The enhanced quality function deployment for developing virtual items in massive multiplayer online role playing games

Because of the huge potential profit, the development of virtual items in massive multiplayer online role playing games (MMORPGs) has lately begun receiving attention. As a successful means for developing new products, the quality function deployment (QFD) has been widely used in devising virtual items. In traditional QFD, information about the customers’ needs and their priorities can be gained through some marketing methods. However, these approaches heavily rely on the subjective results and cannot identify the demands of each customer because of bewildering amount of information. Thus, we adopt the genetic chaotic neural network (GCNN) technique to identify each customer’s needs and their priorities and propose the enhanced qualify function deployment (EQFD). However, in most of the existing literature, the equations to describe chaos dynamics are fixed and rigid corresponding to different nonlinear dynamic systems. In fact, for many chaotic systems in applications, it is often difficult to obtain accurate and faithful mathematical models, regarding their physically complex structures and hidden parameters. Therefore, GCNN is proposed in this paper, where GA is embedded into the chaotic neural network to generate and refine the equations of chaotic systems. By experimenting our methods with several benchmark methods, the proposed GCNN is found to demonstrate a clear advantage over other identifying methods, and EQFD is proven to be a feasible technique for developing the virtual items in MMORPGs. 2007 Elsevier Ltd. All rights reserved.