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The suggestions system is a part of total quality management to create individual and group spirit of partnership between staff and increase efficiency in the organization. Also, diagnosis and improvement process is one of the steps of the chain in the processes of suggestions system. In this study, an approach has been proposed to evaluate efficiency of organizations in performing suggestions system with these aims: (1) Reviewing all the elements in the successful implementation of the suggestions system and (2) providing an effective scientific approach to evaluate the organizations on implementing this system considering the uncertainty in the data. Methodology used in this study included the following techniques: (1) Factor analyzing to clarify the internal correlation between significant criteria and detect the major criteria and (2) using robust data envelopment analysis (RDEA) model to evaluate efficiency of organizations in performing suggestions system. The method is based on 3 inputs and 17 outputs in which some outputs are uncertain scores in form of intervals with uncertain bounds. This model has been solved for different Γs, and a value of weights and rankings for each Decision Making Unit (DMU) has been saved by using the obtained values. In the following a simulation has been used to compute the conformity of the rankings from the RDEA model with reality. Doing so shows that the maximum conformity occurs Γ = 6. Therefore, we can conclude that specific values of Γ can maximize conformity and thus more authentic final rankings for the DMUs in this interval of Γ may be expected.

Evaluation of the suggestions system performance using robust DEA model: The case of National Iranian Gas Company