The Research And Design Of Automobile After-Sale Service System Based On B2B2C

With the rapid development of economy and the improvement of people’s living standard, China has become the world’s largest automobile manufacturer and consumer. After-sales service is an important part of the automotive industry chain. As the scale of China’s automotive aftermarket continues to expand in recent years and after-sales services continue to mature, automakers are paying more attention to the participation of customers. Customers’ opinions and suggestions on service play a more and more important role in enhancing the competitiveness of the service. The B2B2C mode which combines the B2B mode and the B2C mode is gradually popular. Based on the platform of electronic commerce, it has become an important tool for after-service businesses to attract customers and increase revenue by connecting car prices, after-sales service agencies and clients, providing convenient information query, reservation service and feedback function.KM Automobile manufacturing plant, the prototype enterprise of this thesis, has been using the B2B mode of after-sales service management. The information exchange mechanism between the vehicle manufacturing plant and the after-sales service station group has been quite perfect, and it has guaranteed the smooth after service. However, as an important part of after-sales service, customers are not fully involved in it. Customer’s reservation of service and feedback, etc., can only be carried out by the traditional means of communication. In view of this situation, we study the B2B2C mode of automobile after-sales service, and design an automobile after-sales service management solution based on B2B2C mode, which includes customers, after-sales service stations, vehicle factory, so that customers can easily reserve their required service, and automobile manufacturing plant and after-sales service station can accurately and effectively get customer feedback to improve the quality of their product and service.At the same time, to help the automobile manufacturing plant and the after-sales service station effectively use the customer’s opinions, this thesis studies the text keyword extraction algorithm. Based on the TextRank algorithm, we propose an improved scheme for keywords extraction that takes into consideration the frequency, part of speech, word span and local phrase combination. On this basis, combining with the semantic similarity calculation method, we design an automatic marking scheme and retrieval scheme of customer comments, not only to store customer views effectively, but also to ensure the accuracy of the retrieval. In the end, based on the three-tiered B/S structure, we use the C# language, designing and implementing the automobile after service system based on B2B2C.