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In conventional DEA models, decision making units (DMUs) are generally assumed as a black-box while the performance of decision making sub-units (DMSUs) and their importance play crucial roles in  analyzing the performance of systems which have internal processes. The present paper introduces an ideal network which have efficient processes and next purposes a new approach for evaluating importance of network components (DMSUs) based on comparison with the ideal network. Eventually, overall efficiency of network system will be determined which can be decomposed to the weighted efficiency of its sub-processes. As the result of the purposed approach, we can determine the situations that the network would perform better by improving the efficiency of the important DMSUs which have a vital impact on network performance.

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Data envelopment analysis is a non-parametric approach for evaluating efficiency score of peer decision making units which consume multiple inputs to produce multiple outputs. The conventional data envelopment analysis models consider decision making units as black-boxes by ignoring internal sub-processes of the production units, while network-data envelopment analysis models have been proposed for determining the efficiency score of network systems. The current paper develops a network-data envelopment analysis super efficiency model to rank and compare the performance of network systems. The proposed general network super-efficiency model can be used for ranking multi-stage production units. The new approach is then applied for evaluating wheat productions in Iran provinces. Traditional models are used as well as the new network data envelopment analysis model to calculate a set of super-efficiency scores for provinces under the investigation. The research extends the application of data envelopment analysis method to judgment and decision making in wheat farming as a network production process.