Service quality improvement strategies of online car-hailing based on SPC-PCN method

Abstract

Online car-hailing service is practicing the concept of sharing, bringing new energy and convenience to the transportation market. However, with its rapid development, service issues have become increasingly prominent, and improving service quality is the key to the sustainable growth of the online ride-hailing industry. Microblog, as a major online platform for gathering public views, have become one of the significant media for publishing and disseminating information nowadays, which also contains numerous views of online taxi users on online taxi services. Aiming at the deficiency of online car-hailing service under microblog public opinion, this paper integrates Service Profit Chain (SPC) and Process Chain Network (PCN) from the perspective of service management. Firstly, a crawler program is used to collect the Internet Word of Mouth data related to online taxi. Then, a BERT text classification model is constructed to roughly classify the data, and the accuracy of this model is tested to 94.54 %. Afterwards, layer segmentation is implemented based on SPC and CatBoost. Besides, a series of problems in the current online taxi service, such as poor attitude of drivers, unsafe driving, and inefficient communication with the customer service staff, have been identified by using sentiment analysis and frequent mining methods. Finally, PCN analysis is used to optimize the online taxi service, proposing strategies such as setting a reservation reminder function, building a dynamic feedback mechanism, and establishing a contact point for lost and found items. The new SPC-PCN online taxi service system constructed in this paper is vital for service quality optimization, and can also promote the sustainable growth of the online taxi market.