Research On Evaluation System Of E-Service In Airlines

With the rapid development of e-commerce, more and more passengers choose electronic service of airline, e-service become a very important part of airlines service. So the objective and reasonable evaluation of electronic services to enhance the aviation company’s overall service quality is very important.But there is a lack of reasonable evaluation system in the current study, which can not provide theoretical support for the evaluation of the electronic service for the airlines. In order to improve the quality of service and help airlines increase themselves market competitiveness,the evaluation system of the electronic service of the airline company was researched from the following aspects:Firstly,the appropriate and generality of e-service quality evaluation model E-S-QUAL was chosen to be the base model based on the existing studies. Then the characteristics of the airlines e-service was analyzed and the preliminary evaluation index was determined. In order to analyze the evaluation index objectively, the data was obtained by the questionnaire survey. Then the initial index system was conducted by factor analysis,the finalized airlines e-service quality evaluation index system was identified by adding and reducing some dimensions,.Secondly, the evaluation indexes and the weight of item was calculated by entropy weight method.Then,the fuzzy comprehensive evaluation method was combined with the determined e-service quality evaluation index system and weight calculation results to calculate the airlines e-service quality grading.Finally, in order to improve the practicability of the model, help the airline use process conveniently, effectively and rapidly analyze the airlines e-services evaluation on the sample data, the fuzzy neural network algorithm was used in MATLAB programming.In conclusion, airlines e-service evaluation system was established based on the customer perspective and the evaluation results of pre-sale, after-sale and the whole e-service model was good. In the end, Calculation process was optimized by fuzzy neural network and the procedure was proved available.