Research On Optimization Method For Service Window Of Bank Based On Queuing Theory

With the sustainable development of economy and the enhancing of people’s finance consciousness, the frequency of people dealing with banks is becoming higher and higher. Although banks have always been trying to increase their service ability, customer’s requirement to bank’s service level is rising at the same time. Besides, the type of business for customer is more and more variable. The contradiction between customer and bank service has always not been solved essentially and one of the most widely concerned problems is the customer queuing phenomenon before service window of bank.In order to reduce this phenomenon, banks usually increase the investment of related equipment and the number of service windows to decrease customers’ waiting time and dissatisfaction of service. To some extent, these measures alleviate the problem of queuing. However, it will increase the bank’s operation cost undoubtedly. In addition, some banks try to increase the service intensity of window to improve their service efficiency, but it is easy to make employees’ overworking and service enthusiasm reducing. How to keep a good relationship among customers’ waiting time, the cost of bank and windows service intensity becomes an urgent problem bank policy-makers need to solve.Combining the research home and abroad, this paper conducts a deep research on bank service window optimization problem based on queuing theory. The main content can be summarized as follows:First of all, this paper proves that one M/M/c queuing system’s working efficiency is higher than c M/M/1 queuing system to explain the reason why banks should choose single queue of multi server desks queuing system at the same business. Next, this paper proposes the amount model of bank service window and the grouping model of bank service window of two stages to set the queuing system of bank. At the first stage, there is the amount model of bank service window. The basic idea: considering customers’ waiting time, cost of bank and windows’ service intensity, it builds the amount model of service window based on M/M/c queuing system to decide how many service windows to set. At the second stage, there is the grouping model of bank service window. The basic idea: in order to further reduce the waiting time of customer and shorten the queue length of queuing system, making average service time as the primary index, combining with business volume and service features, it builds the grouping model of bank service window based on M/D/1 queuing system on the basis of windows set in the first stage. In this model, each type of window provides fixed kind of service and the service time is close to fixed length distribution. And then, the paper does empirical research on the above models to verify their effectiveness and confirms that the system has the most reasonable configuration and best service efficiency after optimized. Finally, this paper puts forward some feasible measures to further reduce customers’ waiting time according to the factors affecting the efficiency of bank queuing system.