Administrative corruption: Providing a fuzzy inference system of good governance to combat corruption

Nowadays the word “corruption” is always seen in majority of news headlines. We can only subscribe the increase of corruption in organizations and other institutions with reference to the press and all kinds of mass media. A while ago, by announcing the perceptual indicators of corruption Iran was introduced as a country with high corruption. This study aims to propose a comprehensive model to measure the administrative corruption through a widespread study in the review of literature of previous studies. In this study the definition of fuzzy systems of effective factors on administrative corruption including predictive variables of a good governorship of a world bank like: comment right and responding, political stability, lack of violence, the effectiveness of government, the quality of regulations, the authority of law and the control of corruption have been used. In this research all various dimensions of a good governorship to fight against the corruption were used as an input of the fuzzy inference system and of corruption as an output of a system. Afterwards, the membership dependencies and fuzzy rules, the fuzzy inference system for measuring the administrative corruption was designed by using good governorship indicators. And finally, the output of the model was compared with the experts´ opinion. Also rule formation was extracted by applying the opinion of five university professors. The results of the study showed that the results of experts´ opinion and those of the fuzzy inference system were close together and this represents a high validity of a system. We can say that the main reason of this validity lies in the identification of appropriate units of measurement for predicting. For this study the units of measurement were extracted from the World Bank.