A General Bayesian Network Approach to Analyzing Online Game Item Values and Its Influence on Consumer Satisfaction and Purchase Intention

摘要: Many online game users purchase items with which to play free-to-play games. Because of a lack research into there is no specified framework for categorizing the values items, this study proposes four types item based on an analysis literature regarding characteristics. It then investigate how perceive satisfaction and intention from proposed values. Though regression has been used frequently answer kind question, we propose new approach, General Bayesian Network (GBN), can be performed in understandable way without sacrificing predictive accuracy. Conventional techniques, such as analysis, do not provide significant explanation problem because they are fixed linear structure limited explaining why customers likely if satisfied their purchases. In contrast, GBN provides flexible underlying questionnaire survey data offers robust decision support question by identifying its causal relationships. To illustrate validity solving study, 327 valid questionnaires were analyzed using what-if goal-seeking approaches. The experimental results promising meaningful comparison results.