Queuing System Optimization based on Customer Experience of Chinese Commercial Intelligent Bank Branches

In recent years, the competition of Chinese commercial banks comes not only from traditional banking, but also from emerging internet finance. The competition environment of the banks becomes more and more intense. Hence, how to keep and improve competitiveness is a core and vital question for the banks. As one of the main factors affecting the competitiveness, customer experience attracts growing attention in the bank service channels. In this paper, we focus on the customer experience in the intelligent bank branches, which is an important service channel for Chinese commercial banks. More precisely, we study on the queuing problem of the intelligent bank branches with virtual teller machines (VTMs), and two queuing models, mixed queuing model and separated queuing model, are proposed for the intelligent bank branches. The performance of the queuing models is evaluated both in the waiting time of the customers and the work intensity of the manual tellers by simulation. The results show that, compared to traditional bank branches, the customer experience of the intelligent bank branches is improved greatly, and the separated queuing model performs better than the mixed queuing model.