Abstract: With the improvement of people's living standard, time becomes more and more important. However, queuing may waste a lot of people's time. Existed researches show that customers tend to have an expectation on waiting time when they choose to enter a queuing system for service. If their actual waiting time exceed to their expectation, they will choose to leave or abandon the service. Therefore, the expectation of customers on waiting time will influence customers' behaviors and lead to the flow of customers in queuing system, then affecting the revenue of service provider. In this paper, three strategies are proposed to address this problem based on a stylized M/M/1 system. First and foremost, the related basic theory (i.e. the expected waiting time is not considered) of service pricing is introduced. Then, providing three new strategies by incorporating the expected waiting time of customers: update pricing according to the customers' expectation on waiting time, adjusting the customer expectation by discounting, and improving service rate without changing original price. Later on, the above three strategies are optimized and analyzed based on the optimization of revenue. Further, the corresponding optimal results are compared with existing works, respectively. Finally, the corresponding management insights are proposed based on the analysis of optimal results. The findings of this paper are as follows: When customers hold an expected waiting time in queuing, the service provider are inclined to make more revenue than maintaining the original pricing by adopting above three proposed strategies. If customers are sensitive to cost (i.e., moderate discount can effectively prolong the customers' expectation on waiting time), the discount strategy is better than the update pricing strategy. If perception of customers on time is stronger than the customers' perception on cost (i.e., moderate discount fail to effectively prolong the customers' expectation on waiting time), the update pricing strategy is better than the discount strategy. Obviously, when the cost of improving the service rate is low, service providers are bound to achieve the maximum revenue by improving the system service rate. This research shows important reference value and instructional significance for service providers who value the expected waiting time of customers in service pricing.

Key words: service system, queuing theory, expected waiting time, pricing strategy, optimization