Efficiency measures for a non-homogeneous group of family farmers

Gomes, Eliane Gonçalves; Mello, João Carlos Correia Baptista Soares de; Freitas, A. C. R. de

doi:10.1590/s0101-74382012005000026

Cited by 11 publications

(20 citation statements)

References 30 publications

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“…Second, we use a separate DEA model for each cluster, and evaluate the relative efficiency of each plot within the cluster. Finally, we use an algorithm [3] to countervail for non-homogeneity among plots.…”

Section: Methodsmentioning

confidence: 99%

“…In [9], the beef cattle production was examined using a unitary input DEA model combined to relative efficiency measures generated by the inverted DEA frontier. In [3], DEA models were used to compare the performance of farms cultivated with different technologies, and an algorithm for calculating the relative efficiency scores taking into account such non-homogeneity was proposed. In [10], the performance of producers were analysed, using SOMs and cross-evaluation DEA models.…”

Section: Dea's Application In Agriculturementioning

confidence: 99%

“…In this sense, our proposal differs from [10], which used the DEA cross-efficiencies as inputs to the SOMs procedure for expost clustering. Additionally, we apply the algorithm developed in [3] to enable the direct comparison of plots from different clusters.…”

Section: Dea's Application In Agriculturementioning

confidence: 99%

“…less seasonal variation) in production, large variety of items produced and high volume of products offered for sale. For that, we use an alternative approach that combines Data Envelopment Analysis (DEA [1]), Self-Organizing Maps (SOMs [2]) and a compensating algorithm proposed by [3].…”

Section: Introductionmentioning

confidence: 99%

“…To surpass such inconvenience, we will further apply the algorithm of [3] to compensate for the non-homogeneity of the plots.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Productive performance of small peri-urban farms using self-organizing maps and data envelopment analysis

Rubem¹,

Moura²,

Oliveira³

et al. 2015

WIT Transactions on Ecology and the Environment

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In this paper, we aim to analyze the productive performance of plots cultivated by family farmers. We use an alternative Data Envelopment Analysis (DEA) approach to calculate the relative efficiency of such plots. Notwithstanding, DEA's basic assumption includes the homogeneity of the production units under analysis. Herein, as the chemical composition of the soil varies considerably among plots, directly influencing their fertility, and, thus, their productivity levels, the plots shall be grouped into homogeneous clusters first. For that, we use SelfOrganizing Maps, based on their comparative advantages to other methods. Then, the relative efficiencies of plots within each cluster will be assessed using separate DEA models. Nonetheless, a direct comparison among the scores of plots from different clusters is not feasible, because the relative efficiency of a production unit can solely be compared to those inserted in the same set of analysis. Hence, to overcome such inconvenience, we further apply a technique that allows compensating for the non-homogeneity of plots. The results indicate that, when countervailing the effects of the chemical composition of the soil, the plots with favorable conditions do not necessarily present better productive outcomes.

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Section: Methodsmentioning

confidence: 99%

Section: Dea's Application In Agriculturementioning

confidence: 99%

Section: Dea's Application In Agriculturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…To surpass such inconvenience, we will further apply the algorithm of [3] to compensate for the non-homogeneity of the plots.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Productive performance of small peri-urban farms using self-organizing maps and data envelopment analysis

Rubem¹,

Moura²,

Oliveira³

et al. 2015

WIT Transactions on Ecology and the Environment

View full text Add to dashboard Cite

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Integrated performance evaluation method study and performance based department ranking: a case study

2020

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Enterprise companies, which make future strategic plan, need to view overall performance. In this direction, monitoring decision-making unit (DMU) performances is a critical issue. Therefore, it should be fair and consistent performance evaluation and prepared open and clear reports. To handle with these requirements, this study focusses on establishing a comprehensive method of performance evaluations (PE). Five main stages exist as a framework of the study. Firstly, right PE tool are selected in terms of strategic frame of companies. In this study, we examine balanced scorecard (BSC) approach that considers not only financial but also non-financial topics to watch overall performance. BSC has key performance indicators (KPI) that show objectives and actualizations belonging to related DMU, and BSC also provides proper and summary reports including different perspectives. The next step is determination of KPI's weights. Analytic hierarchy process (AHP) is applied to determine KPI priorities. Because BSC evaluates DMU'S separately, it does not provide satisfied comparison among different DMU's. In here, we propose data envelopment analyses (DEA) that is linear program based non-parametric approach. However, DEA works correctly for only homogeneous DMU's. As a third step, classification process is applied to ensure homogeneity. Then, using BSC KPI's as outputs and DMU budgets as input, DEA model is run for each class. As a last step, we separate DMUs into categories using efficiency score obtained from fourth stage. To determine category numbers, Hierarchical Clustering Analyze (AHCA) method is used and group elements are selected with applying K-Means Clustering Analyze technique. At the end, a case study is given to show how developed model is applied within a company that uses only BSC tool for PE currently. It could be said that this integrated methodology is more efficient and reliable for decision-making process.

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Network-centric benchmarking of operational performance in aviation

Gopalakrishnan

Balakrishnan

2021

Transportation Research Part C: Emerging Technologies

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Efficiency measures for a non-homogeneous group of family farmers

Cited by 11 publications

References 30 publications

Productive performance of small peri-urban farms using self-organizing maps and data envelopment analysis

Productive performance of small peri-urban farms using self-organizing maps and data envelopment analysis

Integrated performance evaluation method study and performance based department ranking: a case study

Network-centric benchmarking of operational performance in aviation

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