tough, the percentage of fully educated farm managers does not exceed 20% in any particular region. Likewise, another authors (Raheli et al, 2017;Shanmugam & Ventkataramani, 2006) show that education is powerful driver of efficiency at the district level in the long term. Nevertheless, there are some studies (Novak et al, 2015; Idris et al, 2013) claiming that the level of training and education is not related with the agricultural efficiency.…”

Section: Resultsmentioning

confidence: 95%

A two-stage DEA model to evaluate agricultural efficiency in case of Serbian districts

Horvat

Radovanov

Popescu

et al. 2019

Ekonomika poljoprivrede

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Since the efficient agricultural sector is one of the most important drivers of country's economic development, the main objective of this paper was to examine relative technical efficiency of agricultural production in 25 Serbian districts using two-stage data envelopment analysis. Results of this research indicate that the efficiency score values lie between 70% and 100%, therefore it can be concluded that the agricultural sector of Serbia performs at a high level of efficiency, with the average efficiency score of 90%. The lowland region of Vojvodina is characterized with the highest efficiency scores, while districts in the southeastern part of Serbia have the lowest efficiency score values. Furthermore, the Tobit regression model was applied that one may examine the drivers of technical efficiency scores. The results show the significance of agricultural training among farm managers, land irrigation and age of farm holders in altering agricultural efficiency among Serbian districts.

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“…This input was the largest contributor of the total energy consumption, comprising 58.55% (Figure ). Several researchers have reported that the energy consumption of chemical fertilizer was the highest energy consumer during Iranian crop production in general . Soheili‐Fard et al .…”

Section: Resultsmentioning

confidence: 99%

Integration of principal component analysis and artificial neural networks to more effectively predict agricultural energy flows

Nikkhah

Rohani

Rosentrater

et al. 2019

Env Prog and Sustain Energy

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There are some studies regarding the prediction of agricultural energy flows using artificial neural networks (ANNs). These models are quite sensitive to correlations amongst inputs, and, there are often strong correlations amongst energy inputs for agricultural systems. One potential method to remediate this problem is to use principal component analysis (PCA). Therefore, the purpose of this research was to predict energy flows for a specific agricultural system (Iranian tea production) via a novel methodology based on ANNs, and using principal components as model inputs, not raw data. PCA results showed that the first and second components could account for more than 99% of variation in the data, thus the dimensions of the data set could be decreased from six to two for the prediction of energy flows for Iranian tea production. Using these principal components as inputs, an ANN model with 2–15–1 structure was determined to be optimal for energy flow modeling of this system. To conclude, the results of this study highlighted that the use of PC as ANN inputs improved ANN model prediction through reducing its complexity and eliminating data colinearity. Many agricultural systems could benefit from using this methodology for energy modeling. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13130, 2019

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A two-stage DEA model to evaluate sustainability and energy efficiency of tomato production

Cited by 64 publications

References 26 publications

Evaluation of Environmental Efficiency of Edible Canna Production in Vietnam

Evaluation of Environmental Efficiency of Edible Canna Production in Vietnam

A two-stage DEA model to evaluate agricultural efficiency in case of Serbian districts

Integration of principal component analysis and artificial neural networks to more effectively predict agricultural energy flows

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