A Study Of Supplier Strategy Through Consumer Reviews Mining On Computational Experiment

with the improvement of logistics and online paying service, online shopping has become the most important way of shopping, and has become more and more important to suppliers. Online shopping freed customers from travelling, but in the mean time makes them uncertain of real product value.Therefore their purchase decision is based on the information they gathered from the internet. Study has shown that user-generated product information on the Internet attracts more interest than vendor information. How can suppliers use the information in the customer reviews to make decisions, which is the problem this paper tried to solve.Many researchers have established the importance of customer reviews. The existing literature typically gives methods to evaluate the impact of customer reviews. In this paper, we posit that the customer’s belief about a certain product feature is formed through customer reviews. We used social science computational experiment to build a customer purchase decision makingmodel, and give supplier three strategies:negativestrategy, customer orientation strategy. The customer agent has its own utility function, while supplier agent has its own information gathering function.With several experimental groups and hundreds of experiments, we come to the conclusion that with the customer orientation strategy the bad reviews will lower down and then the demand will rise eventually, and with the tech strategy, the value of the product feature which repeats most in the customer review will be larger, in return the good review will increase, and finally the demand increases.