| Summary: | 碩士 === 國立交通大學 === 資訊管理研究所 === 102 === With the rapid development of internet websites, more and more online games are produced. Virtual Worlds (VWs) are getting more attention because of the booming trend of on-line games. The highly growth market of VWs attract many companies to join the contest. But the fierce competitions result in a high customer turnover and shortage of profit. Moreover, the unsatisfied customer may spread negative word-of-mouth effect to the company. Therefore, how to predict the churner in the virtual worlds and satisfy them has becoming an important issue.
Even though customers churn prediction has been studying in the telecom, financial and retail industry to reduce customer turnover rate, but has not been applied in the virtual worlds to solve the customers’ turnover problem. The objective of this research is to develop a novel virtual world customer churn prediction method. This study analyzes the relationship between customer churn and three kinds of user behaviors in virtual world. The behaviors include virtual life behaviors, social contact behavior, and social influences of social circle neighbors. Our proposed model use random forest and neural network to classify the customer churn in virtual worlds by the three user behaviors mentioned above. The results shows our propose model considering both user’s activity energy and social circle neighbors’ social influence will have better performance. Also, the result shows the performance of decision tree is better than neural network for customer churn prediction in virtual worlds.
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