| Summary: | 碩士 === 東海大學 === 工業工程與經營資訊學系 === 93 === In Taiwan, Industries consist mainly in computer peripheral equipments, fashion clothing and electronic products. These kinds of goods share similar characteristics, for example uncertainty, sales season and etc. While the product functions or attributes have not been changed, however due to changes in demand, these products will have to be sold for lower prices as a result. These kinds of variety product’s supply and competence, in general, have following two conditions：(1) Product competence in the same industries；(2) Product competence from different industries. A new emerging product is not intended to achieve a high sales volume; in fact it is intended for a diffusion process. Newer generation products with enhanced applications and functions will utilize market’s full potential, hence replacing the older generation products.
Our research searches industry’s competitive information and utilizes relevant historical data to infer the market demand function of each generation. According to experiences of enterprise knowledge management system, we utilize multi-generation model to decide the fittest volume and to confer the speculated quantity model of oligopoly market for the Game Theory. On the basis of the Stackelberg duopoly model, we consider the enterprise dynamic competitive behaviors to setup the mutual reaction function and to decide the fittest competitive price, comparing with the predictive supply price to choose the fittest pricing strategy. In order to conform to the practical market situation, we combine with the industry’s cost structure and revise the market linear demand function to non-linear one.
Furthermore, utilizing the Multi-Generation Diffusion Model of the Norton and Bass to explain the technological products take the place of multi-generation models of spreading. We not only fix the product price and the advertisement budget values but also view both of them as variables to solve the both situations by means of genetic algorithms, comparing the multi-generation product’s total revenue, the best evolutionary generations, and the time to market. By way of controlling the timing of product to market and considering the profit, the findings will not only facilitate a better understanding on corporation’s strategies and the relationship between multi-generation product’s spreading process and its life cycle but also maximize its overall profit.
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