文献类型：期刊文献

英文题名：Optimal Allocation of Online Content Combination Pricing under Mixed Revenue Mode

作者：Yao, Yue[1]; Cheng, Yan[1]; Xie, Yingying[1]

机构：[1] School of Business, East China University of Science and Technology, Shanghai, China

年份：2019

起止页码：491

外文期刊名：2019 IEEE 6th International Conference on Industrial Engineering and Applications, ICIEA 2019

收录：EI(收录号：20192307013496)

语种：英文

外文关键词：Economics - Costs

摘要：The development of Internet makes the rapid expansion of the business model based on providing online content service to online users. In recent years, the promotion of the payment model has brought new profit increasing point for content service providers. Single-on-demand payment and bundling subscription payment are widely used payment methods. If the two modes are combined, the service providers will often get more benefits. So in the mixed revenue model, online content service providers need to decide how to set a reasonable price for each charge mode in order to maximize expected revenue. In this paper, the user's value estimation model is constructed based on time preference theory and loss aversion theory. Furthermore, the variable neighborhood search algorithm is used to simulate and verify the optimal pricing strategy of various charging model combinations. ? 2019 IEEE.