Evaluation of Urban Passenger Satisfaction of The Quality of Urban Public Transport Services in Ahvaz

The development of public transport can help to improve the traffic situation, but if the quality of public transport is low and the confidence can cause traffic congestion. The aim of this study was to evaluate satisfaction with the quality of urban passenger transport services in the metropolitan city of Ahvaz. This study in terms of cross - and in terms of functional purpose. For data collection requirements in terms of research, library and field method is used. The study population included all residents 7Ganh Ahvaz. The sample obtained by the sample in the study population of 350 passengers who were in the path of the bus randomly during the early hours of the morning, afternoon and evening are selected and then to analyze the data Inventory of SPSS software has been used. Descriptive results obtained show that 4% of people questioned the quality of public transport, urban and very good, 26.9% good people, 42.7% of the quality of this type of service average, 18% weak and 8.3% of passengers on public services in the city Ahvaz has been described as very poor. The one-sample t-test results indicate that the Ahvaz citizen satisfaction with the quality of public transport services, with an average (3.1) is located in the upper moderate. The test also shows that 7 children in Ahvaz between regions in terms of satisfaction there. According to the average obtained can be said that residents 1, 6, 7 and 2, respectively, the most satisfaction with the quality of urban public transport services, and least satisfied in the District 8 of Ahvaz. And finally the results of the Pearson correlation coefficient implies that the independent variables (age, sex, education, income, occupation) and the dependent variable (satisfaction) there is a positive relationship. But in the meantime, the income component of the correlation coefficient of 0.573 and a significance level of 0.034 and 0.562 with a significance level of 0.036 job component and a significant positive correlation with the dependent variable.