Combined Tactics Negotiation Model with Bayesian Learning in E-Commerce

摘要

In the transaction process, the effective negotiation may cause more profits. In B2C and C2C, sellers only can use the fixed price or auction because they have no time and energy to bargain with buyers who are random on time and quantity, which reduces the benefits and successful transaction rate. This article established a negotiation model to solve this problem. This model conforms to the general negotiation flow and involves Bayesian learning function. In original Bayesian learning, the conditional probability is hard to obtain. The shortcoming is remedied in this model. It makes this negotiation model simple, effective and have learning ability.