A Dynamic Simulation For Ticket Policy Research Based On Consumer Choice

Currently, with rapid development of the concert market, the number and income of the concert will continue to improve, but due to the short time development of the industry, there are some shortcomings about market operations and services. Scholars mostly focus on the study of concert environment and pricing, while this paper combines consumer behavior and revenue management and make a dynamic revenue simulation based on consumer choice.Concert industry is facing dynamic uncertain market demand, but its limited capacity and product make it cannot like other industry deal with demand by its storage. During simulation concert ticket sales, according to the literature and the author’s experience, this study reasonable set some parameters, the concert tickets are divided into five classes according to the tickets properties. And based on the idea of dynamic programming, concert retailer divide the ticketing process into three stages, at each stage they need to decide product portfolio and quantity. We do simulation based on the Logit model to quantify the probability of customer’s choice of different products.Through the simulation of several situations in real life:First, the order of customer arrival; Second, the change of market demand; Third, the changes of the product variety. Probability based on consumer choice of different products in the above case, the relatively good income and portfolio compare different authors hope to get an intuitive understanding of how to arrange to make the tickets meet the customer demand as much as possible, thereby enhancing the proceeds of the concert. Finally, we suggest three ways to improve the revenue management:offer discounts or coupons; market segments and constantly updated revenue management program.We extend the concept of efficient sets developed by Liu and van Ryzin (2008) to the network case. Unfortunately, their model is not solvable for most realistic networks because of the large dimensionality of the state space. Hence, the only practical approach is to try to approximate the decision problem.If academics would be willing to work with individual retailers to understand their true complexity, they could make an enormous contribution in adding rigor and science to the retailers planning process, much as academics have done in other areas like finance, marketing and strategy.